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ASSESSMENT OF THE ADOPTION OF APPAREL COMPUTER AIDED DESIGN TECHNOLOGY TRAINING IN SELECTED PUBLIC
UNIVERSITIES IN KENYA
BY
VERONICA WAMBUI KAMAU (B.Sc)
(H60/10169/2007)
A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN
FASHION DESIGN AND MARKETING IN THE SCHOOL OF APPLIED HUMAN SCIENCES OF KENYATTA UNIVERSITY
NOVEMBER, 2012
ii
DECLARATION
This thesis is my original work and has not been presented for a degree in any
other university
Signature ------------------------------------ Date----------------------
Veronica Wambui Kamau
H60/10169/2007
This thesis has been submitted for review with our approval as University
Supervisors.
Signature ------------------------------------ Date----------------------
Dr. Dinah W. Tumuti
Department of Fashion Design and Marketing
Signature ------------------------------------ Date----------------------
Dr. Lucy Ngige
Department of Community Resource Management and Extension
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DEDICATION
To my husband Alex Njonde and our children Edward, Kamau and Gathoni.
iv
ACKNOWLEDGEMENTS
I am indebted to my supervisors Dr. Dinah Tumuti and Dr. Lucy Ngige for their
scholarly guidance, close supervision and patience in working with me since the
inception of this research to the end. Special thanks to Mr. Adon Ombura for his close
supervision, guidance in technical areas, encouragement and moral support during the
writing of proposal and thesis.
I am grateful to Mrs. Bosibori for her assistance and guidance in the entire period of
this project. I would like to thank the staff of the Department of Fashion Design and
Marketing for their helpful advice and constructive comments during the development
of this work. I would also extend my thanks to my colleagues Monica Cheruiyot and
Verah Acheing for their moral support, encouragement and advice as I undertook this
study.
I would also like to thank my husband Alex Njonde for his moral, financial and
technical support. I wish to acknowledge Kenyatta University, School of Applied
Human Sciences for granting me a Masters Scholarship.
Above all, I am grateful to the Almighty God for sufficient grace and health that
enabled me to complete this study.
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TABLE OF CONTENTS DECLARATION .................................................................................................... II
DEDICATION ....................................................................................................... III ACKNOWLEDGEMENTS ................................................................................... IV
TABLE OF CONTENTS ....................................................................................... V LIST OF TABLES ................................................................................................. IX
LIST OF FIGURES ................................................................................................ X OPERATIONAL DEFINITIONS OF KEY CONCEPTS AND TERMS ........... XI
ACRONYMS AND ABBREVIATIONS ............................................................ XIII ABSTRACT .......................................................................................................... XV
CHAPTER ONE ...................................................................................................... 1
INTRODUCTION ................................................................................................... 1
1.0 BACKGROUND TO THE STUDY ............................................................. 1
1.1 Statement of the Problem ................................................................................ 4
1.2 Purpose of the Study ........................................................................................ 6
1.3 Objectives of the Study .................................................................................... 7
1.4 Research Questions .......................................................................................... 7
1.5 Null Hypotheses ............................................................................................... 7
1.6 Theoretical Frameworks.................................................................................. 8
1.7 Significance of the Study................................................................................ 10
1.8 Assumption of the Study ................................................................................ 10
1.9 Delimitations of the Study ............................................................................. 11
1.10 Limitations of the Study............................................................................. 11
CHAPTER TWO ................................................................................................... 12
LITERATURE REVIEW...................................................................................... 12
2.0 INTRODUCTION ...................................................................................... 12
2.1 Apparel Industry in Kenya ............................................................................ 12
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2.2 Apparel Design Training in Kenya ............................................................... 14
2.3 Education and Technology in the Era of Globalization ............................... 15
2.4 Computer Aided Design (CAD) ..................................................................... 17
2.5 CAD in Designing........................................................................................... 20
2.6 CAD in Pattern Making, Grading and Marker Making .............................. 21
2.7 Computer Technology for Customized Services ........................................... 22
2.8 CAD/CAM in Cutting .................................................................................... 24
2.9 CAD/CAM in Sewing ..................................................................................... 24
2.10 Technology Transfer, Adoption and Diffusion ......................................... 26
2.11 Summary .................................................................................................... 28
CHAPTER THREE ............................................................................................... 30
RESEARCH METHODOLOGY .......................................................................... 30
3.0 INTRODUCTION ...................................................................................... 30
3.1 Research Design ............................................................................................. 30
3.2 Variables ........................................................................................................ 31
3.3 Location of the Study ..................................................................................... 31
3.4 Target Population .......................................................................................... 32
3.5 Sample and Sampling Procedures ................................................................. 32 3.5.1 Sample Distribution ................................................................................. 33 3.5.2 Sampling Procedures ................................................................................ 34
3.6 Data Collection Instruments and Procedures ............................................... 35 3.6.1 Questionnaires ......................................................................................... 36 3.6.2 Observation Checklists ............................................................................. 36
3.7 Pretesting........................................................................................................ 37 3.7.1 Validity .................................................................................................... 37 3.7.2 Reliability ................................................................................................ 37
3.8 Data Analysis ................................................................................................. 39
3.9 Ethical Considerations ................................................................................... 39
CHAPTER FOUR ................................................................................................. 41
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RESULTS AND DISCUSSION ............................................................................. 41
4.0 INTRODUCTION ...................................................................................... 41
4.1 Social Demographics ...................................................................................... 41
4.2 Apparel CAD Technology used in Apparel Industries ................................. 42
4.3 Apparel CAD Technology Program .............................................................. 44 4.3.1 Awareness of Apparel CAD ..................................................................... 44 4.3.2 Apparel CAD Courses .............................................................................. 45 4.3.3 Mode of Covering the Units ..................................................................... 47 4.3.4 Mode of Teaching .................................................................................... 48
4.4 Teaching/learning Resources for Apparel CAD Training ............................ 49 4.4.1 Computer Hardware and Software used in Apparel CAD ......................... 50 4.4.2 CAD Training Facilities ........................................................................... 52 4.4.3 Learning Materials Used for Apparel CAD Training Programme ............. 53
4.5 Human Resource in Apparel CAD Technology ............................................ 55 4.5.1 Lecturers’ Training in Apparel CAD ........................................................ 55 4.5.2 Staff Development Programs in Apparel CAD ......................................... 56
4.6 Universities Collaboration with Apparel Industries ..................................... 57 4.6.1 Sourcing of Employees to Work in Apparel CAD-related Jobs ................. 59
4.7 Training Gaps in Apparel CAD Technology Training ................................. 60 4.7.1 Industry Rating of Student Interns ............................................................ 60 4.7.2 Rating of Apparel CAD in Training Program ........................................... 60 4.7.3 Ranking of CAD Training Needs ............................................................. 63
4.8 Hypotheses Testing ........................................................................................ 65
4.9 Summary ........................................................................................................ 68
CONCLUSION AND RECOMMENDATIONS .................................................. 72
5.0 INTRODUCTION ...................................................................................... 72
5.1 Summary ........................................................................................................ 72
5.2 Implications of the Findings .......................................................................... 73
5.3 Conclusion ...................................................................................................... 73
5.4 Recommendations for Policy and Practice ................................................... 75
5.5 Recommendations for Further Research ...................................................... 75
REFERENCES ...................................................................................................... 77
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APPENDICES ....................................................................................................... 85 Appendix I: Student Questionnaire ...................................................................... 85 Appendix II: Lecturer Questionnaire .................................................................... 92 Appendix III: Industry Questionnaire ................................................................... 97 Appendix IV: Observation Checklist for the Industries ...................................... 102 Appendix V: Observation Checklist for Training Institutions ............................. 103 Appendix VI: List of Apparel Industries ............................................................ 105 Appendix VII: Research Authorization from National Council for Science and Technology ........................................................................................................ 107 Appendix VIII: Research Permit from Export Processing Zone Authority .......... 108 Appendix IX: Reliability Analysis ..................................................................... 109
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LIST OF TABLES Table pages
2.1: Apparel CAD systems………………………………………………………..19 3.1: Frequency distribution of the sample………………………………………...33 3.2: Sampling procedures of the respondents……………………………………..34 3.3: Sampling procedures of the universities and industries……………………...34 3.4: Cronbach alpha……………………………………………………………….38 4.1: Students sample characteristics………………………………………………41 4.2: Frequency distribution of apparel CAD systems…………………………….43 4.3: Frequency distribution showing awareness of apparel CAD technology……44 4.4: Frequency distribution of mode of covering the units……………………….48 4.5: Frequency distribution of student responses on mode of teaching ………….48 4.6: Frequency distribution of availability of design studio………………………49 4.7: Frequency distribution of computer hardware and software for apparel CAD49 4.8: Frequency distribution of adequacy of computer hardware and
software for CAD training……………………………………………………51 4.9: Frequency distribution of CAD facility provider…………………………….52 4.10: Frequency distribution of adequacy of teaching and learning materials……..52 4.11: Frequency distribution of respondents’ rating availability of learning
Materials……………………………………………………………………...54 4.12: Frequency distribution of lecturers training in apparel CAD………………...55 4.13: Frequency distribution of staff development policies………………………..56 4.14: Frequency distribution of areas of collaboration between universities
and the industries……………………………………………………………..58 4.15: Frequency distribution of other areas of training of labour force……………59 4.16: Frequency distribution of industry sourcing of employees to work in
CAD-related jobs…………………………………………………………….59 4.17: Frequency distribution of industry head of departments rating of
student interns………………………………………………………………...60 4.18: Frequency distribution of students rating of apparel CAD training………….60 4.19: Frequency distribution of lecturers rating of apparel CAD training…………61 4.20: Frequency distribution of industry heads of department rating of apparel CAD
training……………………………………………………………………..…62 4.21: Frequency distribution of students ranking of apparel CAD training needs…63 4.22: Frequency distribution of lecturers ranking of apparel CAD training needs...64 4.23: Frequency distribution of industry identification of training gaps…………...64 4.24: Comparison of mean between the respondents on student knowledge in
apparel CAD………………………………………………………………….65 4.25: Comparison of mean between the respondents on responses of the
apparel CAD training program……………………………………………….66 4.26: Comparison of students’ and lecturers’ rating of the teaching and
learning resources…………………………………………………………….67
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LIST OF FIGURES Figure page No. 1.1: Factors associated with adoption of apparel CAD technology------------- 9 4.1: Pie chart showing distribution of apparel CAD courses -------------------- 45 4.2: Learning materials for apparel CAD training -------------------------------- 53
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OPERATIONAL DEFINITIONS OF KEY CONCEPTS AND TERMS Adoption It is a decision to make full use of an innovation as the best course of action available, in this case the implementation of Computer Aided Design (CAD) in the training program (Rogers, 1995), Apparel Clothing and related products Computer Aided Design (CAD) It is the use of computer systems to assist in creation, modification, analysis or optimization of design (Groover & Zimmer’s, 1984). Computer Aided Design/Computer Aided Manufacture (CADCAM) This is the process by which computers are employed to enhance development and manufacture of products (Groover & Zimmer’s, 1984). Computer Aided Manufacture (CAM) It is the use of computer systems to plan, manage and control the operations of manufacturing through either direct or indirect computer interface with production resources (Groover & Zimmer’s, 1984). Clothing A covering designed to be worn on a person's body Cut Make and Trim (CMT) EPZ These firms are sub-contracted by other firm or retailers to make the products for them once they are supplied with fabric, design and patterns (Kinyanjui &McCormick, 2002). Cutting processes Garment-cutting Fashion Style that is popular at a particular time Garment-making Referred in the industries as sewing processes and in the learning institutions as garment making Integrated mills These are production and manufacturing facilities in which raw fibre is refined, woven into material and then used to produce clothing (Wise Geek, 2003). Mass customization The ability to prepare enmasse individually designed products and communications to meet each customer requirements.
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Observation checklist A measurement instrument for recording data in observation study Technology It is expertise or advancement in skill and machinery. It is innovation in action, involving the generation of knowledge and processes to develop systems that solve problems and extend human capabilities (Klein glass, 2005). Throughput The quantity of raw material or information processed or communicated in a given period by an electronic device Throughput time Time taken to design, cut and make the garment to completion Training Teaching in the respective field where computer technology is used for product development.
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ACRONYMS AND ABBREVIATIONS
AGOA : Africa Growth Opportunity Act
ANOVA : Analysis of Variance
BSc : Bachelor of Science
CAD : Computer Aided Design
CADCAM : Computer Aided Design & Computer Aided Manufacture
CAM : Computer Aided Manufacture
CBT : Computer Based Technology
CD-ROM : Compact Disc, Read-Only-Memory
CHE : Commission for Higher Education
CMT : Cut Make and Trim
CRITO : Centre for Research on Information Technology and
Organisation
NC : Computer Numeric Control
3D : Three Dimensional
DIT : Directorate of Industrial Training.
EPZ : Export Processing Zone
EPZA : Export Processing Zone Authority.
HE : Higher Education
ILO : International Labour Organisation
ICT : Information Communication Technology
ILS : Integrated Learning System
IT : Information Technology
KACE : Kenya Advanced Certificate of Education
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KCE : Kenya Certificate of Education
KIE : Kenya Institute of Education
KNEC : Kenya National Examination Council
KU : Kenyatta University
MTM : Made to Measure
NC : Numerically Controlled
NCST : National Council for Science and Technology
OECD : Organisation for Economic Cooperation and Development
POS : Point-of- Sale
RATES : Regional Agricultural Trade Expansion Support
STI : Science, Technology and Innovation
SPSS : Statistical Package for Social Sciences
UNESCO : United Nations Education, Scientific and Cultural
Organization.
UK : United Kingdom
UNIDO : United Nations Industrial Development Organisation
USA : United States of America
WWW : World Wide Web
2D : Two Dimensional
3D : Three Dimensional
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ABSTRACT The study examined the levels of adoption of Computer Aided Design (CAD) technology in training of clothing, apparel design courses. Application of apparel CAD technology in the training of the future labour force is a major step in coping with dynamic changes apparent in the textile and apparel industry. Application of apparel CAD technology in production processes in the textile and apparel firms is crucial if the industry is to remain competitive in the global market. The study aimed to establish whether apparel CAD training in selected public universities adequately addressed the changing labour requirement in the Kenyan apparel market, new demands in global apparel market and Kenya Vision 2030. The study focused on determining the status of apparel CAD technology program by assessing course contents, availability of teaching/learning resources and manpower to handle apparel CAD training. Descriptive survey research design was employed to investigate and describe status of the adoption of apparel CAD training in selected public universities and to determine established collaboration between universities and apparel industries in Kenya. A survey of 113 respondents from public universities and apparel industries was conducted. A total of 62 student respondents who included all third and fourth years as well as school-based and masters students from apparel design departments in the three universities, were purposively selected because they had undertaken a unit in apparel CAD. Twenty one lecturer respondents drawn from the three universities in the apparel design departments were included because they imparted skills to the students. Thirty heads of departments from six apparel industries were selected because the employees and interns worked under them. The universities included in the study were; Kenyatta University located in Nairobi; Moi University in Eldoret, and Egerton University in Nakuru. Apparel Industries included United Aryan (EPZ) Limited and MidCo Textiles (EA) Limited from Nairobi, Global Apparels EPZ Limited., AllTex EPZ Limited and Protex EPZ Limited from Athi River and Ken-Knit (Kenya) Limited from Eldoret. The study employed document analysis, questionnaires, interview schedules and observation checklists to obtain the data. The result showed that the adoption of apparel CAD technology at the public universities was low. The lecturers who had been trained in state of art CAD technology accounted for 28.6%. Appropriate CAD hardware and software teaching/learning resources were limited and accounted for 23.8%. The training students received was inadequate to prepare them to work in apparel industry. Only 23.3% of the students on industrial internship in apparel industries were rated as adequately trained. CAD courses did not adequately address specific areas of apparel design but dealt with basic introductory courses such as Corel Draw, Adobe Photoshop, and Adobe Illustrator. Heads of departments in the apparel industries pointed out that there was shortage of practical skills among the graduates and interns, whereas student respondents indicated provision of CAD hardware and software as the most urgent need. Lecturers in the departments of apparel design indicated that there was need for lectures to be trained in apparel CAD. Analysis of variance (ANOVA) results showed that there was no significant difference between computed means of respondents in relation to student knowledge in apparel CAD by the industries, students and lecturers and therefore, they agreed that the training on CAD technology the graduates received did not adequately meet the labour requirement in the apparel industry. It was concluded that collaboration between the universities and apparel industries in the area of curriculum development, CAD training for academic staff and students as well as provision of CAD teaching and learning resources be promoted.
1
CHAPTER ONE
INTRODUCTION
1.0 Background to the Study
Rapid changes in fashion and apparel market have been brought about by the
technological innovations and advancement in textile and apparel industry. Computer
Aided Design (CAD) and Computer Aided Manufacture (CAM) are at the centre of
this explosive growth of technology (Konzen & Locker, 2000) as it holds
considerable promise for delivery gains in efficiency and quality. CAD is a design
tool used for creating garments. CAM is a manufacturing tool that controls automated
processes (Gray, 1998; Groover & Zimmers, 1984). CAD/CAM is the application of
computers to enhance the manufacture and development of products. The systems
allow design to be generated rapidly and adjusted equally quickly without diminishing
creativity that provides better communication and integration between product
development systems (Istook, 2000). Today, some of the textile and apparel industries
employ computer technologies from management to retail and from design to
manufacturing (Yan & Florito, 2002).
The apparel CAD was incepted in 1970 and has evolved into a powerful tool for
product development and manufacture as it has developed from early stages of
computer modelling to the modernized concept of CAD integration with CAM
(Grolier, 1996). The Apparel CAD has received considerable attention in research
over the years (Hardaker & Fozzard, 1995), with an aim of saving on production time
and improving quality (Disher, 1991; Gray, 1998; Hunter, King & Lowson, 2000; Bae
& May-Plumlee, 2005). Even with automation of the system, the industry will require
2
specialized manual intervention and therefore the need for some experts to operate
and supervise systems (Kang & Kim, 2000). It is, therefore, crucial to have systems
for developing and harnessing the human resource of the industry to their maximum
potential.
Advances in technology and computer literacy in specialized fields are an important
consideration for the contemporary industries and institutions of higher learning
(Gillespie, 1991). Rapid pace of technological advancement in many industries,
including the apparel industry, has forced businesses to demand for a computer-
literate workforce (Smith & Necessary, 1996). Studies have shown that there are an
increasing number of jobs that require the use of computer technologies (Fraser &
Goldstein, 1985, MacAulay, 1993). This is because training and education are
influenced by the labour market demand. In today’s fast, inter-related and versatile
economy, employers are looking for productive employees who are quick, creative,
flexible and up-to-date with new technology. Employees with these qualities can keep
up with changing systems and techniques in the workplace (World Bank, 1999).
Textile and apparel industries that adopt or embrace advanced technology and
computerization will gain competitive advantage to carry out collaborative research,
design and production, marketing and networking with international companies.
Kenya being a developing country attracted investors due to opportunities that arose
as a result of the Africa Growth Opportunity Act (AGOA). Apparel manufacturing
firms were set up, most of them in the Export Processing Zones (EPZ). This led to the
revival of the apparel industry in Kenya (International Labour Organisation, 2000).
The program aimed at promoting exports, foreign exchange earnings, transfer of
3
technology and skills, employment creation and enhancement of industrialization
(Republic of Kenya, 2002). Investment in Kenya has enabled technology to be in use
in most apparel industries. Although cheap labour has been the main source of
competitiveness in Kenya, as with other African and Asian countries, it is no longer a
viable factor anymore (Byoungho, 2004). The dynamics of the textile and apparel
sector and globalization is forcing most countries to change their strategies. As the
industry sector develops, its competitive advantage should be changed accordingly
(Porter, 1990), and that is why investment in the new technology is inevitable if it is
to compete in the global market. Today, the apparel CAD technology is the most
urgent and important tool if efficiency and quality are to be achieved. This translates
to having a well-trained labour force to coordinate and facilitate the manufacturing
processes.
Fashion design and clothing technology, as distinct courses in the universities, were
started in mid-1990s in Kenya, prior to this they were considered as part of home
science. Formally, they were offered in secondary schools and examined at Kenya
Certificate of Education (KCE) and Kenya Advanced Certificate of Education
(KACE) levels until 1987 and 1989 respectively, and as technical courses to date at
craft and grade test levels which are basic levels of skills training. Although clothing
diploma was taught in few colleges, national syllabus by the Kenya Institute of
Education (KIE) was availed in 1996 and since then, the syllabus has not been
reviewed to accommodate the changes in technology. This makes the graduates
inadequately prepared for the job market.
4
Fashion, textile, apparel and clothing training are gaining popularity as the market
realizes the need for personnel to work in the industry or set up businesses that cater
for changing needs in the market. Apparel CAD training was introduced in various
universities in Kenya by early 2000 either as distinct or combined units in clothing,
textiles and fashion design departments to cater for changing labour requirements.
The structure of higher education (HE), while traditionally resistant to innovation, is
being dramatically affected by changes brought by information technologies
(Gillespie, 1991). However, effective financing has been identified as the most critical
factor that affects quality of university education. Mwapachu (1995) and Shabani
(1997) maintain that poor funding affects quality of teaching, availability of learning
resources and maintenance of physical facilities. Most universities experience conflict
over resource allocation between administrative and academic computing (World
Bank, 1994). Unfortunately, the decision-makers in universities consider demands for
improved administrative as imperative and end up allocating less to academic
instructional needs (Gillespie & Deborah, 1984). The quality of curricula should be
considered if it is to be beneficial in the world of work (United Nations Education,
Scientific and Cultural Organization, 1998).
1.1 Statement of the Problem
Apparel industry has thrived in Kenya from 1990s due to the opportunity created by
the Africa Growth Opportunity Act (AGOA). This has brought some changes in the
technology in use in this industry. Although little has been documented regarding use
of CAD technology in textile and apparel industries in Kenya, a survey of apparel
industries indicates that CAD technology is in use in this industry from design to
manufacturing and management to retailing of products (ILO, 2000). Training
5
institutions such as Evelyn School of Design, Kenya Polytechnic University and
College of Technology, Moi University, Egerton University, Kenyatta University and
Nairobi University, among others, prepare students to work in textile and apparel
industries. Apparel CAD technology training has been introduced in some universities
to cater for the changing workplace requirement. Kenya’s system of education has
been criticized to be supply-driven and therefore, does not adequately respond to
market needs (Republic of Kenya, 2007). Moreover, the existing education system
was often perceived as too theoretical and not specific enough for the particular needs
of the industry and this might have had an impact in implementation of new
disciplines in training programs. There was, therefore, the need to assess apparel CAD
technology training to determine its current status in adoption and training.
The goal of Kenya being a middle income industrialized country by 2030 provided
another opportunity for assessing apparel CAD technology training. Vision 2030
proposed intensified application of Science, Technology and Innovation (STI) to raise
productivity and efficiency levels (Republic of Kenya, 2007). To achieve this goal,
the newest technology in the market needed to be adopted in all processes of
production and ensure technical staffs were qualified to handle operations in the
industries. The government also proposed to create an STI policy framework to
enable more resources to be devoted to scientific research, technical capabilities of the
workforce and raising the quality of teaching in science and technology in
polytechnics and universities (Republic of Kenya, 2007). Apparel CAD technology
training was crucial in achieving this goal as it provided qualified labour-force to
work in apparel industries. Gaps in training needed to be identified so that they could
6
be addressed, hence, there was need to assess current status of apparel CAD
technology training.
The clothing and textile industry was also impacted by global changes and therefore,
to remain competitive, it had to adopt new technology in the market. Apparel CAD, a
recent technology in the market, is the driving force to industrialization in the apparel
and textile sectors, and hence, evaluation of training offered was crucial. This
necessitated the researcher to investigate the status of apparel CAD technology
training programs offered by apparel design departments in public universities in
Kenya.
1.2 Purpose of the Study
The purpose of the study was to establish the status of apparel CAD training in
selected public universities. It sought to investigate status of apparel CAD programs
by scrutinizing the areas specific to the apparel CAD in relation to apparel design and
manufacturing, availability of teaching and learning resources and trained personnel
to teach apparel CAD technology as well as finding out whether there were staff
development policies in place to ensure that staff was trained to handle the program.
The research also aimed at determining whether there was collaboration between
apparel industries and universities in regard to curriculum development, staff needs
and internship.
7
1.3 Objectives of the Study
The study was guided by the following objectives:
i. To assess the status of apparel CAD technology academic training program in
selected public universities in Kenya.
ii. To determine the status of teaching and learning resources used for apparel CAD
technology program.
iii. To identify competencies of academic staff in apparel CAD technology training in
the departments of apparel design in the Universities.
iv. To determine areas of collaboration between the universities and the apparel
industry.
1.4 Research Questions
I. Was the staff in the departments of apparel design in the universities trained in
apparel CAD technology?
II. In which areas did the universities and industries collaborate?
1.5 Null Hypotheses
According to Fraenkel and Wallen (2006), “hypothesis is a prediction of some sought
regarding the possible outcomes of a study.” The study employed null hypothesis
(H0). Therefore the hypotheses were stated as follows:
Ho-1 There is no significant difference between computed means of the students,
lecturers and the industry respondents in response to students’ knowledge in apparel
CAD technology training.
8
Ho-2 There is no significant difference between the computed means of the students,
lecturers and industry’s respondents in response to the apparel CAD training
program.
Ho-3 There is no significant difference between lecturers and students response to the
availability of teaching/learning resources.
1.6 Theoretical Frameworks
The theoretical frameworks for this study were derived from the systems theory.
Systems theory was advanced in 1940s by Ludwig Von Bertalanffy. Systems
approach integrates the analytic and the synthetic method encompassing both holism
and reductionism. Holistic approach sees system behavior as independent from the
properties of the elements while reductionism says the law governing the parts
determines or causes the behaviour of the whole. Therefore the Systems Theory
focuses on arrangement of and relations between parts which connect them into a
whole (Hylighten &Jostling, 1992). The way parts are organised and how they
interact with each other determines the properties of that system.
Systems interact in open systems. These open systems interact with other systems
outside of themselves. All open systems have a boundary, an input, an output and a
throughput function. The boundary separates system and environment. System is in
constant process of taking in inputs and transforming them into outputs. Systems
Theory is applicable to adoption of apparel CAD technology training where parts such
as apparel CAD academic program, teaching and learning resources, student-lecturer
competencies, university-industry collaboration and industrial technical support
9
interact and in a throughput function, the adoption of apparel CAD technology is
achieved as the output (figure1.1).
Lecturer-studentcompetencies
INPUTS
Apparel CAD academic program
U n iv e r s ity - in d u str y c o lla b o r a tio n
Industr ial technicalsupport
C A D te a c h in g a n d le a r n in g r e s o u r c e s
PROCESS
Throughput Function
OUTPUT
Adoptionof ApparelCAD Technology Training
Figure 1.1: Factors associated with adoption of apparel CAD technology. Adapted from Heylighten (1998)
Different parts of a system in this case referred to as inputs which include the
university apparel CAD academic program, lecturers/student competencies, technical
support, teaching/learning resources and university-industry linkages in a throughput
function enable the adoption of apparel CAD technology training. However the
inputs determine the outputs in the open system. If teaching and learning resources are
not adequate, or apparel CAD program is not appropriate, and university-industry
collaboration is limited, adoption of apparel CAD technology training will be
affected.
10
Open systems have anticipatory control. They regulate by anticipating errors before
they occur and take corrective measures before final output. This form of regulation is
called feed forward control. If adoption of apparel CAD technology training is to be
effective, it should be managed before processing of input takes place. To realise this
objective the researcher assessed the independent variables, the inputs, to determine
their effect on dependent variable, the output. These formed the basis of the research
being undertaken.
1.7 Significance of the Study
The study aimed at highlighting the gaps that existed in apparel CAD technology
training which was to form basis for:
a. Improvement of the quality and the relevance of curriculum in apparel CAD
technology training.
b. Implementing staff development policies to enhance training in the emerging
technologies such as apparel CAD technology.
c. Upgrading the teaching and learning resources for apparel CAD technology
training in the universities.
d. Ensuring a better fit between the demand and supply of trained human
resources in apparel CAD technology for the apparel industry.
1.8 Assumption of the Study
The researcher assumed that the target population had some knowledge and
understanding of the apparel CAD technology.
11
1.9 Delimitations of the Study
The study was limited to students and lecturers within the selected universities and
departmental heads within few industries. Therefore implications and generalizations
of results obtained at other institutions should be done with caution since situations
are dissimilar at different times.
1.10 Limitations of the Study
The study concentrated on design and manufacturing areas of apparel CAD
technology in training and use in apparel industry leaving areas of marketing and
retailing since the study was constrained by time and financial costs. The researcher
further realizes what the limitations of this study would have in terms of apparel CAD
analysis in the whole apparel supply chain and in training.
12
CHAPTER TWO
LITERATURE REVIEW
2.0 Introduction
The study concentrated on product design and the manufacture aspect of apparel
CAD. The study focused on the apparel industry and apparel design training in Kenya
as well as education and technology in the era of globalization. Specific areas of the
apparel CAD were discussed, and these included CAD in pattern making, grading,
marker making, designing, cutting, sewing and mass customization. Technology
transfer, adoption and diffusion were also discussed.
2.1 Apparel Industry in Kenya
Apparel and textile industry is one of the oldest and important manufacturing
activities in Kenya. The industry rapidly grew in the post-independence period to
become the second largest employer after the public service in 1970s and 1980s
(Ndirangu & Ikiara, 2004) due to protectionism of the local industry by the
government and backward linkages with the textile industry (Kamau, 2005). With
liberalization of the market in 1990, the garment industry was affected by the surge of
imports of both new and used clothing which were fairly priced and considered of
higher quality than local clothing, hence preferred (Ongile & McCormick, 1996).
The African Growth and Opportunity Act (AGOA) availed an opening for the apparel
industries to export their products to United States of America (USA). This opened up
an opportunity for growth and revival of apparel and textile sector in Kenya. AGOA
was signed into law in the USA in the year 2000. The act offered tangible incentives
for African countries to continue their efforts to open their economies and build free
13
markets. AGOA extended duty-free and quota-free benefits to imports of a number of
apparel items and textile products. The Act gave the beneficiary Sub-Saharan
countries, Kenya included, a window period to develop their own base for textile raw
materials, allowing use of fabrics and other materials on apparel items from any part
of the world (Export Processing Zone Authority, 2005).
Apparel industries are characterized by differences in production patterns. Integrated
mills are production and manufacturing facilities in which raw fibre is refined, woven
into material and then used to produce apparel products (Wise Geek, 2003). Some
engage in full range of production activities where they design products, make
patterns, cut make and trim apparel products for export. These are often referred to
automated EPZ industries. Some large exporters are “Cut-Make and Trim (CMT)
contractors. These firms are sub-contracted by other firms or retailers to make their
products once they are supplied with fabric, design and patterns (Kinyanjui
&McCormick, 2002).
Although a diversity of technology is used in Kenya’s apparel industry, little
documentation has been given and therefore, difficult to identify the level of
technology or technical requirements in the industry (ILO, 2000). Indeed, an explicit
human resources development direction for the industry is not clear, although post-
secondary institutions have been established to address the issue of labour
requirement (Wiese, 1975).
14
2.2 Apparel Design Training in Kenya
The process of globalization and industrialisation has put higher demands on labour
market to supply skilled workers (Salinger, 2006).Apparel design education has
received attention in the recent years mainly due to changes in the market and the
need to have professionals to work in apparel industries or set up fashion businesses
to cater for a dynamic market. Presently, only a limited number of specialized courses
are offered by local colleges and universities. Apparel design courses are offered at
different levels, the lowest grade test level examined by the Directorate of Industrial
Training (DIT) (Wiese, 1975) artisan, craft and diploma examined by the Kenya
National Examination Council (KNEC) and Bachelor of Science (BSC), master’s and
doctorate degrees by the universities. Public technical institutes such as Machakos
Technical Training Institute, Rift Valley Institute of Science and Technology, Eldoret
and Mombasa Polytechnics among others have not been able to include apparel CAD
as a separate unit since they follow a national syllabus prepared by Kenya Institute of
Education which has not been reviewed since 1996.
Private institutions such as Buruburu Institute of Fine Art and Evelyn College of
Design also offer diploma and certificate courses most of which are tested by external
bodies such as City and Guilds or internally by the said colleges. Universities are
autonomous and therefore are able to make changes in the curriculum offered; hence,
universities teaching apparel design have been able to include apparel CAD as a unit
in their programs.
15
2.3 Education and Technology in the Era of Globalization
Although dynamic changes in design and manufacturing have taken place, shortage of
technologically trained people in all aspects of computer aided design and
manufacturing (CADCAM) is being experienced since technology changes faster than
the societal system including education (Emptage, 1991). To be successful in the field
of designing and manufacturing, one must continuously learn new concepts and skills.
The economic structure of a country has an obvious relationship to education as it is
the framework for development (Eshiwani, 1993; DeGregori, 1989). As countries face
the era of globalization, technological innovation and emergence of new economies, a
well-educated population is a requirement for the competitive world market (World
Bank, 1999; UNESCO, 1998). Although extraordinary developments have taken place
in various technologies, they are underutilized in the training they provide (UNESCO,
1998). Biggs et al., (1994) cite technological drawbacks, financial problems,
insufficient market information and institutional coordinating mechanisms as main
impediments to growth. Study carried out in Northern Ireland on the skill needs
assessment for apparel sector identified a gap exists in core technical skills and
knowledge amongst designers and garment technologists due to changes in
technology and lack of investment in staff training. Shortage of sector specific
technical topics was a significant barrier to development within the industry (Skill
Fast UK, 2006).
Developed countries like the United States and the United Kingdom are also faced
with slow uptake of apparel CAD technology, citing lack of information, experts and
training coupled with systems cost as the main reasons (Hardaker & Fozzard, 1995;
16
Yan & Florito, 2002). Kenya, like India is also faced with a problem of low level
technology and training of workforce (Bheda, 2003). This is attributed to training
structures that are deficient, hence unable to adequately prepare learners for a
dynamic or changing labour market. Secondary and higher education in these
countries demonstrate considerable insufficiency because post-secondary institutions
have strong bias towards law, social sciences and other art subjects (El-Namaki,
1998). The missions of the universities, being institutions of higher education and
research, are to undertake training and research activities to empower citizens with
necessary skills and information for development of the society (Achola, Gray &
Wanjala, 1990). Presently in Kenya, a number of universities are struggling to meet
daily financial obligations and the pursuit of academic excellence. Low funding from
the exchequer and increased enrollment without commensurate improvement of
available resources has adverse effect on universities (UNESCO, 1998).
The structure and conception of school that evolved in the last century is quite
incompatible with effective use of new technologies. The view of teaching as
transmission of information from teachers to their students has little place for students
using new technologies to accomplish meaningful tasks (Collins, 1996). Apparel
industries are themselves changing, with computer based technology playing a greater
part in design and manufacturing processes. Educators therefore have a duty to
prepare students so that they are familiar with the technologies they will encounter in
a working environment (World Bank, 2000). Educators often find themselves in a
dilemma. Some educators return to the academia after several years in industry.
Others have predominantly been involved in training and are therefore often hesitant
to enter and overlap into other fields of design or even technology. The same methods
17
of teaching are still implemented for the reason that they have become a good base of
knowledge. It does not mean that the knowledge supplied is not feasible; it simply
means that the recognized method of teaching often excludes the possibility of
incorporating changes occurring in industry into the syllabus (Ryder, 2005). The
quality of curricula calls for special care in the definition of the objectives of the
training provided in relation to the world of work and the needs of the society
(Commission for Higher Education, 2003).
The impact of technology has meant that it is possible to offer students a range of
resources to enable them to engage in self-directed studies in apparel technology.
Computer-based training systems can be accessed through tools such as the Compact
Disc, read-only-memory (CD-ROM) or the World Wide Web (WWW) as they are
available in thousands of multimedia or hypertext programs. Various instructional
formats are available. These include simulations, tutorials, help systems, integrated
learning Systems (ILS) and teacher demonstration programs (Wilson, Sherry,
Dobrovolny, Batty & Ryder, 2000).
2.4 Computer Aided Design (CAD)
Computer Aided Design (CAD) technology is becoming increasingly apparent in
textile and apparel industries due to the competitive nature of businesses in the sector
(Hardaker & Fozzard, 1998; Collier & Collier, 1990; Glock & Kunz, 2005). Apparel
products are seasonal in nature and therefore require speedy delivery which can be
achieved through effective and efficient operations (Glock & Kunz, 2005). As
technologies converge, apparel CAD technology is evolving into an integrated
environment that drives the entire company. Apparel CAD technology is not only
18
serving design and production functions within the company, but it has also become
an integral part of company including in areas of sourcing, merchandising, and
marketing. “The evolution of the computer is making it possible to extend the
designer’s mental as well as physical capabilities” (Owen, 1991). Computer, when
used only as extension of the designer’s medium, allows the designer to complete the
design process with greater efficiency.
In the apparel industry, CAD systems are mainly used in various processes such as
garment design, pattern preparation, pattern grading and marker making. CAM
systems include computerized sewing machines, fabric spreading, cutting systems and
mover systems used in apparel production (Ondogon, 1994). CAD is a recognized
tool in the clothing industry, with many commercial systems available to assist in the
process (Hardaker & Fozzard, 1998; Ross, 2001). CAD systems supporting garment
manufacture processes consist of computer hardware, software and communication
equipment (Groover & Zimmer’s, 1984; Stjepanovic, 1995). The development of a
new generation of complex and powerful computers and software packages places
more intricate requirements from computer hardware (Hutchinson & Sawyer, 1995).
The computer hardware of the new generation apparel CAD systems for designing the
models, collection of patterns, marker making layout and cutting in the production of
garments basically consists of ; CAD server, powerful micro-computers for particular
work stations, high resolution colour graphic displays, input and output devices,
communication devices and special equipment for laying and cutting (Stjepanovic,
1995). Interactive input devices, apart from keyboard and mouse, include digitizer,
graphic, video camera, digital scanner and spectrophotometer. Computer controlled
output devices include plotters, colour hardcopy devices, colour video and
19
photographic cameras, printers, automated spreading and labeling machines and
automated cutting machines (Stjepanovic, 1995).
Apparel CAD software consists of a computer program to implement computer
graphics on the system, and an application program to facilitate the engineering
functions of the user company (Groover & Zimmer’s, 1984).
Table 2.1: Apparel CAD systems
Apparel CAD systems
Packages/modules Description of tasks
Gerber technology
Acc works studio Acc mark 8000 Acc mark 100 & 200 Acc mark silhouette 200 Pattern Design 2000
-Sketches, line drawings, colour ways, fashion illustrations, draping, textile and knitting design. -Pattern making, grading -Marker making, automatic marking and plotting -Pattern design by draping, or full-scale drafting, grading and marking -Design package
Lectra U41a graphic U41a Sketch Modaris basic Modatris grader U41a 3D Diamino APM
-Design -Create technical drawing and design elements. -Pattern digitizing, design modification. -creation and application of grade rules. -3D texture mapping, 3D sample visualization, pattern flattening and pattern development. -3D/2D simulation
Assyst Assy CAD Nester
-Pattern design, digitizing, grading, manual marker making -Automatic marking
Scanvec Digitize PDS Grade Custom fit Mark Nest++ Match++
-Digitizing -Pattern making by digitizing or drafting -grading -Make custom fit garments by entering body measurements for individual customers. -Automatic or manual marking, matching -Automatically generates and extremely an extremely tight marker -Pattern layout for stripes and plaids
Tukatech Tuka design -Pattern drafting and grading
20
Tuka pattern Tuka Tuka Cads
-Made-to-measure pattern based on a given pattern. -Grading and marking -Pattern design grading and marking
CADCAM solutions
Fashion CAD Pattern design Pattern grading Pattern detailing Marker layout
-Pattern creation/ Import -Pattern creation/ Import -Grading -Insert seams, symbols, text -Manual marker
Source: Manufacturing Technology Centre, (1999)
Examples of Apparel CAD systems are listed on Table 2.1. Some of these apparel
CAD systems have been modeled for training purposes or for use in small apparel
companies. These apparel CAD systems have been modeled in different sizes to be
used by design studios, in small as well as large companies.
Apparel CAD technology in use is not yet standard across the entire apparel sector,
although many companies in Kenya have readily embraced automated design and are
continuously improving its functionality. The major problems encountered are
significant costs involved in investing in apparel CAD technology, which include
purchase of apparel CAD hardware and software as well as acquisition of skills
required to properly utilize the apparel CAD program. Information and training in use
of CAD is mainly availed by suppliers, in-house training, as well as program experts
within the company and consultants or service providers.
2.5 CAD in Designing
Apparel CAD technology in designing started to receive a lot of attention as a creative
design tool and by the end of 1980s, researchers were actively looking at ways to
integrate this tool more effectively. Although CAD programs have been developed
specifically for apparel industry and apparel CAD training, fashion design students
21
mostly used basic CAD design programs. These basic CAD programs were also
available to graphic, architecture, fine art and textile students and included Adobe
Illustrator, CorelDraw and Adobe Photoshop which allow students to communicate
their designs professionally (Ryder, 2005).
Apparel design and styling software systems allow designers to develop designs
through electronic sketching, freehand sketching with the stylus pen and data tablet or
scanning of images into the system (Glock & Kunz, 2005). Template programs such
as snap fashion and style manager consist of libraries of garment components that can
be combined in countless ways to rapidly design a garment. Imaging programs
manipulate data using screen pixels. The program is used for idea generation, story
boards, illustration and many forms of textile design. The software programs offer
greater integration with the fabric and garment design offering new possibilities to the
designer. 2D and 3D software programs have enabled designers and retailers to make
decisions based on virtual fabrics and virtual designs. Collections can be visualized by
mapping fabrics onto sketches and photographs, thus creating virtual models and
reducing amount of samples needed in each season. The most significant benefit of
garment systems is the speed with which a design can be developed. There is need to
have computers in the design studio where students can interact with the software and
integrate it into the design process as another design tool (Ryder, 2005).
2.6 CAD in Pattern Making, Grading and Marker Making
Pattern grading and marker making were the first area in apparel industry to use
computer technology in their production in 1970s when apparel CAD technology
developed. These initial systems functioned as isolated islands. The systems were
22
expensive and could be afforded by few (Hands, Cathy, Hergeth & Hudson, 1997;
Stjepanovic, 1995). In 1980s, considerable progress was made in commercial
development and application of computers and automatic systems to pattern grading
and marker making. There was rapid uptake of these new methods and a dramatic
decrease in the price of entry level (Byrne, 1995; Hands et al., 1997). Use of apparel
CAD enabled a greater throughput of styles in a shorter time period hence an effective
response to the competitive market demand.
Pattern making on CAD systems is based on block pattern concept. Basic blocks are
entered into computer systems using a digitizer or scanner that converts pattern shapes
into coordinates data. Production patterns, styles changes and revisions are executed
by CAD program (Glock & Kunz, 2005). Examples of CAD pattern systems include
Gerber and lectra among other systems. A computerized system take vector based
pattern and marks certain nodes as growth points. The patterns are converted into a
range of patterns of different sizes (Aldrich, 2004). The pattern pieces are either
automatically laid or manipulated to produce the most economical marker which is
then plotted on a flat bed or drum plotter to produce a paper marker or directly
transferred to the Numerically controlled (NC) machine (Aldrich, 1992).
2.7 Computer Technology for Customized Services
Mass customization, a process by which garments are produced for individual
customers following their body measurement, is the newest apparel technology in 21st
century (Vignali, Vrontis & Vronti, 2004; Kotler 1997). This concept of intelligent
manufacture, advanced by Stylios and Sotomi in 1997, brought about use of computer
garment cutting pattern construction following individual body measurements. Mass
23
customization is seen as a new strategy for achieving competitive advantage. It is
customer rather than production oriented and it is based on the idea of market
adaptation to suit individual needs both on a national and international level. This
technology has enabled high quality customized products to be availed to the
customers at low prices, within the shortest time possible, all over the world (Fang,
2003; Petrak & Rogale, 2001; Istook, 2002; Glock & Kunz, 2005). Pioneer
manufacturers have already introduced personal tailored-made clothes with the aid of
three-dimensional body-scanners, interactive point-of-sale (POS) terminals and
telecommunication networks (i.e. Internet). All these components are linking the
customer’s decisions with the production line, wherever in the world it might be.
In mass customization, certain software and hardware packages and equipment exist.
Three dimensional (3D) body scanners are used to transform the human body into
graphic forms. They provide accurate information about the body, which can then be
downloaded to the pattern adjustment process. Retailers such as Hugo Boss and
Escada are currently adopting more integrated CAD/CAM systems. This evolutionary
idea does not only meet the demanding customers’ needs, but also time and
accumulated stock is significantly reduced. CAD technology has acknowledged
benefits for clothing manufacturers and the underlying message seems to be that it is
essential for survival (World Clothing Manufacturer, 1997). Even the smallest
companies should be investing in CAD (Tait, 1997). Currently, the biggest drawback
is the systems cost and the cost of training employees, but with time, they will be
affordable as they become available from different manufacturers.
24
2.8 CAD/CAM in Cutting
Use of CADCAM in the cutting room started in 1970s led by Gerber in the USA.
Computer systems for grading patterns and producing markers developed rapidly and
offered significant reduction in lead times and labour costs for generating new styles,
modifying the existing ones and most significant the reduction of fabric utilization
(Byrne, 1995). Pattern generated by marker making systems can be directed to
automated cutting machines which are operated without the help of human hands
(Hands et al., 1997).
Laser cutter is extensively used for cutting fabric in apparel industry. It uses a laser
beam to cut fabric. Laser cutting systems spread the fabric on a pallet and move it to
the cutting zone to be cut. After cutting, the pallet is moved to the other side of the
cutting zone where the cut parts are removed, while the successive parts are cut.
Patterns longer than the cutting zone are automatically divided by software into
frames that fit into cutting zone area. Laser cutting systems cut the fabric while it is
in motion. Cutting is the only garment manufacturing operation to have been fully
automated. Advanced robotics have been increasingly introduced in the cutting room
for retrieving fabric from store, loading it onto carriage and removing cut material
(Byrne, 1995).
2.9 CAD/CAM in Sewing
The pace of technological innovation for sewing operations in the garment industry
was slow up to the beginning of the 1980s as it concentrated on manufacture of faster
and more durable sewing machines and the development of attachments for
specialized tasks. The major technological changes occurred in 1980s when micro-
25
electronics penetrated all stages of garment production. These are used either to speed
up production on task dedicated machines or increase flexibility of multi-purpose
machines (Konzen & Locker, 2000).
The main improvements were the use of micro-electronic control units which are
attached to the standard industrial sewing machines to handle more complex tasks.
When CAD systems are linked to manufacturing equipment which is also controlled
by computer, they form an integrated system CAD/CAM. CAM equipment, which
utilizes computers, helps to eliminate operator error, achieve consistency and reduce
labour costs. Equipment usage can also be pre-determined leading to more significant
savings. The savings on reduced workforce and machine efficiency can be equated to
the high cost of the capital equipment, hence, making the investment worthwhile.
a Other innovations included tension free stitching with little or no intervention from
the operator, new and improved fabric feeding and machines that operate with various
degree of automation (Hughes & Hines, 1993; collier, 1990). A wide variety of
programmable, electronic sewing machines are available. Specialized machines are
available for stitching pants, cuffs, pockets, attaching collars and waistbands,
hemming, sewing buttons and buttonholes, attaching belt loops, bar tacking and over
lock stitching. More sophisticated models may have a touch pad interface, pre-
programmed stitch libraries, automatic thread cutters and automated back stitching.
In knitting technology, an electronic knitting machine with a computer for reading
needle patterns input from a floppy disk or cartridge contains electronic selection
units that have two selecting points for knit, tuck, three-way technique, transfer and
26
receive. The selection made at this point passes through a cam track. An electronic
step motor controls the presser cams and stitch cams, which alternate in the direction
of the carriage. These are for drawing the needle down to pull more or less yarn into
the needle hook to form a different size of knitted loop.
2.10 Technology Transfer, Adoption and Diffusion
New technologies have enabled acquisition of industrial technology which has been
an underlying factor in diversification of export and economic growth of countries
globally. To be able to compete effectively in the global market, there is need to use
technologies as they change (Lall, 2001) and this entails upgrading technologies,
skills and productivity in existing activities. Advanced technology has challenged the
producers in developing countries by undermining their cost advantage and presenting
them with new parameters of competition.
Due to the nature and speed of technological innovations and the accompanying
organizational changes, developing countries are finding it more difficult to keep up
with these changes and, therefore, the technology gap between them and the
developed countries is increasing. These trends affect not only the direction,
composition and volume of international trade in textiles and apparel, but also the
industrialization process and labour markets at country and regional level. The
dynamics of globalization can propel faster industrial growth hence technological
transfer is inevitable. Adjusting to increased global competition has placed
unprecedented demands on industrial capabilities, hence, institutions should be
enhanced to deal with the challenge of global competition. To respond to
globalization opportunities, the industrial sector will need significant upgrading of
27
manufacturing capabilities (United Nations Industrial Development Organisation,
2002).
Developing countries are more involved in technology transfer and in most cases the
adoption of technology (Andrej, 2005): The ability to diffuse technologies rapidly and
effectively is vital to success. To use new technologies, there is need for investment
by the user in order to create new skills, information and institutional support.
Mastering technology requires continuous upgrading and deepening of technologies,
human capital and supporting networks (Lall, 2001). Scientific and technical
manpower resources would also be needed for the transfer of technology from abroad
and its adaptation, upgrading and assimilation in the economy (Gupta, 2004).
Developing technological competence has long been identified as one of the most
complicated issues facing developing countries today. Kenya has limited and
fragmented technology support systems as with other Sub-Saharan countries, and this
affects the technology adoption process (Lall et al., 1994; Wignaraja & Ikiara, 1999;
McCormick, Kinyanjui & Ongile, 1997). Adoption of technology is not an automatic
process, but occurs gradually as some users wait to see how it has worked for the
others (Moore, 1991). When adopting technology the gains are more at early stages of
adoption but with high risks (Rogers, 1995). To remain competitive some industries
are at the forefront seeking new technology in the market and evaluating the gains
they will derive from adopting it. Educationalists have a great role to play in the
adoption process, as they put the necessary structures in place to ensure appropriate
knowledge is transmitted. Both universities and apparel industries should work
together if training is to be relevant.
28
For technology to be transferred, expertise is fundamental. Knowledge and
technological progress have become more important to the realization of economic
prosperity within an integrated world economy (UNIDO, 2002). These forces are
exerting profound influence on the industry, applying manufacturing context based on
knowledge and technological progress. Learning is considered the key to the effective
transfer and diffusion of technology and to achieving innovation, industrial growth
and international competitiveness (Mytelka, 1998). Competitiveness is sustained by
continuously improving products, processes, customer services and management
routines. Investment in education, research and development is crucial in ensuring
technological competitiveness.
2.11 Summary
Apparel industry has benefited from various developments and innovations in apparel
CAD technology, though they are underutilised both in training and the industry.
Studies carried out indicate designers and garment technologists have insufficient
technical skills due to inadequate investment in training. The curriculum in use has
minimum sector specific topics and this is a barrier to development of apparel
industry. Even with developed countries like USA and UK, adoption of apparel CAD
is low, citing lack of information, experts, training and costs as main the hindrances.
Although survey indicates some apparel industries in Kenya employ apparel CAD
technology, little documentation has been done, hence it becomes difficult to identify
the level of apparel CAD technology in use. Little research has been done to address
the apparel industry’s technological requirements in Kenya, hence making it difficult
29
to clearly define apparel CAD technology needs. Kenya’s limited and fragmented
technology support system affects the technology adoption process.
Gaps exist in training with few universities offering training in apparel CAD
technology training, hence few graduates trained in apparel CAD technology.
Inadequate teaching and learning resources and bureaucratic procedures in the
universities hinder effective implementation of education policies in Kenya and this
also affects implementation of apparel CAD technology training. Moreover, the
Kenyan system of education has been criticized to be supply driven, hence not
specific enough to the needs of industry. This affects the implementation of new
disciplines such as apparel CAD technology training.
30
CHAPTER THREE
RESEARCH METHODOLOGY 3.0 Introduction
This chapter describes the research design used during the study, location where the
study was undertaken, method employed in data collection and the analysis of data. It
also identifies target population, sample and sampling procedures, instruments and
pretesting of these instruments.
3.1 Research Design
According to De Vos (1998), a research design is a blue print or detailed plan of how
a research is to be conducted. It is the overall plan of obtaining answers to the
questions being studied and for handling some intricacies encountered during the
research process (Polit & Beck, 2004). Descriptive survey research design was used to
identify and describe variables identified in the study (Orodho, 2004). This research
design was appropriate as it described the state of affairs as it existed in adoption of
apparel CAD technology training. The research design enabled the researcher to
search for deeper understanding of apparel CAD Technology training as it was not
only a method of data collection but it involved classification, analysis, comparison
and interpretation of data.
Descriptive survey research design employed survey method to collect the data in
order to explain variables identified in the study. Gay (1992) defines survey as an
attempt to collect data from members of a population with respect to one or more
variables. It helped the researcher to examine variables and determine their effects.
The survey method employed was crucial as it helped to increase familiarity with the
31
area of research. The survey method was the appropriate mode of inquiry due to its
flexibility both in sample and in categorizing the questions to be used during data
collection. Survey method also allowed different perspectives to be employed, hence
the respondents had more freedom to give their points of view (Jones, 1985).
3.2 Variables
Variables are conditions or characteristics which the researcher can manipulate,
control and observe (Fraenkel& Wallen, 2006). In research, there are two variables,
independent and dependent variables. According to Hatch and Farhady (1982)
independent variable is a major variable which the researcher hopes to investigate
whereas dependent variable is one the researcher observes and measures to determine
the effect of the independent variable. The nature of dependent variable depends on
what independent variable does to it (Fraenkel & Wallen, 2006). The independent
variables of the study were apparel CAD academic program, teaching and learning
resources, student-lecturer competencies, university-industry collaboration and
industrial technical support, while dependent variable was adoption of the apparel
CAD technology training.
3.3 Location of the Study
The study was carried out in public universities in Kenya teaching apparel design
courses. These universities included, Kenyatta, Moi, and Egerton. Kenyatta
University is located on the outskirts of Nairobi; Moi in Eldoret, and Egerton in
Nakuru. Apparel industries were also included in the study. Apparel Industries
included United Aryan (EPZA) Ltd and MidCo (EA) Textiles Ltd from Nairobi,
32
Global Apparels Kenya EPZ Ltd, AllTex EPZ Ltd and Protex EPZ Ltd from Athi
River and Ken Knit (Kenya) Ltd from Eldoret.
3.4 Target Population
Target population was drawn from departments of apparel design in selected public
universities. These universities included Kenyatta, Moi, Maseno and Egerton.
However during the time of the study, Maseno University had first year students only
in apparel design program and therefore it was not included in the study. The study
targeted third and fourth year apparel design students as well as school based and
masters students undertaking apparel design programs in the selected universities. The
masters, school-based, third and fourth year apparel design students were targeted
because they had undertaken a unit or units in apparel CAD during their training.
Lecturers were also part of the target population because they were involved in
training.
The researcher also targeted departmental heads in various apparel industries because
they had direct contact with interns and graduates employed and also they had some
knowledge in the area of study the researcher aimed to explore. These industries
included integrated mills, Cut Make & Trim – Export Processing Zone (CMT-EPZ)
mills and fully automated Export Processing Zone (EPZ) industries (see appendix vi).
3.5 Sample and Sampling Procedures
The researcher used both probability and non-probability sampling methods to obtain
the sample used in the study. Probability sampling is one where every unit in the
population has a chance of being selected in the sample, while non-probability is a
33
technique where samples are gathered in a process that does not give all the
individuals in the population equal chances of being selected (Kombo & Tromp,
2006).
3.5.1 Sample Distribution
Table 3.1: Frequency distribution of the sample Sample Frequency (N) Percent (%)
Students 62 55
Lecturers 21 18.5
Industry head of departments 30 26.5
TOTAL 113 100%
A survey of 113 respondents, who consisted of 21 university lecturers, 62 students
and 30 heads of departments from the industry, participated in the study. The sample
included third and fourth year apparel design students, school based and master’s
students who were enrolled in the departments of apparel design in the three selected
public universities in Kenya. Twenty one lecturers from these departments were also
involved in the study. Thirty heads of departments from selected apparel industry
participated in the study.
Response rate was high. Among the sixty nine student respondents targeted in the
study, sixty two responded, and this was 89% of the responses expected. A total of
twenty one responses out of twenty four expected responses were obtained from
lecturers in the departments of apparel design in the three selected public universities
in Kenya. Data from the apparel industries was obtained from heads of departments
which included 30 responses, or 100% of total responses expected.
34
3.5.2 Sampling Procedures
Table 3.2: Sampling procedures of the respondents
Respondents Sampling procedures
Reason
Students Entire population Small population Lecturers Entire population Small population Industry respondents - Departmental Heads
Purposive Had direct contact with students and employees
The target population included third and fourth year apparel design students as well as
school based and masters students undertaking apparel design programs in the
selected universities. After identifying the target population, the sample intended for
the study was found to be small and therefore the researcher included the entire
population in the research. Another group of respondents drawn from the departments
of apparel design in the universities were the lecturers. They were involved in the
training of the students. The entire population was also included in the study because
it was small. From each industry, five respondents were picked amongst the
departmental and section heads. The sample was appropriate as they were directly
involved with employees and students in the industry.
Table 3.3: Sampling procedures of the universities and the industries Categories Sampling procedures Reason
Universities purposive Training Apparel CAD Industries Integrated mills Simple random Few Industries (8)
Fully automated EPZ industries
Simple random
Few Industries (13)
Cut Make &Trim EPZ industries
purposive - snowballing
There was no response even after repeated trials
35
Three public universities offering apparel design courses namely Kenyatta, Moi and
Egerton universities were purposively selected. This was because they had included
apparel CAD technology training in their program.
Apparel industries included fully automated EPZ industries, Cut, Make & Trim EPZ
and integrated Mills. Two categories of industries were identified through random
sampling while one was obtained through purposive sampling using snow balling
method (Mugenda & Mugenda, 1999). The researcher identified a list of apparel
industries to be included in the study guided by a list from Export Processing Zone
Authority (EPZA) and from Directorate of Industrial Training (DIT) attachment
coordinating unit. The researcher classified the industries into three categories: Cut,
Make and Trim (CMT) EPZ; Integrated Mill and fully automated EPZ industries.
Three lists were prepared which included eight integrated mills, eleven CMT-EPZ
industries and thirteen fully automated EPZ industries. Simple random sampling was
used to determine the industries to be included in the study. The group sample was
obtained where each name was recorded separately. Papers were folded and shuffled
thoroughly and then picked one at a time, with the shuffling repeated to ensure a
representative sample.
3.6 Data Collection Instruments and Procedures
The study employed document analysis, questionnaires, interview schedules and
observation checklists. Document analysis was used to evaluate academic programs.
The questionnaires with both open-ended and close-ended questions were circulated
to the students and lecturers. An observation checklist was used by the researcher to
record the teaching and learning resources used for apparel CAD technology courses.
36
Face-to-face interviews lasting about one hour were conducted amongst the heads of
departments in the participating apparel industries.
3.6.1 Questionnaires
The researcher used questionnaires to carry out the research. The questionnaires were
prepared to collect data from lecturers, students and apparel industries heads of
departments (see appendix I-III). The research instrument had both open-ended and
close-ended questions. Close-ended questions are those the respondents must choose
between fixed alternative answers. Open-ended questions will give the respondents
freedom of the response. An interview schedule was used to collect information from
the industries. The interview schedule made it possible to obtain data required to meet
specific objectives of the study.
3.6.2 Observation Checklists
Observation is a commonly used method in data collection or to record evidence.
Tilstone (1998) defines observation as, “the systematic and an accurate collection of
usually visual evidence, leading to informed judgments and to make the necessary
changes to accepted practices”. Therefore, observation as a research technique entails
collection of evidence, examination or analysis of data and formation of significant
judgment based on the evidence and subsequent implication. The study employed
non-participant observation to record industrial machinery in the apparel industries
(appendix IV) and the teaching and learning resources in the universities (appendix,
V). The information was used to validate data collected.
37
3.7 Pretesting
The researcher pre-tested the instruments to determine their reliability and validity
using identical samples from selected public universities and apparel industries. The
pretest study helped in foreshadowing research problems and questions, in
highlighting gaps and in considering broader and highly significant issues such as
research validity, ethics and representation, Sampson, (2004) concurs.
3.7.1 Validity
Validity is the accuracy and meaningfulness of inferences which are based on
research results (Mugenda & Mugenda, 1999). Content validity is a measure of the
degree to which data collected using a particular instrument represents content of a
particular concept. To enhance content and face validity, the researcher used some
experts in the area to study the questionnaires to determine the relevance of content
and their suggestions were considered in revising the instruments. The researcher also
used observation checklist to validate the data from the student respondents in relation
to teaching and learning resources as well as apparel CAD equipments and machinery
identified by industry respondents. Various methods were used to collect the data and
this is often referred to as triangulation. These methods included document analysis,
questionnaires, interview schedules and observation checklists. The data collected
from these sources was used to validate the data.
3.7.2 Reliability
Reliability is a measure of the degree to which a research instrument yields consistent
results after repeated trials (Mugenda & Mugenda, 1999; Nachmias & Nachmias,
1992). To determine content reliability, the researcher administered questionnaires six
38
student respondents in apparel design departments in the universities. The researcher
also collected data from six lecturers from apparel design departments in the
participating universities. The researcher also administered six questionnaires to the
respondents from two industries. Cronbach Alpha was used to measure internal
consistency among a set of survey items which the researcher believed would all
measure the same construct, and were therefore correlated with each other, and thus
could be formed into some type of scale. Items on Likert scale were measured using
Cronbach Alpha. Cronbach Alpha can be written as a function of the number of test
items and the average inter correlation among these items. The formula which was
used to compute cronbach alpha is shown below.
α = N. C V+ (N-1).C N- Is equal to number of items
C- is the average inter item co-variance among the items
V- equals the average variance
Cronbach alpha measured the internal consistency of the items and each item loadings
were based on its corresponding construct.
Table 3.4: Cronbach alpha Variable Cronbach No of Item Knowledge in apparel CAD technology 0.8720 5 Apparel CAD training program. 0.8960 6 Availability of teaching/learning resources. 0.9250
6
Overall α 0.8976
The Table 4.1 illustrates the findings of the study concerning the reliability analysis.
Each item loadings for cronbach alpha and composite reliability exceeded 0.70 and
therefore they were adopted in the study. From the findings, the coefficient was
39
0.8976 which was closer to one making the instrument very reliable. Mugenda and
Mugenda (2003) indicate that a correlation coefficient of value closer to one was very
reliable.
3.8 Data Analysis
Quantitative and qualitative approaches were used to analyze data. Content analysis
was used for qualitative data obtained from the document analysis, in-depth
interviews and observation checklists. Quantitative data was analyzed using the
Statistical Package for the Social Sciences (SPSS). These included graphical
representations of data, where the data were grouped and summarized in terms of
tables, graphs, pie charts and percentages. T-test was used to test differences on
computed means of responses obtained from lecturers and students on availability of
teaching/learning resources. Analysis of variance (ANOVA) was used to test the
differences between students, lecturers and industry computed means of responses
obtained on students’ knowledge of the apparel CAD technology program.
3.9 Ethical Considerations
The researcher sought permission from the National Council for Science and
Technology (NCST) to undertake the research (appendix VII). In the universities,
permission was further sought from vice-chancellor’s office, who requested the
departments of clothing and textiles, apparel design to allow the researcher to
undertake the study. To undertake data collection from EPZ industries, permission
was obtained from Export Processing Zone Authority (appendix, VIII). Before any
interview with the respondents, they had to give their informed consent before
participation in the study. The respondents were assured of total confidentiality and
40
anonymity by using level of study instead of their names and assuring them that the
information given would only be used for the purpose of the study.
41
CHAPTER FOUR
RESULTS AND DISCUSSION
4.0 Introduction
The main objective of the study was to assess the status of apparel CAD training in
four public universities, namely, Kenyatta, Moi and Egerton. The researcher also
collected data from six industries, namely, Ken Knit, MidCo, United Aryan, Protex,
AllTex and Global apparels. The results obtained helped to determine the status of
apparel CAD training. The researcher has presented the findings from the data
collected to answer the objectives identified in the study.
4.1 Social Demographics
Table 4.1: Student sample characteristics
1. Age Minimum 20 Maximum 46 Mean 30 Standard. Deviation 8.8
2. Gender Male 6 (10%) Female 56 (90%)
3. Year of Study Year II (School based) 18 (29%) Year III (Regular) 23 (37%) Year IV (Regular) 14 (23%) Masters 7 (11%)
4. Level of study Undergraduate (regular & school based) 55 (89%)
Masters 7 (11%) The researcher collected data from 62 student respondents and the minimum age of
the student respondents was 20 years and maximum was 46 years with a mean age of
30 and standard deviation of 8.8 (Table, 4.2). Ninety percent of the respondents were
females whereas males were 10%. This meant that the course was mostly undertaken
42
by females. Thirty seven percent of student respondents were third years and they
were part of the 89% of the undergraduates. This sample was selected because they
had undertaken a unit in apparel CAD.
The researcher also obtained data from lecturers teaching in the apparel design
departments in the selected universities. A total of twenty one responses were
obtained. Lecturers were included because they provided manpower to impart apparel
CAD skills to the students. Data from the apparel industries was obtained from thirty
heads of departments. The heads of departments were included in the study because
they were in contact with interns and graduates who worked in the apparel industry.
4.2 Apparel CAD Technology used in Apparel Industries
To effectively analyze the data for apparel CAD technology training in the
universities, and to highlight the gaps that existed in the study, research was carried
out to identify apparel CAD in use in the apparel industries. Available research had
failed to document the apparel CAD technology in use in the apparel industries in
Kenya, although studies carried out had indicated apparel CAD was being used (ILO,
2000). This necessitated the researcher to collect and analyze the data. The results
were used for comparison purposes and also as reference where information on
apparel CAD technology was required.
From the study it was found that the apparel CAD systems which were commonly
used in the apparel industries were Gerber and Lectra. Sewing processes mostly used
machines with microprocessors and also employed computerized embroidery to
decorate or brand products.
43
Table 4.2: Frequency distribution of apparel CAD systems Apparel CAD systems
CAD in design
CAD in pattern drafting and grading
CAD in cutting processes
CAD in sewing processes
N % N % N % N % Gerber 10 33.3 11 37 9 30 - - Lectra 2 6.7 1 3 - - - - Computerized knitting 3 10 1 3 - - - - Computerized embroidery
- - - - - - 11 37
Machines with microprocessors
- - - - - - 18 60
No response 15 50 17 57 21 70 1 3 TOTAL 30 100 30 100 30 100 30 100
The study results pointed out that, Gerber apparel CAD systems were in use in most
apparel industries (Table, 4.1). Thirty seven percent of the respondents said Gerber
apparel CAD systems were used for pattern drafting and grading, while 33.3%
indicated that Gerber systems were used for designing and 30% pointed out that they
were used for garment cutting. Use of machines with microprocessors in sewing
processes was identified by 60% of the respondents, while 37% pointed out
computerized embroidery was in use in the apparel industries. This is a clear
indication that apparel industries in Kenya have embraced use of apparel CAD
technology in their production processes, though at different levels, in various
categories of the apparel industries. During the study, fully automated EPZ had
employed apparel CAD technology in both the preproduction and production phases,
whereas CMT-EPZ used apparel CAD systems in pattern grading, marker making,
fabric spreading, cutting systems, mover systems and in computerized sewing
machines. Application of CAD systems in the integrated mills was minimal and only
few sewing machines were computerized. All categories of firms were using
computerized embroidery to brand their products or those ordered by their customers.
44
4.3 Apparel CAD Technology Program
The researcher collected data to determine the status of apparel CAD technology
training in selected public universities.
4.3.1 Awareness of Apparel CAD
Table 4.3: Frequency distribution showing awareness of apparel CAD technology
Variable Frequency Percent CAD awareness 60 96.7 Not aware 2 3.3 Total 62 100.0 The study results indicated that 96.7% of student respondents were aware of apparel
CAD technology (Table 4.3). Areas of apparel CAD technology identified by the
respondents included CAD in designing, AutoCAD, CAD in pattern drafting and
grading, CAD in garment-cutting and CAD in garment-making. Thirty eight out of
sixty two respondents were aware of CAD in designing, pattern drafting and grading
respectively. This is an indication that respondents were aware of cutting-edge
technology in apparel industry. Studies have shown that graduates are aware of
increasing use of computers in the job market and therefore, recognize the need to
become computer literate in their area of specialization (McAulay, 1993). Most of the
students are joining the universities having acquired basic computer skills and hence
they are able to navigate the World Wide Web (WWW) in search of information in
their area of specialization. The zeal for knowledge is driving the students to seek for
any information available in the internet that suits their needs. Students are also
finding it easier to access information they require from internet when undertaking
their projects and assignments. Therefore they have a lot of information in their field
of specialisation.
45
4.3.2 Apparel CAD Courses
The study results indicated areas of apparel CAD technology covered by the students.
Specific areas covered in the apparel CAD identified by the respondents included:
CAD in Design
AutoCAD
Pattern Drafting and Grading
Garment Making
17
Apparel CAD Courses
percentage
cad in design
auto cad
cad in pattern drafting & grading
cad in design pattern drafting & grading
cad in design and auto cad
cad in design + pattern drafting & grading+ garment making
45.2%
29%
8.1%
11.3%
3.2%3.2%
Figure 4.1: Pie chart showing distribution of apparel CAD courses
There were variations among the students respondents on the number of apparel CAD
areas covered in the syllabus in the training programs in various universities.
Majority of the respondents covered CAD in design as indicated by 45.2% followed
closely by AutoCAD at 29% (See Figure 4.1). AutoCAD, being a basic design course
for preparing students undertaking interior design, architecture and engineering
CAD in design
Auto CAD
CAD in pattern drafting &grading
CAD in design pattern drafting &grading
CAD in design & auto CAD
CAD in design + pattern drafting & grading + garment making
46
courses was mainly taught in Egerton and Moi universities to prepare them for
interior design course. Much attention was given to CAD in design and AutoCAD.
These were basic introductory courses in apparel CAD technology which were also
easily available in universities to students undertaking Graphic Design, Fine Arts and
Engineering courses. This showed that majority of the students had covered CAD in
design for their preparation to join the apparel industry.
These results are also supported by course documents which indicated areas of
apparel CAD covered by the three universities. Kenyatta University had two units for
undergraduate program. These included computer application in fashion design and
textiles, a first year course, and CAD in fashion design, a fourth year course. The first
year unit introduced basics of computer application, while other areas were geared
toward CAD in design. The fourth year unit introduced design packages such as
adobe illustrator, Corel draw and adobe Photoshop. In the Masters program, computer
application in fashion design entailed introduction to computer hardware, software
and design packages, namely, Adobe Illustrator, Corel Draw and Adobe Photoshop.
From the course documents, the apparel CAD course offered concentrated more on
CAD in Design with minimal coverage in the three other areas which include CAD in
pattern drafting and grading; CAD in garment-cutting and CAD in garment-making.
Specific apparel softwares and hardware in use in the apparel industries from different
suppliers like Lectra, Gerber, Assyst and PAD systems were barely included in the
study. This meant that the course is in its early stages of adoption where the
departments were struggling with acquisition of teaching and learning resources as
well as preparing appropriate curriculum for this area of study.
47
Egerton University apparel CAD units included Computer Aided Drawing and
Design, a second year unit, and Pattern Grading and Computer Aided Design, a fourth
year unit. Areas of Computer Aided Drawing and Design included exploration of
interactive design, its possibilities, issues of avenues, application packages of
drawing, drafting, painting, typographic design such as AutoCAD, ArchiCAD and
Adobe illustrator. Pattern Grading and Computer Aided Design covered CAD in
fashion, textiles and pattern cutting as well as digitizing patterns using different
methods of grading. Areas of apparel CAD were addressed and covered in this unit,
though during the study the university also lacked adequate teaching and learning
resources, which was a major hindrance to appropriate delivery of apparel CAD
program. The courses covered mostly concentrated on three areas which included
CAD in design, AutoCAD and CAD in pattern drafting and grading. However, the
university also lacked adequate computer hardware and software to train in specific
apparel CAD units hence work was mostly done theoretically except for AutoCAD
where the software was available.
Both the course documents and the students indicated that only basic CAD programs
were covered in the universities. The course units failed to adequately address specific
areas of apparel CAD which were being used by the apparel industry.
4.3.3 Mode of Covering the Units
The study revealed that apparel CAD units were covered either as separate units or as
part of other units (Table 4.4).
48
Table 4.4: frequency distribution of mode of covering the units
Mode of covering the units
CAD in design
CAD in pattern drafting and grading.
CAD in garment-cutting
CAD in garment-making
N % N % N % N % Separate 40 64.5 9 14.5 1 1.6 2 3.2 Combined 19 30.6 18 29 9 14.5 6 9.7 No response 3 4.8 35 56.5 52 83.9 54 87.1 TOTAL 62 100.0 62 100.0 62 100.0 62 100.0
As a separate unit, CAD in design was covered as indicated by 64.5% , while as part
of other units, it was taught as indicated by 30.6% of the respondents (Table, 4.4).
Other three areas, namely CAD in pattern drafting and grading, CAD in garment-
cutting and CAD in garment making were poorly covered.
4.3.4 Mode of Teaching
Table 4.5: frequency distribution of student responses on mode of teaching Mode of teaching apparel CAD units
CAD in design
CAD in pattern drafting and grading.
CAD in garment-cutting
CAD in garment-making
N % N % N % N % Theory 9 14.5 14 22.6 7 11.3 5 8.1 Practical 11 17.7 3 4.8 2 3.2 1 1.6 Both 38 61.3 11 17.7 9 14.5 6 9.7 No response 4 6.5 34 54.8 53 85.5 56 90.3 Total 62 100.0 62 100.0 62 100.0 62 100.0 Apparel CAD being a practical course, the researcher sought to know how the units
were covered (Table, 4.5). The unit contents of apparel CAD in design had both
theoretical and practical work as indicated by 61.3% responents. The study results
indicate that practical work was poorly covered in all four apparel CAD areas with the
highest being 17.7% for CAD in design. The study results differ with the Desiree
49
(2003) research which indicated that Computer Aided design, as with other design
and construction skills, is practical oriented, and accounts for 80% of subject content,
with theory accounting for about 10-20%. Desiree (2003) indicated that the only
possible way of learning design or computer application is by practising. This calls for
availability of computers in the design studios where students can access them easily.
4.4 Teaching/learning Resources for Apparel CAD Training
Table 4.6: Frequency distribution of availability of design studio
Design Studio Frequency Percent Availability 5 8 Not available 57 92 Total 62 100.0
It was revealed from the study that apparel CAD technology was being offered
without design studios for practical sessions. Ninety two percent indicated that there
were no design studios in their institutions while only 8% of the students indicated
availability of design studios (Table 4.6). This is also supported by lecturers where
76.2% indicated that there were no design studios. This showed that although
universities had implemented apparel CAD technology, they had not acquired
necessary equipments and facilities to support training. Ryder (Design, 2005),
indicated that design studios with relevant facilities were a prerequisite for
appropriate training in apparel CAD. The nature of training offered in apparel CAD
calls for availability of design studios with relevant facilities. This will improve
delivery of apparel CAD programs and enable students to interact with the software
and hardware effectively.
50
4.4.1 Computer Hardware and Software used in Apparel CAD
Table 4.7: Frequency distribution of computer hardware and software for apparel CAD
a. Hardware type
Hardware Frequency Percent Desktops 28 45 None 28 45 Laptops 6 10 Total 62 100.0
b. Software type
Software Frequency Percent AutoCAD 17 28 Adobe Photoshop 13 21 Corel Draw 10 16 Adobe Illustrator 7 11 None 15 24 Total 62 100.0
From the study, the results showed that desktop computer hardware was available to
most students for use as identified by the students (see table 4.7a). Forty five percent
said they were using desktop computers while 10% used their own laptops. With the
student population of over 70 students, the respondents indicated that there were few
computers in the departments of apparel design in relation to number of students, and
that is why they used computers from other departments. This meant that the
departments gave limited consideration to acquisition of computer hardware and
software when implementing the apparel CAD program.
The software commonly used by the students was for CAD in design (see table
4.7b).These included basic design software like AutoCAD at 28%, Adobe Photoshop
at 21%, Corel Draw at 16% and Adobe Illustrator at 11%. AutoCAD software had a
51
majority of users at 28%. The apparel CAD software identified by respondents during
the study were basically for introducing students to apparel CAD and were also easily
available in universities to students undertaking Graphic Design, Fine Arts and
Engineering courses. This is an indication of limited exposure of the students to
specific apparel CAD software in use in the apparel industries from different suppliers
like Lectra, Gerber and Assyst systems. The results differ with Smith (2008) study
findings, indicating increased use of CAD software among the undergraduates in
apparel programs. This calls for the apparel design departments to re-evaluate their
apparel CAD programs with a view of making necessary changes to be in-line with
current needs of the apparel industry. Review of curriculum will enable universities
identify software in use and those required for appropriate implementation of the
apparel CAD curriculum.
Table 4.8: Frequency distribution of adequacy of computer hardware and software for CAD training
Computer hardware and software Frequency
(N) Percent
(%) Availability 5 23.8 None 16 76.2 Total 21 100.0
The study results revealed that majority of the student respondents pointed out that
computer hardware and software for apparel CAD technology training in their
institutions was inadequate (Table 4.8). Of the total student respondents, 76.2%
indicated computer hardware and software necessary for training CAD in design were
not adequate with only 23.8% indicating that the facilities were available. The
students reported that the computers were few compared to the number of students
undertaking the course hence accessibility was difficult.
52
4.4.2 CAD Training Facilities
Table 4.9: Frequency distribution of CAD facility provider CAD facility provider
Frequency (N)
Percent (%)
None Engineering department(Egerton) Fine Art department ((KU) Fashion design dept Directorate of Industrial Training (DIT) Personal laptop School computer lab
24 12 9 7 6 3 1
39.0 19.4 14.5 11.0 9.7 4.8 1.6
Total 62 100.0
The respondents also indicated that they used computers from other departments
(Table 4.9). In Kenyatta University, the students mostly used computers from Fine
Arts Department, while in Egerton University the students used computers from
Engineering Department. In Moi University the students used the school computer
lab. School-based students indicated they used facilities from DIT to study apparel
CAD program.
Table 4.10: Frequency distribution of adequacy of teaching/learning resources Adequacy of teaching/learning resources
CAD in design
CAD in pattern drafting and grading
CAD in garment-cutting
CAD in garment-making
N % N % N % N % Adequate 7 11.3 3 4.8 2 3.2 2 3.2 Not adequate 51 82.3 27 43.5 14 22.6 12 19.4 No response 4 6.5 32 51.6 46 74.2 48 77.4 Total 62 100.0 62 100.0 62 100.0 62 100.0
With the study having revealed unavailability of design-studios for practical sessions,
the lecturers and students were further required to indicate adequacy of teaching and
learning resources for apparel CAD training (Table 4.10). The study results revealed
that 82.3% of the student respondents pointed out that apparel CAD teaching and
53
learning resources were inadequate. In all the other three areas, namely CAD in
pattern drafting and grading, CAD in garment cutting and CAD in garment making,
the students noted unavailability of adequate apparel CAD teaching and learning
resources for effective and efficient training.
To qualify the aspect of unavailability of teaching and learning resources to train
apparel CAD technology in the universities, a questionnaire was also administered to
lecturers teaching in the department on availability of necessary teaching and learning
resources for training apparel CAD technology. It was clear from the lecturers that
there was lack of adequate teaching and learning resources to train students on apparel
CAD technology. Seventy six percent of the respondents said that there were no
adequate teaching and learning resources to handle apparel CAD technology training
in their institutions.
4.4.3 Learning Materials Used for Apparel CAD Training Programme
Figure 4.2 identifies learning materials used for apparel CAD training.
Figure 4.2: Learning materials for apparel CAD training
54
To further evaluate the status of apparel CAD training, availability and type of
teaching/learning materials used for training was analyzed. Figure 4.2 showed that
CAD in design training mostly used lecture notes as indicated by 30.5%. The CAD in
garment making technology was poorly covered at 1.2%. Giving handouts to students
was also a common method of teaching apparel CAD technology in the university.
The use of CD-ROM and the internet services was common among the students in
Kenyatta University as a source of learning materials for apparel CAD, following the
increased availability of the internet services in the university. During the survey, the
students appreciated the presence of internet at the libraries because of lack of up-to-
date textbooks on apparel CAD technologies. Students downloaded the learning
materials from the internet.
Table 4.11: Frequency distribution of respondents’ rating availability of the learning materials
Availability of learning materials
Poor Fair Good Very good
No response
Total
N % N % N % N % N % N % Journals 13 21.0 1 1.6 1 1.6 0 0 47 75.8 62 100 Handouts 16 25.8 12 19.4 19 30.7 6 9.7 9 14.5 62 100 Textbooks 10 16.1 6 9.7 6 9.7 1 1.6 39 62.9 62 100 Lecture notes 8 12.9 14 22.6 26 42 4 6.5 10 16.1 62 100 CD-ROMs 14 22.6 2 3.2 2 3.2 0 0 44 71.0 62 100 Internet 14 22.6 4 6.5 10 16.1 7 11.3 27 43.5 62 100 e-learning 15 24.2 0 0 0 0 0 0 47 75.8 62 100 Respondents’ rating of the accessibility of learning materials for apparel CAD
training in the study area revealed a pathetic situation where most of the respondents
revealed that there was limited access to learning materials (Table, 4.11). Internet
sources rated 11.3% as very good while others were rated to be less than 10%. This
was as a result of inadequate computer labs and computers in the libraries within the
55
universities. This meant that although apparel CAD technology was introduced,
necessary learning materials such as textbooks and journals are not adequate for
studying apparel CAD technology. The results agree with Ayler (2011) findings
which identified inadequacy of staff and learning resources as the main impediment to
the implementation of curricula. Lack of manpower, teaching and learning resources
had affected apparel CAD training. Therefore, there is need to continually re-define
quality and excellence and regularly review academic resources for public universities
to ensure that they are adequate and appropriate to support the programmes being
offered (Commission for Higher Education , 2003).
4.5 Human Resource in Apparel CAD Technology
4.5.1 Lecturers’ Training in Apparel CAD
To identify human resource/staff training in apparel CAD technology, a questionnaire
was administered to the lecturers in respective departments teaching apparel CAD
technology in the universities. The target universities included Kenyatta, Egerton and
Moi University.
Table 4.12: Frequency distribution of lecturers training in apparel CAD
From the study results, only, 28.6% lecturers had received training in apparel CAD
technology (Table, 4.12). To further determine how the lecturers received training in
apparel CAD technology, a questionnaire was administered. The study results
Mode of training Frequency
N Percent
% On regular programme 3 14.3 On job training 3 14.3 Not trained 15 71.4 Total 21 100.0
56
indicated 14.3% received training on a regular program, while a similar percentage
received their training through on-job training. The results also indicated 71.4% were
not trained. Study findings revealed that few lecturers were trained in apparel CAD
technology. These findings are supported by Regional Agricultural Trade Expansion
Support (2003) study results indicating lack of qualified staff as limitation to the
exploitation of the USA market potential. There is need to develop an explicit human
resource development plan for the apparel industry. Muchangi (2011) also identified
inadequate in-service training of lecturers as the main challenge facing
implementation of curricula. There is need for more formal training of lecturers to
enhance proper training of the students in apparel CAD technology. Similar view was
shared by Skill Fast UK (2006) study; “assessment of apparel industry skill needs”
where they identified a gap exists in core technical skills and knowledge in apparel
CAD due to changes in technology and lack of investment in staff training. They
recommended that there is need to improve the core technical skills of the staff.
4.5.2 Staff Development Programs in Apparel CAD
Table 4.13: Frequency distribution of staff development policies
Staff development policies Frequency
N Percent
% Availability 5 23.8 None 16 76.2 Total 21 100.0
Study results had indicated that most of the lecturers in the departments of apparel
design in the selected universities had not received training in apparel CAD
technology. This was mainly due to limited policies in the universities to enhance in-
service training. Among the lecturer respondents interviewed, 76.2% said there were
no policies geared towards capacity building for apparel CAD training in the
57
universities (Table 4.13). This posed a great problem to the training offered in apparel
CAD technology, which must be addressed by the departments concerned in the
universities. Apparel CAD being a new area in technology, requires that staff
development policies be initiated by the training institutions if they have to keep up
with changes in technology. Results revealed that more training is required to upgrade
the current skills amongst the trainers to enhance training in line with market needs.
O’Neil and Routledge (2003) concur with the results that teachers lack necessary
support to use new technology. A report by the Centre for Research on Information
Technology and Organisation CRITO (1999) indicates that most teachers receive
professional development to learn about “computer technology” and software
mechanics, rather than how to integrate computers into their instruction. Yan and
Florito (2007) study results also indicate lack of adequate experts in training as major
hindrances in the adoption of apparel CAD technology.
4.6 Universities Collaboration with Apparel Industries
Universities and industries interacted in various ways to ensure students were
adequately prepared to work in the industries. The most common areas of
collaboration identified included field visits and practicum/internship/industrial
attachment. However, the level of interaction determined the quality of graduates
joining the labour market.
58
Table 4.14: Frequency distribution of areas of collaboration between universities and the industries
Areas of collaboration Frequency N
Percent %
Practicum/attachment & field visits Curriculum development None
24 1 5
80 3 17
Total 30 100.0%
Table 4.14 showed field visits and practicum as the main areas of collaboration.
Curriculum development was rated the poorest at 3%. This meant that universities
were preparing their academic program in apparel CAD with minimum consultation
with the apparel industry. This might have contributed to low levels of apparel CAD
technology training in the universities as was revealed by the study. The universities
thus ought to consultant with the apparel industry to get to know specific areas that
are in demand. According to the Industrial Adjustment Strategy Committee (1999)
report, the experience of those who offer training in apparel industry is that the
involvement of industry in design and delivery of training programs is essential.
Industry participation in academic and research activities in the universities is
inevitable if university education is to be relevant in the world of work. To enhance
the contribution of industries toward academic and research activities, it is important
that the industry representatives participate in policy and decision making through
university organs such as councils, senate and faculty boards. Universities should also
have representatives in boards and other organs governing industries (Shabani, 1997).
59
Table 4.15: Frequency distribution of other areas of training of labour force Other ways of industry contribution in training of labour force
Frequency N
Percent %
Training of newly recruited staff 14 43.3 On job training 11 36.7 Seminars and workshops 3 10.0 No response 3 10.0 Total 30 100
Apart from field visits and practicum, 43.3% of the heads of departments in the
apparel industries indicated that newly recruited staff were trained before involving
them in actual production activities (Table, 4.15). Another method of training
identified was on-job training as indicated by 43.3% of the respondents. On job
training ensured staff acquired necessary skills used in the production processes and
management of apparel industries. Seminars and workshops were identified as
another method of upgrading skills and training amongst the labour force.
4.6.1 Sourcing of Employees to Work in Apparel CAD-related Jobs
Table 4.16: Frequency distribution of industry sourcing of employees to work in apparel CAD related jobs Sourcing of employees for apparel CAD related jobs
Employees No Response Total N % N % N %
Expatriates 21 70.0 9 30 30 100.0 On job training 20 66.7 10 33.3 30 100.0 Experience 2 6.7 28 93.3 30 100.0 Consultation 1 3.3 26 96.7 30 100.0
Results identified on-job training (66.7%) as another method of ensuring staff is well
prepared for the job market (Table 4.16). Industries also employ expatriates in CAD
related jobs. This was indicated by 70% of industry respondents.
60
4.7 Training Gaps in Apparel CAD Technology Training
4.7.1 Industry Rating of Student Interns
Table 4.17: Frequency distribution of industry heads of departments rating of student interns Students’ training Frequency Percent Not adequately trained 23 76.7 Adequately trained 7 23.3 Total 30 100.0
Table 4.17 indicates industries heads of departments’ response on students who join
them on attachment or are employed. The respondents indicated that 76.7% are not
adequately trained and only 23.3% well-trained. This was a clear indication of the
need to improve apparel CAD training at the universities for purposes of providing
well-trained labour-force to the apparel industry. It was noted by the industries that
there was need to fully involve the students in practicals to gain hands-on experience
during the training.
4.7.2 Rating of Apparel CAD in Training Program
The study results revealed how the students, lecturers and heads of departments in the
apparel industries responded as regards to training received by students in apparel
CAD technology.
Table 4.18: Frequency distribution of students rating apparel CAD training Rating apparel CAD technology
CAD in design
CAD in pattern drafting and grading.
CAD in garment-cutting
CAD in garment-making
N % N % N % N % Poor 19 30.6 14 22.6 8 12.9 7 11.3 Fair 17 27.4 5 8.1 2 3.2 2 3.2 Good 23 37.1 6 9.6 3 4.8 0 0 No response 3 4.8 37 59.7 49 79 53 85.5
Total 62 100 62 100 62 100 62 100
61
Student respondents rated CAD in design as good at 37.1%, while other three areas,
namely CAD in pattern drafting and grading, CAD in garment cutting and CAD in
garment making were poorly rated as good at less than 10% (Table 4.18). This meant
that the student respondents were of the opinions that, the training they received in
apparel CAD did not prepare them adequately to undertake CAD-related jobs in the
apparel industry.
. Table 4.19: Frequency distribution of lecturers rating apparel CAD training
Rating apparel CAD technology
CAD in design
CAD in pattern drafting & grading
CAD in garment-cutting
CAD in garment-making
N % N % N % N % Poor 15 71.5 17 81.0 17 81.0 17 81.0 Fair 2 9.5 0 0 4 19.0 4 19.0 Good 2 9.5 0 0 0 0 0 0 No response 2 9.5 4 19 4 19 4 19
Total 21 100 21 100 21 100 21 100
It was revealed by the lecturers who were preparing the students for the apparel
industry that the training was poor (Table, 4.19). This was indicated by lecturers
rating the training as poor at 71.5% for CAD in design, 81% each for three areas
namely CAD in pattern drafting and grading, CAD in garment cutting and making
respectively. This is an indication of an underlying problem in apparel CAD program,
which the study expects to reveal once all the research questions and hypotheses have
been addressed.
62
Table 4.20: Frequency distribution of industry heads of departments rating of apparel CAD training
Rating apparel CAD technology
CAD in design
CAD in pattern drafting & grading.
CAD in garment-cutting
CAD in garment-making
N % N % N % N % Poor 4 13.3 2 6.7 2 6.7 5 16.7 Fair 8 26.7 7 23.3 8 26.7 16 53.3 Good 1 3.3 0 0 0 0 0 0 No response 17 56.7 21 70.0 20 66.7 9 30.0
TOTAL 30 100 30 100 30 100 30 100
The heads of departments in the apparel industries were required to rate the training of
students at the universities in four areas of apparel CAD technology (table 4.20). Only
3.3% indicated training in CAD in design as good while most indicated training as
fair. Those who indicated CAD in garment making as fair accounted for 53.3%,
followed by 26.7% of the respondents who also indicated CAD in design and garment
cutting as fair respectively. From the study results, it is clear that majority of the
respondents indicated apparel CAD training as fair. This meant the training in apparel
CAD the students received did not adequately address the needs of the apparel
industries.
The students, lecturers and head of departments indicated that the training the students
received was inadequate to prepare them for CAD-related jobs in the apparel
industries. Similar view is shared by MacAulay (1993) study findings, which
indicated that students are finding themselves not adequately prepared on specialized
industry software upon graduation. Although survey of apparel industries in Kenya
had indicated that apparel CAD technology was used, the training students received
had failed to prepare the graduates adequately to undertake jobs in apparel industries
63
(ILO, 2000). This indicates that the training program is deficient and therefore, the
apparel design departments need to address the gaps highlighted in the study. The
results also agree with Desiree (2003) study findings on CAD training needs, which
found out that although CAD was offered, not enough was accomplished in CAD
training to ensure students were fully CAD literate. This meant that the number of
students leaving apparel design departments had no sufficient knowledge to take up
CAD-related jobs in the textile and apparel industries. The researcher recommended
improvement of CAD resources, availing of CAD software programs and
development of apparel CAD curricula.
4.7.3 Ranking of CAD Training Needs
Table 4.21: Frequency distribution of students’ ranking of apparel CAD training needs
The study results indicated that the student respondents identified provision of ICT
hardware and software as the most urgent need at 41% (Table, 4.21). This was
followed by the need for provision of apparel CAD design studio at 22.6%. Review
curriculum and provision of adequate teaching/learning resources were also identified
as areas that needed to be addressed at 12.9% respectively.
Ranking of CAD training needs Frequency (N)
Percent %
ICT hardware/software CAD design studio & equipment Review curriculum Teaching/Learning Resources CAD Trained Lecturers No response
25 14 8 8 6 1
41.0 22.6 12.9 12.9 9.7 1.6
Total 62 100.0%
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Table 4.22: Frequency distribution of Lecturers ranking of CAD training needs Lecturers’ ranking of CAD training needs
Frequency (N)
Percent %
CAD Trained Lecturers (Retrain/Retooling) ICT hardware/software Teaching/Learning Resources CAD design studio & equipment Review curriculum University-Industry links
6 5 4 2 2 2
28.5 24
19.0 9.5 9.5 9.5
Total 21 100.0%
The respondents indicated the need for lecturers in the departments of apparel design
to be trained in the cutting edge technologies in apparel CAD (Table 4.22). Twenty
four percent indicated the need for providing adequate hardware and software for
training in apparel CAD technology. Availability of teaching and learning resources
were ranked third at 19% while design studio, review of curriculum and university-
industry links were rated 9.5% respectively.
Table 4.23: Frequency distribution of industry identification of training gaps
Heads of departments in the apparel industries indicated student interns and graduates
had minimal practical skills (Table 4.22). This was indicated by 76.7% of industry
respondents. Others included theory work and basic machine use.
Training gaps in apparel CAD technology
Frequency (N)
Percent %
Practical skills Theory work Basic machine use No response
23 4 1 2
76.7 13.3 3.3 6.7
Total 30 100.0%
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4.8 Hypotheses Testing
Ho-1 There is no significant difference between computed means of the students,
lecturers and the industry respondents in response to students’ knowledge in
apparel CAD technology training.
Table 4.24: Comparison of means between the respondents on student knowledge in apparel CAD Respondents Mean Std
Deviation F-value
2.773
Df
112
P value
.067 Students 1.596 0.615 Lecturers 1.810 0.422 Industry 1.566 0.733 *p<0.05
One way analysis of Variance (ANOVA) results showed that the lecturers had a mean
of 1.810 followed by students with 1.596 and industry with 1.566 (Table 4.24). The
results obtained were F=2.773, df=2, 112; p=0.067 implying that there was a very
high evidence to show that there was no significant difference between the means of
the three groups. P-value (p=0.067) results showed that the difference was not
significant, hence, the hypothesis was retained. Therefore, the industry concurred with
the students and lecturers that the training students received was not adequate to
prepare them to work in apparel industries.
The results agree with Wilkinson (1992), survey of apparel industry, where the study
identified lack of computing and electronic expertise, shortages of appropriately
skilled labour and cost of training as some of the reasons of slow uptake of
technology. The study concluded that graduates were not appropriately trained to
handle CAD-related jobs in the apparel industry. This is further supported by a study
carried out by Yan and Florito (2002) indicating lack of adequate experts in apparel
66
CAD and appropriate training as main hindrances in its usage. Significant scope,
therefore, exists for the industries and institutions of higher learning to play a
significant role in facilitating the adoption of apparel CAD technology.
Ho-2 There is no significant difference between the computed means of the
students, lecturers and industry’s respondents in response to the apparel CAD
training program.
Table 4.25: Comparison of means between the respondents’ responses of the apparel CAD training program Respondents Mean Std
Deviation F-value
10.068
df
102
P value
.001 Students 2.109 0.786 Lecturers 2.600 0.681 Industry 3.000 0.000 *p<0.05
Findings show that the industry had a mean of 3.000 followed by lecturers with 2.600
and the students with mean of 2.109 (Table, 4.25). One way analysis of Variance
(ANOVA) investigated rating among the three groups. The F=10.068, df=2, 102;
p=0.001 implying that there was very high evidence showing that the mean level of
rating of apparel CAD technology training was significantly different among the three
groups. To investigate how the rating differed, multiple comparisons (pair wise test)
were done using Bonferroni test. This test revealed that the industry had a p value of
(0.001) which differed with the students and lecturers at (P value =0.004)
respectively. Therefore, there was no difference between lecturers and students rating
of the training program (P value =0.004). It was evident that the industry had
indicated that the training program was inadequate while the lecturers and students
had pointed out that the training program adequately addressed the needs of labour
67
market. This can be attributed to limited collaboration between the universities and
the apparel industries in regard to curriculum development.
Ho-3 There is no significant difference between lecturers and students response to
the availability of teaching/learning resources.
A T-test technique is used to test whether there are significant differences between
two means derived from two samples or groups at a specified probability level
(Mugenda & Mugenda, 1999). In this study the independent t-test was employed to
test the differences between students and lecturers rating of the availability of
teaching/learning resources. This is because an independent t-test shows whether or
not the difference between two samples means is significant (Hinton, 1995).
Table 4.26: Comparison of students and lecturers rating of teaching/learning resources Rating availability of teaching /learning resources
Mean Std. Deviation
T-Value 2.828
df 80
Sig. T 0.001
Students 1.56 .914
Lecturers 0.98 .361 *p<0.05
Table 4.26 results showed differences between students and lecturers rating
availability of teaching and learning resources. The students’ mean tended to be
higher than the lecturers. Independent Samples T-Test were conducted and test results
were; t (80) =2.828, P-value= 0.001 at 95% confidence level therefore the null
hypothesis was rejected. It was concluded that there was a significant difference
between students and lecturers rating of availability of teaching learning resources for
apparel CAD training.
68
4.9 Summary
The study results indicate that 96.7% of the student respondents were aware of
apparel CAD technology. This was mainly due to accessibility of information from
internet. Areas of apparel CAD technology covered by the students included CAD in
design, AutoCAD, CAD in pattern drafting and grading, CAD in garment cutting and
CAD in garment making. Much attention was given to CAD in design and AutoCAD
at 45.2% and 29% respectively. This is because they are basic introductory courses in
apparel CAD technology and are also easily available in universities to students
undertaking graphic design, fine arts and engineering courses. The course documents
also indicated that universities mainly dealt in basic introductory courses especially
for CAD in design and AutoCAD.
Desktop computers were most common type of hardware available during training,
though only 23.8% of the respondents indicated that the computer hardware and
software were available. This meant that computer hardware and software were few.
This made the apparel design departments use facilities from other departments. In
Kenyatta University, the students mostly used computers from the Fine Arts
Department, while in Egerton University the students used computers from the
Engineering Department and in Moi University the students used the school computer
lab. School-based students indicated they used facilities from DIT to study apparel
CAD program.
Most of the respondents revealed that learning materials for apparel CAD training
were inadequate. Lecture notes were the most common method of availing learning
materials to students as indicated by 30.5%, followed by giving of handouts to
69
students. The results also indicated that textbooks and journals were few, but internet
services were available in the libraries and computer rooms.
From the study results, only 28.6% of the lecturers’ respondents from the department
of apparel design had received training in apparel CAD technology, which they either
received as training on a regular program or through on-job training. Therefore few
staff were available to train students in apparel CAD technology, and hence the need
for appropriate staff development policies. The research findings indicated that 23.8%
said that there existed development policies, but they were not actively adhered to.
Apparel CAD, being a new area in technology, requires that staff development
policies be initiated by the training institutions if they have to keep up with changes in
technology.
Areas of collaboration identified included field visits, practicum/internship and
curriculum development. Curriculum development was the lowest at 3%. This meant
that industry input in curriculum development was minimal. This might have
contributed to low levels of apparel CAD technology training adoption in the
universities as was revealed by the study. The universities thus ought to consult with
the apparel industry to get to know of the specific areas in demand.
The study results showed that only 23.3% of the industry interns were well-trained.
This was a clear indication of the need to improve apparel CAD training at the
universities for purposes of providing well-trained labour-force to the apparel
industry. It was noted by the industries that there was need to fully involve the
students in practicals to gain hands-on experience during the training. Students rated
70
CAD in design as good at 37.1%, while other three areas, namely CAD in pattern
drafting and grading, CAD in garment-cutting and CAD in garment-making were
poorly rated as good at less than 10%. This meant that the student respondents
indicated that the training they received in apparel CAD did not prepare them
adequately to undertake CAD-related jobs in the apparel industry.
Lecturers rated training as poor at 71.5% for CAD in design, 81% each for CAD in
pattern drafting and grading, CAD in garment-cutting and garment-making
respectively. This is an indication of an existing problem in apparel CAD training
program. The heads of departments in the apparel industries indicated training in
CAD in design as good at 3.3% while most indicated training as fair. Those who
indicated CAD in garment-making as fair accounted for 53.3%, followed by 26.7% of
the respondents who also indicated CAD in design and garment cutting as fair
respectively. From the study results, it is clear that, majority of the respondents
indicated apparel CAD training as fair. This meant that the training in apparel CAD
the students were receiving, did not adequately address the apparel CAD needs of the
apparel industries.
The study results indicated that the student respondents identified provision of ICT
hardware and software as the most urgent need at 41%. This was followed by the need
for provision of apparel CAD design studio at 22.6%. Review of curriculum and
provision of adequate teaching/learning resources were also identified as areas that
needed to be addressed at 12.9% respectively.
Twenty eight percent of the lecturer respondents in the department of apparel design
indicated the need for lecturers to be trained in the cutting edge technologies in the
71
market. Twenty four percent pointed out the need for providing adequate ICT
hardware and software for training in apparel CAD. Availability of teaching and
learning resources were ranked third at 19% while design studios, review of
curriculum and university-industry links were rated at 9.5% respectively. Industry
respondents indicated practical skills were insufficient. This was indicated by 76.7%
of industry respondents. Others areas including theory work and basic machine use
were also perceived to be weak. One way analysis of Variance (ANOVA) results
indicated that the industry concurred with the students and lecturers that the training
students received was not adequate to prepare them to work in apparel industries.
72
CHAPTER FIVE
CONCLUSION AND RECOMMENDATIONS
5.0 Introduction
This chapter gives an in-depth analysis of the results obtained by highlighting the
gaps that existed in apparel CAD training and hence, recommending necessary
measures to help in improving apparel CAD training.
5.1 Summary
1. The study showed that although majority of students were aware of apparel
CAD technology, the training they received was unsatisfactory to prepare
them for the world of work. The same view was shared by lecturers in their
departments.
2. It was noted that appropriate teaching and learning resources were inadequate
to enhance training in the apparel CAD technology.
3. The study also showed that majority of lecturers had not received the
necessary training to handle apparel CAD program.
4. Staff development policies were inadequate to ensure lecturers received the
state-of-art technologies like apparel CAD technology.
5. Collaboration between universities and the apparel industries were limited to
student attachments and field visits.
6. The industries concurred with students and lecturers that the training the
students received was not adequate for them to undertake apparel CAD-related
jobs.
73
5.2 Implications of the Findings
The research findings have implications for theory, policy and further research. As far
as theory is concerned, the study has significant contribution to the understanding of
apparel CAD technology training in the universities. The study has brought to the
limelight fundamental issues relating to apparel CAD training in the universities that
have adopted its training. The study findings described the status of teaching/
learning resources, human resources and apparel CAD program. As for policy, the
research findings suggest that continuous and sustained programs in apparel CAD
technology largely depend on provision of teaching and learning resources, adequate
manpower and appropriate curriculum. Therefore, while it is recognized that adoption
of apparel CAD technology requires support from stakeholders at various levels, there
is need for universities to provide requisite, resources both human and financial. This
can be done through staff development programs for human resource and industry-
university collaboration for technical support. At the moment, opportunities for
professional development are unplanned and uncoordinated. Staff development
should be incorporated in the strategic plan of both the universities and the
departments and budgeted for. The findings provide a good background for further
research in apparel CAD training needs in order to improve the curriculum to suit the
labour market.
5.3 Conclusion
i. Although apparel CAD technology is taught in universities, the results
obtained from this study clearly indicated that there is deficiency in apparel
CAD technology training. The study indicated that in most universities, only
two units in apparel CAD were taught during the four years of study which
74
were not adequate in preparing students for CAD-related jobs in the market.
The results further indicated that the training concentrated on basic
introductory courses like CAD in design, ignoring specific apparel CAD
programs used in the apparel industries. There is need to enhance training in
line with market needs and this calls for effective adoption of apparel CAD
technology training this being the modern concept in apparel production
processes.
ii. Teaching/learning resources were also inadequate making training both in
practical and theoretical areas difficult. Few desktop computers were
provided, making it difficult for all students to access them. Furthermore these
computers lacked appropriate apparel CAD software.
iii. The fact that only minority of academic staff were trained in apparel CAD
technology clearly indicated that there was inadequate trained human
resources to handle the apparel CAD technology program at the university
level.
iv. There was lack of appropriate staff development policies to enhance training
in apparel CAD technology. Inappropriate training structures had created
problems which trickled down to the industry level, where trained graduates
could not meet the industry labour requirements for apparel CAD technology-
related employment.
75
5.4 Recommendations for Policy and Practice
i. It’s clear from the study that a gap exists in training that needs to be addressed
by universities and the industries if Vision 2030 is to be achieved, and if the
training is to promote students’ job opportunities in apparel industries. It is
therefore necessary to critically address the training in apparel CAD
technology by reviewing the apparel CAD curriculum, and determining the
necessary teaching/learning and human resources.
ii. There is need to involve the apparel industries in the design and delivery of
apparel CAD technology training. This will give direction and cohesion to
training as well as initiating basic training and professional development
initiatives. This will help to relate what is learned to the world of work.
iii. Availability of the state-of-the-art apparel CAD technology teaching and
learning resources will enable students to do projects in real life settings.
Training facilities that are economical, more flexible, more modular and better
adapted to the training needs are required.
iv. The delivery of training programs and internet-based courses (e-learning)
should focus on bridging the gap in knowledge and best practices in the
apparel industry.
5.5 Recommendations for Further Research
i. An evaluation of the apparel CAD curriculum needs to be conducted in all
training institutions in Kenya
76
ii. Further research needs to be carried out to establish collaboration between the
apparel industries and universities and other training institutions in Kenya.
77
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APPENDICES
Appendix I: Student Questionnaire
The Respondent,
REF: REQUEST FOR FILLING THE QUESTIONNAIRE.
I’m a Masters student in Kenyatta University, Department of Fashion Design and Marketing carrying out a research on “Assessment of the Adoption of Apparel CAD Technology Training in Selected Public Universities in Kenya”.
I will highly appreciate if you contribute by answering this questionnaire. The information given will be confidential and will only be used for the purpose of the study. Thank you.
Instructions: Answer ALL questions
Personal Details
Age-------------------------------------------------------------------------------------------------
Sex--------------------------------------------------------------------------------------------------
Year of study--------------------------------------------------------------------------------------
Questions 1) Are you aware of apparel CAD programs in fashion design and clothing?
Yes No
2) If yes, list down areas of apparel CAD you are aware of?
---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ----------------------------------------------------------------------------------------------
86
3) Which units did you cover in apparel CAD studies? Name the units and their codes. ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ----------------------------------------------------------------------------------------------
4) Which areas of apparel CAD listed below did you cover in your syllabus? Tick
where appropriate.
CAD in design
CAD in pattern drafting and grading.
CAD in Garment-cutting
CAD in Garment-making Others (specify) ----------------------------------------------------------------------------------- ------------------------------------------------------------------------------------------------------- ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- 5) Are they taught as separate units or combined with other units?
CAD in design CAD in pattern drafting and grading.
CAD in Garment-cutting CAD in garment-making
6) In each case below did you cover theory or practical or both? Tick where appropriate.
CAD in design CAD in pattern drafting and grading.
Theory Practical Both
Separate unit Combined
87
CAD in garment-cutting CAD in garment-making
Others(specify)--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- 7) How would you rate apparel CAD training you have received in each category
listed below?
CAD in design CAD in pattern drafting and grading. CAD in garment-cutting
CAD in garment-making
8) Does the institute have a design-studio where apparel CAD practicals are
undertaken? Yes No
9) If Yes, answer question 11, if No, how were equipments, facilities, computer
hardware and software provided during the study.
--------------------------------------------------------------------------------------------------- --------------------------------------------------------------------------------------------------- --------------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------------
10) List down equipments, facilities, computer hardware and software you used when studying apparel CAD in each area below.
CAD in design.----------------------------------------------------------------------------
---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ----------------------------------------------------------------------------------------------
5. E
xcel
lent
4. V
ery
good
3. G
ood
2. F
air
1. U
nsat
isfa
ctor
y
88
CAD in pattern drafting and grading.-------------------------------------------------- ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ----------------------------------------------------------------------------------------------
CAD in garment-cutting.----------------------------------------------------------------
---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ----------------------------------------------------------------------------------------------
CAD in garment-making.----------------------------------------------------------------
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
11) Do you feel that equipment, facilities, computer hardware and software provided
are adequate for each category listed below?
CAD in design
CAD in pattern drafting and grading.
CAD in garment-cutting
CAD in garment-making
12) How do you rate the availability of equipment, facilities, computer hardware and
software for each category listed below?
CAD in design
CAD in pattern drafting and grading.
CAD in garment-cutting CAD in garment-making
Yes No
5. E
xcel
lent
4. V
ery
good
3. G
ood
2.
Fair
1. U
nsat
isfa
ctor
y
89
13) Which of the following learning materials are available to you during training?
CAD in design CAD in pattern drafting
and grading.
CAD in garment-cutting
CAD in garment-making Others(specify)--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- 14) How do you rate the availability and accessibility of learning materials listed
below?
Journals
Handouts
Textbooks
Lecture notes
CD-ROM Internet sources
e-learning
Jour
nals
Han
dout
s
Text
book
s
Lect
urer
not
es
CD
RO
M
e-le
arni
ng
Inte
rnet
sour
ces
5. E
xcel
lent
4. V
ery
good
3. G
ood
2. F
air
1. U
nsat
isfa
ctor
y
90
15) Have you ever undertaken an industrial attachment or practicum in an apparel industry using apparel CAD program in their manufacturing process?
Yes No If yes, did you have an opportunity to work using apparel CAD process? Yes No 16) Which of the categories indicated below did you have an opportunity to work
with?
CAD in design
CAD in pattern drafting and grading.
CAD in garment-cutting
CAD in garment-making Others(specify)---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
17) How would you rate the training you received in college in preparing you for
apparel CAD related jobs in the industry?
CAD in design
CAD in pattern drafting and grading.
CAD in garment-cutting
CAD in garment-making
5. E
xcel
lent
4. V
ery
good
3. G
ood
2. F
air
1. U
nsat
isfa
ctor
y
91
18) How would you rate the training program you undertook for preparing you to work in the textile and apparel industry?
5 Excellent
4 Very good
3 Good
2 Fair
1 Unsatisfactory
19) What would you like to be improved in apparel CAD training? -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
92
Appendix II: Lecturer Questionnaire
Respondents Letter Veronica Wambui Kamau, Kenyatta University, Box 43844-00100, NAIROBI
Dear Sir/Madam, REF: REQUEST FOR FILLING THE QUESTIONNAIRE.
I’m a Masters student in Kenyatta University, Department of Fashion Design and Marketing carrying out a research on “Assessment of the Adoption of Apparel CAD Technology Training in Selected Public Universities in Kenya”. I will highly appreciate your contribution in answering the questionnaire attached. The information given will be held confidential.
Thank you Yours’ Faithfully, Kamau V. W.
Instructions: Answer ALL questions 1. Is apparel CAD taught in this institution?
Yes No 2. Do you teach apparel CAD program in this institution?
Yes No 3. Have you received any training in apparel CAD? Yes No 4. How did you receive this training?
93
On a regular program
On job training
Apparel CAD training organized by the department
Others(specify)------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ 5. Are there staff development policies that allow one to get training in apparel
CAD? Yes No
6. How would you rate apparel CAD training taught in this institute in each category
listed below?
CAD in design
CAD in pattern drafting and grading.
CAD in garment-cutting
CAD in garment-making 7. Is there a design-studio in the department where students undertake apparel CAD
practicals? Yes No
5. E
xcel
lent
4. V
ery
good
3. G
ood
2. F
air
1. U
nsat
isfa
ctor
y
94
8. How do you rate the availability of equipment, facilities, computer hardware and software for each category listed below?
CAD in design
CAD in pattern drafting and grading.
CADCAM in garment-cutting
CADCAM in garment-making 9. Which learning materials are available to students for learning purposes in the
following areas?
CAD in design
CAD in pattern drafting and grading.
CAD in garment-cutting
CAD in garment-making Others(specify)--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
5. E
xcel
lent
4. V
ery
good
3. G
ood
4. F
air
1. U
nsat
isfa
ctor
y
Jour
nals
Han
dout
s
Text
book
s
Lect
urer
not
es
CD
RO
M
e-le
arni
ng
Inte
rnet
Sou
rces
95
10. How do you rate the availability and accessibility of learning materials listed below?
Journals
Handouts
textbooks
lecturer notes CD-ROM Internet sources
e-learning
11. How would you rate the training undertaken by students in college in preparing
them for apparel CAD related jobs in the industry?
CAD in design
CAD in pattern drafting and grading.
CAD in garment-cutting
CAD in garment-making
5. E
xcel
lent
4. V
ery
good
3. G
ood
2. F
air
1. U
nsat
isfa
ctor
y
5. E
xcel
lent
4. V
ery
good
3. G
ood
2. F
air
1. U
nsat
isfa
ctor
y
96
12. How would you rate the training program undertaken by students in preparing them to work in the textile and apparel industry?
5 Excellent
4 Very good
3 Good
2 Fair
1 Unsatisfactory
13. In which areas do apparel design department in this university interact with the
industry?
Field visits
Practicum
Curriculum development Others(specify)------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ 14. What would you like to be improved in apparel CAD training? --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
97
Appendix III: Industry Questionnaire
Respondents Letter
Veronica Wambui Kamau, Kenyatta University, Box 43844-00100, NAIROBI
Dear Sir/Madam, REF: REQUEST FOR FILLING THE QUESTIONNAIRE.
I’m a Masters student in Kenyatta University, Department of Fashion Design and Marketing carrying out a research on “Assessment of the Adoption of Apparel CAD Technology Training in Selected Public Universities in Kenya”. I will highly appreciate your contribution in answering the questionnaire attached. The information given will be held confidential and will only be used for the purpose of the study.
Thank you Yours’ Faithfully, Kamau V. W.
Instructions: Answer ALL questions Questions 1. Are the students you receive for practicum or industrial attachment or
employment adequately prepared to work in the industry? Yes No 2. Which areas listed below do you use apparel CAD technology in production
process?
CAD in designing
CAD in pattern drafting and grading.
CAD in cutting-processes
CAD in sewing-processes
98
Others(specify)---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- 3. Which equipment, facilities, computer hardware and software are used in your
firm for apparel CAD related jobs in each category listed below? .
CAD in designing.----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
CAD in cutting-processes.--------------------------------------------------------------
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
CAD in sewing-processes.------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
4. Do they have knowledge in apparel CAD programs? Yes No 5. How would you rate training received by the trainees who you receive in each
category listed below? CAD in designing CAD in pattern drafting and grading CAD in cutting-processes CAD in sewing-processes
5. E
xcel
lent
4. V
ery
good
3. G
ood
2. F
air
1. U
nsat
isfa
ctor
y
99
Others(specify)---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- 6. How would you rate the training undertaken by students in college in preparing
them for apparel CAD related jobs in the industry?
CAD in designing
CAD in pattern drafting and grading
CAD in cutting-processes
CAD in sewing-processes 7. How would you rate the training program undertaken by students in preparing
them to work in the textile and apparel industry? 5 Excellent
4 Very good
3 Good
2 Fair
1 Unsatisfactory
8. In which areas do clothing, textiles, and fashion design departments in universities interact with the industry?
Field visits
Practicum
Curriculum development
5. E
xcel
lent
4. V
ery
good
3. G
ood
2. F
air
1. U
nsat
isfa
ctor
y
100
Others(specify)-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
9. Are you involved in curriculum development in colleges and universities?
Yes No 10. Specify which areas the students are well-prepared. ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- 11. Which areas can you identify where the gaps or deficiencies exist in the training
programs in relation to the needs of the industry? ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ 12. Where do you get employees to work in apparel CAD related jobs? ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ 13. In which ways do you contribute to training institutions to ensure appropriate
labour force is adequately prepared to work in the garment industries? -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
101
14. As employers of the graduates from these institutions, what changes would you
like to see in the apparel CAD training programs? ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- 15. Feel free to make any additional comment about apparel design trainees as future
employees of apparel industry.
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
102
Appendix IV: Observation Checklist for the Industries
1. Apparel CAD equipment and facilities available ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ----------------------------------------------------------------------------------------------
2. CAM equipment and facilities available. ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ----------------------------------------------------------------------------------------------
3. Technical staff for apparel CAD program. ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- 4. Sources of staff to work in apparel CAD jobs.
---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------------------- --------------------------------------------------------------------------------------------- --------------------------------------------------------------------------------------------- --------------------------------------------------------------------------------------------- ----------------------------------------------------------------------------------------------
103
Appendix V: Observation Checklist for Training Institutions
1.0 Apparel CAD systems available -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- 2.0 Design studio --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- 3.0 Equipments --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- 4.0 Computers
Hardware --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Software ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
5.0 Learning resources -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
104
Books --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Journals --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- E-learning services ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Internet sources ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Others specify ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
105
Appendix VI: List of Apparel Industries
Integrated and Clothing Mills
1. Sun Flag, Textiles and Knit Wear Ltd.
2. MidCo Textile (EA) Ltd.
3. Ken Knit (Kenya) Ltd
4. Bedi Investments
5. Vaja Manufacturers Ltd.
6. Jadees knitting Factory Limited
7. Straight Line Enterprise Ltd.
8. Alpha Knits Ltd.
9. Wild Elegance Ltd
Cut Make and Trim (CMT) EPZ Industries
1. Global Apparels Kenya EPZ Ltd.
2. Apex Apparels EPZ Ltd.
3. Orange Styles EPZ Ltd
4. Sahara Stitch EPZ Ltd
5. Rising Sun (K) EPZ Ltd
6. Mega Garment (K) EPZ Ltd
7. Rolex EPZ Ltd
8. Baraka Apparel EPZ Ltd
9. Protex EPZ Ltd
10. Birch Investments (EPZ) Ltd
11. Tri-Star EPZ Ltd
106
Fully Automated EPZ Industries
1. United Aryan (EPZ) Ltd
2. Ricardo (EPZ) International
3. AllTex EPZ Ltd
4. Ashton Apparel EZ Ltd
5. JAR Kenya EPZ Ltd
6. Kapric Apparels EPZ Ltd
7. California Link EPZ Ltd
8. Union Apparels EPZ Ltd
9. Sin Lane EPZ Ltd
10. Mirage Fashion Wear EPZ Ltd
11. Mega Industries Kenya EPZ Ltd
107
Appendix VII: Research Authorization from National Council for Science and Technology
108
Appendix VIII: Research Permit from Export Processing Zone Authority
109
Appendix IX: Reliability Analysis
Knowledge in apparel CAD technology
Reliability Statistics
Cronbach's
Alpha
Cronbach's
Alpha Based on
Standardized
Items N of Items
.872 .845 6
summary Item Statistics
Mean Minimum Maximum Range
Maximum /
Minimum
Item Variances .776 .247 1.142 .895 4.619
Inter-Item Correlations .118 -.144 .346 .489 -2.408
Summary Item Statistics
Variance N of Items
Item Variances .104 6
Inter-Item Correlations .020 6
Scale Statistics
Mean Variance Std. Deviation N of Items
22.6993 7.184 2.68022 6
ANOVA with Cochran's Test
Sum of Squares df Mean Square Cochran's Q Sig
Between People 170.012 142 1.197
Within People Between Items 856.476 5 171.295 454.400 .000
Residual 491.191 710 .692
Total 1347.667 715 1.885 Total 1517.678 857 1.771
Grand Mean = 3.7832
110
Apparel Training program.
Reliability Statistics
Cronbach's Alpha
Cronbach's Alpha Based on
Standardized Items N of Items
.896 .891 6
Summary Item Statistics
Mean Minimum Maximum Range
Maximum /
Minimum
Item Variances 3.068 2.114 4.242 2.127 2.006
Inter-Item Covariances 1.499 .035 3.200 3.165 91.986
Summary Item Statistics
Variance N of Items
Item Variances .635 9
Inter-Item Covariances .752 9
Scale Statistics
Mean Variance Std. Deviation N of Items
30.3261 135.558 11.64294 9
ANOVA with Cochran's Test
Sum of Squares df Mean Square Cochran's Q Sig
Between People 677.790 45 15.062
Within
People
Between Items 24.000 8 3.000 15.003 .059
Residual 564.667 360 1.569
Total 588.667 368 1.600 Total 1266.457 413 3.066 Grand Mean = 3.3696
Intraclass Correlation Coefficient
95% Confidence Interval
IntraclassCorrelationa Lower Bound Upper Bound
Single Measures .489b .375 .618
Average Measures .896c .844 .936
111
Two-way mixed effects model where people effects are random and measures effects are fixed.
a. Type C intraclass correlation coefficients using a consistency definition-the between-measure
variance is excluded from the denominator variance.
b. The estimator is the same, whether the interaction effect is present or not.
c. This estimate is computed assuming the interaction effect is absent, because it is not estimable
otherwise.
Intraclass Correlation Coefficient
F Test with True Value 0
Value df1 df2 Sig
Single Measures 9.603 45 360 .000
Average Measures 9.603 45 360 .000
Two-way mixed effects model where people effects are random and measures effects are fixed.
Availability of Teaching Resources
Reliability Statistics
Cronbach's Alpha
Cronbach's Alpha Based on
Standardized Items N of Items
.925 .920 5
Summary Item Statistics
Mean Minimum Maximum Range Maximum / Minimum
Item Variances .818 .264 1.077 .813 4.083
Inter-Item Covariances .406 -.148 .923 1.071 -6.222
Summary Item Statistics
Variance N of Items
Item Variances .047 5
Inter-Item Covariances .058 11
Scale Statistics
Mean Variance Std. Deviation N of Items
19.5714 53.648 7.32450 5
112
ANOVA with Cochran's Test
Sum of Squares df Mean Square Cochran's Q Sig
Between People 63.403 13 4.877
Within
People
Between Items 7.494 10 .749 17.173 .071
Residual 53.597 130 .412
Total 61.091 140 .436 Total 124.494 153 .814
Grand Mean = 1.7792
Intraclass Correlation Coefficient
95% Confidence Interval
IntraclassCorrela
tiona Lower Bound Upper Bound
Single Measures .496b .308 .734
Average Measures .915c .831 .968
Two-way mixed effects model where people effects are random and measures effects are fixed.
a. Type C intraclass correlation coefficients using a consistency definition-the between-measure
variance is excluded from the denominator variance.
b. The estimator is the same, whether the interaction effect is present or not.
c. This estimate is computed assuming the interaction effect is absent, because it is not estimable
otherwise.
Intraclass Correlation Coefficient
F Test with True Value 0
Value df1 df2 Sig
Single Measures 11.829 13 130 .000
Average Measures 11.829 13 130 .000
Two-way mixed effects model where people effects are random and
measures effects are fixed.
