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Qualitative Research in EducationAssumptions of Qualitative Research

Difference between Qualitative & Quantitative Research

By

Laraib

(15061701-005)

M.Phil 1st

Supervised by

Dr. Syed Shafqat Ali shah

Department of Education

UNIVERSITY OF GUJRAT

Session 2015-2017

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Table of Contents

1 Introduction ..................................................................................................................................... 42 Quantitative Researches .................................................................................................................................... .43 Qualitative Researches ..................................................................................................................................... 54 Summaries of Differences ..................................................................................................................................... 65 Mixed Method Approach ......................................................................................................................................76. Differences between Qualitative and Quantitative Inquiry

…………………………………………………………………………………………8

7. Difference Between Qualitative & Quantitative Research…………………………………………………………………………………………108. References…………………………………………………………………………………………11

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Assumptions in Qualitative Research

By Laraib M.Phil Scholar

1. IntroductionThe motivation of quantitative and qualitative research in two different paradigms – the

positivism and constructionist or post-positivism, accounts to a great extent for their

controversial discussion. Quantitative research can be described as a cause-effect relationship,

searching for standardization, reproducibility, and measurability. Qualitative research aims at

understanding and interpreting behaviors’, contexts, and interrelations. At first sight, these two

approaches to the understanding of science seem to be competing and even incompatible; there

are many publications contributing to the elaboration of their differences. However, lately there

have been considerations that quantitative and qualitative methods are two sides of one coin and

can complement each other in certain research situations. This summary gives a short overview

of these two methodologies, their strengths and weaknesses in the explanation of social realities,

and finally discusses a new approach to science, namely the combination of both.

2. Quantitative Researches:There are many explanations to quantitative research, yet Aliaga & Gunderson (2002) describe it

as explaining a phenomenon by collecting quantitative (numerical) data that are analyzed using

mathematically based methods such as statistics. A common misconception is that quantitative

data does not require data that is naturally available in quantitative form. Non-quantitative data

(such as beliefs and/or attitudes) can be transformed into quantitative form by using

measurement instruments such as Likert scales. Despite its limitations, quantitative methods

have been more prominent in social sciences traditionally due to the fact that natural sciences

and their standard methods were seen as a model in this field (Flick, 2006). Yet, perhaps it was

the Chicago school that gave rise to widespread use of qualitative research in social sciences;

however, this did not last too long as Columbia school disrupted this convention and laid the

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foundations of today, where the debate is still not fully resolved. Today, quantitative research is

often placed in opposition to qualitative research, still a legacy of “clashes of schools”, dating

back to early 1900s (Hamel, Dufour & Fortin, 1993). The incompatible worldviews underlying

quantitative and qualitative methods gave birth to this ‘paradigm war’. It is often argued that the

quantitative research is more realistic and objective as compared to the qualitative research and

the researchers’ consensus is to use quantitative methods if there is a hypothesis to test, using

deductive reasoning.

The main strength of quantitative research is that it is neutral and easily generalizable; however,

it is challenging to gauge the theoretical constructs (e.g. innovation) in social sciences and

proxying them with several variables usually undermines establishing causality.

3. Qualitative Researches:The qualitative turn in social research took place during the 70`s as a countermovement to

quantification, the landmark of natural sciences (Mayring 2002). This turn addressed the critique

of quantitative methods and research strategies, often judged as too standardized in order to

reflect the facets of social reality. Instead of testing, measuring, and experimenting, qualitative

research aims at understanding the subject of study (Mayring 2002). Creswell defines qualitative

research as the process of understanding a social or human phenomenon, based on

methodological research traditions. Researchers aim at generating a complex, holistic view, at

analyzing and describing the standpoint of the subjects within a natural context (Creswell 1998).

Hoffmann-Riem even advocates to let the theoretical structure of the object of research emerge

from the research subjects (1980, p.343). In the meanwhile qualitative social research has turned

into an interdisciplinary point of reference for new qualitative approaches (Mayring 2002).

Several lines of research can be seen as the roots of qualitative methods. Aristotle is regarded as

their prime father; for him historic and evolutionary developments as well as inductive

approaches belong to the understanding of science. Further precursor of qualitative thinking is

Gianbattista Vico who sees the practical and the truth as non-universal, but dependant on time

and space. Hermeneutics, as the effort to develop a foundation for scientific text interpretation, is

as well seen as one of the originators of qualitative approaches (Mayring 2002).

The main strength of qualitative research is its ability to create knowledge about new

phenomenon and complex interrelations that have not yet been researched thoroughly or at all

(Seipel & Rieker 2003). In such cases it is per definition a suitable approach for theory building,

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elaboration, and testing, where theory implies a reference to context. Adequate methods for data

collection within a qualitatively-oriented research project are e.g. problem-centred or narrative

interviews, group discussions, semi-structured interviews, archival or content analysis. Most of

these are very time-consuming due to two reasons: 1) the emphasis of qualitative research

methods is on context and verbal access to data (Hoffmann-Riem 1980) and 2) the research

process is circular and interactive. An inevitable consequence is the rather small sampling when

compared to quantitative methods. The exploratory and explanatory character of qualitative

research becomes apparent through the flexibility of the approach, the personal involvement, and

the openness of the researcher to the research subjects and the research process. However,

according to Mayring (1990, p. 17) this does not imply that the research process is not controlled

and does not follow well-grounded rules. Very important to the process are the illustration of the

context, the intersubjective traceability of the interpretation, and the relevance of the results.

Qualitative research explicitly turns itself against reliability and validity, the quality criteria that

apply for quantitative research. It has been often critiqued to be lacking scholarly rigor (Gioia,

Corley & Hamilton 2012), which makes it necessary to clearly state what quality criteria apply

for this kind of research. However, up to now there is no unambiguous agreement in the

scientific community about a criteria “catalogue” for qualitative research.

4. Summaries of Differences:

A comparison of quantitative and qualitative research can be carried out on various levels, e.g.

application domain, prerequisites, research process, etc. The main differences between the two

approaches come from their underlying science models. These models differ in their

understanding of how phenomena should be studied. The aim for objective and precise

prediction characterizes the natural science model (quantitative), whereas thick descriptions of

incidents that advance the understanding of human behaviour distinguish the human science

model (qualitative).

This fundamental difference implies the remaining ones. Due to its precise and seeking for

objectivity nature, quantitative research focuses on the quantification of concepts and their

relationships via measurement. In contrast, qualitative research tries to understand qualities of

entities via text production and interpretation. Quantitative researchers study phenomena with a

distant and objective science stance from the outside; whereas qualitative researchers are

engaged in face-to-face interactions and role taking from the inside. The deductive nature of

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quantitative research implies a rather selective approach, where a small number of key variables

across many data points are researched. Qualitative research aims at a holistic view of

phenomena and more often deploys an inductive, exploratory approach.

The last two differences refer to the research process and its impact on the segment of social

reality that is studies. Due to a pre-structured and linear research process, quantitative methods

allow for a static image of that segment. Qualitative methods follow a more flexible, open-ended

and circular process, so they enable a dynamic view of the segment. Despite these fundamental

differences, both methodologies can be successfully combined into one research design.

5. Mixed Method Approach:When comparing quantitative and qualitative research, Wilson (1982) argues for a balanced use

of both, considering the object or phenomenon of research and not relying upon philosophical

doctrines. The increasing popularity of mixed methods could be due to many factors, one of

them being the intention of utilizing the strengths of both qualitative and quantitative research.

Also, the interdisciplinary nature of mixed methods can address the increasing complexity of

social reality. Moreover, the insights gained from the combination of both qualitative and

quantitative research provide a better and expanded understanding of the research subject.

Finally, it could also be argued that mixed methods help to better understand, explain, or build

on the results from quantitative and qualitative approaches. Before discussing the different types

of mixed methods designs, it is helpful to discuss the several aspects that influence the design of

procedures for mixed methods study. These are timing, weighting, and mixing strategies

(Cresswell, 2002).Timing refers to the order of data collection. Data could be collected

sequentially or concurrently. Weighting refers to where the priority is given in collection of data,

either quantitative or qualitative. The strategy of deciding the weighting also depends on the

extent of treatment of one type of data and the use of primarily an inductive or deductive

approach. Mixing refers to either that the qualitative and quantitative data are actually merged. It

is possible to merge data at several stages such as during the collection or while doing the

analysis or finally during the interpretation stage. The primary aim here is to collect one form of

data and have the other form of data provide supportive information.

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6. Differences between Qualitative and Quantitative Inquiry

Qualitative Examples from the tools tests

Quantitative Examples from the tools tests

Lower number of respondents

Honduras and Mali, approximately 12 clients per individual tool and 6 focus groups

Higher number of respondents

In Honduras and Mali between 72 and 96 respondents were included in the Impact Survey.

Open-ended questions and probing yield detailed information that illuminates nuances and highlights diversity

Loan Use Strategies Over Time tool demonstrates the diversity and complexity of how clients vary their loan activities over time

Specific questions obtain predetermined responses to standardized questions

Impact survey results reported the percent of clients who believed their enterprise income had increased in the last year and whether significantly more clients than non-clients reported increases

Data collection techniques vary

Focus group discussions and in-depth individual interviews

Relies on surveys as the main method of data collection

Impact Survey and Client Exit Survey

Control group not required

In Honduras and Mali, only participants' views obtained

Control or comparison groups required to determine program impact

Comparison groups were composed of incoming clients who had not yet received program services

More focused geographically (limited use of vehicles)

Specific locations identified for special characteristics; for example, urban vs. rural, vendors vs. manufacturers

More dispersed geographically (more use of vehicles)

In Mali, three categories of communities (towns, large villages, small villages) with three categories of clients (one-year, two-year, and incoming)

More varied techniques in data analysis

Simple content analysis is applied with the Loan Use Strategies Over Time and Client Empowerment tools, with a focus on grouping

Relies on standardized data analysis.

Use of Epi Info software to report descriptive statistics (prevalence and means) and to test for statistically significant differences between sample groups

More suitable when Interviews took one to Relies on more Impact Survey takes 45-

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time and resources are limited

two hours to conduct, but fewer were done

extensive interviewing 60 minutes with each client and done with large number; Client Exit Survey takes 25 minutes

Empowering and participatory

Asks for participants' reflection on their experience

Not empowering Areas of inquiry are predetermined

Sampling depends on what needs to be learned

Clients selected by key variables; for example, gender, time in program, type of loan obtained

Sampling focus is on probability and "representativeness"

what needs to be learned Clients selected by key Considerable effort to randomly select clients within stratified samples to ensure “representativeness” of results and comparability of sample groups

Provides information on the application of the program in a specific context to a specific population

In Honduras, the Loan Use Strategies Over Time tool highlighted differences between individual and village bank clients

More likely provides information on the broad application of the program

In Mali, stratified samples clarified differences between rural and urban areas, but responses also pooled for general comparison to nonclient group

Explores causality Generates hypotheses Suggests causality Tests hypotheses (Patton, 1990;Gosling and Edwards, 1995; Carvalho and White, 1997)

7. Differences between Qualitative & Quantitative Research

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Qualitative Methods Quantitative MethodsMethods include focus groups, in-depth interviews, and reviews of documents for types of themes

Surveys, structured interviews & observations, and reviews of records or documents for numeric information

Primarily inductive process used to formulate theory or hypotheses

Primarily deductive process used to test pre-specified concepts, constructs, and hypotheses that make up a theory

More subjective: describes a problem or condition from the point of view of those experiencing it

More objective: provides observed effects (interpreted by researchers) of a program on a problem or condition

Text-based Number-based

More in-depth information on a few cases Less in-depth but more breadth of information across a large number of cases

Unstructured or semi-structured response options

Fixed response options

No statistical tests Statistical tests are used for analysis

Can be valid and reliable: largely depends on skill and rigor of the researcher

Can be valid and reliable: largely depends on the measurement device or instrument used

Time expenditure lighter on the planning end and heavier during the analysis phase

Time expenditure heavier on the planning phase and lighter on the analysis phase

Less generalizable More generalizable

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8. References: Aliaga, M. & Gunderson, B. (2002). Interactive statistics. New Jersey: Prentice Hall.

Creswell, J. W. (1998). Qualitative Inquiry and Research Design: Choosing Among Five

Traditions. Thousand Oaks, CA: Sage..

Creswell, J.W. (2002), Research design. Qualitative, quantitative and mixed method

approaches. Chapter 11: Mixed methods procedures, pp. 208-227

Flick, U. (2006), An introduction to qualitative research (3 ed.). Chapter 3: Qualitative

and quantitative research, pp 32-43, London: Sage.

Gioia, D. A., Corley, K.G., Hamilton, A.L. (2012), Seeking Qualitative Rigor in

Inductive Research: Notes on the Gioia Methodology. Organizational Research Methods,

vol. 16 (1), p.15-Hamel, J., Dufour, S. & Fortin, D. (1993), Case Study Methods. Sage

Publication, Newbury Park, California.

Hoffmann-Riem, C. (1980), Die Sozialforschung in einer interpretativen Soziologie - Der

Datengewinn. Kölner Zeitschrift für Soziologie und Sozialpsychologie, vol. 32, p.339-

372.

Mayring, Ph. (2002), Einführung in die Qualitative Sozialforschung. Eine Anleitung zum

qualitativen Denken (5. ed.), p. 9-18, München: Psychologie-Verlags-Union.

The book is well-suited for prospective researchers and introduces the background,

developments, and methods of qualitative social research.

Seipel, Ch. & Rieker, P. (2003), Integrative Sozialforschung. Konzepte und Methoden

der qualitativen und quantitativen empirischen Forschung. Weinheim/München: Juventa.

Wilson, T. P. (1982). Qualitative oder quantitative Methoden in der Sozialforschung.

Kölner Zeitschrift für Soziologie und Sozialpsychologie, vol. 34, p. 487-508.

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Table of Contents

1 Concept..................................................................................................................................... 112 Construct.................................................................................................................................... .113 Constant..................................................................................................................................... 114 Themes..................................................................................................................................... 125 Variables......................................................................................................................................126 Types of variables…………………………………………………………………………………………137 References…………………………………………………………………………………………18

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Variables in Qualitative Research

By Isma Baig M.Phil Scholar

1 Concept:

What is Concept?

Expresses an abstraction formed by generalization from particulars.” (Kerlinger)

Examples:

Scientific: weight, mass, energy, force, etc.

Emotions: happiness, sadness, fear, anxiety, etc.

2 Constructs:What is a construct?

“It has the added meaning, however, of having been deliberately and consciously invented or

adopted for a special scientific purpose.” (Kerlinger)

Examples:

Intelligence

Concept: used theoretically

Construct: “defined and specified [so] that it can be measured and observed” (Kerlinger)

3 Constant:

What is Constant?

The value of a constant remains the same (fixed) during the study.

Examples:

Numerical Value, Grade, etc.

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4 Themes:

What is Theme?

Theme is underlying meaning of the story.It is a universal Truth.

Example:

Significant Statements, Valuable Lesson, Central idea etc.

5 Variables:

•What is a variable?

“A variable is a symbol to which numerals or values are assigned.” (Kerlinger)

Variable: any characteristic that can vary across individuals, groups, or objects.

For Example:

Height / Weight

Profession

Grade-point average (GPA) OR Percentage

Level of interest

test score, etc

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6. Types of Variables:

Quantitative Variables:

A variable that can be measured numerically is called a Quantitative Variable. Quantitative

variables have further two types of variables that are given below:

Discrete Variable:

A variable whose values are countable is called a Discrete Variable. For Example: Number of

children, Family Size, Number of books, School Enrollment etc.

Continuous Variable:

A variable that can take on any of a continuously ordered set of values within some specified

range is called a Continuous Variable. For Example: Age, Experience, Motivation, and

Achievement

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Qualitative or/ Categorical Variable:

A variable that cannot assume a numerical value but can be classified into two or more

nonnumeric categories is called a Qualitative or/ Categorical Variable.

The independent variable:

It is the factor that is measured, manipulated or selected by the experimenter to determine its

relationship to an observed phenomenon. It is a stimulus variable or input operates within a

person or within his environment to effect behavior. Independent variable may be called factor

and its variation is called levels.

The dependent variable:

The dependent variable is a response variable or output. The dependent variable is the factor that

is observed and measured to determine the effect of the independent variable; it is the factor that

appears, disappears, or varies as the researcher introduces, removes, or varies the independent

variables.

Moderate variable:

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It is the factor that is measured, manipulated or selected by the experimenter to discover whether

it modifies the relationship of the independent variable to an observed phenomenon. The term

moderate variable describes a special type of independent variable, a secondary independent

variable selected to determine if it affects the relationship between the study’s primary

independent variable and its dependent variable.

Control variable:

Control variables are factors controlled by the experimenter to cancel out or neutralized any

effect they might otherwise on the observed phenomena. A single study can not examine all of

the variables in a situation (situational variable) or in a person (dispositional variable); some

must be neutralized to guarantee that they will not exert differential or moderating effects on the

relationship between the independent variables and dependent variables.

Intervening variable:

An intervening variable is the factor that theoretically effects observed phenomena but can not be

seen, measured, or manipulated; its effects must be inferred from the effects of the independent

and moderate variable on the observed phenomena.

Consider the hypothesis:

Among students of the same age and intelligence, skill performance is directly related to the

number of practice trials, the relationship being particularly strong among boys, but also holding,

though less directly, among girls’. this hypothesis that indicates that practice increases learning,

involve several variables.

Independent variable: ………..number of practice trail

Dependent variable:…………...skill performance

Control variable:……………… age, intelligence

Moderate variable:…………….gender

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Independent Variables

Moderate variables

Control variables

Intervening variables

Dependent variables

Intervening variable:………….. learning

Causes relationship effects

References:

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Aliaga, M. & Gunderson, B. (2002). Interactive statistics. New Jersey: Prentice Hall.

Creswell, J. W. (1998). Qualitative Inquiry and Research Design: Choosing Among Five

Traditions. Thousand Oaks, CA: Sage..

Creswell, J.W. (2002), Research design. Qualitative, quantitative and mixed method

approaches. Chapter 11: Mixed methods procedures, pp. 208-227

Flick, U. (2006), An introduction to qualitative research (3 ed.). Chapter 3: Qualitative and

quantitative research, pp 32-43, London: Sage.

Gioia, D. A., Corley, K.G., Hamilton, A.L. (2012), Seeking Qualitative Rigor in Inductive

Research: Notes on the Gioia Methodology. Organizational Research Methods, vol. 16 (1),

p.15-Hamel, J., Dufour, S. & Fortin, D. (1993), Case Study Methods. Sage Publication,

Newbury Park, California.

Hoffmann-Riem, C. (1980), Die Sozialforschung in einer interpretativen Soziologie - Der

Datengewinn. Kölner Zeitschrift für Soziologie und Sozialpsychologie, vol. 32, p.339-372.

Mayring, Ph. (2002), Einführung in die Qualitative Sozialforschung. Eine Anleitung zum

qualitativen Denken (5. ed.), p. 9-18, München: Psychologie-Verlags-Union.

The book is well-suited for prospective researchers and introduces the background,

developments, and methods of qualitative social research.

Seipel, Ch. & Rieker, P. (2003), Integrative Sozialforschung. Konzepte und Methoden der

qualitativen und quantitativen empirischen Forschung. Weinheim/München: Juventa.

Wilson, T. P. (1982). Qualitative oder quantitative Methoden in der Sozialforschung. Kölner

Zeitschrift für Soziologie und Sozialpsychologie, vol. 34, p. 487-508.

http://www.zeepedia.com/read.php

%3Fvariables_and_types_of_variables_moderating_variables_research_methods%26b

%3D71%26c%3D6

http://kevnull.com/presentations/iasummit2006/Communicating%20Concepts%20Through

%20Comics.pdf

http://Understanding Comics, Scott McCloud .com.pk

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