Exploring the effects of gender and learning styles Exploring the effects of gender and learning styles

on computer programming performance: on computer programming performance:

implications for programming pedagogyimplications for programming pedagogy

Adviser: Ming-Puu Chen

Presenter: Li-Chun Wang

Lau, W. W. F. & Yuen, A. H. K. (2008). Exploring the effects of gender and

learning styles on computer programming performance: Implications for pro

gramming pedagogy. British Journal of Educational Technology, 1-17.

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AbstractAbstract• This study aims to investigate the effects of This study aims to investigate the effects of gender and learning stylgender and learning styl

es on computer programming performancees on computer programming performance. .

• From the curriculum implementation perspectives, learning style helFrom the curriculum implementation perspectives, learning style hel

ps address the issue of learner differences, resulting in a shift from a ps address the issue of learner differences, resulting in a shift from a

teacher-centred approach to a learner-focused approach.teacher-centred approach to a learner-focused approach.

• Results indicated that no gender differences in programming perforResults indicated that no gender differences in programming perfor

mance were found after controlling for the effect of student ability.mance were found after controlling for the effect of student ability.

• Academic ability had a differential effect on programming knowledAcademic ability had a differential effect on programming knowled

ge. ge.

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IntroductionIntroduction• Learning to program still plays a role in promoting information literLearning to program still plays a role in promoting information liter

acy in technology education.acy in technology education.

• Learning to program has been widely recognised as a highly cognitiLearning to program has been widely recognised as a highly cogniti

vely demanding task for students and has posed a lot of difficulties fvely demanding task for students and has posed a lot of difficulties f

or them at the outset.or them at the outset.

• Chamillard and Karolick (1999) argue that learning style data can hChamillard and Karolick (1999) argue that learning style data can h

elp students to ‘develop their study habits, to help instructors select telp students to ‘develop their study habits, to help instructors select t

heir instructional strategies more effectively and to help researchers heir instructional strategies more effectively and to help researchers

better understand how different learning styles can affect student perbetter understand how different learning styles can affect student per

formance.formance.

• However, most studies have been focused on university students anHowever, most studies have been focused on university students an

d little is known about the impact of learning styles on secondary scd little is known about the impact of learning styles on secondary sc

hool students in a Hong Kong context.hool students in a Hong Kong context.

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IntroductionIntroduction• Gender and programming performanceGender and programming performance - Research on gender and programming performance tends to produce

inconclusive results.

> > no gender differenceno gender difference

> > women perform better than menwomen perform better than men : : dedication and hard work that dedication and hard work that may have been brought on by the anxiety of not being expected to do may have been brought on by the anxiety of not being expected to do wellwell

• Learning styles and programming performanceLearning styles and programming performance - Myers-Briggs: personality type - Myers-Briggs: personality type

> Sensing students performed better than intuitive students> Sensing students performed better than intuitive students

> Judging students achieved higher results than perceptive students> Judging students achieved higher results than perceptive students

- - Felder-SilvermanFelder-Silverman

> Reflective learners outperformed active learners> Reflective learners outperformed active learners

> Verbal learners outperformed visual learners> Verbal learners outperformed visual learners

Certain learning styles are associated with higher academic Certain learning styles are associated with higher academic achievement irrespective of the learning style instruments being achievement irrespective of the learning style instruments being used.used.

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IntroductionIntroduction• Gregorc Style DelineatorGregorc Style Delineator

- The human mind has channels through which information is received anThe human mind has channels through which information is received an

d expressed most efficiently and effectivelyd expressed most efficiently and effectively

- Mediation abilities:Mediation abilities:

> > Concrete sequential (CS):Concrete sequential (CS): learners tend to perceive reality through their learners tend to perceive reality through their

physical senses and think in an orderly, logical, and sequentially mannerphysical senses and think in an orderly, logical, and sequentially manner

> > Concrete random (CR):Concrete random (CR): learners like to experiment with ideas and concelearners like to experiment with ideas and conce

pts and think intuitively, instinctively, impulsively and independentlypts and think intuitively, instinctively, impulsively and independently

> Abstract sequential (AS):> Abstract sequential (AS): learners are logical and analytical individuals learners are logical and analytical individuals

who have a preference for mentally stimulating task and environmentwho have a preference for mentally stimulating task and environment

> Abstract random (AR):> Abstract random (AR): learners have a strong sense on the world of feelilearners have a strong sense on the world of feeli

ng and emotion and tend to think in a nonlinear and emotional mannerng and emotion and tend to think in a nonlinear and emotional manner

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• The nature of programming knowledgeThe nature of programming knowledge

- Shneidreman and Mayer (1979):- Shneidreman and Mayer (1979):

> Synta> Syntactic knowledgectic knowledge: : the details of how computation is implemented in a the details of how computation is implemented in a

particular programming languageparticular programming language

> Semantic knowledge:> Semantic knowledge: requires understanding of programming constructs requires understanding of programming constructs

and concepts that are independent of specific programming languagesand concepts that are independent of specific programming languages

- Bayman and Mayer (1988):- Bayman and Mayer (1988):

> Syntactic knowledge:> Syntactic knowledge: the features and facts of the language the features and facts of the language

> Conceptual knowledge: > Conceptual knowledge: a conceptual model of the systema conceptual model of the system

> Strategic knowledge: > Strategic knowledge: the use of syntactic and conceptual knowledge to sothe use of syntactic and conceptual knowledge to so

lve novel problemslve novel problems

IntroductionIntroduction

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• The nature of programming knowledgeThe nature of programming knowledge

- The programming performance test in this study:- The programming performance test in this study:

> Declarative knowledge (DK)> Declarative knowledge (DK): : about knowledge of some factual about knowledge of some factual

information like definition of terms and it is described as a type of information like definition of terms and it is described as a type of

knowing-what knowledgeknowing-what knowledge

> Procedural knowledge (PK):> Procedural knowledge (PK): type of knowing-how knowledge type of knowing-how knowledge

> Conditional knowledge (CK): > Conditional knowledge (CK): type of knowing-when knowledgetype of knowing-when knowledge

> Strategic knowledge (SK): > Strategic knowledge (SK): type of knowing-why knowledgetype of knowing-why knowledge

IntroductionIntroduction

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• Participants: Secondary 4-5 studentsParticipants: Secondary 4-5 students

• Content: Bubble sorting allgorithmContent: Bubble sorting allgorithm

• Grouped: academic performance in primary schoolsGrouped: academic performance in primary schools

• Instruments: GSD, programming performance testInstruments: GSD, programming performance test

MethodMethod

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• Effects of gender and learning styles on programming Effects of gender and learning styles on programming performanceperformance

ResultsResults

• Prediction of programming performance by learning stylesPrediction of programming performance by learning styles

10• Main effect of band Main effect of band DK, PK : B1 >B2 DK, PK : B1 >B2

• Main effect of learning styles Main effect of learning styles DK: AS, CS > CR; SK: CS > CR, AR DK: AS, CS > CR; SK: CS > CR, AR

AS, CS > CRAS, CS > CR

CS > CR, ARCS > CR, AR

ResultsResults

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DiscussionDiscussion• There were no gender differences found in programming performThere were no gender differences found in programming perform

ance ance

• Main effect of band Main effect of band DK, PK : B1 >B2 DK, PK : B1 >B2

- Academic ability has a differential effect on programming knowledge.- Academic ability has a differential effect on programming knowledge.

• Main effect of learning styles Main effect of learning styles DK: AS, CS > CR; SK: CS > CR, DK: AS, CS > CR; SK: CS > CR,

ARAR

- Their preference for an unstructured learning condition make learning Their preference for an unstructured learning condition make learning

computer programming a stumbling block to them as writing a progracomputer programming a stumbling block to them as writing a progra

m is a highly structured and procedural endeavour.m is a highly structured and procedural endeavour.

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ImplicationsImplications• First, students’ ability has a positive influence on programming performanceFirst, students’ ability has a positive influence on programming performance

- To provide additional resources to support the weaker students, a remedial program - To provide additional resources to support the weaker students, a remedial program

could be offered.could be offered.

• Second, although there were statistically significant learning style group effects on Second, although there were statistically significant learning style group effects on

programming performance, programming scores decreased towards the higher level programming performance, programming scores decreased towards the higher level

of programming knowledge.of programming knowledge.

- Using interventions like planning strategy for algorithmic development and - Using interventions like planning strategy for algorithmic development and

programming through interactive teaching approachprogramming through interactive teaching approach

• Third, sequential learners outperformed random learners in all measures of Third, sequential learners outperformed random learners in all measures of

programming knowledgeprogramming knowledge

- Random students are potentially at risk in computer science or computer application - Random students are potentially at risk in computer science or computer application

coursescourses

- Random learners should be given extra attention in learning to program - Random learners should be given extra attention in learning to program

- Group discussions- Group discussions