Adaptive Collaborative Unix Meta-tutorial for computer science students

1. Adaptive Hypermedia & Assistive Technologies Adaptive Collaborative Unix Meta-tutorialfor computer science students

2. Rosta Farzan, Masters Student Math & Computer Science Department California State University, Hayward rosta@acc.csuhayward.edu Hilary J. Holz, Asst Professor Math & Computer Science Department California State University, Hayward hholz@csuhayward.edu

3. Research Problem

4. Less Confidence & Interest in computer science Less exposure to informal education Less experience in computing skills such as Unix Lower retention rate of female students in computer science

5. [3]

6. Goals • Help students • understand Unix concepts • make use of online resources • Remove some barriers of equity in computer science program

7. Supporting collaboration through leaving traces Objectives • Supporting adaptation through clustering • Collect qualitative data • Two cohorts of 50 students • Collect quantitative data • Within a small cohort of 10 students

8. Background

9. Research at Carnegie Mellon University “Organize Workshops to teach UNIX and questions that the womenfeel are stupid to ask [1]” [1] • Main problems in bringing & retaining of female students • Experience gap • Confidence doubts • Curriculum and pedagogy • Peer culture

10. Research in Mathematics Education • Subjective Knowers & connected Knowers • Acquire knowledge • Listening to themselves • Accessing others’ experiences • Female students gain more in collaborative environment Feminist Pedagogy [4]

11. Exceptional program @ California State University, Hayward • High ratio of female and minority students [2]

12. One female ?! Research at California State University, Hayward Traditional curriculum and classroom design does not meet female and minorities students’ need Online courses No coherent approach to help students move from Windows to Unix • Flexibility • Learning at their own time and pace [6]

13. Approach

14. AdaptiveCollaborativeOnlineUnixMeta-Tutorial Learning Unix Concepts Learn about Online Resources & Communities

15. Adaptation Individual Learning Style Student Modeling Usability issues Individual Objectives Clustering based on interaction behavior Individual Preferences No questionnaire No Username & Password

16. Collaboration - Social Navigation Footprints on the sand of time are not made by sitting down • Closer to what happens in the traditional classroom • Learners leave notes for themselves as well as others • Encouraging to write notes change the status of learners from passive to active Collaborate through following footprints of others [7]

17. Perl Monk Online Tutorial Online Tutorial • Just in Time Learning • Learning with efficiency • At student’s own pace • Anytime & any location • Address non-traditional students’ need Learn from online communities

18. Prerequisite for many computer science core courses Most schools do not offer a traditional course to teach Unix skills Not possible to teach Unix in formal classes [6]

19. Meta-Tutorial • Annotated & Categorized links to existing resources • Graphical (e.g. Color) & text annotation • Metadata assigned to each section • Using XML • Dublin Core set [10] • Gateway to Educational Material (GEM) set [14] • Our own defined set <name> File permission </name> <language> English </language> <audience> <beneficiary> beginner </beneficiary> <level> hard </level> </audience> <relation> <IsDetailsOf>fileMgmnt</IsDetailsOf> </relation> <comment> useful information </comment>

20. Research Methodology

21. Collecting data from learners Design & Development Revision Iterative & Participatory Design [5]

22. Initial Hypotheses • Less use of online resources • Pages with graphics • Less use of communication tools • More reading of comments • Follow the given order • Less details or depth • Less use of online resources • Less use of communication tools • Spend more time on introductory pages Female Beginner

23. First phase: Data Collection • Early in the design process • Avoid extra cost & complication Goal: Cognitive model of computer science students’ behavior • Preliminary survey among 300-350 computer science students • Task based interview • Tutorial with similar characteristics

24. Description of Cohorts • Preliminary Survey • Freshman • Introduction to Computer Science and Programming Methods • Sophomore • Programming Language Concepts, and Data Structures and Algorithms • Junior • Web Site Development, and Introduction to Systems Programming • Graduate level • Software Engineering of Web Based System. • Interview subsequent cohort of 10 students • Female, Male, different age group, various level of knowledge

25. Summary • Human subject involvement • First time in computer science department @ CSUH • Departmental approval • Process of Institutional Review Board approval

26. Summary • Data collection - First formal phase • Collect finely structures data • Build the cognitive model of computer science behavior • Implementation • Build database (postgreSQL) • Implement the system (Perl) • Build metadata set

27. Sponsors • CREW • Collaborative Research Experience for Women • California State University Hayward Foundation Inc. • ACCLAIM • Alameda County Collaborative for Learning and Instruction in Mathematics

28. 8. Dove Chocolate 9. http://www.clipart.com 10. http://dublincore.org 11. http://sourceforge.net 12. http://www.acm.org 13. http://www.w3c.org 14. http://www.geminfo.org http://www.perlmonks.org http://unix.org References • Blum, L. (2001). Women in Computer Science: The Carnegie Mellon Experience • California State University, Hayward. Institutional Research and Analysis. • CRA Taulbee Trends: Women Students & Faculty, (2002). • Jacobs, E. J., Becker R. J. Multicultural and Gender Equity. General Yearbook Editor, Boston College. • Kelly, E. A., Lesh A. R. (2002). Design Experiments in Mathematics Education. • Sawhney, H. and Farzan, R. (2002). Teaching Unix Skills to Undergraduate and Graduate Students in Computer Science. • Wexelblat, A. and Maes, P. (1999), Footprints: History-Rich Tools for Information Foraging