Predictors for Success in Studying CS SIGCSE 2004

1. Predictors for Success in Studying CSSIGCSE 2004 Brenda Wilson Murray State University

2. What Are the Factors for Success in Computer Science?

3. 1st Study (2000-2001): Contributing Factors for Success in CS • 12 factors studied – midterm grade • CS 1 • 130 students enrolled in CS1 • 105 subjects voluntarily participated • only 19 females (18%) • 29% freshmen, 29% sophomores, 22% juniors, 12 % seniors, 8% graduate students

4. Possible Factors for Success… • Previous programming experience • Previous non-programming computing experience • Attribution for success/failure (luck, difficulty of task, ability, effort) • Self-efficacy • Comfort level • Encouragement from others • Work style preference • Math background • Gender

5. Results:( multiple regression R2 = .4443,p = .0001) 12 factors studied • Comfort level – most significant(p = .0002) • Math background (p = .0050) • Attribution to luck (p = .0233 )negative influence

6. Results: Previous Computing • Multiple Regressionon 5 types of previous computing experiences & midterm grade(R2 = .15, p = .0041) • 2 significant predictors: • Previous Programming Course(positive correlation) • Playing Games(negative correlation)

7. 2nd study(2003):A Study of Learning Environments Associated with Computer Courses • Survey – Spring, Summer, Fall • 862 participants • 429 females • 433 males • Enrolled in any computer course – applications and/or programming

8. Data collected • Age • Gender • Classification • Major • Use of computer labs on campus • Access to a computer • Time spent on computer Activities • Computer assignment preference • Level of confidence • Type of work preferred (Indiv vs. group) • Importance of lab session

9. Results: Time on computer activities.(all students)

10. Gender differences – Working on Assignments(% of total time)

11. Gender differences – E-mail(% of total time)

12. Gender differences – Web surfing(% of total time)

13. Gender differences - Games(% of total time)

14. Results: Type of assignment preferred • Game • Application program (education, medicine, agriculture, business, etc.) • Math

15. Type of Assignment (application, game, math)

16. Type of Work (Individual vs. Group)

17. Recommendations from my research: • Provide environment which encourages students to ask/answer questions in/out of class, free of intimidation • Provide opportunities for students to get help • Smaller numbers in classes • Stress math background in advising students • Match between class assignments & test questions to eliminate attribution to luck

18. Recommendations from my research: • Show how particular topic might be used in gaming, applications to other fields, & pure mathematics. • Give choice for assignments • Delay group work for upper level courses

19. Other Suggestions: • Recruitment efforts need to go back to earlier grades(even before high school) to spark interest in potential CS students from minority groups (e.g. female & other under-represented groups) • Have a “presence” in area high schools to influence qualified students to major in CS

20. Our Efforts to attract “qualified” students: • visits & talks to Middle School (Junior High) students • visits & presentations to High School Math & Science clubs & classes • special meetings with females in upper level high school math classes • demonstrations on what computer programming is • talk about careers in Computer Science & Computer Information Systems

21. Your Thoughts….???