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Issue No.09 - September (2013 vol.46)
pp: 60-66
Allison Elliott Tew , University of Washington Tacoma
Brian Dorn , University of Nebraska at Omaha
Measuring student learning in computer science education presents particular challenges, making objective assessment elusive to educators and researchers. Development and validation of the FCS1 and CAS assessment tools demonstrate both the feasibility and benefits of validated assessment instruments in this discipline.
Computer science education, Context awareness, Computer languages, Learning systems, Collaboration,education, computer science education, validated assessment tools, student learning, Computing Attitudes Survey, CAS, CS1
Allison Elliott Tew, Brian Dorn, "The Case for Validated Tools in Computer Science Education Research", Computer, vol.46, no. 9, pp. 60-66, September 2013, doi:10.1109/MC.2013.259
1. M. McCracken et al., “A Multi-National, Multi-Institutional Study of Assessment of Programming Skills of First-Year CS Students,” SIGCSE Bulletin, vol. 33, no. 4, 2001, pp. 125-180.
2. P.R. Pintrich et al., “Reliability and Predictive Validity of the Motivated Strategies for Learning Questionnaire (MSLQ),” Educational and Psychological Measurement, vol. 53, no. 3, 1993, pp. 801-813.
3. D. Hestenes,M. Wells,, and G. Swackhamer,“Force Concept Inventory,” The Physics Teacher, vol. 30, 1992, pp. 141-158.
4. C.H. Crouch and E. Mazur,“Peer Instruction: Ten Years of Experience and Results,” Am. J. Physics, vol. 69, no. 9, 2001, pp. 970-977.
5. P.A. Moss,B.J. Girard,, and L.C. Haniford,“Validity in Educational Assessment,” Rev. Research in Education, vol. 30, no. 1, 2006, pp. 109-162.
6. R.L. Brennan, ed., Educational Measurement, 4th ed., Am. Council on Education/Praeger Publishers, 2006.
7. L.J. Cronbach,“Test Validation,” Educational Measurement, 2nd ed., R.L. Thorndike, ed., Am. Council on Education, 1971, pp. 443-507.
8. A. Elliott Tew,“Assessing Fundamental Introductory Computing Concept Knowledge in a Language Independent Manner,” doctoral dissertation, College of Computing, Georgia Tech, 2010.
9. , Standards for Educational and Psychological Testing, Am. Educational Research Assoc., Am. Psychological Assoc., and Nat’l Council on Measurement in Education, 1999.
10. J.C. Valentine,D.L. DuBois,, and H. Cooper,“The Relation between Self-Beliefs and Academic Achievement: A Meta-Analytic Review,” Educational Psychologist, vol. 39, no. 2, 2004, pp. 111-133.
11. D. Hammer,“Epistemological Beliefs in Introductory Physics,” Cognition and Instruction, vol. 12, no. 2, 1994, pp. 151-183.
12. M.T.H. Chi,P.J. Feltovich,, and R. Glaser,“Categorization and Representation of Physics Problems by Experts and Novices,” Cognitive Science, vol. 5, no. 2, 1981, pp. 121-152.
13. W.K. Adams et al., “A New Instrument for Measuring Student Beliefs about Physics and Learning Physics: The Colorado Learning Attitudes about Science Survey,” Physical Rev. Special Topics in Physics Education Research, vol. 2, no. 010101, 2006, pp. 1-14.
14. A. Elliott Tew,B. Dorn,, and O. Schneider,“Toward a Validated Computing Attitudes Survey,” Proc. 8th Ann. Conf. Int’l Computing Education Research (ICER 12), ACM, 2012, pp. 135-142.
15. B. Dorn and A. Elliott Tew,“Becoming Experts: Measuring Attitude Development in Introductory Computer Science,” Proc. 44th ACM Technical Symp. Computer Science Education (SIGCSE 13), ACM, 2013, pp. 183-188.
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