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Assessment Commons

Assessment Commons is an open learning space that curates content for faculty and assessment professionals through resources and tools for student learning outcomes assessment, teaching and learning, program review and accreditation.

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Research Design Resources

Johnson, R. B., Onwuegbuzie, A. J., & Turner, L.A. (2007). Toward a definition of mixed methods research. Journal of Mixed Methods Research, 1(2), 112–133. 

Kelley, K., Clark, B., Brown, V., & Sitzia, J. (2003). Good practice in the conduct and reporting of survey research. International Journal for Quality in Health Care, 15(3), 261–266. 

Singer, E., & Bossarte, R. M. (2006). Incentives for survey participation: When are they “coercive”? American Journal of Preventive Medicine, 31(5), 411–418. 

What Works Clearinghouse. (2020). What Works Clearinghouse Procedures Handbook, Version 4.1. U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance. 

Assessment and Measurement Resources

Allen, S., & Knight, J. (2009). A method for collaboratively developing and validating a rubric. International Journal for the Scholarship of Teaching and Learning, 3(2). 

Braun, H. I., & Mislevy, R. (2005). Intuitive test theory. The Phi Delta Kappan, 86(7), 488–497. JSTOR. 

Black, P., Harrison, C., Lee, C., Marshall, B., & Wiliam, D. (2004). Working inside the black box: Assessment for learning in the classroom. The Phi Delta Kappan, 86(1), 8–21. JSTOR. 

Brown, N. J. S., & Wilson, M. (2011). A model of cognition: The missing cornerstone of assessment. Educational Psychology Review, 23(2), 221–234. JSTOR. 

Montenegro, E., & Jankowski, N. A. (2020). A new decade for assessment: Embedding equity into assessment praxis (Occasional Paper No. 42; p. 26). University of Illinois and Indiana University, National Institute for Learning Outcomes Assessment (NILOA). 

Statistical Resources

Bell, B. A., Ferron, J. M., & Kromrey, J. D. (2008). Cluster size in multilevel models: The impact of sparse data structures on point and interval estimates in two-level models. Proceedings of the Joint Statistical Meetings, Survey Research Methods Section, 1122–1129. 

Costello, A., & Osborne, J. (2019). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Practical Assessment, Research, and Evaluation, 10(1). 

Dimitrov, D. M. (2010). Testing for factorial invariance in the context of construct validation. Measurement and Evaluation in Counseling and Development, 43(2), 121–149. 

Dushoff, J., Kain, M. P., & Bolker, B. M. (2019). I can see clearly now: Reinterpreting statistical significance. Methods in Ecology and Evolution, 10, 756–759. 

Höfler, M., Pfister, H., Lieb, R., & Wittchen, H.-U. (2005). The use of weights to account for non-response and drop-out. Social Psychiatry and Psychiatric Epidemiology, 40, 291–299. 

Little, R. J. A. (1988). A test of missing completely at random for multivariate data with missing values. Journal of the American Statistical Association, 83(404), 1198–1202. 

MacDonald, P., & Paunonen, S. V. (2002). A Monte Carlo comparison of item and person statistics based on Item Response Theory versus Classical Test Theory. Educational and Psychological Measurement, 62(6), 921–943. 

Raudenbush, S. W., & Bryk, A. S. (1988). Methodological advances in analyzing the effects of schools and classrooms on student learning. Review of Research in Education, 15, 423–475. 

Rubin, D. B. (1976). Inference and missing data. Biometrika, 63(3), 581–592. 

Program Evaluation Resources

American Evaluation Association. (2011). Public Statement on Cultural Competence in Evaluation.  (PDF)

Chen, H. T., Donaldson, S. I., & Mark, M. M. (2011). Validity frameworks for outcome evaluation. In Advancing validity in out-come evaluation: Theory and practice (Vol. 130, pp. 5–16). New Directions for Evaluation. 

Thurston, W. E., Graham, J., & Hatfield, J. (2003). Evaluability assessment: A catalyst for program change and improvement. Evaluation & the Health Professions, 26(2), 206–221.