Research in Engineering Education Symposium 2011 - rees2009

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Universidad Politécnica de Madrid (UPM) Página 726 de 957 CIs. In this context, the application of modern methods of psychometrics and diagnostic modeling has the potential to determine the diagnostic capacity of CIs and to suggest ways to improve the CIs. Diagnostic feedback is a key component for formative use of CIs in classrooms. Recommendations for Engineering Education A substantial instructional challenge within the engineering disciplines is to find practical methods for instructors to ensure that students develop deep conceptual understandings within their disciplines and to identify ready assessment methods for determining whether students have achieved these deeper understandings along with necessary topic knowledge and problem solving expertise. CIs provide a particular type of assessment that could materially improve engineering education in just these ways. A rigorous and systematic application of a framework for evaluating the validity of assessments intended for classroom use has the potential to identify and guide needed improvements. Early findings from our examinations of existing CIs clearly indicate that CIs can benefit from standardization of methods and approaches for CI development and validation, and from application of modern psychometric methods for profiling students’ conceptual understanding, including misconceptions. Expanding the range of CI uses to include formative assessment within classes could provide a substantial improvement in engineering education practice. Support for this Work This work has been supported by the following grants from the U.S. National Science Foundation: CCLI Project #0920242, REESE Project #0918552 and REESE Project #0815065. References Allen, K., Stone, A., Rhoads, T. R., & Murphy, T. J. (2004). The Statistics Concepts Inventory: Developing a Valid and Reliable Instrument. In Proceedings of the ASEE Annual Conference and Exposition. American Educational Research Association, American Psychological Association, & National Council on Measurement in Education. (1999). Standards for educational and psychological testing. Washington, DC: American Educational Research Association. Black, P., Harrison, C., Lee, C., Marshall, B., & Wiliam, D. (2004). Assessment for Learning – putting it into practice. Buckingham: Open University Press. DiBello, L., Roussos, L. & Stout, W. (2007). Review of cognitively diagnostic assessment and a summary of psychometric models (979-1030). Invited chapter in Handbook of Statistics, Volume on Psychometrics, Rao, C.V., and Sinharay, S. (Eds.). Proceedings of Research in Engineering Education Symposium 2011 Madrid, 4 th - 7 th October 2011
Universidad Politécnica de Madrid (UPM) Página 727 de 957 Duschl, R., Schweingruber, H., & Shouse, A., (Eds.), (2007). Taking Science to School: Learning and teaching science in grades K-8. Washington, DC : National Academies Press. Hansen, M. & Steif, P. (2006). Using results from concept inventories to improve teaching: Providing feedback on concept scores. Proceedings of the American Educational Research Association Annual Conference. Kane, M. (2004). Certification testing as an illustration of argument-based validation. Measurement, 2(3), 135–170. Messick, S. (1989). Validity. In R. L. Linn (Ed.), Educational measurement (3rd ed., pp. 13– 103). New York: American Council on Education/Macmillan. Miller, R. L., Streveler, R., Olds, B., & Nelson, M. (2005). Concept inventories meet cognitive psychology: Using beta testing as a mechanism for identifying engineering student misconceptions. Proceedings of the American Society for Engineering Education Annual Conference (electronic), Portland, Oregon. Miller, R. L., Streveler, R., Olds, B., Chi, M., Nelson, M. & Geist, M. (2006). Misconceptions about Rate Processes: Preliminary Evidence for the Importance of Emergent Conceptual Schemas in Thermal and Transport Sciences. Proceedings of the American Society for Engineering Education Annual Conference (electronic), Chicago, Illinois. Pellegrino, Chudowsky & Glaser (Eds.) (2001). Knowing what students know: The science and design of educational assessment. Washington, DC, National Academy Press. Santiago Roman, A.I. (2009). Fitting cognitive diagnostic assessment to the concept assessment tool for statics (CATS). PhD Dissertation, Purdue University. Steif, P. S., & Dantzler, (2004). A statics concept inventory: development and psychometric analysis. Journal of Engineering Education, 94 (4), 363-371. Steif, P. S., & Hansen, M. A., (2007). New practices for administering and analyzing the results of concept inventories, Journal of Engineering Education, 96, 205-212. van der Linden, W. J. & Hamilton, R. K. (Eds.) (1996) Handbook of modern item response theory. Springer. Copyright statement Copyright © 2011 James W. Pellegrino, et al.: The authors assign to the REES organisers and educational non-profit institutions a non-exclusive licence to use this document for personal use and in courses of instruction provided that the article is used in full and this copyright statement is reproduced. The authors also grant a non-exclusive licence to REES to publish this document in full on the World Wide Web (prime sites and mirrors) on CD- ROM and in printed form within the REES 2011 conference proceedings. Any other usage is prohibited without the express permission of the authors. Proceedings of Research in Engineering Education Symposium 2011 Madrid, 4 th - 7 th October 2011
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