AACR Publications

We are pleased to share with you some of our academic publications and other recent efforts to disseminate important developments and research to the broader community. Some publications may be downloadable directly from us, while others may be accessed through the Journal publisher provided in the links. Please feel free to contact the author(s) if you have specific questions about any of the work listed here.

2013

Beggrow, E. B., Ha, M., Nehm, R. H., Pearl, D., & Boone, W. J.. (2013). Assessing Scientific Practices Using Machine-Learning Methods: How Closely Do They Match Clinical Interview Performance?. Journal of Science Education and Technology. presented at the 07/2013. doi:DOI 10.1007/s10956-013-9461-9
Prevost, L. B., Haudek, K. C., Norton-Henry, E., Berry, M. C., & Urban-Lurain, M.. (2013). Using Computerized Lexical Analysis of Student Writing to Facilitate Just-in-Time-Teaching in Large Enrollment Biology Courses. Society for the Advancement of Biology Education Research (SABER) Annual Meeting. presented at the 07/2013, Minneapolis, MN: SABER.
Haudek, K. C., Urban-Lurain, M., & Russell, A. A.. (2013). Exploring Computerized Lexical Analysis to Predict Calibrated Peer Review Ratings of Student Writing in Chemistry. In National Association on Research in Science Teaching. presented at the 04/2013, Rio Grande, Puerto Rico: NARST.
Prevost, L. B., Knight, J., Smith, M. K., & Urban-Lurain, M.. (2013). Student writing reveals their heterogeneous thinking about the origin of genetic variation in populations. In National Association on Research in Science Teaching. presented at the 04/2013, Rio Grande, Puerto Rico: NARST.
Weston, M., Parker, J. M., & Urban-Lurain, M.. (2013). Comparing Formative Feedback Reports: Human and Automated Text Analysis of Constructed Response Questions in Biology. In National Association on Research in Science Teaching. presented at the 04/2013, Rio Grande, Puerto Rico: NARST.
Lira, C. T., & Elliott, J. R.. (2013). Facilitating Learning in Thermodynamics and Computations Using Technology. Annual Meeting of the American Institute of Chemical Engineers. San Franscisco, CA: AIChE.

2012

Prevost, L. B., Haudek, K. C., Urban-Lurain, M., & Merrill, J. E.. (2012). Examining student constructed explanations of thermodynamics using lexical analysis. In Frontiers in Education. presented at the 10/2012, Seattle, WA: Frontiers in Education.
Haudek, K. C., Prevost, L. B., Merrill, J. E., & Urban-Lurain, M.. (2012). Lexical and qualitative analysis of students’ written responses and interviews explaining chemical functional group behavior in cellular biology. Society for the Advancement of Biology Education Research (SABER) Annual Meeting. presented at the 07/2012, National Meeting of the Society for Advancement of Biology Education Research: SABER.
Prevost, L. B., Knight, J., Smith, M. K., Haudek, K. C., Merrill, J. E., & Urban-Lurain, M.. (2012). Using Lexical Analysis to Explore Students’ Written Responses to Genetics Concept Assessment-Derived Items. Society for the Advancement of Biology Education Research (SABER) Annual Meeting. presented at the 07/2012, National Meeting of the Society for the Advancement of Biology Education Research: SABER.
Weston, M., Haudek, K. C., Prevost, L. B., Lyons, C., Urban-Lurain, M., Merrill, J. E., & Parker, J. M.. (2012). How are students interpreting constructed response questions? Using computerized lexical analysis to identify key concepts in student writing. Society for the Advancement of Biology Education Research (SABER) Annual Meeting. presented at the 07/2012, Minneapolis, MN: SABER.
Prevost, L. B. (2012). Insight into Student Thinking in STEM: Lessons Learned from Lexical Analysis of Student Writing. Transforming Research in Undergraduate STEM Education. presented at the 06/2012, St. Paul, MN: TRUSE.
Urban-Lurain, M. (2012). Insight into Student Thinking in STEM: Lessons Learned from Lexical Analysis of Student Writing. Michigan State University; East Lansing, MI. presented at the 05/2012.
Nehm, R. H., Ha, M., & Mayfield, E.. (2012). Transforming Biology Assessment with Machine Learning: Automated Scoring of Written Evolutionary Explanations. Journal of Science Educational Technology, 21(1). doi:10.1007/s10956-011-9300-9

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This material is based upon work supported by the National Science Foundation (DUE grants: 1438739, 1323162, 1347740, 0736952 and 1022653). Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the NSF.