Developing Computer Resources to Automate Analysis of Students' Explanations of London Dispersion Forces

TitleDeveloping Computer Resources to Automate Analysis of Students' Explanations of London Dispersion Forces
Publication TypeJournal Article
Year of Publication2020
AuthorsNoyes, K, McKay, RL, Neumann, M, Haudek, KC, Cooper, MM
JournalJournal of Chemical Education Research
Date Published10/2020
AbstractComputer-assisted analysis of students’ written responses to questions is becoming a possibility due to developments in technology. This could make such constructed response questions more feasible for use in large classrooms where multiple choice assessments are often considered a more practical option. In this study, we use a previously developed prompt and coding scheme to characterize students’ explanations of the origins of London dispersion forces in order to develop machine learning resources that can carry out such an analysis for large numbers of students. We found that by using large numbers of human coded student responses (N = 1,730) we could subsequently automatically characterize students’ responses at a high level of accuracy compared to human coders. Furthermore, these resources were developed using responses from several different groups of students across multiple institutions to ensure both that our resources can work well with students from different backgrounds and that these computer resources can detect the different ways in which students explain this phenomenon. Such resources may help instructors to administer more complex open-ended assessment tasks to larger numbers of students and analyze the responses capturing language corresponding to causal mechanistic reasoning. Instructors could then use this information to better support their students’ learning.
DOI10.1021/acs.jchemed.0c00445
Refereed DesignationRefereed

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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.