Graduation Year
2020
Document Type
Dissertation
Degree
Ph.D.
Degree Name
Doctor of Philosophy (Ph.D.)
Degree Granting Department
Chemistry
Major Professor
Jeffrey R. Raker, Ph.D.
Committee Member
Wayne C. Guida, Ph.D.
Committee Member
Jennifer E. Lewis, Ph.D.
Committee Member
Luanna B. Prevost, Ph.D.
Keywords
constructed-response, education research, Lewis acid-base, tutorial design, unimolecular substitution
Abstract
In order to evaluate student understanding of chemical reactions and reaction mechanisms, it is necessary to ask students to construct written or oral explanations of mechanistic representations. Studies have shown that students can reproduce pictorial representations of organic chemistry mechanisms without understanding the meaning of the representations. Grading written assessments is time-consuming, which limits their use in large-lecture courses. To address this limitation, lexical analysis and logistic regression techniques can be used to develop models that predict human scoring for constructed-response items. In this dissertation, students’ responses to constructed-response items about what is happening and why in organic chemistry reaction mechanisms are explored. Specifically, student responses about an acid−base proton-transfer mechanism (Chapter 3) and a unimolecular substitution (i.e., SN1; Chapter 5) mechanism are examined. The acid−base proton-transfer item was scored for use or non-use of the Lewis acid−base model. The SN1 item was scored for three levels of explanation sophistication.
The utility of predictive text analysis models for the development of instructional materials is exemplified in Chapter 4. A research-based tutorial was designed to increase student use of the Lewis acid−base model in their written responses. The predictive model was employed to efficiently analyze students’ responses before and after the tutorial to assess the effectiveness of the tutorial. The tutorial was found to have a positive impact on use of the Lewis model.
The lexical analysis and logistic regression techniques used in this dissertation can be applied to many other contexts to produce predictive models. Such models can be used in the classroom to help instructors and students evaluate the quality of their explanations. Instructional tools such as the Lewis acid−base tutorial in Chapter 4 can be used to help students construct the knowledge necessary to appropriately explain reaction mechanisms. As many have called for the use of writing in the science classroom, techniques like those presented in this dissertation could pave the way for open-access, efficient ways to provide feedback for writing prompts in organic chemistry courses and classes in the sciences as whole.
Scholar Commons Citation
Dood, Amber J., "Asking Why: Analyzing Students' Explanations of Organic Chemistry Reaction Mechanisms using Lexical Analysis and Predictive Logistic Regression Models" (2020). USF Tampa Graduate Theses and Dissertations.
https://digitalcommons.usf.edu/etd/8189
