Authors: Helena C. Malinakova
Source: Journal of Chemical Education (article, 2024-12-12)
Field: Chemistry — Physical and Theoretical Chemistry

Longitudinal Study of Students’ Study Approaches in Organic Chemistry Classes: Using Structural Equation Modeling (SEM) to Detect a Response Shift in Data from the OCH-Adjusted M-ASSIST Instrument Organic chemistry presents a significant obstacle for students seeking entry into health-related professions. Students’ ability to develop effective study approaches is an important predictor of success in the course. Herein, we report an investigation utilizing an OCH-adjusted M-ASSIST instrument to assess possible changes in students’ study approaches in the Organic Chemistry I course. Surveys for this study were completed in October and December of the first semester of the Organic Chemistry I course at the University of Kansas and afforded 84 individually paired responses. Furthermore, students’ attitudes toward utilizing supplementary study tools (Study Cards and Concept Maps) were interrogated by a four-question survey administered on the same dates. Confirmatory Factor Analysis (CFA) of the responses to the OCH-adjusted M-ASSIST instrument revealed a notable difference in a few individual factor loadings between the models for the October and December data as well as an increase in a negative covariance between the Deep and Surface learning factors. Analysis of these changes between the models for the October and December data utilizing the chi-square difference (χDIF2) test for pairs of nested SEM (structural equation modeling) models including the assessment of statistical power, yielded two significant conclusions. First, a statistically significant negative correlation between Deep and Surface learning develops only after the October sampling date and is present only in the models for the December data. Second, a response shift (reprioritization, which means a change in factor loadings) was detected in student responses to the OCH-adjusted M-ASSIST instrument and involves a single item (a question from the “relating ideas” subsection of the instrument) loading on the Deep learning factor. However, the average learning scores (both Deep and Surface) in this longitudinal did not change across the study time frame. Responses to questions regarding the use of Study Cards and Concept Maps revealed that a significant decrease in students’ ability to apply these study tools toward meaningful learning occurred by the end of the semester. The greatest effect size was noted for students’ assessment of their use of Concept Maps, potentially indicating challenges they experience when processing material of increasing complexity. Our results suggest that an important reevaluation, or self-reassessment in students’ study approaches, is taking place in the second half of the Organic Chemistry I course demonstrating that the same group of students changes their interpretation of a single item on the instrument. Conceivably the students perceive the process of “relating ideas” differently or with a changed emphasis toward the end of the semester (reprioritization). Furthermore, students develop a more defined study approach that either gravitates more strongly toward the Deep learning or toward the Surface learning approaches, rather than a mixture of both. These insights have both fundamental significance for the understanding of the learning process and practical implications for the designs of teaching methodologies. Structural equation modeling ; Confirmatory factor analysis ; Psychology ; Mathematics education ; Test (biology) ; Chemistry ; Statistics ; Social psychology ; Mathematics Various Chemistry Research Topics ; Science Education and Pedagogy ; Advanced Text Analysis Techniques