# Investigating the Evolution of Student Attitudes toward Science in a General Chemistry Course Using Latent Class and Latent Transition Analysis

## TL;DR

This study tracks how student attitudes toward science change during a chemistry course, revealing distinct groups and shifts in self-belief and interest.

## Contribution

The novel use of latent class and transition analysis reveals hidden patterns in student attitudes and highlights equity-related trends in STEM persistence.

## Key findings

- Three distinct student attitude groups were identified at the start of the semester.
- Student groups evolved over the semester, with notable shifts in self-belief and desire to pursue science.
- Female and second-year students were overrepresented in groups with lower science aspirations by the end of the course.

## Abstract

As science, technology, engineering, and mathematics
(STEM) education
researchers continue to explore ways to increase college student persistence
in STEM fields, the affective domain (e.g., attitudes, perceptions,
and self-efficacy) stands out as an area that can significantly impact
these efforts. Latent class analysis (LCA) and latent transition analysis
(LTA) are mixture modeling approaches that take a person-centered
approach to quantitative research, which can help us to further our
efforts to diversify STEM fields. This study seeks to use LCA and
LTA to investigate how students’ attitudes toward science in
general chemistry evolve over a semester. Using the Modified
Attitudes toward Science Inventory (mATSI), we grouped students
based on their responses to pre- and postsurvey items from the mATSI.
We found three distinct groups (classes) of students at the beginning
of the semester: (i) students with strong desires to pursue science
fields and high self-belief in their abilities to do well in science
courses (high–high), (ii) students with moderate desires and
low self-belief (mod-low), and (iii) students with moderate desires
to pursue science fields and moderate self-belief (mod-mod). Over
the course of the semester, these 3 groups evolved into (a) high desires
and high self-belief (high–high), (b) high desires and low
self-belief (high-low), and (c) low desires and low self-belief (low-low).
At the beginning of the semester, about 80% of the participants were
classified in the high–high group with the remaining 20% categorized
into the other two groups; however, by the end of the semester, about
70% were in the high–high group, with 30% distributed across
the other two groups. Using LTA and exploring the characteristics
of the student groups, we found that in groups where female and second-year
students were overrepresented, male and first-year students tended
to be underrepresented and vice versa. For example, female and second-year
students were overrepresented in groups more likely to leave the general
chemistry course with lower desires and self-belief, while male and
first-year students were overrepresented in groups more likely to
leave general chemistry with higher desires and self-belief Using
the LCA approach, we were able to explore groups (e.g., “high-low”
and “low-low”) that tend to get swallowed up by the
noise of the majority (in this case, the “high–high”
group). We hope the findings from this study encourage equity-based
researchers to continue to think about how they approach quantitative
data to give a voice to participant groups that may sometimes be hidden
under the guise of not having enough statistical significance/power.