First Advisor

Jack Barbera

Term of Graduation

Spring 2022

Date of Publication


Document Type


Degree Name

Doctor of Philosophy (Ph.D.) in Chemistry







Physical Description

1 online resource (xi, 408 pages)


Incorporating active learning into a course has been generally found to lead to improved student learning outcomes; however, not all students benefit from these environments to the same extent. Although active learning environments provide the opportunity for students to interact and engage with the material, whether a student decides to do so is completely up to them. Therefore, the goal of this dissertation was to begin exploring active learning environments through the lens of student engagement and relevant associated variables (i.e., self-efficacy and student perceptions). This was completed through three separate but related projects.

Project I focused on investigating flipped courses at five different institutions, specifically in relation to students' interactions with and perceptions of pre-class materials (PCMs), as well as their self-efficacy. Students' interactions with and perceptions of required pre-class videos for each course were evaluated through student survey responses. A possible trend was found between the amount of peer-to-peer interaction included during the face-to-face (F2F) class time and how many videos students watched and when they watched them. Student responses also included feedback about what they found helpful and not helpful about the videos, such as being able to watch the videos at their own pace but also being unable to ask questions. An additional survey focused around students' self-efficacy was also administered to three of these institutions. The results showed that students' chemistry self-efficacy (CSE) tended to increase over the term. Comparisons of students' CSE at the end of the term between the different institutions indicated that there may be a relation between self-efficacy and the structure of the course.

Project II centered around students' perceptions of active learning environments. A previously developed survey, the Assessing Student Engagement in Class Tool (ASPECT), did not function as expected in the active learning environments at Portland State University (PSU). Therefore, two modified ASPECT (mASPECT) versions were created to address these concerns, as well as to account for two different active learning environments: Deliberative Democracy (DD) activity days and clicker question days. Data collected with the mASPECT versions were analyzed using exploratory factor analysis (EFA) and cognitive student interviews. Data collected after a DD activity resulted in three factors of 'personal effort', 'value of environment', and 'classroom support', whereas data collected after a clicker question day resulted in three similar 'personal effort', 'value of environment', and 'classroom support' factors, in addition to a fourth 'social influence' factor. Although the factors discovered for each version were similar, they were not identical.

The goal of Project III was to develop a survey measure to assess multiple dimensions of student engagement (i.e., behavioral, cognitive, emotional, and social) in worksheet activities and begin to explore the effect of engagement between different groups and in relation to student outcomes. Overall, this project led to the development of the Activity Engagement Survey (AcES), which was informed by both qualitative student interviews and quantitative survey responses. Both qualitative and quantitative results provided evidence that students perceived the two dimensions of behavioral and cognitive engagement to be very similar when considering engagement in worksheet activities, which led to a combined behavioral/cognitive factor. In addition, social engagement themes were discovered throughout the student interviews and items to address social engagement were included in the final survey when students worked on the worksheet with others. Confirmatory factor analysis (CFA) was used to assess possible models of engagement with data collected with the AcES. The most appropriate model was found to be a bifactor model, which includes an overall engagement factor in addition to individual factors of behavioral/cognitive, emotional, and social engagement, with a negative method factor to account for negatively worded survey items. This type of model was found to be most appropriate for data collected from students who worked with others (BC-E-S AcES), as well as with data from students who worked alone and were not asked to respond to social engagement items (BC-E AcES). Data collected with the AcES was then used to explore different comparisons. Although validity evidence was insufficient to allow for comparisons between in-person and remote environments, validity evidence was found to support the comparison of student engagement between students that worked with others and those that worked alone in the remote environment. Results showed that students who worked in a group had higher overall and behavioral/cognitive engagement then those that worked on the activities individually. Additionally, the relation between students' engagement in an activity and their understanding of the material covered in the activity was assessed using multiple linear regression. Overall, only behavioral/cognitive engagement was found to be significantly related to students' understanding of the material.


© 2022 Nicole Naibert

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