Abstract

Online learning sessions are becoming increasingly common. In this study, we reviewed over 150 studies of online and blended learning, revealing that the factors that affect student preferences for online or in-person learning vary widely and compiled a table of these factors. They can be categorized as either learning preferences or current lifestyle conditions. To better understand these preferences, we implemented an intervention in which college-level engineering students were given the choice to attend either an online or in-person session for a class they normally attended in a different modality. We compared college students' stated preferences with demonstrated attendance for online or in-person instruction. We surveyed approximately 150 undergraduate students from two different courses in engineering who participated in both in-person and online learning experiences. We conducted a pre and post survey, created based on the categories formed from our literature review. Data were analyzed using a paired sample t-test, Phi correlations, and structural equation modeling in order to determine the most salient combination of preferences that affect students' choice to attend either an online or in-person class. Furthermore, this research specifically sought to understand why students' stated preferences may or may not align with their demonstrated attendance for online or in-person learning. Based on survey results, we used targeted interviews to understand student choices from 13 students whose choices did not match their stated preferences. We found that most students in our context of a typical in-person university prefer in-person instruction, but they also want some online class sessions if it is more convenient for them at the time. Through applying The Reasoned Action Approach and Model, we analyzed students' stated preferences and compared these with their demonstrated actions. The analysis revealed that students' self-prediction via a survey about whether or not they would attend an online class session was statistically significant at predicting their actual attendance, whereas stated preference for some online class sessions were not predictive. This finding suggests that preference-based surveys may not reliably predict students' actions in regards to attending online or in-person class sessions. Instead, we recommend using a survey with an appropriate predictive question, which will allow universities and professors to determine if it will be worth investing the time and resources in to creating online class sessions.

Degree

PhD

College and Department

David O. McKay School of Education; Instructional Psychology and Technology

Rights

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