Doctoral Candidate Brochure: Katie H. Asaro

Doctoral Dissertation Defense
of
Katie H. Asaro

For the degree of

Doctor of Philosophy
Learning Sciences

Investigating the Impact of Lecture Voice Match or Mismatch on Student Expectations and Evaluations in Online Learning

June 4, 2025
10:00 A.M.
Microsoft Teams

Investigating the Impact of Lecture Voice Match or Mismatch on Student Expectations and Evaluations in Online Learning

How do design elements in online courses influence student satisfaction and motivation? One underexplored factor is the match or mismatch between the instructor’s voice and the voice used in pre-recorded lectures. This issue is especially relevant in base course models, where non-designer instructors (NDIs) teach the course using pre-developed materials that may feature a different faculty member’s voice.

Guided by the Community of Inquiry (CoI) framework and Expectancy-Value Theory (EVT), this dissertation examined how voice match or mismatch impacts student satisfaction, expectancy beliefs, task value, and evaluations of the instructor.

A between-subjects design with 309 participants was used. A MANOVA revealed significant group differences based on voice condition, and a follow-up Discriminant Function Analysis identified a small but meaningful group separation. Instructor evaluations and overall satisfaction were the strongest contributors to this difference, while expectancy beliefs and task value played a smaller role.

These findings suggest that the instructor plays a meaningful role in asynchronous online courses and that even small course design features, such as the voice of narration, can influence students’ early perceptions. These insights have practical implications for institutions using base course models, highlighting the importance of reinforcing the instructor’s role in the course and their credibility through intentional course design. This study contributes to ongoing research on best practices in online learning environments