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Student motivation and instructional clarity: Linking experience sampling method data to objective behavioural
Alina Oschwald1, Julia Moeller2, Bärbel Kracke1
1Institute of Educational Science, Friedrich Schiller University Jena, Jena, Germany.
The British Journal of Educational Psychology
|April 19, 2025
Summary
Instructional clarity in lectures did not predict overall student motivation. However, detailed explanations positively influenced students
Area of Science:
- Educational Psychology
- Higher Education Pedagogy
- Learning Sciences
Background:
- Student motivation is influenced by situational factors, including teaching behaviors.
- Instructional clarity is a key teaching behavior hypothesized to impact student expectancies and task values.
- Previous research often relies on self-report data, necessitating combined objective and subjective measures.
Purpose of the Study:
- To investigate the relationship between lecturers' instructional clarity and university students' learning motivation.
- To combine experience sampling method (ESM) data on student motivation with video-coded instructional clarity.
- To examine how specific indicators of instructional clarity predict different facets of student motivation.
Main Methods:
- Utilized a dataset combining ESM self-reports of motivation from 155 preservice teachers over 10 weeks.
- Collected and qualitatively coded video recordings of 81 lecturers for instructional clarity (detail, variation, inconsistency).
- Employed cross-classified multilevel models to analyze the nested data structure (situations within students, clarity ratings).
Main Results:
- No significant association was found between overall instructional clarity indicators and global measures of motivation.
- Detailed explanation, a facet of instructional clarity, positively predicted students' expectations of success.
- Detailed explanation also positively predicted students' perceptions of effort costs.
Conclusions:
- While overall instructional clarity may not directly impact global motivation, specific components like detailed explanations are influential.
- Combining objective observational data (videos) with subjective self-reports (ESM) offers a robust approach to studying teaching-learning dynamics.
- This methodology provides a more nuanced understanding of how teaching behaviors affect student motivation in authentic learning environments.
Keywords:
experience sampling methodinstructional clarityintensive longitudinal datalecturer claritysituated expectancy‐value theoryMore Related Videos
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