Exploring Student Perceptions of In-Class Interactive Activities in Post-Secondary Information Technology Courses
Bibliographic record
Abstract
In-class interactive activities are widely used to promote engagement in higher education, yet student perspectives on specific designs remain underexplored in information technology courses. This study examines perceptions of individual and group activities, with and without peer discussion, and compares reactions to theoretical and practical prompts. A cross-sectional survey was administered across two academic terms, encompassing six sections in three information technology courses, and surveyed master's and undergraduate students, yielding 279 responses. The survey measured three dimensions (enjoyment, inclusion, and understanding) on a five-point Likert scale and invited optional open-ended comments. Data were analyzed using descriptive statistics for scaled items and a brief thematic review of comments to identify recurring sentiments about activity design and implementation. The study maps design choices to student experience. It outlines implications for integrating interactive activities into post-secondary information technology courses, while noting limitations and priorities for future multi-site, performance-based research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".