IMPACT OF LANGUAGE AND STRUCTURE OF INSTRUCTIONS ON STUDENTS’ CONFIDENCE TOWARDS COMPLETING ASSIGNMENTS
Bibliographic record
Abstract
First-year engineering students usually spend more time on courses assignments and projects that they perceived to be more difficult, which increases students’ workload and impacts their persistence in engineering programs. Students possess a higher level of confidence also tend to perform better on the tasks. Therefore, it is important to explore the impact of different aspects of assignment instructions on students’ perceived confidence, and establish a comprehensive set of guidelines for first-year course instructors and curriculum designers in instruction writing. 
 This research builds on existing first-year engineering student workload survey to identify the students’ confidence level on assignments in each first-year courses taught in University of Toronto. We compared assignment instructions in first-year engineering courses that students perceived to be difficult and easy, and conducted a focus group study to analyze students’ confidence level towards the same assignments but two different instructions. Observations suggest that students perceived assignments involving new concepts and complex problem context appear to be more difficult. Qualitative responses from students suggest that short instructions with explanations of course connections using plain language could increase students’ self-confidence towards completing these assignments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".