Utilisation of High-Impact Educational Practises (HIPS) to Engage Undergraduates: A Preliminary Case Study
Bibliographic record
Abstract
The purpose of this preliminary study is, firstly, to identify the most preferred high-impact educational practises (HIPs) among undergraduates and, secondly, to recommend best practises and strategies for implementing HIPs in higher education. This study included 61 undergraduates from a variety of degree programmes that implemented HIPs in one general studies course. Descriptive statistics and frequency were used to analyse the data. The findings revealed that the most popular HIP among undergraduates is service/community-based learning (SBL), and the least preferred HIP among undergraduates is Intensive Academic Writing (IAW). This study's findings are critical for preliminary understanding of the importance of learning styles in order to be effective and sensitive in teaching and learning, to have flexible and diverse instructional planning, and to diversify teaching methods. This was a preliminary case study that emphasised the significance of HIPs in the higher education curriculum and their implementation for a positive academic learning experience among undergraduates.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".