Assessing Students’ Approaches and Perceptions to Learning in Physics Experiments Based on Simulations and At-Home Lab Kits
Bibliographic record
Abstract
Our study evaluates students’ approaches to and perceptions of the use of hands-on at-home laboratory kits (HALK) experiments, open-source computer-based simulations (OSCBS), and their combination (OSCBS-HALK) in undergraduate introductory asynchronous online physics courses. Anonymous survey data from students who had completed online physics courses with labs based on simulations, at-home lab kits, or both were collected using a modified version of the Learn Questionnaire (MVLQ). Findings in this study indicate that among the six scales (interest and relevance; peer support; staff enthusiasm and support; teaching for understanding; alignment; and constructive feedback) used to measure students’ perceptions of the teaching and learning environments, interest and relevance, peer support, and teaching for understanding had statistically significant different means across the three lab types. Post-hoc comparisons using the Tukey HSD test for the interest and relevance scale indicated that students viewed using a combination approach of OSCBS and HALK labs (M = 3.98, SD = 0.61) more significantly positive than using computer-simulated labs only (M = 3.56, SD = 0.75). Compared to other labs, computer-simulated labs were perceived to lead to a deep approach to learning. However, they had the lowest interest and relevance, peer support, and alignment ranking among the three lab groups. Thus, developing strategies to improve students’ engagement and ability to translate the simulations into physical processes is recommended for OSCBS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".