Conceptualization, Development and Validation of an Instrument for Investigating Elements of Undergraduate Physics Laboratory Learning Environments: The UPLLES (Undergraduate Physics Laboratory Learning Environment Survey).
Bibliographic record
Abstract
First-year undergraduate physics laboratories are important physics learning environments. However, there is a lack of empirically informed literature regarding how students perceive their overall laboratory learning experiences. Recipe formats persist as the dominant form of instructional design in these sites, and these formats do not adequately support the development of students’ inquiry processes. There may be valid reasons for the lack of research into students’ views of their undergraduate physics laboratory learning environments, but work should be done to address these issues so that such research can occur. This paper describes the development and validation of a 23-item instrument, the UPLLES (Undergraduate Physics Laboratory Learning Environment Survey) that was undertaken as part of a multi-year project that is aimed to develop guided-inquiry oriented Physics laboratories for first-year students at the University of (name). The UPLLES was developed and validated through factor analysis using 476 student responses. The five sub-scales of the UPLLES are, Inquiry Orientation, Integration, Material Environment, Student Community, and Instructor Support. The value of the UPLLES within a battery of measures for evaluating reform efforts in undergraduate physics laboratories is discussed.
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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 | 0.038 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".