Students and Instructors as Partners in Designing Labs: The Value of Conflicting Perspectives
Bibliographic record
Abstract
Laboratories are critical to undergraduate education in most STEM disciplines. In principle, they provide opportunities to apply theoretical knowledge, build psychomotor skills and engage in problem solving exercises with an emphasis on experiential learning. Designing these experiences poses challenges for educators, particularly in finding the right balance of pedagogical value and student engagement. As the perception of educators and that of students of the relative importance of these parameters may not always align, it is important to examine instructor and student attitudes towards lab experiences. In this contribution, we outline two studies that examine which dimensions of laboratory experiences instructors and students value, and how they respectively evaluate these dimensions. In this we used a qualitative interview approach to examine how the student perspective can affect development of virtual labs. Though the instructor and student see similar goals in general for laboratory experiences, they have differing views on what constitutes the explicit and implicit goal. For the faculty member, the explicit goal is to foster a practical connection to abstract theoretical concepts, with the implicit goal of discovery and creativity. For the student, the opposite was the case. The lab is expected to give an explicit opportunity for discovery, problem solving and critical thinking, with the generalizability of the concepts or connection to theory as of secondary importance. These studies suggest that not only do the instructor and student value different aspects of learning (i.e., pedagogical value versus engagement) in the lab, but that they also do not even evaluate those aspects similarly. This disconnect between the instructor and student perspective could lead to the development of lab experiences, particularly in the virtual realm, that will ultimately fail to deliver the intended outcomes. These studies suggest that including the student perspective is essential to ensuring the success of labs.
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".