Doing Open Science in a Research-Based Seminar: Students’ Positioning Towards Openness in Higher Education
Bibliographic record
Abstract
This study investigates undergraduate students’ attitudes towards and experiences with open education practices (OEP) in a research-based linguistics seminar. Data was collected through written assignments in which two groups of students in subsequent terms were surveyed on their willingness to publish (a) academic posters in open access (OA); (b) teaching concepts as open educational resources (OER); and (c) personal reflections on the research process in OA. Through qualitative data analysis, we examine students’ apprehensions and motivations to publish their artifacts. We find that key motivators are a sense of belonging, personal reward, and an active contribution to a culture of collaboration, whereas apprehensions are grounded in concerns about the quality of their work, uncertainties about licensing, and fear of vulnerability through visibility. We show that open science practices and OEP can be combined synergistically in process-oriented, research-based, and collaborative seminar concepts, and we formulate recommendations for lecturers on how to successfully address OEP in the classroom.
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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 | 0.021 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".