Undergraduate Science Majors’ orientations to science and teaching in an out-of-school-time science outreach program.
Bibliographic record
Abstract
In this paper, we present learnings from a pilot study that brought pre-service teachers (PSTs) and undergraduate science majors (USMs) into contact with disadvantaged youth through science lessons offered in an out-of-school-time context. The program, Teaching Science in the Zone , had the goals of elicited youths’ science-related talk, and supporting their identity work. However, the success of the teaching project was limited, as preliminary analysis suggests that novice teachers were more focused on achieving instructional goals and ‘delivering content’ than on facilitating youths’ science talk, curiosity, and identification with science. Interview data along with video diaries, field notes and reflection data were collected from 6 PSTs and USMs participating in the program. This paper reports on three USMs identity work in relation to science and science teaching. Findings suggest that although they all discuss access to various forms of ‘science capital’ in narrating their trajectories into science, they do so in ways that suggest different forms of engagement with science. We argue that these different forms of engagement in science may impact the orientations USMs take to teaching science in OST contexts, and at the same time influence their science identity trajectories.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".