Confirmatory factor analysis of two self-efficacy scales for astronomy understanding and robotic telescope use
Bibliographic record
Abstract
This paper presents the results of a confirmatory factor analysis on two self-efficacy scales designed to probe the self-efficacy of college-level introductory astronomy (Astro-101) students (n 15181) from 22 institutions across the United States of America and Canada. The students undertook a course based on similar curriculum materials, which involved students using robotic telescopes to support their learning of astronomical concepts covered in the "traditional" Astro-101 courses. Previous research by the authors using these self-efficacy scales within a pre-/post-test approach showed both high reliabilities and very high construct validities. However, the scale purporting to measure students' self-efficacy in relation to their use of the astronomical instrumentation associated with online robotic telescopes was particularly skewed and required further investigation. This current study builds on the previous work and shows how a slight adjustment of the survey items presents an improved and robust scale for measuring self-efficacy.
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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 | 0.017 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".