Assessing the Stability and Replicability of the Associations between Goal Orientation and Self-Regulated Learning Strategies: A Pre-Registered Replication of Muis and Franco (2009)
Bibliographic record
Abstract
In this pre-registered replication of findings from Muis and Franco [2009; Contemporary Educational Psychology, 34(4), 306-318], college students (N = 978) from across the United States and Canada were surveyed regarding their goal orientations and learning strategies. A structural equation modelling approach was used to assess the associations between goal orientations and learning strategies. Twelve of the sixteen associations (75%) tested by Muis and Franco replicated successfully in the current study. Mastery approach goals positively predicted endorsement of all learning strategies (Rehearsal, Critical Thinking, Metacognitive Self-Regulation and Elaboration). Performance avoidance goals negatively predicted critical thinking, while positively predicting metacognitive self-regulation and rehearsal. Evidence for moderation by assignment type was found. No evidence of the moderation of these associations by gender, underrepresented minority status, or course type (STEM, Humanities, or Social Sciences) was found. The reliability of common scales used in educational research and issues concerning the replication of studies using structural equation modeling are 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 | 0.060 | 0.139 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".