Goal Setting, Academic Reminders, and College Success: A Large-Scale Field Experiment
Bibliographic record
Abstract
This article presents an independent large-scale experimental evaluation of two online goal-setting interventions. Both interventions are based on promising findings from the field of social psychology. Approximately 1,400 first-year undergraduate students at a large Canadian university were randomly assigned to complete one of two online goal-setting treatments or a control task. In addition, half of treated participants were offered the opportunity to receive follow-up goal-oriented reminders through e-mail or text messages to test a cost-effective method for increasing the saliency of treatment. Across all treatment groups, we observed no evidence of an effect on grade point average, course credits, or second-year persistence. Our estimates are precise enough to discern a 7% standardized performance effect at a 5% significance level. Our results hold by subsample, for various outcome variables, and across a number of specifications.
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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 | 0.004 | 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 | 0.001 |
| 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 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".