Educational Attainment Post-Pandemic: An Examination of Growth Mindset Language and Strategies in Graduate Students
Bibliographic record
Abstract
This paper examines growth mindset, an evidence-based strategy posited by Carol Dweck (2007), within the framework of a classroom at a private, faith-based university. In a post-pandemic time where many students and people have felt adverse effects on their ability to adapt, this research studies the impact of mindset language and strategies on a student’s internal locus of control. The specific question the researchers posited was, does growth mindset language and strategies within a graduate-level class affect a student’s internal locus of control?Participants in this study were Master of Business Management students taking an online employee development course at Azusa Pacific University. The online course was modified to use growth mindset language and strategies. Changes in language focused on effort, starting with the syllabus and project instructions and continuing throughout the course. For example, language used in the weekly overviews focused on effort and explaining why effort was important.Survey results indicated that the graduate students did not report an increase in their level of growth mindset or locus of control. This is hypothetically due to the high level of growth mindset and internal locus of control already felt by the participants. This moves the focus for graduate students from mindset to the environment they are learning in, including the level of psychological safety felt by the students in the classroom.
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 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 | 0.002 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".