Self‐reflection, growth goals, and academic outcomes: A qualitative study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Goal-setting theory continues to be among the most popular and influential theories of motivation and performance, although there have been limited academic applications relative to applications in other domains, such as organizational psychology. AIMS: This paper summarizes existing quantitative research and then employs a qualitative approach to exploring academic growth via an in-depth reflective growth goal-setting methodology. SAMPLE: The study focuses on 92 UK final-year students enrolled in an elective advanced interpersonal skills and personal development module, with self-reflection and growth goal setting at its core. METHOD: Qualitative data in the form of regular reflective written diary entries and qualitative questionnaires were collected from students during, on completion of, and 6 months following the personal growth goal-setting programme. RESULTS: About 20% of students' self-set growth goals directly related to academic growth and performance; students reported that these had a strong impact on their achievement both during and following the reflective programme. Growth goals that were indirectly related to achievement (e.g., stress management) appeared to positively impact academic growth and other outcomes (e.g., well-being). A follow-up survey revealed that growth goal setting continued to impact academic growth factors (e.g., self-efficacy, academic performance) beyond the reflective programme itself. CONCLUSIONS: Academic growth can result from both academically direct and indirect growth goals, and growth goal setting appears to be aided by the process of simultaneous growth reflection. The implications for promoting academic growth via this unique learning and development approach are discussed.
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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 | 0.001 |
| 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) | 0.001 | 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 it