Reflective Diaries as a Tool for Promoting Learning and Teaching in Higher Education
Bibliographic record
Abstract
The concept of reflection has become increasingly prevalent in higher education over recent decades, particularly in the domains of teaching and learning. Being a reflective learner means that students can critically evaluate their learning, determine areas of their learning that need further development and make themselves more independent learners. This paper discusses a case study where reflective diaries were used to facilitate and assess both learning and teaching methods. As an assessment method, reflective diaries can assess students’ comprehension of the course content and can also promote critical self-reflection and enhance self-awareness (Biggs, 1999; O’Rourke, 1998). The data were collected through individual interviews and reflective diaries written by undergraduate students at the University of Dhofar. Data analysis indicates that the use of reflective diaries proved beneficial for enhancing both teaching and learning experiences. This is because the process of writing the diaries requires students to reflect on the learning activities that have taken place in class, analyze their own learning and express it in a personal way. Reflective diaries can also enable teachers to evaluate their teaching methods and generate feedback for improving their classroom practices.
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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 | 0.029 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".