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Record W4400505083 · doi:10.5430/wjel.v14n6p217

Reflective Diaries as a Tool for Promoting Learning and Teaching in Higher Education

2024· article· en· W4400505083 on OpenAlexvenueno aff
Hatem Essa

Bibliographic record

VenueWorld Journal of English Language · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceMathematics educationPsychology

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.862
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.399
Teacher spread0.381 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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