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Record W1895430497 · doi:10.5539/ies.v8n9p25

The Development of Reflective Undergraduate Students: Assessing the Educational Benefits of Reflective Learning Logs in Entrepreneurship Module

2015· article· en· W1895430497 on OpenAlexvenueno aff
Yeoh Khar Kheng, Sethela June

Bibliographic record

VenueInternational Education Studies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsnot available
Fundersnot available
KeywordsFormative assessmentMathematics educationReflection (computer programming)PsychologyCritical thinkingEntrepreneurshipThematic analysisProcess (computing)Data collectionHigher educationReflective writingPedagogyQualitative researchSociologyComputer science

Abstract

fetched live from OpenAlex

The objective of this paper is to analyze written reflections on learning log of among the third and final year students undertaking an entrepreneurship module. Data was collected in the form of written reflection taken from the learning log of 140 students from 3 classes. At the end of the collection only 136 students’ responses were managed to be collected given 4 students failed to hand in the learning log. A thematic approach was utilized to present the reflections of the students and all data was recorded in a verbatim format. Findings show that most students have never written a reflective log or essay in the formative assessment. As a consequence, they had difficulty in writing the reflection when being requested to do so. This has resulted in their reflection being written descriptively which lacks in critical analysis and deep thinking. The results of this investigation have strongly suggested the need to urgently develop among the students the skills in writing reflectively as they go through the process of higher education which be useful in molding their future professional and entrepreneurial behavior as when they entered the job market which requires a critical reasoning ability. The limitation and future were discussed.

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)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.159
GPT teacher head0.534
Teacher spread0.376 · 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 designObservational
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

Citations3
Published2015
Admission routes1
Has abstractyes

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