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Record W2097588487 · doi:10.5539/ass.v9n16p95

Blogging to Enhance Writing Skills: A Survey of Students’ Perception and Attitude

2013· article· en· W2097588487 on OpenAlexvenueno aff
Nur Ehsan Mohd Said, Melor Md Yunus, Luke Kenny Doring, Alfian Asmi, Farah Aqilah, Lisa Kwan Su Li

Bibliographic record

VenueAsian Social Science · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsnot available
Fundersnot available
KeywordsPerceptionPerspective (graphical)PsychologyPositive attitudeCollaborative writingMathematics educationMedical educationPedagogyComputer scienceSocial psychologyMedicine

Abstract

fetched live from OpenAlex

Several studies concur that the use of a blog can positively enhance learning in the second language classroom and that blogs can improve writing skills. Research has confirmed positive uses of the blog which include writing for an audience and peer review, the development of a student’s analytical skills and the development of a sense of community through a collaborative learning environment via weblog. This paper presents the results of a research project which was undertaken to investigate a group of 33 students in Universiti Kebangsaan Malaysia. Data were collected via online questionnaire survey related to their perception and perspective on the implementation of blogging activities to teaching writing skills. Results suggested that the participants have positive perceptions and attitude in using blog to improve writing skills and they perceived that blogging was an effective tool to teach writing in English that helped them improve their writing and kept them motivated.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.026
GPT teacher head0.455
Teacher spread0.429 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations44
Published2013
Admission routes1
Has abstractyes

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