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Record W2765534680 · doi:10.5539/mas.v11n11p20

Distance Learning – A Potential Opportunity for Thailand

2017· article· en· W2765534680 on OpenAlexvenueno aff
Nachayapat Rodprayoon, Chompu Nuangjamnon, Stanislaw Maj

Bibliographic record

VenueModern Applied Science · 2017
Typearticle
Languageen
FieldComputer Science
TopicOnline Learning and Analytics
Canadian institutionsnot available
Fundersnot available
KeywordsAccreditationDistance educationWorkforceQuality (philosophy)Higher educationAgency (philosophy)Open learningMedical educationComputer sciencePedagogyPsychologySociologyCooperative learningPolitical scienceTeaching methodMedicine

Abstract

fetched live from OpenAlex

Distance learning is a global phenomenon with a wide range of available courses; however concerns exist regarding both course quality and educational standards. Within Australia the further and higher education sectors are highly regulated by the Tertiary Education Quality and Standards Agency and the Australian Skills Quality Authority respectively. All educational providers must meet the appropriate compliance requirements. The Open Universities Australia consortium is a group of eight Australian Universities. This consortium offers 44 undergraduate awards and 127 postgraduate awards; however they are predominantly in disciplines suitable for distance learning. The Engineering Institute of Technology offers a wide range of accredited distance learning courses but to people already in the workforce. Despite the widespread availability of eLearning tools such as mobile learning and well established instructional platforms within Thailand Online Distance Learning (ODL) is not well represented. In order to analyze potential barriers to this mode of learning a group of Thai university students attended a 1.5 hour lecture remotely and feedback was collected. The results clearly demonstrate that within this single cohort there was considerable interest in studying in a distance learning mode.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.959
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0010.001
Open science0.0030.001
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 head0.025
GPT teacher head0.290
Teacher spread0.264 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations1
Published2017
Admission routes1
Has abstractyes

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