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Record W2248531306

A Study On Learner Readiness For MobileLearning At Open University Malaysia

2009· article· en· W2248531306 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueKnowledge based platform (Open University Malaysia) · 2009
Typearticle
Languageen
FieldComputer Science
TopicMobile Learning in Education
Canadian institutionsnot available
FundersOpen University Malaysia
KeywordsMobile phoneQuarter (Canadian coin)PreparednessMedical educationOpen universityPsychologyDistance educationPedagogyMedicineEngineeringGeographyPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Prior to embarking on mobile learning, a study was conducted to determine the readiness of learners at the Open University Malaysia (OUM), Malaysia’s first open and distance learning university. The study conducted in the last quarter of 2008 attempted to determine, among others, the extent of ownership of a mobile phone, readiness to be a mobile learner as indicated by questions such as willingness to buy a new mobile device and preparedness to subscribe to additional mobile services, types of materials they would like to receive and their perceptions about m-learning. Out of a total of 6,000 questionnaires distributed, 2,837 were returned. The respondents were from 31 learning centres from all parts of the country. Most of the respondents were between 31 and 35 years old and were largely undergraduates. The findings indicate that almost all (98.91 percent) learners at OUM have a mobile phone and that 82.84 percent of the respondents can imagine themselves learning through mobile devices. When further questioned, 47.98 percent of the learners stated they would be ready for m-learning within six months and another 15.73 percent believed they will be ready within 6 to 12 months. In other words, 63.71 percent of students are ready for m-learning within the next 12 months. The paper highlights the findings and implications to the m-learning project at the university

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.

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 categoriesMeta-epidemiology (narrow), Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.003
Open science0.0060.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.048
GPT teacher head0.296
Teacher spread0.248 · 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