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Record W2134353924

Unlocking Language Education with Emerging Technologies: An Overview of Attitudes and Effectiveness

2013· article· en· W2134353924 on OpenAlexvenueno aff
Muhammad Ali Imran, Tenzila Khan

Bibliographic record

VenueJournal of academic and applied studies · 2013
Typearticle
Languageen
FieldComputer Science
TopicMobile Learning in Education
Canadian institutionsnot available
Fundersnot available
KeywordsAutonomyContext (archaeology)Mathematics educationPsychologySignificant differencePreferenceIngenuityEnglish languagePedagogyMedical educationComputer scienceMathematicsPolitical scienceStatisticsGeographyMedicine
DOInot available

Abstract

fetched live from OpenAlex

Present study sets out to investigate the attitude/opinion of university students regarding application of emerging technologies (iPad) in the context of ESL (English as second language) classrooms in Pakistan. The study was delimited to students of Punjab University (PU, a public sector university) and Beaconhouse National University (BNU, a private sector university), both top rated universities of Lahore and where English language teaching is given preference. The data was collected from 45 students of PU and 35 students of BNU via random sampling techniques. Collected data was organized and prepared for computer analysis with Statistical Package for Social Science (SPSS) version (16.0). Mean and Standard Deviation (SD) were calculated in order to describe opinions while t- test and ANOVA were applied to identify difference in opinion of respondents. Findings illustrated the significance of iPad employment in the face of improving level of learners’ motivation and concentration and rendering them more autonomy, ingenuity, exposure and versatility.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.802
Threshold uncertainty score0.213

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.031
GPT teacher head0.360
Teacher spread0.329 · 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.

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

Citations0
Published2013
Admission routes1
Has abstractyes

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