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Record W2782401903 · doi:10.5430/ijhe.v7n1p1

Usage of Mobile Phone Applications and Its Impact on Teaching and Learning

2018· article· en· W2782401903 on OpenAlexvenueno aff
Nitza Davidovitch, Roman Yavich

Bibliographic record

VenueInternational Journal of Higher Education · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsnot available
Fundersnot available
KeywordsSpare timePhoneMobile phoneThe InternetPsychologyAssociation (psychology)Leisure timePopulationApplied psychologyMedical educationAdvertisingMultimediaEngineeringBusinessComputer scienceMedicineSociologyDemographyTelecommunicationsOperations managementPhysical therapyPhysical activityWorld Wide Web

Abstract

fetched live from OpenAlex

This study continues studies on the concept of leisure as culture dependent – between tradition and modernity, while focusing on the usage of mobile phone applications and its impact on teaching and learning within a unique population. The study examined the association between having NetSpark on one’s Smartphone and utilization of spare time among students who had or did not have the program installed. The assumption is that when the program is installed students will be more inclined to engage in non-internet related activities, such as spending time with friends, and when the program is not installed they will be more inclined to stay at home and be on the internet and will display less active life of other types. The research population included 120 9th-12th grade female students at a religious high school, aged 14-18. Half were students had had the NetSpark program installed on their phones, and half had not. The study used three questionnaires: a sociodemographic questionnaire, a questionnaire on Smartphone usage patterns, and a questionnaire on utilization of leisure time.The research findings show no association between use of Smartphone applications and of the internet among students in whose phones the program had been installed versus those in whose phones it had not been installed. Secondly, no association was found between utilization of leisure time among students in whose phones the program was installed versus those in whose phones it had not been installed. Furthermore, no difference was found between the total time for which respondents had been using cellular phones of by religiosity, and no difference was found in the joint effect of religiosity + program on the variable daily duration of internet use. Moreover, no difference was found in use of cellular applications between respondents who had / did not have the NetSpark program installed, however use of cellular applications was found to be higher among respondents who ranked themselves less religious than among respondents who ranked themselves as highly religious. Finally, no difference was found in the utilization of leisure time (various activities) among respondents with different levels of religiosity.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.714
Threshold uncertainty score0.192

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 studies0.0000.000
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 head0.012
GPT teacher head0.399
Teacher spread0.386 · 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

Citations18
Published2018
Admission routes1
Has abstractyes

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