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Record W2893394084 · doi:10.19173/irrodl.v19i4.2970

Parents’ and Students’ Attitudes Toward Tablet Integration in Schools

2018· article· en· W2893394084 on OpenAlexvenueno aff
Sha Zhu, Harrison Hao Yang, Jason MacLeod, Yinghui Shi, Di Wu

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsnot available
FundersMinistry of Education of the People's Republic of China
KeywordsPsychologyScale (ratio)Test (biology)Medical educationMedicine

Abstract

fetched live from OpenAlex

This study explored parents’ and students’ attitudes toward tablet usage in a formal educational setting. A total of 212 students from four 7th-grade classes, along with 145 of their parents, responded to the Tablet Acceptance Questionnaire. Quantitative methods including a t-test and partial least square (PLS) analyses were employed to examine students’ and parents’ attitudes toward tablet integration in schools, and to investigate factors influencing students’ and parents’ attitudes toward tablet usage, respectively. The results indicated significant differences between students’ and parents’ attitudes. Empirical findings suggested students hold more positive views than their parents with regard to tablet usage, tablet benefits for learning, and technical advantages and ease of use. Conversely, parents expressed greater concern over potential negative effects of tablet usage in education than do their children. This study also suggested educational benefits of tablet usage were the key factor influencing both students’ and parents’ attitudes. Based on the cross-examined understanding of parents’ and students’ attitudes, suggestions for large scale tablet initiatives are proposed.

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)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.153
Threshold uncertainty score0.472

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
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 science0.0010.001
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 head0.128
GPT teacher head0.493
Teacher spread0.365 · 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

Citations15
Published2018
Admission routes1
Has abstractyes

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