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Record W2770058420 · doi:10.5539/ies.v10n12p109

The Reality and Difficulties of Employing ICT in Teaching from the Perspective of Math Teachers of Middle Stage in Riyadh

2017· article· en· W2770058420 on OpenAlexvenueno aff
Mona S. Alghamdi

Bibliographic record

VenueInternational Education Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Technology Integration
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationInformation and Communications TechnologyPerspective (graphical)PsychologyTest (biology)Middle levelMathematicsComputer scienceEngineering

Abstract

fetched live from OpenAlex

The present study aims to identify the reality and difficulties of employing Information Communication Technology (ICT) in teaching from the perspective of female Mathematics teachers of middle stage in Riyadh, Saudi Arabia. The study sample consisted of (165) female Math teachers of middle stage in Riyadh. The tool utilized is a questionnaire; and in order to answer the study questions and verify the validity of its hypotheses, the author used frequencies, arithmetic means, standard deviations, ANOVA, and the Tukey Test. The results showed that the degrees of the availability of most of the domains of using devices and applications in teaching of Math were (often and sometimes). The results also showed that the availability of most of indicators of ICT employment in the teaching of Math for the middle stage was (often), the degree of the difficulties that limit the employment of ICT in the teaching of Math from the perspective of Math teachers was high and medium. The results also showed that there were no statistically significant differences (α ≤ 00.05) between the means of responses of the participants due to both scientific qualification and specialization. The results also showed statistically significant differences (α ≤ 00.05) between participants’ responses due to years of experience. In addition, there were no statistically significant differences (α ≤ 00.05) between the means of responses of the participants on each domain of the questionnaire due to years of experience.

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)0.006
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 score0.324
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.129
GPT teacher head0.468
Teacher spread0.339 · 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

Citations4
Published2017
Admission routes1
Has abstractyes

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