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Record W2419123694 · doi:10.17220/ijpes.2015.02.004

Pre-service Teachers’ Perceptions of Technology and Multiliteracy Within the Inclusive Classroom

2015· article· en· W2419123694 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Psychology and Educational Studies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsNipissing University
Fundersnot available
KeywordsPerceptionTechnology integrationPlan (archaeology)Service (business)PsychologyMathematics educationPedagogyLimitingEducational technologyMedical educationEngineeringMedicineBusinessMarketing

Abstract

fetched live from OpenAlex

The increased use of technology in today’s schools has created new possibilities for pre-service teachers and their students. Rather than limiting the use of technology based on student ability, it is now possible for pre-service teachers to develop integrated multiliteracy lessons that integrate technology and enhance student learning. Technology in the form of apps for iPads, iPods, and desktop computers enable teachers to achieve this goal; however, pre-service teacher’s perceptions of technology and teacher self-efficacy in relation to technology may influence whether technology is integrated into their lessons. This paper examines 144 primary/junior pre-service teacher’s self-efficacy and perceptions of technology before and after developing an app based multiliteracy lesson plan. Findings suggest that new teachers were more comfortable with the idea of integrating technology into their lessons after researching and completing a lesson plan focusing on the use of apps within an inclusive classroom.

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)0.001
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 score0.283
Threshold uncertainty score0.316

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.045
GPT teacher head0.437
Teacher spread0.392 · 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