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Record W4310232037 · doi:10.5539/ies.v15n6p94

Sustaining Education by Actualizing Affordances of Social Media Platforms During the Pandemic

2022· article· en· W4310232037 on OpenAlexvenueno aff
Naser G. H. Ali, Rabab D. Alsaffar, Yousif H. Alenzi, Faisal M. Almutairi

Bibliographic record

VenueInternational Education Studies · 2022
Typearticle
Languageen
FieldComputer Science
TopicDigital literacy in education
Canadian institutionsnot available
Fundersnot available
KeywordsAffordanceSocial mediaPsychologyQualitative researchPedagogySociologyComputer scienceCognitive psychologySocial scienceWorld Wide Web

Abstract

fetched live from OpenAlex

This paper draws on the affordances theory and investigates the ways in which pre-service teachers are sustaining social media uptake in learning by taking advantage of the opportunities afforded by the new delivery methods during the pandemic. This research is part of a descriptive mixed methods study. A questionnaire and in-depth, qualitative interviews were used to explore pre-service teachers’ perceptions of the affordances of social media platforms for learning and the actualization of those affordances. The survey and interview data were analyzed through the theoretical lens of affordance theory. The results suggest that the pre-service teachers actualized the affordances of social media by their knowledgeable use in a dynamic learning environment. The key findings are that the teachers perceived the social media applications to be flexible, useful and practical (functional affordances), bridges formal and informal learning and supported self-regulated learning (cognitive affordances), allowed pre-service teachers to assume new identities and discover learning as independent learners who had control over their learning (identity creation affordances), and fostered interaction and collaborative feedback (social affordances). Lack of guidance or lack of teacher presence was the main constraint. This research produces new knowledge and analysis and makes new theoretical contributions on the specific affordances of social media technologies. This study adds to and extends existing literature by contributing to an understanding of the actualization of the affordances of social media platforms.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.343
Threshold uncertainty score0.409

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.033
GPT teacher head0.357
Teacher spread0.324 · 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 designQualitative
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

Citations2
Published2022
Admission routes1
Has abstractyes

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