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Record W1843317122 · doi:10.21432/t2v315

Human-Computer Interaction: A Review of the Research on its Affective and Social Aspects

2003· review· en· W1843317122 on OpenAlexaffvenue
Colette Deaudelin, Marc Dussault, Monique Brodeur

Bibliographic record

VenueCanadian Journal of Learning and Technology · 2003
Typereview
Languageen
FieldComputer Science
TopicDigital Communication and Language
Canadian institutionsUniversité du Québec à MontréalUniversité du Québec à Trois-RivièresUniversité de Sherbrooke
Fundersnot available
KeywordsLocus of controlPsychologyQualitative researchCognitionUsabilitySocial psychologyHuman–computer interactionCognitive psychologyComputer scienceSocial scienceSociology

Abstract

fetched live from OpenAlex

Prevailing research influenced by cognitive psychology has dealt mainly with the cognitive aspects of the human-computer interaction (HCI). The advent of computers in schools should prompt educational researchers to scrutinize the affective and social aspects of student-computer interactions since they play an important role in learning. A review of 34 qualitative and non-qualitative studies was conducted. Its main purpose is to synthesize results and to highlight important issues that research has left unsolved. Results concern the nature of the HCI (social or parasocial), the interface (mainly a comparison between graphic and text types), and the relation between variables linked to HCI (mainly trust, locus of control, attitude, ease of use, and liking).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.010
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.110
GPT teacher head0.407
Teacher spread0.298 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations10
Published2003
Admission routes2
Has abstractyes

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