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Record W2758118303 · doi:10.19173/irrodl.v18i6.2995

Assessing Acceptance Toward Wiki Technology in the Context of Higher Education

2017· article· en· W2758118303 on OpenAlex
Παναγιώτα Αλτανοπούλου, Νικόλαος Τσέλιος

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsnot available
Fundersnot available
KeywordsUsabilityTechnology acceptance modelUnified theory of acceptance and use of technologyContext (archaeology)PsychologyBig Five personality traitsComputer sciencePersonalityClass (philosophy)Social influenceSocial psychologyHuman–computer interaction

Abstract

fetched live from OpenAlex

<p class="3">This study investigated undergraduate students’ intention to use wiki technology. An extension of the Technology Acceptance Model (TAM) has been used by taking into account not only students’ wiki perceived utility and usability, but also Big Five personality characteristics and two other variables, social norms, and facilitating conditions, as proposed in the Unified Theory of Acceptance and Use of Technology (UTAUT). Students’ beliefs before (pre-wiki scenario) and after (post-wiki scenario) the actual use of the wiki system were investigated, with 85 and 86 participants respectively. The hypotheses were tested using partial least squares analysis. For the pre-wiki scenario, 8/15 hypotheses were confirmed and 11/15 for the post-wiki scenario. The relationship between perceived ease of use and perceived usefulness was found to be of the highest magnitude. The most notable difference across the two scenarios was that the relation between perceived ease of use and attitudes towards use was significant only in the first scenario. The results demonstrate that the proposed TAM-extended model could predict students’ wiki acceptance.</p>

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)0.007
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.724
Threshold uncertainty score0.503

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.004
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 science0.0020.001
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 head0.222
GPT teacher head0.552
Teacher spread0.329 · 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