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Record W2972821019 · doi:10.28945/4411

Does Size Matter? Instructors’ and Students’ Perceptions of Students’ Use of Technology in the Classroom

2019· article· en· W2972821019 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Information Technology Education Research · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsUniversity of Waterloo
FundersUniversity of Waterloo
KeywordsClass (philosophy)Class sizeMathematics educationTask (project management)PsychologyPerceptionAffect (linguistics)Medical educationComputer scienceMedicineEngineering

Abstract

fetched live from OpenAlex

Aim/Purpose: The aim of this study was to explore whether students’ self-initiated personal technology use differ by class size as well as to explore students and instructors’ perspectives on whether students’ technology use in class is a problem. Background: Because class size influences several aspects of student engagement, it is plausible that class size would affect students’ technology behaviours, but, to our knowledge, no study has directly examined class size as a factor in students’ on- and off-task technology use. There is also a paucity of research on how the use of off-task technology affects instructors. Methodology: We surveyed all undergraduate students and faculty in one Faculty at a Canadian university in Fall 2016. A total of 478 students and 36 instructors completed the survey. The survey contained questions about students’ and instructors’ behaviours and attitudes towards the use of technology in class. Quantitative data were analyzed in SPSS and Excel and qualitative excerpts from short-answer questions on the survey were analyzed in NVIVO 8. Contribution: This paper demonstrates that students’ on- and off-task technology use in class is influenced by class-size. It also informs us on the impact students’ technology use has on instructors in the academic classroom. Findings: Student-initiated technology use increased significantly as class size increased. Students and instructors expressed little concern about the impact of class-related technology use on learning and views did not differ significantly between these two groups. Although both students and instructors believed off-task technology use hinders learning, their views differed significantly, with more instructors than students feeling strongly that students’ use of technology in class is a problem. Recommendations for Practitioners: We need to develop guidelines on how to address off-task technology use in class. Recommendation for Researchers: More research is needed to explore how the use of technology in class affects instructors. Impact on Society: Higher education industry needs to consider how to manage the use of off-task technology in class. Future Research: We need to explore further how to mitigate the factors contributing to the off-task technology use in academic 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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.382
Threshold uncertainty score0.329

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.408
Teacher spread0.389 · 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