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Record W2097340688 · doi:10.28945/2103

Engagement in Digital Lecture Halls: A Study of Student Course Engagement and Mobile Device use During Lecture

2015· article· en· W2097340688 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

VenueJournal of Information Technology Education Research · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsLaptopStudent engagementOnline courseMobile deviceMedical educationMobile phonePsychologyCourse (navigation)MultimediaMathematics educationComputer scienceEngineeringMedicineWorld Wide Web

Abstract

fetched live from OpenAlex

Universities have experienced increases in technology ownership and usage amongst students entering undergraduate programs. Almost all students report owning a mobile phone and many students view laptops and tablets as educational tools, though they also report using them for non-academic activities during lectures. We explored the relationship between student course engagement and the use of smartphones, laptops, cell phones, and tablets during lecture. Undergraduate students responded to an online survey asking about both course engagement and mobile device habits. Results show that smartphone use was most strongly related to lowered course engagement and while laptop use was related to lowered engagement, it was to a lesser extent. In contrast, overall engagement of students using tablets or cell phones was not significantly different than those who did not.

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)0.005
metaresearch head score (Gemma)0.003
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 score0.630
Threshold uncertainty score0.546

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.068
GPT teacher head0.442
Teacher spread0.374 · 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