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Record W2589188363 · doi:10.1177/1469787417693495

Considerations for using personal Wi-Fi enabled devices as “clickers” in a large university class

2017· article· en· W2589188363 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

VenueActive Learning in Higher Education · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Teaching Methods
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsClickerMobile deviceAttendanceClass (philosophy)PopularityComputer scienceMultimediaPsychologyMathematics educationWorld Wide Web

Abstract

fetched live from OpenAlex

Interactive student response systems, commonly referred to as clickers, have increased in popularity in higher education classrooms as a means to improve engagement and enhance learning. Clicker systems come with handheld devices as well as a radio frequency receiver. A Wi-Fi connection to the receiver is possible, enabling students to use their personal smartphones, tablets, or laptops instead of the handheld device. The objective of this study was to determine the feasibility of students using their personal Wi-Fi enabled devices as clickers in a large university class. In addition, we sought to elicit student perceptions of clicker use in general. Overall, the majority of students preferred using their personal devices, thus saving several minutes of class time in distribution and collection. Students gave very positive feedback on the use of clickers; however, they did not like that clickers could be used to track attendance and participation.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.351
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.134
GPT teacher head0.441
Teacher spread0.307 · 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