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Record W2527383016 · doi:10.19173/irrodl.v17i5.2561

Exploring Communication and Course Format: Conversation Frequency and Duration, Student Motives, and Perceived Teacher Approachability for Out-of-Class Contact

2016· article· en· W2527383016 on OpenAlexvenueno aff
Catherine Brooks, Stacy L. Young

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2016
Typearticle
Languageen
FieldPsychology
TopicCommunication in Education and Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsConversationClass (philosophy)PsychologyFace-to-faceComputer-mediated communicationDuration (music)Mathematics educationCourse (navigation)Online courseMedical educationPedagogyComputer scienceThe InternetWorld Wide WebCommunicationMedicineEngineering

Abstract

fetched live from OpenAlex

<p class="3">This study explored how course instructional format (i.e., online, face-to-face, or hybrid) is related to the frequency and duration of out-of-class communication (OCC) between college instructors and students, to student motives for communicating with teachers, and to perceived teacher approachability for conversation outside of class. Though differences in frequency of and student motives for engaging in OCC were not significant, students enrolled in face-to-face courses reported significantly more ongoing/durative OCC with their instructors compared to students enrolled other course types (i.e., online or hybrid). Students in fully online courses reported instructors to seem less receptive to but also less discouraging of OCC than students in face-to-face or hybrid courses. Overall, this study offers a sense of how students who seek informal interaction with instructors beyond the classroom are faring amid the increased reliance on web-based learning environments in higher education.</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.

How this classification was reachedexpand

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)0.004
metaresearch head score (Gemma)0.001
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 score0.212
Threshold uncertainty score0.192

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
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 science0.0000.000
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 head0.346
GPT teacher head0.529
Teacher spread0.183 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations16
Published2016
Admission routes1
Has abstractyes

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