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Record W2011471298 · doi:10.5539/ies.v3n2p3

Student Perceptions of Teachers’ Nonverbal and Verbal Communication: A Comparison of Best and Worst Professors across Six Cultures

2010· article· en· W2011471298 on OpenAlexvenueno aff
Alexia Georgakopoulos, Laura K. Guerrero

Bibliographic record

VenueInternational Education Studies · 2010
Typearticle
Languageen
FieldPsychology
TopicCommunication in Education and Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsConversationNonverbal communicationPsychologyClass (philosophy)PerceptionSocial psychologyDevelopmental psychologyCommunicationComputer science

Abstract

fetched live from OpenAlex

Students from six countries—Australia, Japan, Mexico, Sweden, Taiwan, and the United States—recalled the extent to which their best or worst professors used various forms of communication that have been associated with effective teaching. Across cultures, best professors were perceived to employ more nonverbal expressiveness, relaxed movement, in-class conversation, and out-of-class communication than worst professors. Relative to Japanese and Taiwanese students, Australian and U.S. students perceived their professors to use more nonverbal expressiveness. Students from Australia, Sweden, and the U.S. also perceived their best professors to use more in-class conversation than students from Japan or Taiwan perceived their best professors to use. However, Australian and U.S. students also perceived their best professors to use less out-of-class communication than did students from the other four countries. There were also differences in the forms of communication that discriminated between best and worst professors in each culture. For example, nonverbal expressiveness and in-class conversation were the best discriminators for Australian and U.S. students, whereas out-of-class communication and relaxed movement were the best discriminators for Japanese and Taiwanese students.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.075
Threshold uncertainty score0.510

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.128
GPT teacher head0.585
Teacher spread0.456 · 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

Citations14
Published2010
Admission routes1
Has abstractyes

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