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The influence of instructional methods on the quality of online discussion

2006· article· en· W2094349848 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

VenueBritish Journal of Educational Technology · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsAthabasca UniversityMcGill University
Fundersnot available
KeywordsWebQuestDeliberationOnline discussionConstruct (python library)PsychologyQuality (philosophy)CognitionMathematics educationDiscussion boardContent analysisPedagogyComputer scienceSociologyMultimediaPolitical scienceEpistemologySocial science

Abstract

fetched live from OpenAlex

Abstract In this case study, we examined the influence of five groups of communication activities on the quality of students’ contributions to online discussion. The activities were the nominal group technique, debate, invited expert, WebQuest and reflective deliberation. Quality of discussion was operationalised as cognitive presence , a construct developed to investigate the role of critical discourse in higher, distance education contexts. Using the quantitative content analysis technique, the postings of 19 students in an undergraduate university course were assigned to one of the four categories of cognitive presence. Across the five activities, the proportion and number of contributions categorised in the highest phases of cognitive presence was low (20.21%), but was highest during the Webquest and debate activities. There are three advantageous qualities of these two activities, we argue: They were well structured. They provided clearly defined roles and responsibilities for the students. They provoked the students to explicitly confront others’ opinions.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.435
Threshold uncertainty score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
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 head0.024
GPT teacher head0.416
Teacher spread0.393 · 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