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Record W2090112737 · doi:10.5539/hes.v3n5p68

Pedagogical Implications of Using Discussion Board to Improve Student Learning in Higher Education

2013· article· en· W2090112737 on OpenAlexvenueno aff
Amani K. Hamdan Alghamdi

Bibliographic record

VenueHigher Education Studies · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
Fundersnot available
KeywordsBlackboard (design pattern)PsychologyHigher educationMedical educationMathematics educationSample (material)Control (management)Test (biology)MedicineComputer science

Abstract

fetched live from OpenAlex

This study reports on the pedagogical implications of using the Blackboard feature Discussion Board (DB) to improve students’ learning in higher education. The study sample included three sections of female students – a total of 155 students – in an undergraduate course at an international university in Saudi Arabia. The impact of using DB on first-year female students’ achievement was assessed through quantitative analyses of pre- and post-tests. The effect of DB on students’ attitudes was ascertained by means of qualitative analyses of students’ responses to a post-treatment questionnaire. The results indicated that students in the experimental group showed a greater degree of improvement in test scores than those in the control group, and that posting to Blackboard was positively related to improvement among those in the control group but not among those in the experimental group.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.142
GPT teacher head0.484
Teacher spread0.342 · 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 source (direct Gemma or distilled Codex), 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

Citations24
Published2013
Admission routes1
Has abstractyes

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