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Record W1483022990 · doi:10.19173/irrodl.v16i2.2019

Guidelines towards the facilitation of interactive online learning programmes in higher education

2015· article· en· W1483022990 on OpenAlexvenueno aff
Lydia Mbati, Ansie Minnaar

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
Fundersnot available
KeywordsFacilitatorEducational technologySynchronous learningConstructivist teaching methodsObservational studyDistance educationOpen learningPedagogyConstructivism (international relations)Collaborative learningPsychologyCurriculumObservational learningHigher educationFacilitationBlended learningLearning sciencesExperiential learningMathematics educationCooperative learningTeaching methodMedicine

Abstract

fetched live from OpenAlex

The creation of online platforms that establish new learning environments has led to the proliferation of institutions offering online learning programmes. However, the use of technologies for teaching and learning requires sound content specialization, as well as grounding in pedagogy. While gains made by constructivism and observational learning are well documented, research addressing online practices that best encourage constructivist and observational learning in Open and Distance Learning (ODL) contexts is limited. <br /><br />Using a phenomenological methodological approach, this research explored the lived experiences of online learning programme facilitators at an Open and Distance Learning higher education institution. The findings of this research study revealed that facilitators did not use constructivist and observational learning pedagogies to a large extent in their interaction with students. It is concluded that during the curriculum planning phase, facilitators should decide on methods and media to arouse the students’ attention and stimulating constructivist and observational learning amongst students during online courses. This also implies a more reasonable facilitator-student ratio because large numbers of students per facilitator proves not feasible in online learning. The paper concludes by providing guidelines for the facilitation of interactive online learning programmes.

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)0.011
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.886
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.314
GPT teacher head0.558
Teacher spread0.244 · 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.

Study designOther design
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

Citations58
Published2015
Admission routes1
Has abstractyes

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