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Record W1606158957 · doi:10.19173/irrodl.v15i4.1585

An investigation into the management of online teaching and learning spaces: A case study involving graduate research students

2014· article· en· W1606158957 on OpenAlexvenueno aff
Rohan Jowallah

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
Fundersnot available
KeywordsAsynchronous communicationDistance educationComputer sciencePsychologyAsynchronous learningComputer-mediated communicationSpace (punctuation)Mathematics educationPedagogyWorld Wide WebSynchronous learningThe InternetTeaching methodCooperative learning

Abstract

fetched live from OpenAlex

<p>This research evaluates the strategies implemented to support the research activities of postgraduate students pursuing online master’s programs in the University of the West Indies Open Campus, as well as the activities of their supervisors. The three main strategies employed were (1) the use of a web-based ‘teaching-learning space’ to facilitate asynchronous interaction between students and their supervisors; (2) the provision of a scheduling tool to facilitate the planning of one-on-one meetings via a synchronous web-conferencing tool; and (3) the organization of research seminars using the same web-conferencing tool.</p><p>This research used Moore’s theory of transactional distance and social cognitive theoretical framework to guide the project. Moore’s model reemphasizes the need for stronger forms of communicating for online students, whereas the cognitive framework focuses on the need for social interaction among learner and teacher. Participants were graduate students (<em>n</em> = 34). All participants were required to complete a questionnaire online. Data were also collected from postings in discussion forums. Overall, notwithstanding limitations, the data shows there are benefits to be gained from conducting student research activities in an online environment.</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)0.074
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.868
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0740.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
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 head0.176
GPT teacher head0.539
Teacher spread0.363 · 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 designQualitative
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

Citations25
Published2014
Admission routes1
Has abstractyes

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