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Record W2112458762 · doi:10.5430/jnep.v3n10p139

Learning through reflection: Supervising DRC master’s degree students within the open distance and learning context

2013· article· en· W2112458762 on OpenAlexvenueno aff
Lizeth Roets

Bibliographic record

VenueJournal of Nursing Education and Practice · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsnot available
FundersNew Partnership for Africa's DevelopmentUniversiteit van die Vrystaat
KeywordsContext (archaeology)Distance educationScholarshipNarrativePedagogyInternationalizationSupervisorDiversity (politics)Reflection (computer programming)SociologyPsychologyPolitical scienceComputer scienceGeographyBusiness

Abstract

fetched live from OpenAlex

The internationalisation of higher education is a global imperative that impacts on students and supervision practices in various ways. Culture and language diversity, as well as the characteristics of the students themselves in Open and Distance Learning, have been given little attention and the impact is not always taken into account. When implementing a scholarship development programme across language borders, factors such as culture and socio-economic background need to be taken into account because both can have an effect on the supervisory practices and success of such a programme. Supervision in a language not understood by the supervisor and the master’s degree students in the DRC challenged traditional western methodologies and paradigms. A qualitative narrative reflection was therefore undertaken to both critically reflect on the challenges encountered and initiate innovative ideas. Indeed, I can say that, in my supervisory practice, the western body of knowledge was challenged. As a result, new research methodology initiatives to improve distance education research supervision had to be initiated and implemented.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.445
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0010.003
Open science0.0000.000
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 head0.273
GPT teacher head0.502
Teacher spread0.230 · 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

Citations6
Published2013
Admission routes1
Has abstractyes

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