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Record W4410193510 · doi:10.19173/irrodl.v26i2.7915

Critiquing the Role of Field Facilitation in Open and Distance Learning Within a Resource-Constrained Environment in the Global South

2025· article· en· W4410193510 on OpenAlexvenueno aff
Robert Chagwamtsoka Kalima, Carolyn Grant, Sherran Clarence, Sioux McKenna

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Learning Practices
Canadian institutionsnot available
Fundersnot available
KeywordsFacilitationDistance educationField (mathematics)Resource (disambiguation)Educational technologyComputer scienceOpen educationKnowledge managementPsychologyMathematics educationWorld Wide Web

Abstract

fetched live from OpenAlex

Field facilitation is a crucial pedagogical intervention aimed at supporting student learning in resource-constrained open and distance learning environments, particularly in the Global South. This study used second generation activity theory to analyse a field facilitation intervention in an education faculty at a Malawian university, particularly the ways in which student learning and understanding was enabled or undermined while implementing field facilitation. The findings showed that many of the benefits of field facilitation were constrained for a number of reasons related to recruitment and training, pedagogies and understanding of student needs, and the materials and approaches used in field facilitation. For the field facilitation intervention to be fully effective as a means to deepen student learning, it needs to be embedded in the curriculum rather than implemented as an add-on activity, field facilitators need to be fully supported in their role, and the tools and materials available for teaching and tutoring need to be carefully designed within the resource constraints of the learning environment. These findings may inform reflection and further action in similarly resource-constrained contexts that are working to improve the success of open and distance learning.

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)0.018
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.670
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.012
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 head0.061
GPT teacher head0.476
Teacher spread0.416 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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