MétaCan
Menu
Back to cohort
Record W2885613562 · doi:10.1108/qrde-04-2018-0003

Conceptualizing Formal And Informal Learning In Moocs As Activity Systems

2018· article· en· W2885613562 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueQuarterly review of distance education · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Education and Learning Practices
Canadian institutionsUniversity of CalgaryUniversity of SaskatchewanAlgonquin College
Fundersnot available
KeywordsFormal learningInformal learningEducational technologyMathematics educationInformal educationDistance educationElectronic learningPsychologyPedagogyComputer scienceHigher educationSociologyPolitical science

Abstract

fetched live from OpenAlex

This article considers formal and informal learning activities in massive open online courses (MOOCs). MOOCs are often broadly positioned as either cMOOCs (based on connectivistic pedagogies) or xMOOCs (based on cognitivistic/behavioristic pedagogies). In a recent International Review of Research in Open and Distance article, Anders (2015) proposed a tripartite scheme for placing MOOCs on a continuum from content-based (xMOOCs) to community/task-based (cMOOCs) to network-based hybrids. Anders’ model is based on a meta-analysis of literature-based case studies of existing pedagogical approaches in MOOCs. In contrast, our in situ case study examined an emergent, hybrid MOOC design. The study shared in this article is focused on establishing the presence of both formal and informal learning activities in a network-based hybrid approach to MOOC design. The establishment of these two activity systems extended to include opportunities for boundary crossings between them. An outcome is a cultural-historical activity theory-informed model that extends commonly used and recognized MOOC typologies.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.815
Threshold uncertainty score0.318

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.037
GPT teacher head0.404
Teacher spread0.367 · 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