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Record W2025683676 · doi:10.1108/10650740910967393

Open, connected, social – implications for educational design

2009· article· en· W2025683676 on OpenAlexaff
Alec Couros

Bibliographic record

VenueCampus-Wide Information Systems · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsConnectivismOriginalityOpenness to experienceOpen educationComputer scienceOpen learningInstructional designValue (mathematics)Massive open online courseTransparency (behavior)Distance educationLearning environmentKnowledge managementPsychologyPedagogyMathematics educationWorld Wide WebLearning theoryTeaching methodCooperative learningMultimediaSocial psychology

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to describe the design and implementation of an open access, graduate education course where openness, connectivism, and social learning are guiding principles. The described experience aims to offer insight into developing courses that respond to changes in the manner in which individuals learn, connect, and form knowledge. Design/methodology/approach The course implements Web 2.0 and open source software within the learning environment. Pedagogical processes are also congruent with philosophies inherent in the open source movement, especially group collaboration and transparency. Findings The facilitation of this course is complex and would likely be difficult for many instructors. However, student satisfaction is high and long‐term, social learning benefits are perceived to be positive. Originality/value This course is one of the first of its kind, and one that inspired other explorations into open teaching/pedagogical course formats.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.025
metaresearch head score (Gemma)0.050
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.025
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.050
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0060.023
Scholarly communication0.0150.011
Open science0.0020.008
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0170.002

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 head0.053
GPT teacher head0.372
Teacher spread0.319 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations42
Published2009
Admission routes1
Has abstractyes

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