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Record W4403048932 · doi:10.54337/nlc.v11.8750

Learning in the wild

2018· article· en· W4403048932 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

VenueProceedings of the International Conference on Networked Learning · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsUniversity of British ColumbiaToronto Metropolitan University
Fundersnot available
KeywordsZoologyPsychologyBiology

Abstract

fetched live from OpenAlex

The theoretical lenses, empirical measures and analytical tools associated with social network analysis comprise a wealth of knowledge that can be used to analyse networked learning. This has popularized the use of the social network analysis approach to understand and visualize structures and dynamics in online learning networks, particularly where data could be automatically gathered and analysed. Research in the field of social network learning analysis has (a) used social network visualizations as a feedback mechanism and an intervention to enhance online social learning activities (Bakharia & Dawson, 2011; Schreurs, Teplovs, Ferguson, de Laat, & Buckingham Shum, 2013), (b) investigated what variables predicted the formation of learning ties in networked learning processes (Cho, Gay, Davidson, & Ingraffea, 2007), (c) predicted learning outcomes in online environments (Russo & Koesten, 2005), and (d) studied the nature of the learning ties (de Laat, 2006). This paper expands the understanding of the variables predicting the formation of learning ties in online informal environments. Reddit, an online news sharing site that is commonly referred to as ‘the front page of the Internet’, has been chosen as the environment for our investigation because conversations on it emerge from the contributions of members, and it combines perspectives of experts and non-experts (Moore & Chuang, 2017) taking place in a plethora of subcultures (subreddits) occurring outside traditional settings. We study two subreddit communities, ‘AskStatistics’, and ‘AskSocialScience’, in which we believe that informal learning is likely to happen in Reddit, and which offer avenues for comparison both in terms of the communication dynamics and learning processes occurring between members. We gathered all the interactions amongst the users of these two subreddit communities for a 1-year period, from January 1st, 2015 until December 31st, 2015. Exponential Random Graph models (ERGm) were employed to determine the endogenous (network) and exogenous (node attributes) factors facilitating the networked ties amongst the users of these communities. We found evidence that Redditors’ networked ties arise from network dynamics (reciprocity and transitivity) and from the Redditors’ role as a moderator in the subreddit communities. These results shed light into the understanding of the variables predicting the formation of ties in informal networked learning environments, and more broadly contribute to the development of the field of social network learning analysis.

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 score0.790
Threshold uncertainty score0.360

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 communication0.0000.000
Open science0.0010.000
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 head0.060
GPT teacher head0.356
Teacher spread0.296 · 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