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Record W3106881665 · doi:10.21125/iceri.2020.2041

COLLABORATION IN FACE TO FACE VERSUS ON-LINE TEACHING

2020· article· en· W3106881665 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueICERI proceedings · 2020
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsnot available
Fundersnot available
KeywordsFace (sociological concept)Face-to-faceComputer scienceLine (geometry)Artificial intelligenceSociologyMathematics

Abstract

fetched live from OpenAlex

In Canada, the perspective changed from working independently to collaborating in education. In industry, teams that work collaboratively often access greater resources, recognition and rewards when facing competition for finite resources. The reported study deals with preparing future teachers to implement collaboration while they are learning about it themselves based on theoretical tenets and practical applications. Activities devised were of a three tier action-oriented nature requiring task completion, and based on the backdrop of collaboration, similar to cooperation but taking it to a higher level with active participation of all the members. In this case, we explored a collaborative annotated vocabulary task, including drawing pictures and contributing names and expressions in writing where relevant. Collaboration requires awareness, motivation, self-synchronization, participation, mediation, reciprocity, reflection and engagement, then the question of how to increase collaboration among student participants required serious pondering when having to deliver this, through on-line courses, especially given that some learners have only basic access to technological means. So, instructors had to bridge the gaps both theoretically and practically. The methodology was qualitative (Creswell & Poth, 2018), using interaction analysis (Gardner, 2019). We also looked at affinity spaces (Gee, 2005) and communities of practice (Lave & Wenger, 1991; Wenger, 1998). The basic question examined was, how is collaboration achieved with this group of university students? After explaining underlying theoretical concepts and grouping students, a second language collaborative task was designed around vocabulary building and learning useful associated expressions. Observational and procedural notes were taken during the process, while the instructor devised a collaborative activity going through the stages of group building, seeking resources, building-in reinforcement stages and during the actual collaboration through break-up rooms of selected participants during on-line work and use of the chat feature as well as page share applications. We observed and analyzed group activity. Among key findings we uncovered the sharing of work-spaces, however if obvious during in-class teaching, break-up rooms did not provide full scope. Students found it difficult to give up control to other people. They did not like being vulnerable, thankfully no grade was attached to the completed task. They found out when it hurt to give in and when to back down. Another issue was the inherent messiness of collaboration. There was also an issue when students lacked self-regulation (Bandura, 1997) and tended to complain about inclusion. Overall great ideas were generated although through some tension; this made participants take more notice and it hopefully added to their learning. Other findings will be discussed including the messiness of collaboration.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.801
Threshold uncertainty score0.757

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.108
GPT teacher head0.440
Teacher spread0.332 · 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