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Record W4319456638 · doi:10.31274/itaa.15937

Scaffolding A/synchronicity for Teaching Literature Review Development Remotely

2022· article· en· W4319456638 on OpenAlexaff
Sandra Tullio-Pow, Kirsten Schaefer, Shelley Haines, Tarah Burke-Harris

Bibliographic record

VenueInnovate to Elevate · 2022
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsComputer scienceReading (process)Presentation (obstetrics)Class (philosophy)Gateway (web page)Asynchronous communicationSet (abstract data type)World Wide WebMultimediaLibrary scienceMathematics educationPsychologyArtificial intelligenceLinguistics

Abstract

fetched live from OpenAlex

Literature reviews clarify the range of research that has been done and where gaps remain. We created an online teaching module using a series of synchronous and asynchronous learning activities to guide students how to read critically to compile an annotated bibliography as a gateway to building a literature review. This module began with a guest presentation from librarians about demystifying literature reviews, next students completed an interactive exercise together to practice reading critically to summarize/chart a journal article, followed by writing a corresponding annotation. The module culminated in a group activity, students were assigned a current research topic (e.g., gender identity) and a set of five related journal articles. Each student was responsible for reading/charting their assigned article prior to class; in class they collectively discussed key themes o write an introduction and summarized results to identify gaps in the literature reviewed to write the conclusion. 

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)0.011
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.839
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.394
Teacher spread0.353 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

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