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Record W2070325925 · doi:10.1109/fie.2010.5673617

Work in progress — An innovation merging “classroom flip” and team-based learning

2010· article· en· W2070325925 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

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicProblem and Project Based Learning
Canadian institutionsCégep de Sorel-TracyAlstom (Canada)
Fundersnot available
KeywordsComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

This work in progress compares two versions of a “classroom flip” instructional strategy in which lectures are moved from inside class to outside class. Class time is then spent on problem solving and feedback. In previous offerings of this materials science course, students were asked to read instructor-supplied lecture notes and complete an on-line warmup assignment prior to class. Informal cooperative learning activities such as think-pair-share were used during class, and clickers provided a mechanism for probing understanding and providing feedback. In the most recent offering, students viewed instructor-prepared multimedia microlectures and took an individual quiz as homework, then repeated the quiz and completed a problem set with an assigned team during class. Thus, the redesigned course delivered multimedia rather than text lectures, and utilized a structured team-based learning strategy rather than informal cooperative learning structures. Moreover, higher level “material selection challenges” were added to the redesigned course. This paper summarizes the planned assessment and evaluation methods to compare the two classroom flip models; results and analysis are not yet complete.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.975
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.034
GPT teacher head0.342
Teacher spread0.308 · 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

Quick stats

Citations73
Published2010
Admission routes1
Has abstractyes

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