MétaCan
Menu
Back to cohort
Record W2792954193 · doi:10.1177/0098628318762894

The Partially Flipped Classroom

2018· article· en· W2792954193 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

VenueTeaching of Psychology · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Teaching Methods
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsFlipped classroomCommitPopularityClass (philosophy)Mathematics educationPsychologyFlipped learningSection (typography)Computer scienceSocial psychologyArtificial intelligence

Abstract

fetched live from OpenAlex

Flipped classrooms are gaining popularity, especially in psychology statistics courses. However, not all courses lend themselves to a fully flipped design, and some instructors might not want to commit to flipping every class. We tested the effectiveness of flipping just one component (a module on junk science) of a large methods course. We compared two sections, one in a traditional format ( n = 128) and the other in a flipped format ( n = 139), based on students’ academic performance and attitudes toward the class structure. Compared to students in the traditional lecture section, students in the flipped section performed significantly better on a quiz tied to the lecture content and rated their enjoyment of the exercise as higher. These findings demonstrate the utility of using partial flipped classroom techniques with large classes.

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)0.011
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.886
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.077
GPT teacher head0.490
Teacher spread0.413 · 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