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Record W4387489264 · doi:10.1525/collabra.88320

Assessing the Replicability of Cognitive Psychology During Remote Experiential Learning via Mobile Phone Technology

2023· article· en· W4387489264 on OpenAlex
Benjamin J. Dyson

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
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".

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCollabra Psychology · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsUniversity of Alberta
FundersUniversity of SussexUniversity of Alberta
KeywordsExperiential learningReplication (statistics)Context (archaeology)Asynchronous communicationMobile phoneObject (grammar)Computer sciencePsychologyCognitionPhoneMobile deviceMultimediaCognitive psychologyData scienceApplied psychologyMathematics educationArtificial intelligenceWorld Wide WebTelecommunicationsGeography

Abstract

fetched live from OpenAlex

A recent global health crisis demanded the wholesale configuration of both teaching and research from in-person to on-line formats. This allowed for an environmental sweep regarding the replicability of some classic and contemporary findings in Cognitive Psychology in the context of an undergraduate course, in which eight portable experimental packages were written for mobile phone. Running across three semesters (average n per study = 585), data consistently produced evidence either for (Faces, Search, Object, RPS, Rotate) or against (Doodle, Trivia) the original findings, with the exception of one study (House) that produced ambiguous findings. The scheme not only allows students exposure to and discussion of the replication crisis within empirical science, but also provides a framework for the future implementation of experiential learning during remote and asynchronous teaching. With continued evaluation made possible via Open Science Framework, a central question is whether on-line data collection violates an essential auxiliary assumption for the replication of in-person data.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.631
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.030
GPT teacher head0.432
Teacher spread0.402 · 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