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Record W3133805225 · doi:10.1017/9781108589789.007

Laboratory-Based Oral Corrective Feedback

2021· book-chapter· en· W3133805225 on OpenAlexaff
Shawn Loewen, Susan M. Gass

Bibliographic record

VenueCambridge University Press eBooks · 2021
Typebook-chapter
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsCarleton UniversityUniversity of Victoria
Fundersnot available
KeywordsCorrective feedbackComputer sciencePsychologyMathematics education

Abstract

fetched live from OpenAlex

This chapter explores various aspects of lab-based research and considers its merits and limitations. We begin with a discussion and definition of lab-based research, considering not only the research venue, the instructor, and the instructional tasks, distinguishing amongst three types of research contexts: lab, classroom with intervention, and classroom without intervention. This differentiation is important in understanding the continuous nature of corrective feedback studies, ranging from lab-based to classroom-based. We further differentiate studies based on the amount of manipulation that is involved, with lab study and classroom intervention studies being characterized by manipulation and nonintervention classroom studies characterized by not having manipulation. We discuss a variety of lab-based studies where there are different degrees of researcher control, illustrating a wide range of research types. Finally, in this chapter we present results from meta-analyses that compare lab-based corrective feedback studies with classroom studies showing greater evidence of the effectiveness of corrective feedback in lab-based studies. Future directions for research in corrective feedback in classroom- versus lab-based studies are outlined.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.760
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.022
GPT teacher head0.241
Teacher spread0.219 · 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
GenreOther

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

Citations2
Published2021
Admission routes1
Has abstractyes

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