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Record W1973562194 · doi:10.1002/tea.20275

Natural pedagogical conversations in high school students' internship

2009· article· en· W1973562194 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

VenueJournal of Research in Science Teaching · 2009
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsInternshipConversationNatural (archaeology)PsychologyPedagogyMathematics educationScience educationMedical educationMedicine

Abstract

fetched live from OpenAlex

Abstract Many science educators encourage student experiences of “authentic” science by means of student participation in science‐related workplaces. Little research has been done, however, to investigate how “teaching” naturally occurs in such settings, where scientists or technicians normally do not have pedagogical training and generally do not have time (or value) receiving such training. This study examines how laboratory members without a pedagogical background or experience in teaching engage high school students during their internship activities. Drawing on conversation analysis, we analyze the minute‐by‐minute transactions that occurred while high school students participated in a leading environmental science laboratory. We find that the participation trajectory was based on demonstration‐practice‐connect (D‐P‐C) phases that continually recurred in the process of “doing” science. Concerning the transactional structures, we identify two basic conversation patterns—Initiate‐Clarify‐Reply (I‐C‐R) and Initiate‐Reply‐Clarify‐Reply (I‐R‐C‐R)—that do not only differ from the well‐known Initiate‐Reply‐Evaluate (I‐R‐E) patterns previously observed in science classrooms, but also could be combined to constitute more complex patterns. With respect to the organization of natural pedagogical conversations, we find that there were not only of preferred and dispreferred modes of responding but also ambiguous dispreferred modes ; and the formulating organization not only includes self‐formulating but also other‐formulating . These natural pedagogical conversations helped, on the one hand, students to clarify their understanding and, on the other hand, technicians (or teachers) to teach toward different needs for different students in different contexts. © 2009 Wiley Periodicals, Inc. J Res Sci Teach 46: 481–505, 2009

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)0.089
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0890.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.008
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 head0.330
GPT teacher head0.624
Teacher spread0.294 · 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