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TAKING EXPERIENTIAL LEARNING ONLINE: STUDENT PERCEPTIONS

2021· article· en· W3171657378 on OpenAlexaffabout
Patricia Danyluk, Theodora Kapoyannis, Astrid Kendrick

Bibliographic record

VenueInternational journal on innovations in online education · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPracticumBachelorPsychologyMedical educationMathematics educationPedagogyExperiential learningOnline learningTeacher educationMultimediaComputer scienceMedicinePolitical science

Abstract

fetched live from OpenAlex

This article examines the impact of an online field experience course designed for Bachelor of Education students during the COVID-19 crisis. When Alberta schools closed two days before preservice teachers' practicum was to begin, all 435 in-school placements had to be canceled. To ensure students were able to progress in their program without disruption, the authors designed a unique online course to replace the traditional in-school practicum. This mixed-methods research study explores the key findings of an online survey of preservice teachers who made the shift to an online environment. The data included examination of course documents and discussions with instructors during weekly community of practice meetings. Through the innovation of the newly created online practicum course, preservice teachers developed an enhanced appreciation for online learning. However, in the absence of kindergarten to grade 12 students, the online practicum was unable to provide some of the more practical aspects of an in-school practicum. The authors have begun to explore a gap in preservice teacher education, which they have coined digital instructional literacy.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.600
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.061
GPT teacher head0.480
Teacher spread0.419 · 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
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".

Quick stats

Citations3
Published2021
Admission routes2
Has abstractyes

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