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Record W3085792691 · doi:10.22492/ije.8.3.05

Framing Undergraduate Perspectives on Experiential Learning Within Soka Education Theory

2020· article· en· W3085792691 on OpenAlexaffabout
Paul D. Sherman, Olivia Boukydis

Bibliographic record

VenueIAFOR Journal of Education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicAdult and Continuing Education Topics
Canadian institutionsUniversity of Guelph-Humber
Fundersnot available
KeywordsExperiential learningFraming (construction)Mathematics educationPedagogyPsychologyEngineering

Abstract

fetched live from OpenAlex

This article reports findings on two studies that explored undergraduate perspectives of experiential learning as a pedagogy that can produce impactful outcomes that align with Makiguchi's concept of Soka (value-creating) education.The twin studies examined perspectives of undergraduate faculty and students by investigating how experiential learning is viewed in terms of its impact on students' sense of happiness and satisfaction, acquired knowledge and skills, and potential for positively contributing to societal welfare.The article addresses how experiential learning provides critical opportunities for students to create value for making significant impact on the wellbeing of both the students and the wider society.Ten instructors and twelve students from a small university in Toronto, Canada, answered a series of identical questions in confidential semi-structured interviews.The data were analyzed for themes related to Makiguchi's values of beauty, gain, and good.A key finding from the analysis suggests that instructors and students agree on the primary importance that experiential learning holds for the value of personal gain (among other things knowledge and skill acquisition), while the values of beauty and social good were seen to be important, but of lesser significance.It is noted that while certain limitations to the research exist, nevertheless, it is suggested that incorporating value creating principles within undergraduate course learning objectives may provide opportunities for encouraging more transformative reflection and action for learners, not only in the pursuit of their own individual happiness, but also for the broader societal context.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.028
Scholarly communication0.0100.007
Open science0.0010.007
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.335
Teacher spread0.319 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2020
Admission routes2
Has abstractyes

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