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Record W4297052480 · doi:10.1080/17408989.2022.2123464

Developing a socially-just teaching personal and social responsibility (TPSR) approach: a pedagogy for social justice for physical education (teacher education)

2022· article· en· W4297052480 on OpenAlexaff
Dylan Scanlon, Kellie Baker, Deborah Tannehill

Bibliographic record

VenuePhysical Education and Sport Pedagogy · 2022
Typearticle
Languageen
FieldHealth Professions
TopicPhysical Education and Pedagogy
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPhysical educationPedagogyCurriculumTeacher educationSociologyEquity (law)Social responsibilityCritical pedagogySocial pedagogyPsychologySocial changePolitical sciencePublic relations

Abstract

fetched live from OpenAlex

Background Social justice as a concept and a pedagogy has (and is) gaining traction in physical education teacher education [Walton-Fisette, J. L., and S. Sutherland. 2018. “Moving Forward with Social Justice Education in Physical Education Teacher Education”. Physical Education and Sport Pedagogy 23 (5): 461–468] and school physical education [Philpot, R., G. Gerdin, W. Smith, S. Linnér, K. Schenker, K. Westlie, K. M. Moen, and L. Larsson. 2021. “Taking Action for Social Justice in HPE Classrooms Through Explicit Critical Pedagogies.” Physical Education and Sport Pedagogy 26 (6): 662–674]. Despite this growing body of research, there seems to be a lack of understanding around the ‘how’ question; ‘how’ can we teach about, through, and for social justice (pedagogies) in PETE (in preparing pre-service teachers) and in school physical education? Reflecting on a number of papers as part of a Special Issue in Physical Education and Sport Pedagogy, [Flory, S. B., and D. Landi. 2020. “Equity and Diversity in Health, Physical Activity, and Education: Connecting the Past, Mapping the Present, and Exploring the Future.” Physical Education and Sport Pedagogy 25 (3): 213–224, 221] suggest the need to re-think and re-imagine physical education curriculum, practice and policy by making new connections and relationships between models-based practices and sociocultural theories.Purpose Guided by asking ‘What is worth doing?’ and ‘Is it working?’ [Hellison, D. 2011. Teaching Personal and Social Responsibility Through Physical Activity. 3rd ed. Champaign, IL: Human Kinetics], we explore, re-conceptualise, and re-imagine the Teaching Personal and Social Responsibility (TPSR) model as an approach to teach about, through, and for social justice (pedagogies).Discussion A Figure, consisting of three strands, was constructed to visualise the socially-just TPSR approach. As part of this, we have reconceptualised the TPSR levels to ‘spaces’. As spaces, students can start in different (and multiple) spaces and move between spaces throughout the lesson. The first two strands of the Figure (social justice topic and the TPSR spaces) inform the pedagogical approaches (strand three) and the pedagogical approaches are underpinned by the teaching about (social justice topic – strand one) and through (TPSR spaces – strand two) social justice. The alignment of the three strands can therefore lead to meaningful, informed, and socially-just learning experiences.Conclusion The need for social justice education is clear. And yet, teachers and teacher educators remain uncertain about how to implement social justice content and pedagogies into physical education contexts such as the field and gymnasium. Honouring Hellison’s forty years of (re)developing the theory of TPSR based on what is learned in practice, we suggest this socially-just TPSR approach may open possibilities and potentialities in which educators (i.e. teacher educators, in-service teachers, and pre-service teachers) can learn to teach about, through and for social justice (pedagogies). We have used the litmus test of ‘What is worth doing?’ to guide us. We truly believe providing educators with a socially-just TPSR approach which may enhance the teaching about, through, and for social justice (pedagogies) is worth doing.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.498
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0060.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.150
GPT teacher head0.531
Teacher spread0.381 · 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 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

Citations21
Published2022
Admission routes1
Has abstractyes

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