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Record W4387743751 · doi:10.4324/9781003347972-9

Decolonizing Assessment Practices in Teacher Education

2023· book-chapter· en· W4387743751 on OpenAlexaboutno aff
Joshua Hill, Christy Thomas, Allison Robb-Hagg

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsnot available
Fundersnot available
KeywordsPedagogyMathematics educationPsychologySociology

Abstract

fetched live from OpenAlex

Ongoing discoveries of mass graves at the former sites of Indian Residential Schools are tragic reminders that the work of advancing truth and reconciliation in Canada must continue. Although the imperative is clear for teacher educators to include Indigenous perspectives in classrooms, many complexities exist that stem from the legacy of colonization. Postsecondary structures and pedagogies are dominated by Western epistemology, and steps must be taken to avoid incorporating Indigenous ways of knowing and coming to know into assimilative frameworks. This chapter presents a collaborative action research design used to work towards decolonizing assessment practices in a fully online teacher-education course. The design drew upon decolonizing principles of storytelling and negotiation to inform shifts in the learning tasks, the formative assessment, and the determination of grades. The challenges encountered and the pedagogical decisions made are discussed with the aim of inviting readers into an ongoing journey of seeking to decolonize assessment practices. The authors are Indigenous and non-Indigenous instructors in a Bachelor of Education after-degree program located in the traditional territories of the Blackfoot Confederacy, the Tsuut’ina Nation, and the Stoney Nakoda Nations.

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)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.912
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.116
GPT teacher head0.462
Teacher spread0.346 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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