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A Case for Accelerated Education - Student Empowerment and Agency

2021· article· en· W3194768068 on OpenAlexaff
Sakina Rizvi

Bibliographic record

VenueInternational Journal for Cross-Disciplinary Subjects in Education · 2021
Typearticle
Languageen
FieldPsychology
TopicGrit, Self-Efficacy, and Motivation
Canadian institutionsMcGill University
Fundersnot available
KeywordsEmpowermentAgency (philosophy)PedagogyPolitical scienceMathematics educationSociologyPsychologySocial science

Abstract

fetched live from OpenAlex

Researchers have published various empirical studies on the veracity of accelerated learning models. Most studies attest to the effectiveness of accelerated learning and highlight the importance of providing students with a nurturing environment to explore and pursue accelerated learning options. However, there is still significant resistance to accelerated learning due to social norms and conceptions about normality, success, and achievement. In the 1970s and 1980s, acceleration was a relatively new phenomenon. Recent scholarship in the field has addressed many of the concerns raised by educational policy makers and teachers about the socio-behavioural impact of accelerated learning. Although the evidence is overwhelmingly positive for acceleration, students who try to learn at a faster pace continue to encounter significant systemic and institutional barriers. To create an inclusive learning environment for all students, educators need to be willing to open the space for alternative pathways for achievement. It is possible to create a brighter future for students by engaging in holistic pedagogy that allows learners to adopt an agentic role in selecting their learning pace.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.784
Threshold uncertainty score0.858

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.059
GPT teacher head0.474
Teacher spread0.415 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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 routes1
Has abstractyes

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