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Record W3183968741 · doi:10.3390/educsci11080376

An Analysis of Education Reforms and Assessment in the Core Subjects Using an Adapted Maslow’s Hierarchy: Pre and Post COVID-19

2021· article· en· W3183968741 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEducation Sciences · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Discipline and Inequality
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMaslow's hierarchy of needsSocioeconomic statusHierarchyPsychologyPedagogyMathematics educationEquity (law)Coronavirus disease 2019 (COVID-19)Diversity (politics)SociologyMedical educationSocial psychologyPolitical scienceMedicine

Abstract

fetched live from OpenAlex

Through the lens of an adapted Maslow’s hierarchy of needs, I have analyzed (1) the impact of the three main educational reforms of the 20th and 21st centuries on culturally and linguistically diverse (CLD)and low-socioeconomic (SES)students in the core subjects up to the COVID-19 pandemic; (2) the efficacy of current classroom assessment practices, and (3) a brief reimagining of how changing equity standards in teaching and assessment post-COVID-19 could aid in CLD and low-SES students achieving a higher self-esteem level. I contend that student success, or self-esteem, can only be achieved by first satisfying the needs at the lower hierarchy levels. By analyzing CLD and SES students’ school experiences, educators and policy-makers can extrapolate the requirements for inclusive, rigorous, and responsive assessments that recognize students’ needs and utilize their cultural and linguistic diversity. As states begin the shift from remote learning back to face-to-face in the fall, more significant considerations of CLD and low-SES students must be ensured.

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.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.169
GPT teacher head0.521
Teacher spread0.352 · 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