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Record W4220932421 · doi:10.22158/selt.v10n2p27

Formative Assessment is a Scaffold for ELs to Reach ZPD’s Second Layer: A Literature Review Study

2022· review· en· W4220932421 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueStudies in English Language Teaching · 2022
Typereview
Languageen
FieldSocial Sciences
TopicStudent Assessment and Feedback
Canadian institutionsUniversity of Manitoba
FundersUniversity of Manitoba
KeywordsFormative assessmentZone of proximal developmentMathematics educationFunction (biology)Process (computing)ScaffoldComputer sciencesortPsychologyAssessment for learningPedagogy

Abstract

fetched live from OpenAlex

Learning and teaching can’t function well without assessing students’ performance. More so, formative assessment is the most essential sort of evaluation in academic contexts. Teachers and students alike benefit from the dynamic nature of this evaluation as it brings students and English teachers closer together, instructors are better able to encourage and assist student learning. Both teachers and students benefit from this assessment process, which helps them better understand each other’s strengths and flaws. Instructors can provide input to students based on their needs, similar to how a building is built. As a result, formative assessment appears to be a scaffold for ELs, assisting them when they encounter difficulties and preparing them to move to an optimum level of efficiency. The purpose of this critical review is to (i) explain formative assessment from major theoretical perspectives. (ii) Conceptualize formative assessment and Scaffolding. (iii) Reiterate my belief that formative assessment propels learners to the second layer of ZPD.

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)0.009
metaresearch head score (Gemma)0.003
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: Review · Consensus signal: Review
Teacher disagreement score0.599
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
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 head0.095
GPT teacher head0.496
Teacher spread0.401 · 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