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Record W2565879373 · doi:10.5539/ies.v10n1p12

Using a Review Book to Improve Knowledge Retention

2016· review· en· W2565879373 on OpenAlexvenueno aff
Rıdvan Elmas, Bülent Aydoğdu, Yakup Saban

Bibliographic record

VenueInternational Education Studies · 2016
Typereview
Languageen
FieldSocial Sciences
TopicEducational Assessment and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationFocus groupPsychologyContent analysisQualitative researchData collectionQualitative propertyPedagogyComputer scienceSociology

Abstract

fetched live from OpenAlex

This study has two primary objectives. The first one is preparation of an efficient review book including a series of activities, which will help fourth grade students exercise what they learned in the elementary science course in a year. The second objective is examination of the prepared book in the framework of student and teacher opinions. In this study, 10 classroom teachers are interviewed at the initial stage. As a result of these interviews, a significant need is determined for a review book for elementary science course, particularly. In the study, qualitative research methods, such as observation, interviews, document analysis and focus group discussion, are used. Data collection tools compose of review book for elementary science course, teacher interview forms, student focus group discussion form and forms, in which students evaluate all activities in the book. The review book prepared by the researchers consists of 38 activities. This book was applied to 25 fifth grade students. These interviews are supported with data of observation and document analysis. The obtained data are analyzed with the content analysis. The review book is considered efficient by teacher and students. This is because it can be applied within a short time and contains whole elementary science topics of fourth grade. Furthermore, teacher can specify students' prior knowledge at the beginning of the academic year and adjust the level and teaching methods in the course accordingly. It can also be used effectively throughout the term.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.819
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.453
GPT teacher head0.642
Teacher spread0.189 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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
Published2016
Admission routes1
Has abstractyes

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