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Record W4367300689 · doi:10.5539/jel.v12n3p86

Development of Science Learning Activities Using Inquiry-Based Learning Management to Improve the Academic Achievement of Secondary School Students

2023· article· en· W4367300689 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Education and Learning · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSTEM Education
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationScience learningPsychologyAcademic achievementLearning ManagementAchievement testInquiry-based learningTest (biology)Active learning (machine learning)Science educationComputer scienceStandardized test

Abstract

fetched live from OpenAlex

The objectives of this research were as follows: (1) to develop learning activities in science and technology subjects using inquiry-based learning for seventh-grade students (12-13 years old); (2) to develop academic achievement for the topic of elements and compounds using inquiry-based learning management activities to meet the 70% requirement; and (3) to assess the satisfaction of seventh-grade students who are taught with inquiry-based learning management. The target group of this study was 24 seventh-grade students on the science and technology course. The research tools included seven inquiry-based learning management plans, an achievement test, and a satisfaction assessment. The results show that synthesizing the approach to learning management using inquiry-based learning led to the formulation of learning activities. Students had better academic achievement, with a mean score of 81.45%, which was above the 70% requirement. Students were satisfied with inquiry-based learning activities, with an average of 4.75 and a standard deviation of 0.48, which is the highest level.

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)0.007
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.226
Threshold uncertainty score0.942

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.052
GPT teacher head0.420
Teacher spread0.368 · 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