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Record W2332949842 · doi:10.5430/ijhe.v5n2p196

How to Improve Students' Comprehension concerning the Major Terms of Functional Groups?--In the Experiment of OrCheTaboo Game

2016· article· en· W2332949842 on OpenAlexvenueno aff
Nalan Akkuzu, Melis Arzu Uyulgan

Bibliographic record

VenueInternational Journal of Higher Education · 2016
Typearticle
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationTabooComprehensionScope (computer science)Relation (database)PsychologyChemistryComputer scienceSociology

Abstract

fetched live from OpenAlex

In this research, for an effective learning of concepts in the scope of functional groups in organic chemistry, it has been developed as “Organic Chemistry Taboo (OrCheTaboo)” which is an educational activity by the researchers. The aim of this study is to analyze the effect of the game OrCheTaboo on learning of concepts related to functional groups. The study group of the research consists of 62 students who took the Organic Chemistry Laboratory Course in the spring term and they enrolled in the Department of Secondary Science and Mathematics Education of a Faculty of Education at a state university in Turkey. Quasi-experimental design with pretest-posttest control group has been used. As a result, the game OrCheTaboo gives the opportunity to be in conceptual development processes like describing the terms to the students, identifying from the other terms or establishing its similar characteristics with the other terms, put their relation forward. Because of these characteristics, while turning the complicated and difficult terms, the game has a positive and active role.

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 score0.778
Threshold uncertainty score0.530

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 communication0.0000.000
Open science0.0010.000
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 head0.035
GPT teacher head0.372
Teacher spread0.337 · 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

Citations12
Published2016
Admission routes1
Has abstractyes

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