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Record W4320010282 · doi:10.22373/jppm.v6i2.14795

Students’ Metacognitive Skills in Solving Probability Investigation-Based Problem

2022· article· en· W4320010282 on OpenAlexaff
Dini Nur Diantik, Eka Resti Wulan, Agus Miftakus Surur

Bibliographic record

VenueAl Khawarizmi Jurnal Pendidikan dan Pembelajaran Matematika · 2022
Typearticle
Languageen
FieldMathematics
TopicMathematics Education and Pedagogy
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsMetacognitionThink aloud protocolPsychologyMathematics educationContext (archaeology)Plan (archaeology)Test (biology)Qualitative researchData collectionCognitionApplied psychologyComputer scienceMathematics

Abstract

fetched live from OpenAlex

This study aims to describe the metacognitive abilities of students in solving opportunity problems with nuanced investigations based on the mathematical abilities of grade 12 students in one of the high schools in Kediri Regency, East Java, Indonesia. This research uses a descriptive type, with a qualitative approach. Data collection techniques in the form of giving tests with the think-aloud method and semi-structured interviews. The research instrument consisted of a problem test with investigative-based and interview guidelines. The research participants consisted of three grade 12 students each with high, medium, and low mathematical abilities. The results of this study indicate that at the stage of understanding the problem, metacognitive activity appears in the form of awareness and evaluation. However, the low participant was not able awareness in a good way and the medium participant was not doing a careful evaluation of the results. In the planning stage, the high and medium participants currently use regulation activities by thinking about the right strategy. Evaluation activities, such as believing in the effectiveness of the strategy and assessing the results appropriately. In the stage of implementing the plan, the high and medium participants are using regulation activities by monitoring the planned solutions properly. Evaluation activities are carried out with an appropriate assessment of each result. However, the opposite appeared for low participant in both previous stages. In the stage of looking back, evaluation activity appears in the form of assessing the suitability of answers to the context of the problem with investigative nuances, but no metacognitive activity was found in low participant.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.637
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.054
GPT teacher head0.351
Teacher spread0.297 · 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.

Study designTheoretical or conceptual
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

Citations0
Published2022
Admission routes1
Has abstractyes

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