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Record W2912016909 · doi:10.5539/ies.v12n2p57

Building Learning Path of Mathematical Creative Thinking of Junior Students on Geometry Topics by Implementing Metacognitive Approach

2019· article· en· W2912016909 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

VenueInternational Education Studies · 2019
Typearticle
Languageen
FieldMathematics
TopicMathematics Education and Pedagogy
Canadian institutionsnot available
FundersDirecció General de Recerca, Generalitat de CatalunyaDirektorat Riset dan Pengabdian Masyarakat
KeywordsMetacognitionMathematics educationConstruct (python library)Process (computing)PsychologyCognitionComputer science

Abstract

fetched live from OpenAlex

Mathematical creative ability is one of the most important skills students must have to process the information provided in resolving the problem. Before using mathematical creative skills, prior knowledge becomes the most crucial thing that allows students to connect all existing information so that they can construct new knowledge through assimilation or accommodation processes. The process of forming mathematical concepts with metacognitive questions that might be carried out by students causes a metacognitive process in students that will affect their mathematical behavior. The purpose of this study is to (1) analyze prior knowledge of what students miss or forget so that they have difficulty to answer the given geometry problem, (2) how the learning path of creative thinking of students with the application of metacognitive approach. This type of research is Design Research to improve the quality of learning. This type of research is research design, data collection techniques .The researcher gave 2 geometry questions to 38 8th graders selected randomly in SMP Medan city. Questions given are tailored to Cognitive level 4 (C4) for questions 1 and C5 for question 2 based on Bloom's taxonomy. Data analysis techniques are descriptive qualitative.This study shows that prior knowledge becomes important to build students' mathematical creative ability to gain new knowledge, especially in the field of geometry. The most problematic topics that make it difficult for them to understand geometry are the area of the rectangle and the cube webs. In dividing the rectangle into two equal parts, students still have not created another form of flat build or have not been able to get out of the rectangular pattern or exactly the same as the available problem. There are five phases of learning trajectory of hierarchically creative mathematical thinking, which is orientation to problem, problem solving plan, plan realization, previous knowledge mastery / concept of mathematical creativity and evaluation of result obtained. Students do metacognition on the learning path of creative thinking in a comprehensive way from evaluation to planning, action to the formation of prior knowledge and selection of creative ideas. From these explanations, it is important that teachers need to ensure students have enough prior knowledge to make it easier to construct new knowledge, as well as to make learning fun and meaningful so that students will remember knowledge in long-term memory.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score0.664

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.105
GPT teacher head0.481
Teacher spread0.376 · 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