“ELIP-MARC” Activities via TPS of Cooperative Learning to Improve Student’s Mathematical Reasoning
Bibliographic record
Abstract
The purpose of this study is to describe and generate interaction model of learning through Elip – Marc activity via TPS cooperative learning in order to improve student’s mathematical reasoning who have valid, practical and effective criteria. “Elip - Marc” is an acronym of eliciting, inserting, pressing, maintening, reflecting and confirming, an activity in the learning process have aim to improve student’s mathematical reasoning. So there are three types product are developed, namely: (1) The interaction learning model, as a conceptual framework and a reference in developing the supporting device. (2) The learning device, for carrying out teaching methods and to measure the practicality and effectiveness of the interaction model and (3) The research instrument to assess the quality of the model and the device. All products are Elip-Marc activity oriented and supported by worksheet with RAT (Reasonable Answer Test) format. All products are declared valid as constructs and content by expert validator. Practicality and effectiveness criteria of the product conducted in even cemester at 2014-2015 by implementation interaction model on eight grade students of ‘SMP Negeri 3 Kepanjen” Malang East Java, Indonesia on the material “Problem solving about three dimension spaces”. By Analysis of the teacher’s Elip-Marc activity and the response of student’s in the learning process obtained conclusions that interaction model is practical and effective, so can improve student’s mathematical reasoning as the intervention results in desired outcomes. So, If (1) the teacher is pleased to be patient and persistent engage students in the learning process through Elip-Marc activities, (2) and supported by the task of “word problems” challenging (3) and motivated by the question that digging (Prompting Questions) and guided (Probing Question), (4) and provide students the necessary scaffolding, (5) and provide space whorksheet adequate workplace, (5) and following the RAT steps, students were motivated to improve mathematical reasoning. However, the authors suggest that the results of this study can be adapted to the other materials in mathematics learning, and hope a lot of teacher willing to implement this model interaction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".