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4 results for “Mathematical reasoning”
Database of the assessment of two instructional design variables in verbal reasoning and mathematical reasoning courses from the perspective of a Peruvian pre-university center students
<p>These are the data obtained from 4 evaluations made to a sample of 630 students of a Peruvian pre-university center. First, two study variables were evaluated: teaching sequence compliance and the student's educational need according to the perspective of 315 students of the verbal reasoning course. Second, the same study variables were assessed in the remaining 315 students of the mathematical reasoning course. This information is being used in research to obtain an academic degree and later to make a publication of a scientific article.</p> <p>For the treatment of these data, inferential statistics was used through the software R version 3.4.4 (2018) The R Foundation for Statistical Computing.</p>
MathChat: Benchmarking Mathematical Reasoning and Instruction Following in Multi-Turn Interactions
<div> <h3>1. follow_up.jsonl</h3> <a href="https://github.com/Zhenwen-NLP/MathChat#1-follow_upjsonl"></a></div> <p>This file contains entries that facilitate follow-up questioning. Each line consists of three keys:</p> <ul> <li><strong>question</strong>: Sourced from the GSM8k testing set.</li> <li><strong>answer</strong>: Corresponding answer from the GSM8k testing set.</li> <li><strong>followup</strong>: Includes two rounds of follow-up questions and reference answers, formatted as a conversation between a user (A:) and an assistant (B:).</li> </ul> <div> <h3>2. error_correction.jsonl</h3> <a href="https://github.com/Zhenwen-NLP/MathChat#2-error_correctionjsonl"></a></div> <p>This file is designed for error correction tasks. Each line consists of three keys:</p> <ul> <li><strong>question</strong>: Sourced from the GSM8k testing set.</li> <li><strong>answer</strong>: Corresponding answer from the GSM8k testing set.</li> <li><strong>error_correction</strong>: Contains a conversation between a user (A:) and an assistant (B:), which includes the original question, an incorrect answer, and the process of correcting the error.</li> </ul> <div> <h3>3. error_analysis.jsonl</h3> <a href="https://github.com/Zhenwen-NLP/MathChat#3-error_analysisjsonl"></a></div> <p>This file also focuses on error correction but employs a different prompt strategy. Each line consists of three keys:</p> <ul> <li><strong>question</strong>: Sourced from the GSM8k testing set.</li> <li><strong>answer</strong>: Corresponding answer from the GSM8k testing set.</li> <li><strong>error_analysis</strong>: Includes a conversation between a user (A:) and an assistant (B:), where the model is prompted to independently determine the correctness of the answer without being explicitly told.</li> </ul> <div> <h3>4. p2p_generation.jsonl</h3> <a href="https://github.com/Zhenwen-NLP/MathChat#4-p2p_generationjsonl"></a></div> <p>This file contains entries for problem generation tasks. Each line consists of three keys:</p> <ul> <li><strong>question</strong>: Sourced from the GSM8k testing set.</li> <li><strong>answer</strong>: Corresponding answer from the GSM8k testing set.</li> <li><strong>new_problem</strong>: A new problem generated by GPT-4 to serve as a reference answer.</li> </ul>
MathChat: Benchmarking Mathematical Reasoning and Instruction Following in Multi-Turn Interactions
<p>This is the math_sync dataset that used in the MathChat paper.</p>
D-PAC data on Mathematical Reasoning.
<p>This dataset contains the data gathered for the master thesis of Kristof Vermeiren at the University Antwerp. The thesis evaluated the use of Comparative Judgement as assessment method in order to evaluate mathematical reasoning of students in secondary education. Two assignments of students were evaluated by comparing their solution strategies. Assessors were asked to motivate why they choose one solution as more preferred than the other.</p>
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