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Mughaz, Dror; Cohen, Michael; Mejahez, Sagit; Ades, Tal; Bouhnik, Dan – Interdisciplinary Journal of e-Skills and Lifelong Learning, 2020
Aim/Purpose: Using Artificial Intelligence with Deep Learning (DL) techniques, which mimic the action of the brain, to improve a student's grammar learning process. Finding the subject of a sentence using DL, and learning, by way of this computer field, to analyze human learning processes and mistakes. In addition, showing Artificial Intelligence…
Descriptors: Artificial Intelligence, Teaching Methods, Brain Hemisphere Functions, Grammar
Cheng, Lu Pien – International Journal for Mathematics Teaching and Learning, 2015
In this study, ways in which 9-year old students from one Singapore school solved 1-step and 2-step word problems based on the three semantic structures were examined. The students' work and diagrams provided insights into the range of errors in word problem solving for 1- step and 2-step word problems. In particular, the errors provided some…
Descriptors: Foreign Countries, Elementary School Students, Elementary School Mathematics, Word Problems (Mathematics)
Hawes, Kathy – Mathematics Teaching in the Middle School, 2007
This article describes activities that promote students' understanding of equation solving through analyzing and correcting student work. (Contains 5 figures.)
Descriptors: Error Analysis (Language), Equations (Mathematics), Problem Solving, Middle School Students
Peer reviewedSinyor, Roberta – CALICO Journal, 1997
Describes several sources of errors made by students of Italian and some of the problem-solving behaviors in drill-and-practice exercises on direct and indirect object pronouns and the present perfect tense. The article identifies an unexpected source of error and a problem-solving behavior not found in the traditional learning environment and…
Descriptors: College Instruction, Computer Assisted Instruction, Error Analysis (Language), Error Patterns

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