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Download full textSouthwell, Rosy; Pugh, Samuel; Perkoff, E. Margaret; Clevenger, Charis; Bush, Jeffrey B.; Lieber, Rachel; Ward, Wayne; Foltz, Peter; D'Mello, Sidney – International Educational Data Mining Society, 2022
Automatic speech recognition (ASR) has considerable potential to model aspects of classroom discourse with the goals of automated assessment, feedback, and instructional support. However, modeling student talk is besieged by numerous challenges including a lack of data for child speech, low signal to noise ratio, speech disfluencies, and…
Descriptors: Audio Equipment, Error Analysis (Language), Classroom Communication, Feedback (Response)
Yuki Takahashi; Narathip Thumawongsa – rEFLections, 2024
In recent years, the shift in the teaching approaches employed in Thai English as a Foreign Language (EFL) classroom provides new opportunities and challenges to the teachers and students form Generation Z (1995-2009) and Generation Alpha (2010-2024). This study examines verb errors among Thai EFL learners from Generation Z and Generation Alpha to…
Descriptors: Age Groups, English (Second Language), Second Language Instruction, Second Language Learning
Direct linkMughaz, 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
