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Gregorcic, Bor; Pendrill, Ann-Marie – Physics Education, 2023
We present a case study of a conversation between ourselves and an artificial intelligence-based chatbot ChatGPT. We asked the chatbot to respond to a basic physics question that will be familiar to most physics teachers: 'A teddy bear is thrown into the air. What is its acceleration in the highest point?' The chatbot's responses, while…
Descriptors: Artificial Intelligence, Physics, Science Instruction, Scientific Concepts
Costello, Eamon; Johnston, Keith; Wade, Vincent – Interactive Learning Environments, 2023
This research investigated how the bug tracker database of the Virtual Learning Environment (VLE) Moodle is developed as an application of crowd work. The bug tracker is used by software developers, who write and maintain Moodle's code, but also by a wider public world of ordinary Moodle users who can report bugs. Despite many studies of the…
Descriptors: Electronic Learning, Educational Technology, Computer Software, Cooperation
Mai Abdullah Alqaed – Advanced Education, 2024
Artificial intelligence (AI) is gaining wide attention in second language learning as a beneficial tool. The current research investigates EFL learners' perceptions and usage of AI applications among 68 undergraduate English language major students. The aim is to enhance students' awareness of valuable AI applications and involve them with AI…
Descriptors: Artificial Intelligence, Student Attitudes, English (Second Language), Second Language Instruction
Vicente Sanjosé; Carlos B. Gómez-Ferragud; Joan Josep Solaz-Portolés – European Journal of Psychology of Education, 2024
This study explores the process itself of comprehension monitoring of worked-out examples in mathematics. A 'reversal error' was embedded in a worked-out example of algebraic nature. Ninety-four engineers in a master's degree program to become secondary teachers of technology were asked to judge the comprehensibility of the statement and the…
Descriptors: Comprehension, Masters Programs, Engineering Education, Teacher Education
Nato Pachuashvili – IAFOR Journal of Education, 2024
Giving feedback has always been the backbone of the English as a Foreign Language (EFL) writing class. Written corrective feedback focuses on responding to students' written work by extensively correcting their errors or offering constructive suggestions for improvements. The process of digitalization of education offered an alternative to…
Descriptors: Feedback (Response), English (Second Language), Second Language Instruction, Writing Instruction
Pernille Fiskerstrand; Siv M. Gamlem – Assessment in Education: Principles, Policy & Practice, 2024
The quality of feedback interactions, when young pupils write, influences their learning processes. Still, teachers tend to use feedback that provides little information to enhance pupils' understanding and learning regarding their literacy skills. More knowledge about feedback interactions for young pupils as they write is needed. Thus, we wanted…
Descriptors: Feedback (Response), Oral Language, Writing Instruction, Literacy
Gao, Jianwu; Ma, Shuang – Language Teaching Research, 2022
This study investigated the intensity and efficacy of automated corrective feedback (CF) in a tutorial CALL (computer-assisted language learning) environment during form-focused drills as compared with those of instructor CF on free writing in the classroom. The English simple past tense, a previously learned target structure, was selected as the…
Descriptors: Feedback (Response), Writing (Composition), Computer Assisted Instruction, Second Language Learning
Cline, Kelly; Zullo, Holly; Huckaby, David A. – Teaching Mathematics and Its Applications, 2020
Common student errors and misconceptions can be addressed through the method of classroom voting, in which the instructor presents a multiple-choice question to the class, and after a few minutes for consideration and small-group discussion, each student votes on the correct answer, using a clicker or a phone. If a large number of students have…
Descriptors: Error Patterns, Misconceptions, Mathematics Instruction, Calculus
Rustam Shadiev; Yingying Feng – Interactive Learning Environments, 2024
Previous review studies do not have a broad and comprehensive perspective on the usage of ACF tools in language learning. To address this gap, we reviewed 82 articles on the use of ACF tools published in the last five years. Results indicate that 43 ACF tools were used in studies to assist writing, grammar, spelling, and collocation and word use.…
Descriptors: Automation, Feedback (Response), Educational Technology, Technology Uses in Education
Schroeder, Noah L.; Chiou, Erin K.; Siegle, Robert F.; Craig, Scotty D. – Journal of Educational Computing Research, 2023
Virtual humans are on-screen characters that are often embedded in learning technologies to deliver educational content. Little research has investigated how virtual humans can be used to correct common misconceptions. In this study, we explored how different types of narrative structures, refutation text and expository text, influence perceptions…
Descriptors: Robotics, Computer Simulation, Educational Technology, Error Correction
Jining Han – Language Learning & Technology, 2024
The present study applied a multiple-case study design to investigate Chinese as a foreign language (CFL) students' responses to computer-mediated coded feedback and the factors that influence students' responses in an online multiple-draft Chinese writing context. Three intermediate-level students of Chinese completed four drafts for which they…
Descriptors: Computer Mediated Communication, Feedback (Response), Student Attitudes, Influences
Hsiu-Chen Hsu – Computer Assisted Language Learning, 2024
Previous studies on web-based collaborative writing have shown that task modality impacts peer interaction patterns and attention to form. However, these studies have primarily focused on contrasting a face-to-face oral condition with a text-based synchronous computer-mediated communication (SCMC) environment. Few studies have compared peer…
Descriptors: Peer Relationship, Attention, Electronic Learning, Asynchronous Communication
Chao-Jung Ko – Computer Assisted Language Learning, 2024
This study aimed to examine the impact of an online writing system (OWS) providing individualized corrective feedback (CF) on learners' self-correction of grammatical errors (GE). It consisted of two phases: the pilot and the formal phases. Four EFL (English as a Foreign Language) Taiwanese university students participated in the study at the…
Descriptors: Feedback (Response), English (Second Language), Second Language Learning, Grammar
Rustam Shadiev; Yingying Feng; Roza Zhussupova; Yueh-Min Huang – Journal of Computer Assisted Learning, 2024
Background: Tele-collaborative projects serve as invaluable platforms for students from diverse countries to engage in cross-cultural communication and exchange cultural knowledge. These projects offer immense benefits in terms of fostering intercultural competence among participants. However, one challenge arises when participants engage in…
Descriptors: Telecommunications, Feedback (Response), Assistive Technology, Verbal Communication
Klimova, Blanka; Pikhart, Marcel – Cogent Education, 2022
The majority of foreign language learning (FLL) has recently been conducted online due to unprecedented changes in society and this trend seems to be global and perpetual even if the situation changes. Unfortunately, there is still low awareness among language instructors of the impact it may have on the corrective feedback they provide to their…
Descriptors: Error Correction, Teaching Methods, Second Language Learning, Second Language Instruction