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Zhang, Shunan; Che, ShaoPeng; Nan, Dongyan; Li, Yincen; Kim, Jang Hyun – Education and Information Technologies, 2023
Considering the importance of group member familiarity in collaborative learning in classroom learning environments, this study examined the impact of group member familiarity on CSCL (computer-supported collaborative learning) in a networked setting. Also, the differences between CSCL in the online environments and FtF (face-to-face)…
Descriptors: Group Dynamics, Familiarity, Cooperative Learning, Computer Assisted Instruction
Torres-Jimenez, Jose; Lescano, Germán; Lara-Alvarez, Carlos; Mitre-Hernandez, Hugo – Education and Information Technologies, 2023
Conflicts play an important role to improve group learning effectiveness; they can be decreased, increased, or ignored. Given the sequence of messages of a collaborative group, we are interested in recognizing conflicts (detecting whether a conflict exists or not). This is not an easy task because of different types of natural language…
Descriptors: Conflict, Identification, Computer Assisted Instruction, Cooperative Learning
Boote, Stacy K.; Galanti, Terrie M. – Mathematics Teacher: Learning and Teaching PK-12, 2023
Mathematics achievement is positively associated with coding in the classroom. By making mathematical relationships visible to students as they code, teachers leverage rich connections between block-based computer programming and mathematical sense making. In this article, the authors describe strategies for adapting a Code.org lesson integrating…
Descriptors: Teaching Methods, Mathematics Instruction, Mathematics Achievement, Coding
Bywater, James P.; Lilly, Sarah; Chiu, Jennifer L. – Journal of Mathematics Teacher Education, 2023
This study examines technology-enhanced teacher responses and students' written mathematical explanations to understand how to support effective teacher responding and the centering of students' mathematical ideas. Although prior research has focused on teacher noticing and responding to students' mathematical ideas, few studies have explored the…
Descriptors: Computer Assisted Instruction, Feedback (Response), Mathematics Instruction, Written Language
Ines A. Martin – Language Learning & Technology, 2023
This study investigated how learners' motivation to improve their pronunciation (i.e., pronunciation-focused motivation) influences their L2 pronunciation achievements. This relationship was explored separately in an online (n = 28) and a face-to-face (F2F) (n = 49) learning environment with beginner learners of German. In the online learning…
Descriptors: Pronunciation, Student Motivation, Second Language Learning, Online Courses
Smith, Lesley Erin – ProQuest LLC, 2023
The strand of feedback research within the field of Instructed Second Language Acquisition (ISLA) examines the effects of feedback on the development of second language (L2) knowledge and learning behaviors. While findings often make claims about the relationship between feedback and language processing, much of this research has not measured…
Descriptors: Feedback (Response), Second Language Learning, Language Processing, French
Faozi, Ferdinand Hanif; Handayani, Putu Wuri – Electronic Journal of e-Learning, 2023
The purpose of the research is to analyze the factors that influence the continuance intention to use Mobile-Assisted Language Learning (MALL) applications in the context of language courses in Indonesia. The study aims to understand the key factors that contribute to users' intention to continue using MALL applications, particularly in the…
Descriptors: Computer Assisted Instruction, Second Language Learning, Foreign Countries, Intention
Jacob C. Crislip; Esai Lopez; Cameron D. Armstrong; Taylor Petell; Laila Abu-Lail; Andrew R. Teixeira – Advances in Engineering Education, 2023
A chemical engineering student's knowledge of theory, experimental design, and real-world processes is tested and enforced in the Unit Operations laboratory courses. However, instructors are facing challenges of delivering high-quality, hands-on laboratory content with limited resources and increasingly large class sizes. Limited in-lab time is…
Descriptors: College Students, Chemical Engineering, Science Laboratories, Computer Simulation
Tianyu Qin – Educational Linguistics, 2023
Dynamic assessment (DA) breaks the traditional dichotomy between assessment and instruction by including mediation in assessment procedures ((Poehner "Dynamic assessment: A Vygotskian approach to understanding and promoting second language development." Springer, Berlin, Germany, 2008)). The focus of DA is on how students or test-takers…
Descriptors: Computer Assisted Instruction, Student Evaluation, Evaluation Methods, Computer Assisted Testing
Xu, Liangbei; Davenport, Mark A. – International Educational Data Mining Society, 2020
The goal of knowledge tracing is to track the state of a student's knowledge as it evolves over time. This plays a fundamental role in understanding the learning process and is a key task in the development of an intelligent tutoring system. In this paper we propose a novel approach to knowledge tracing that combines techniques from matrix…
Descriptors: Artificial Intelligence, Learning Analytics, Computer Assisted Instruction, Student Evaluation
Hyacinth Balediata Bangero – Communication Teacher, 2024
ePUZSOLVED is designed to help students understand the general communication models and experience the advantages and disadvantages of each. It will highlight how various modes of communication, when used appropriately, may lead people to solve problems, as exemplified by the online puzzle. Courses: Introduction of Communication Models, Review of…
Descriptors: Puzzles, Interactive Video, Communication Strategies, Problem Solving
Jionghao Lin; Wei Tan; Lan Du; Wray Buntine; David Lang; Dragan Gasevic; Guanliang Chen – IEEE Transactions on Learning Technologies, 2024
Automating the classification of instructional strategies from a large-scale online tutorial dialogue corpus is indispensable to the design of dialogue-based intelligent tutoring systems. Despite many existing studies employing supervised machine learning (ML) models to automate the classification process, they concluded that building a…
Descriptors: Classification, Dialogs (Language), Teaching Methods, Computer Assisted Instruction
Yen-Jung Chen; Liwei Hsu; Shao-wei Lu – Computer Assisted Language Learning, 2024
It is well known that teachers' feedback plays an important role in students' learning, as it enhances learners' cognitive development; yet there has been little research on how positive feedback given in the form of emojis works in computer-assisted language learning (CALL) courses. In this study, an experiment was designed to clarify how English…
Descriptors: Visual Aids, English (Second Language), Second Language Learning, Feedback (Response)
Wenli Chen; Hua Hu; Qianru Lyu; Lishan Zheng – Journal of Computer Assisted Learning, 2024
Background: Critical thinking is one of the 21st Century competencies for students. While previous research acknowledges the potential of peer feedback to enhance critical thinking skills, particularly within computer-supported collaborative learning (CSCL) environments, there is limited understanding of which specific aspects of critical thinking…
Descriptors: Critical Thinking, Peer Evaluation, Feedback (Response), Cooperative Learning
Mimi Li – International Journal of Computer-Assisted Language Learning and Teaching, 2024
This paper discusses the increasingly prominent role of ChatGPT in providing feedback and assessment for L2 writing in the digital age. It reviews representative studies that address five research strands about the use of ChatGPT in L2 writing contexts. After a critical evaluation of the existing literature, the author extensively explains four…
Descriptors: Second Language Learning, Feedback (Response), Evaluation, Artificial Intelligence