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Showing 1 to 15 of 16 results Save | Export
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Mengke Wang; Taotao Long; Na Li; Yawen Shi; Zengzhao Chen – Education and Information Technologies, 2025
Feedback plays an indispensable role in pre-service teachers' microteaching practice. It provides essential information about their microteaching performance, which is of great significance in their reflection and improvement. As AI and teaching analytics advance, feedback is no longer exclusively human-generated. AI technologies are increasingly…
Descriptors: Feedback (Response), Preservice Teachers, Microteaching, Reflection
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Kyne, Sara H.; Lee, Martin M. H.; Reyes, Charisse T. – Chemistry Education Research and Practice, 2023
Recent developments in digital technologies, including learning analytics are changing educational practices due to the wealth of information available and its utility to inform academic interventions for students. This study investigates the impact of personalised feedback emails on students' academic performance and student success in large…
Descriptors: Academic Achievement, Learning Analytics, Feedback (Response), Electronic Mail
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Mustafa Tepgec; Joana Heil; Dirk Ifenthaler – Assessment & Evaluation in Higher Education, 2025
Despite the widespread implementation of learning analytics (LA)-based feedback systems, there exists a gap in empirical investigations regarding their influence on learning outcomes. Moreover, existing research primarily focuses on individual differences, such as self-regulation and motivation, overlooking the potential of feedback literacy (FL).…
Descriptors: Feedback (Response), Learning Analytics, Outcomes of Education, Transfer of Training
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Dan Zhang – International Journal of Web-Based Learning and Teaching Technologies, 2025
This study explores the application of the task-based teaching method in English education, particularly from the perspective of big data. Traditional English teaching models often fail to meet the diverse needs of students, with the task-based approach, despite being student-centered, encountering challenges such as task difficulty control and…
Descriptors: Task Analysis, Teaching Methods, Learning Analytics, Learner Engagement
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Xiaofang Liao; Xuedi Zhang; Zhifeng Wang; Heng Luo – British Journal of Educational Technology, 2024
Formative assessment is essential for improving teaching and learning, and AI and visualization techniques provide great potential for its design and delivery. Using NLP, cognitive diagnostic and visualization techniques designed to analyse and present students' monthly exam data, we developed an AI-enabled visual report tool comprising six…
Descriptors: Artificial Intelligence, Design, Program Implementation, Formative Evaluation
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Gabbay, Hagit; Cohen, Anat – International Educational Data Mining Society, 2023
In MOOCs for programming, Automated Testing and Feedback (ATF) systems are frequently integrated, providing learners with immediate feedback on code assignments. The analysis of the large amounts of trace data collected by these systems may provide insights into learners' patterns of utilizing the automated feedback, which is crucial for the…
Descriptors: MOOCs, Feedback (Response), Teaching Methods, Learning Strategies
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Zheng, Lanqin; Zhong, Lu; Niu, Jiayu – Assessment & Evaluation in Higher Education, 2022
Learning analytics has been widely used in the field of education. Most studies have adopted a learning analytics dashboard to present data on learning processes or learning outcomes. However, only presenting learning analytics results was not sufficient and lacked personalised feedback. In response to these gaps, this study proposed a learning…
Descriptors: Electronic Learning, Cooperative Learning, Undergraduate Students, Feedback (Response)
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Jia, Qinjin; Young, Mitchell; Xiao, Yunkai; Cui, Jialin; Liu, Chengyuan; Rashid, Parvez; Gehringer, Edward – International Educational Data Mining Society, 2022
Providing timely feedback is crucial in promoting academic achievement and student success. However, for multifarious reasons (e.g., limited teaching resources), feedback often arrives too late for learners to act on the feedback and improve learning. Thus, automated feedback systems have emerged to tackle educational tasks in various domains,…
Descriptors: Student Projects, Feedback (Response), Natural Language Processing, Guidelines
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Wang, Dongqing; Han, Hou – Journal of Computer Assisted Learning, 2021
With the development of a technology-supported environment, it is plausible to provide rich process-oriented feedback in a timely manner. In this paper, we developed a learning analytics dashboard (LAD) based on process-oriented feedback in iTutor to offer learners their final scores, sub-scale reports, and corresponding suggestions on further…
Descriptors: Learning Analytics, Educational Technology, Feedback (Response), Intelligent Tutoring Systems
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Lim, Lisa-Angelique; Dawson, Shane; Gaševic, Dragan; Joksimovic, Srecko; Pardo, Abelardo; Fudge, Anthea; Gentili, Sheridan – Assessment & Evaluation in Higher Education, 2021
Research and development in learning analytics has established viable solutions for scaling personalised feedback to all students. However, questions remain regarding how such feedback is perceived, interpreted and acted upon by stakeholders. The present study reports on the analysis of focus group data from four courses to understand students'…
Descriptors: Student Attitudes, College Students, Emotional Response, Individualized Instruction
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Calvo-Ferrer, José Ramón – International Journal of Game-Based Learning, 2021
The frequency of word exposure in teaching materials, along with corrective feedback, has often been identified as a powerful variable in the learning of vocabulary in a foreign language. The effect of the number of times an action is presented as accurate in digital game-based language learning scenarios (i.e., knowledge of correct response [KCR]…
Descriptors: Feedback (Response), Error Correction, Computer Games, Video Games
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Yamashita, Taichi – Language Learning & Technology, 2021
This study investigated the effects of corrective feedback (CF) during in-class computer-mediated collaborative writing on grammatical accuracy in a new piece of individual writing. Forty-eight ESL students at an American university worked on two computer-mediated animation description tasks in pairs. The experimental group received indirect CF on…
Descriptors: Error Correction, Feedback (Response), Computer Mediated Communication, Synchronous Communication
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Knoop-van Campen, Carolien; Molenaar, Inge – Frontline Learning Research, 2020
In technology empowered classrooms teachers receive real-time data about students' performance and progress on teacher dashboards. Dashboards have the potential to enhance teachers' feedback practices and complement human-prompted feedback that is initiated by teachers themselves or students asking questions. However, such enhancement requires…
Descriptors: Feedback (Response), Technology Integration, Teacher Student Relationship, Behavior Patterns
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Admiraal, Wilfried; Vermeulen, Jordi; Bulterman-Bos, Jacquelien – Technology, Pedagogy and Education, 2020
Computer-based assessments can provide students with feedback to guide their learning as well as inform teachers who extract information to prepare their teaching. Five secondary school teachers were monitored during one school year to answer the following research questions: (1) What kind of student data do teachers use for their teaching…
Descriptors: Learning Analytics, Computer Assisted Testing, Data Use, Formative Evaluation
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Liu, Sannyuya; Peng, Xian; Cheng, Hercy N. H.; Liu, Zhi; Sun, Jianwen; Yang, Chongyang – Journal of Educational Computing Research, 2019
Course reviews, which is designed as an interactive feedback channel in Massive Open Online Courses, has promoted the generation of large-scale text comments. These data, which contain not only learners' concerns, opinions and feelings toward courses, instructors, and platforms but also learners' interactions (e.g., post, reply), are generally…
Descriptors: Course Evaluation, Online Courses, Student Attitudes, Course Content
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