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Anderson Pinheiro Cavalcanti; Rafael Ferreira Mello; Dragan Gaševic; Fred Freitas – International Journal of Artificial Intelligence in Education, 2024
Educational feedback is a crucial factor in the student's learning journey, as through it, students are able to identify their areas of deficiencies and improve self-regulation. However, the literature shows that this is an area of great dissatisfaction, especially in higher education. Providing effective feedback becomes an increasingly…
Descriptors: Prediction, Feedback (Response), Artificial Intelligence, Automation
Arinjoy Basak; Nicole P. Pitterson; Clifford A. Shaffer; Sneha Patel Davison; David A. Dillard; Jacob Grohs – Advances in Engineering Education, 2025
Motivated by the benefits of repeated deliberate practice, we created an interactive exercise system for use in an undergraduate engineering mechanics class that focuses on practicing learned fundamental concepts. These exercises take the form of traditional word problems commonly found in mechanics courses, involving things like selecting and…
Descriptors: Usability, Electronic Learning, Computer Mediated Communication, Engineering Education
Sha, Lele; Rakovic, Mladen; Lin, Jionghao; Guan, Quanlong; Whitelock-Wainwright, Alexander; Gasevic, Dragan; Chen, Guanliang – IEEE Transactions on Learning Technologies, 2023
In online courses, discussion forums play a key role in enhancing student interaction with peers and instructors. Due to large enrolment sizes, instructors often struggle to respond to students in a timely manner. To address this problem, both traditional machine learning (ML) (e.g., Random Forest) and deep learning (DL) approaches have been…
Descriptors: Computer Mediated Communication, Discussion Groups, Artificial Intelligence, Intelligent Tutoring Systems
Mohammed Muneerali Thottoli; Badria Hamed Alruqaishi; Arockiasamy Soosaimanickam – Contemporary Educational Technology, 2024
Purpose: Chatbots and artificial intelligence (AI) have the potential to alleviate some of the challenges faced by humans. Faculties frequently swamped with teaching and research may find it difficult to act in a parental role for students by offering them individualized advice. Hence, the primary purpose of this study is to review the literature…
Descriptors: Academic Advising, Artificial Intelligence, Technology Uses in Education, Role
Niki Chatzipanagiotou; Anita Mirijamdotter; Christina Mörtberg – Learning Organization, 2025
Purpose: This paper aims to focus on academic library managers' learning practices in the context of cooperative work supported by computational artefacts. Academic library managers' everyday work is mainly cooperative. Their cooperation is supported predominantly by computational artefacts. Learning how to use the computational artefacts…
Descriptors: Foreign Countries, Research Libraries, Librarians, Cooperative Planning
Hu, Yuanyuan; Donald, Claire; Giacaman, Nasser – International Journal of Educational Technology in Higher Education, 2022
Automatic analysis of the myriad discussion messages in large online courses can support effective educator-learner interaction at scale. Robust classifiers are an essential foundation for the use of automatic analysis of cognitive presence in practice. This study reports on the application of a revised machine learning approach, which was…
Descriptors: MOOCs, Philosophy, Artificial Intelligence, Computer Mediated Communication
Sativa Thompson; Hayley Didriksen; Elise Swanson; Jennifer Ash – Society for Research on Educational Effectiveness, 2024
Background: Addressing chronic absenteeism is a policy priority, with 36 states and Washington D.C. referencing attendance in ESSA accountability plans (Jordan & Miller, 2017) and a body of research establishing the connections between attendance, achievement, and social development (e.g., Gottfried, 2014; Ginsburg, 2014). The need to find…
Descriptors: Rural Schools, Attendance Patterns, Automation, Costs
Shuxin Tan; Young Woo Cho; Wensi Xu – Interactive Learning Environments, 2023
With the rapid advance in educational technology, electronic feedback (e-feedback) has found its way to EFL writing process. The aim of this study is to investigate the effects of three e-feedback modes, that is, automated written corrective feedback (AWCF), asynchronous computer-mediated communication (ACMC), and their combination on EFL…
Descriptors: Foreign Countries, English (Second Language), Second Language Learning, Feedback (Response)
Monique H. Harrison; Philip A. Hernandez – Grantee Submission, 2022
The interview experience is only one component of the process of interviewing -- software programmes can coordinate the pre-interview steps and begin a digitally-mediated relationship with participants long before the actual interview commences. This essay provides examples of how researchers can maximise their time and energy by digitally…
Descriptors: College Freshmen, Interviews, Computer Uses in Education, Computer Software
Neto, Valter; Rolim, Vitor; Pinheiro, Anderson; Lins, Rafael Dueire; Gasevic, Dragan; Mello, Rafael Ferreira – IEEE Transactions on Learning Technologies, 2021
This article investigates the impact of educational contexts on automatic classification of online discussion messages according to cognitive presence, an essential construct of the community of inquiry model. In particular, the work reported in the article analyzed online discussion messages written in Brazilian Portuguese from two different…
Descriptors: Foreign Countries, Computer Mediated Communication, Discussion, Content Analysis
Hunt, Pihel; Leijen, Äli; van der Schaaf, Marieke – Education Sciences, 2021
While there is now extensive research on feedback in the context of higher education, including pre-service teacher education, little has been reported regarding the use of feedback from teachers to other teachers. Moreover, literature on the potential advantages that the use of technology, for example electronic portfolios and learning analytics,…
Descriptors: Teacher Attitudes, Teacher Evaluation, Peer Evaluation, Feedback (Response)
Shang, Hui-Fang – Interactive Learning Environments, 2022
Previous studies have been done to research the effects of different electronic feedback (e-feedback) modes of helping English as a foreign language (EFL) students improve their writing. The purpose of this study was to employ online peer feedback (OPF) and automated corrective feedback (ACF) to assess EFL learners' writing performance in the…
Descriptors: Computer Mediated Communication, Peer Evaluation, Feedback (Response), Automation
McHugh, Meaghan C.; Saperstein, Sandra L.; Gold, Robert S. – Health Education & Behavior, 2019
Cyberbullying, defined as bullying that takes place using technology, includes similar tactics found in traditional bullying as well as unique approaches such as viral repetition. Nationally, prevalence rates for cyberbullying range from 10% to as high as 40% of school-aged children, depending on the definition and measurement tool applied. The…
Descriptors: Bullying, Computer Mediated Communication, Handheld Devices, Telecommunications
Daniels, Paul – TESL-EJ, 2022
This paper compares the speaking scores generated by two online systems that are designed to automatically grade student speech and provide personalized speaking feedback in an EFL context. The first system, "Speech Assessment for Moodle" ("SAM"), is an open-source solution developed by the author that makes use of Google's…
Descriptors: Speech Communication, Auditory Perception, Computer Uses in Education, Computer Assisted Testing
Orellana, Anymir; Arguello, Georgina; Kanzki-Veloso, Elda – Online Learning, 2020
Captioning of recorded videos is beneficial to many and a matter of compliance with accessibility regulations and guidelines. Like recorded captions, real-time captions can also be means to implement the Universal Design for Learning checkpoint to offer text-based alternatives to auditory information. A cost-effective solution to implement the…
Descriptors: Computer Mediated Communication, Computer Software, Public Speaking, Automation