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Promethi Das Deep; Yixin Chen – Higher Education Studies, 2025
The COVID-19 pandemic significantly disrupted higher education. The sudden and profound transformations it necessitated had a direct and negative impact on higher education students, as evidenced by the widely reported instances of academic disengagement, decreased motivation, and lower performance. This was often due to student burnout caused by…
Descriptors: COVID-19, Pandemics, Electronic Learning, Fatigue (Biology)
Héctor J. Pijeira-Díaz; Shashank Subramanya; Janneke van de Pol; Anique de Bruin – Journal of Computer Assisted Learning, 2024
Background: When learning causal relations, completing causal diagrams enhances students' comprehension judgements to some extent. To potentially boost this effect, advances in natural language processing (NLP) enable real-time formative feedback based on the automated assessment of students' diagrams, which can involve the correctness of both the…
Descriptors: Learning Analytics, Automation, Student Evaluation, Causal Models
Zheng, Lanqin; Long, Miaolang; Chen, Bodong; Fan, Yunchao – International Journal of Educational Technology in Higher Education, 2023
Online collaborative learning is implemented extensively in higher education. Nevertheless, it remains challenging to help learners achieve high-level group performance, knowledge elaboration, and socially shared regulation in online collaborative learning. To cope with these challenges, this study proposes and evaluates a novel automated…
Descriptors: Learning Analytics, Computer Assisted Testing, Cooperative Learning, Graphs
Bünyami Kayali; Mehmet Yavuz; Sener Balat; Mücahit Çalisan – Australasian Journal of Educational Technology, 2023
The purpose of this study was to determine university students' experiences with the use of ChatGPT in online courses. The sample consisted of 84 associate degree students from a state university in Turkey. A multi-method approach was used in the study. Although quantitative data were collected using the Chatbot Usability Scale, qualitative data…
Descriptors: Student Experience, Artificial Intelligence, Natural Language Processing, Electronic Learning
Michael Agyemang Adarkwah; Samuel Anokye Badu; Evans Appiah Osei; Enoch Adu-Gyamfi; Jonathan Odame; Käthe Schneider – Discover Education, 2025
The advancement of artificial intelligence (AI) tools has revolutionized teaching and learning, particularly in healthcare education, where they enhance pedagogy, foster immersive learning, and support healthcare provision. However, their use in healthcare education is contentious, warranting careful examination, especially regarding Generative AI…
Descriptors: Artificial Intelligence, Health Services, Medical Education, Technological Advancement
Prapasiri Klayklung; Piyawatjana Chocksathaporn; Pongsakorn Limna; Tanpat Kraiwanit; Kris Jangjarat – Online Submission, 2023
The development of conversational artificial intelligence (AI) has brought about new opportunities for improving the learning experience in education. ChatGPT, a large language model trained on a vast corpus of text, has the potential to revolutionize education by enhancing learning through personalized and interactive conversations. This paper…
Descriptors: Artificial Intelligence, Interaction, Foreign Countries, Technology Integration
Bilal Khallel Younis – Online Learning, 2024
This study aims to investigate students' self-regulation skills, confidence to learn online, and perception of satisfaction and usefulness of online classes in three learning environments that integrates ChatGPT. In this study, a quasi-experiential design was used to compare three online learning environments that integrate ChatGPT (independent,…
Descriptors: Self Management, Self Esteem, Electronic Learning, Student Attitudes
Bóbó, Míria L. D. R.; Campos, Fernanda; Stroele, Victor; David, José Maria N.; Braga, Regina; Torrent, Tiago Timponi – International Journal of Distance Education Technologies, 2022
Dropping out of school comes from a long-term disengagement process with social and economic consequences. Being able to predict students' behavior earlier can minimize their failures and disengagement. This article presents the SASys architecture based on a lexical approach and a polarized frame network. Its main goal is to define the author's…
Descriptors: Dropout Prevention, Psychological Patterns, Learner Engagement, Electronic Learning
Anna Y. Q. Huang; Jei Wei Chang; Albert C. M. Yang; Hiroaki Ogata; Shun Ting Li; Ruo Xuan Yen; Stephen J. H. Yang – Educational Technology & Society, 2023
To improve students' learning performance through review learning activities, we developed a personalized intervention tutoring approach that leverages learning analysis based on artificial intelligence. The proposed intervention first uses text-processing artificial intelligence technologies, namely bidirectional encoder representations from…
Descriptors: Academic Achievement, Tutoring, Artificial Intelligence, Individualized Instruction
Hernández-Lara, Ana Beatriz; Perera-Lluna, Alexandre; Serradell-López, Enric – Education & Training, 2021
Purpose: With the growth of digital education, students increasingly interact in a variety of ways. The potential effects of these interactions on their learning process are not fully understood and the outcomes may depend on the tool used. This study explores the communication patterns and learning effectiveness developed by students using two…
Descriptors: Game Based Learning, Learning Analytics, Computer Mediated Communication, Asynchronous Communication
Lang, David; Stenhaug, Ben; Kizilcec, Rene – Grantee Submission, 2019
This research evaluates the psychometric properties of short-answer response items under a variety of grading rules in the context of a mobile learning platform in Africa. This work has three main findings. First, we introduce the concept of a differential device function (DDF), a type of differential item function that stems from the device a…
Descriptors: Foreign Countries, Psychometrics, Test Items, Test Format
A Computational Method for Enabling Teaching-Learning Process in Huge Online Courses and Communities
Mora, Higinio; Ferrández, Antonio; Gil, David; Peral, Jesús – International Review of Research in Open and Distributed Learning, 2017
Massive Open Online Courses and e-learning represent the future of the teaching-learning processes through the development of Information and Communication Technologies. They are the response to the new education needs of society. However, this future also presents many challenges such as the processing of online forums when a huge number of…
Descriptors: Electronic Learning, Online Courses, Teaching Methods, Learning Processes
Mazur, Michal; Karolczak, Krzysztof; Rzepka, Rafal; Araki, Kenji – International Journal of Distance Education Technologies, 2016
Vocabulary plays an important part in second language learning and there are many existing techniques to facilitate word acquisition. One of these methods is code-switching, or mixing the vocabulary of two languages in one sentence. In this paper the authors propose an experimental system for computer-assisted English vocabulary learning in…
Descriptors: Vocabulary Development, Vocabulary, Code Switching (Language), English (Second Language)
Alqahtani, Maha; Mohammad, Heba – Turkish Online Journal of Educational Technology - TOJET, 2015
Mobile applications are rapidly growing in importance and can be used for various purposes. They had been used widely in education. One of the educational purposes for which mobile applications can be used is learning the right way to read and pronounce the verses of the Holy Quran. There are many applications that translate the Quran into several…
Descriptors: Electronic Learning, Handheld Devices, Participant Satisfaction, Student Attitudes
Harbusch, Karin; Cameran, Christel-Joy; Härtel, Johannes – Research-publishing.net, 2014
We present a new feedback strategy implemented in a natural language generation-based e-learning system for German as a second language (L2). Although the system recognizes a large proportion of the grammar errors in learner-produced written sentences, its automatically generated feedback only addresses errors against rules that are relevant at…
Descriptors: German, Second Language Learning, Second Language Instruction, Feedback (Response)
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