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Jing Chen; Ruiqi Wang; Bei Fang; Chen Zuo – Interactive Learning Environments, 2024
Online learning has developed rapidly and billions of learners have participated in various courses. However, the high dropout rate is universal and learning performance is not satisfactory. Fortunately, learners have posted a large number of reviews which express their feedback opinions. The fine-grained aspects and opinions existing in reviews…
Descriptors: Online Courses, Feedback (Response), Opinions, Algorithms
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Mark Johnson; Rafiq Saleh – Interactive Learning Environments, 2024
Educational assessment is inherently uncertain, where physiological, psychological and social factors play an important role in establishing judgements which are assumed to be "absolute". AI and other algorithmic approaches to grading of student work strip-out uncertainty, leading to a lack of inspectability in machine judgement and…
Descriptors: Artificial Intelligence, Evaluation Methods, Technology Uses in Education, Man Machine Systems
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Jing Chen; Bei Fang; Hao Zhang; Xia Xue – Interactive Learning Environments, 2024
High dropout rate exists universally in massive open online courses (MOOCs) due to the separation of teachers and learners in space and time. Dropout prediction using the machine learning method is an extremely important prerequisite to identify potential at-risk learners to improve learning. It has attracted much attention and there have emerged…
Descriptors: MOOCs, Potential Dropouts, Prediction, Artificial Intelligence
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Soomaiya Hamid; Narmeen Zakaria Bawany – Interactive Learning Environments, 2024
E-learning is the process of sharing knowledge out of the traditional classrooms through different online tools using internet. The availability and use of these tools are not easy for every student. Many institutions gather e-learning feedback to know the problems of students to improve their systems. In e-learning systems, typically a high…
Descriptors: Feedback (Response), Electronic Learning, Automation, Classification
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Xu Yaqian; Zheng Qinhua – Interactive Learning Environments, 2024
The interactive mechanism between social and concept networks is a key question in connectivist learning, which explains the impact of interaction on cognitive development and knowledge generation. The successful practice of "Internet Change Education: Dialogue between Theory and Practice", the first cMOOC in China, provides data support…
Descriptors: Correlation, Social Networks, Status, MOOCs
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Ibrahim Adeshola; Adeola Praise Adepoju – Interactive Learning Environments, 2024
The launch of OpenAI ChatGPT's language-generation model has raised alarms within many sectors, especially the academic sector. Several academicians have urged universities to develop new forms of assessment after the launch of ChatGPT, which solves academic questions in less than a few minutes. Academic cheating is not a new phenomenon, and the…
Descriptors: Opportunities, Barriers, Artificial Intelligence, Natural Language Processing
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Suping Yi; Rustam Shadiev; Yanyan Zhang – Interactive Learning Environments, 2024
This study reviewed thirty-seven articles on intercultural learning supported by technology. The results are reported in terms of strength of evidence and relationship among research variables. The results indicated the following strength of evidence: (1) moderate evidence showed higher frequency of the technology usage in higher education or…
Descriptors: Literature Reviews, Multicultural Education, Technology Uses in Education, Predictor Variables
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Luyu Zhu; Jia Hao; Jianhou Gan – Interactive Learning Environments, 2024
Nowadays, Massive Open Online Courses (MOOC) has been gradually accepted by the public as a new type of education and teaching method. However, due to the lack of timely intervention and guidance from educators, learners' performance is not as effective as it could be. To address this problem, predicting MOOC learners' performance and providing…
Descriptors: MOOCs, Academic Achievement, Prediction, Bayesian Statistics
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Jiahong Su; Kai Guo; Xinyu Chen; Samuel Kai Wah Chu – Interactive Learning Environments, 2024
The teaching of artificial intelligence (AI) has increasingly become a topic of investigation among educational researchers. Studies of AI education have predominantly focused on the university level; less attention has been paid to teaching AI in K-12 classrooms. This study synthesised empirical studies on K-12 AI education, with the aims of…
Descriptors: Artificial Intelligence, Computer Science Education, Elementary Secondary Education, Teaching Methods
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Kai-Yu Tang; Yuen-Hsien Tseng; Yun-Fang Tu – Interactive Learning Environments, 2024
This study conducted a systematic review to identify the mainstreams of contemporary digital reading research. We performed a co-citation network analysis to examine the streams and features of key topics in digital reading research. We also performed content analysis and used the bibliometrix R-package to map digital reading research themes and…
Descriptors: Reading Research, Citation Analysis, Literature Reviews, Digital Literacy
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Hüseyin Ates; Rabia Meryem Yilmaz – Interactive Learning Environments, 2024
This study was conducted to understand pre-service and in-service teachers' intentions to use mobile-based assessment in classes by integrating theory of planned behaviour, technology acceptance model, and self-determination theory into one conceptual framework. Data were analysed using the structural equation model (SEM). Results of SEM from a…
Descriptors: Teacher Behavior, Intention, Handheld Devices, Telecommunications
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Shalva Kikalishvili – Interactive Learning Environments, 2024
Presented study seeks to examine the potential applications of the OpenAI language model, GPT-3, within the realm of education. Specifically, the inquiry focuses on the feasibility of utilizing GPT-3 to generate essays based on customized prompts. To this end, the experimentation involved providing GPT-3 with tailored prompts derived from diverse…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Opportunities
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Pooja Rana; Mithilesh Kumar Dubey; Lovi Raj Gupta; Amit Kumar Thakur – Interactive Learning Environments, 2024
In recent years, the system of student learning and academic emotions has been taken seriously to re-engineer the teaching-learning process at all levels of education. This research paper considers both aspects of assessing the translation of knowledge i.e. qualitative and quantitative. In the current scenario, quantitative and qualitative…
Descriptors: Educational Assessment, Outcomes of Education, Models, Evaluation Methods
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Agostino Marengo; Alessandro Pagano; Kamal Ahmed Soomro – Interactive Learning Environments, 2024
Soft skills are interpersonal, communication, and personal attributes that enable individuals to interact effectively with others in personal and workplace settings. Despite the significance of soft skills for career success, these skills are not necessarily taught in traditional academic settings. Consequently, education institutions must adopt…
Descriptors: Game Based Learning, Soft Skills, Student Evaluation, Instructional Effectiveness
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Gwo-Jen Hwang; An-Chi Lin; Shao-Chen Chang – Interactive Learning Environments, 2024
Digital games have been used in various disciplines to enhance students' learning interest and effectiveness through the gaming contexts. However, most of the digital educational games use multiple-choice questions to confirm students' learning status, implying the challenge of understanding the actual learning status of students. Also, the gaming…
Descriptors: Game Based Learning, Academic Achievement, Student Behavior, Horticulture
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