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Ritter, Frank E.; Qin, Michael; MacDougall, Korey; Chae, Chungil – Interactive Learning Environments, 2023
We created a list of more than 140 tools that can be used to create tutoring systems, from complete tutoring systems to low-level tools for preparing instructional materials. Based on this list, we present a preliminary ontology of system dimensions that can serve as a base for a comprehensive review or in building systems. We also note that: (a)…
Descriptors: Educational Resources, Intelligent Tutoring Systems, Computer Managed Instruction, Programmed Tutoring
Paladines, José; Ramírez, Jaime; Berrocal-Lobo, Marta – Interactive Learning Environments, 2023
This paper addresses the challenge of integrating a dialog system with an ITS created for supporting procedural training in a 3D virtual environment. To this end, we first describe the desired features of the dialog to be provided to students in such system. Then, we explain some technical issues of our proposal such as the architecture; the…
Descriptors: Intelligent Tutoring Systems, Dialogs (Language), Man Machine Systems, Computer Simulation
Yuhui Yang; Hao Zhang; Huifang Chai; Wei Xu – Interactive Learning Environments, 2023
The COVID-19 pandemic has accelerated the transformation of education forms, and the combination of online and offline teaching has become the core development direction of university teaching at present and in the future. Therefore, appropriate teaching space is urgently needed to support the practice of blended teaching. Firstly, this paper…
Descriptors: Intelligent Tutoring Systems, Instructional Design, Universities, Blended Learning
Jaeho Jeon; Seongyong Lee; Seongyune Choi – Interactive Learning Environments, 2024
Chatbot research has received growing attention due to the rapid diversification of chatbot technology, as demonstrated by the emergence of large language models (LLMs) and their integration with automatic speech recognition. However, among various chatbot types, speech-recognition chatbots have received limited attention in relevant research…
Descriptors: Literature Reviews, Content Analysis, Second Language Learning, Artificial Intelligence
Benmesbah, Ouissem; Lamia, Mahnane; Hafidi, Mohamed – Interactive Learning Environments, 2023
Adaptive learning has garnered researchers' interest. The main issue within this field is how to select appropriate learning objects (LOs) based on learners' requirements and context, and how to combine the selected LOs to form what is known as an adaptive learning path. Heuristic and metaheuristic approaches have achieved significant progress on…
Descriptors: Algorithms, Teaching Methods, Educational Innovation, Genetics
Yousaf, Yousra; Shoaib, Muhammad; Hassan, Muhammad Awais; Habiba, Ume – Interactive Learning Environments, 2023
Learning trend has been shifted from a conventional way to a digital way in the form of E-learning, but it faces a high dropout ratio. Lack of engagement is one of the primary factors reported for this issue as the same type of course content is presented to learners despite their different background, knowledge and learning styles. Different…
Descriptors: Intelligent Tutoring Systems, Cognitive Style, Learner Engagement, Academic Achievement
Rosmansyah, Yusep; Putro, Budi Laksono; Putri, Atina; Utomo, Nur Budi; Suhardi – Interactive Learning Environments, 2023
In this article, smart learning environment (SLE) is defined as a hybrid learning system that provides learners and other stakeholders with a joyful learning process while achieving learning outcomes as a result of the employed intelligent tools and techniques. From literature study, existing SLE models and frameworks are difficult to understand…
Descriptors: Electronic Learning, Artificial Intelligence, Educational Technology, Technology Uses in Education
Jessica Fernanda Silva Barbosa; Geiser Chalco Challco; Ig Ibert Bittencourt – Interactive Learning Environments, 2024
Gender-stereotypical design, such as the predominance of blue colors in interfaces, leaderboards with only men at the top, and male avatars, may have negative effects on women in gamified tutoring systems, especially in courses with a majority of male participation, such as courses of Science, Technology, Engineering, and Mathematics (STEM). We…
Descriptors: Sex Stereotypes, Gamification, Thinking Skills, Negative Attitudes
Daocheng Hong – Interactive Learning Environments, 2024
The digital transformation of education is greatly accelerating in various computer-supported applications. As a particularly prominent application of the human-machine interactive system, intelligent learning systems aim to capture users' current intentions and provide recommendations through real-time feedback. However, we have a limited…
Descriptors: Feedback (Response), Users (Information), Learner Engagement, Tests
Liping Sun; Marjaana Kangas; Heli Ruokamo – Interactive Learning Environments, 2024
Intelligent game-based learning environments have developed and created dynamic, effective, and engaging learning experiences, serving as a tutoring framework for students of different educational levels. Although game-based features have recently been shown to have the potential to improve intelligent tutoring systems in these learning…
Descriptors: Game Based Learning, Literature Reviews, Intelligent Tutoring Systems, Influence of Technology
John S. Y. Lee; Chak Yan Yeung; Zhenqun Yang – Interactive Learning Environments, 2024
A text recommendation system helps language learners find suitable reading materials. Similar to graded readers, most systems assign difficulty levels or school grades to the documents in their database, and then identify the documents that best match the language proficiency of the learner. This graded approach has two main limitations. First,…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Second Language Learning, Language Acquisition
Yun Tang; Zhengfan Li; Guoyi Wang; Xiangen Hu – Interactive Learning Environments, 2023
To better understand the self-regulated learning process in online learning environments, this research applied a data mining method, the two-layer hidden Markov model (TL-HMM), to explore the patterns of learning activities. We analyzed 25,818 entries of behavior log data from an intelligent tutoring system. Results indicated that students with…
Descriptors: Electronic Learning, Learning Activities, Self Management, Intelligent Tutoring Systems
S. Sageengrana; S. Selvakumar; S. Srinivasan – Interactive Learning Environments, 2024
Students are termed "multitaskers," and it is likely that they easily fall prey to other subjects or topics that most interest them. They occasionally took heed or gave close and thoughtful attention to the lectures they were on. In the current educational system, our young generations receive materials from their leftovers, and their…
Descriptors: Electronic Learning, Dropouts, Student Behavior, Student Interests
Venigalla, Akhila Sri Manasa; Chimalakonda, Sridhar – Interactive Learning Environments, 2022
E-books have become more prevalent in the present day, due to their availability and numerous advantages over textbooks, and more so in the domain of computer science and programming. On the other hand, learners also use Q&A websites such as Stack Overflow as these websites provides a platform for asking and answering questions in…
Descriptors: Electronic Books, Textbooks, Web Sites, Programming
Gang Yang; Xiao-Qian Zheng; Qian Li; Miao Han; Yun-Fang Tu – Interactive Learning Environments, 2024
In Chinese, writing is a basic competency that pupils should possess. But it is still challenging for teachers to improve pupils' writing abilities. Therefore, this study proposes an intelligence-based cognitive diagnostic feedback strategy to improve pupils' writing ability and writing learning quality by analyzing their writing performance,…
Descriptors: Foreign Countries, Elementary School Students, Vocabulary Skills, Comparative Analysis