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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
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
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
Gonulal, Talip – Interactive Learning Environments, 2023
Intelligent personal assistants (IPAs), which are voice-activated agents enabling human--computer interaction, have recently been reported to be pedagogically useful agents in language learning. IPAs use various forms of humor to better communicate with users and to compensate for any performance limitations. In order to understand the IPAs' sense…
Descriptors: Intelligent Tutoring Systems, Second Language Learning, Second Language Instruction, English (Second Language)
Wang, Shuai; Christensen, Claire; Cui, Wei; Tong, Richard; Yarnall, Louise; Shear, Linda; Feng, Mingyu – Interactive Learning Environments, 2023
Adaptive learning systems personalize instruction to students' individual learning needs and abilities. Such systems have shown positive impacts on learning. Many schools in the United States have adopted adaptive learning systems, and the rate of adoption in China is accelerating, reaching almost 2 million unique users for one product alone in…
Descriptors: Comparative Analysis, Teaching Methods, Intelligent Tutoring Systems, Foreign Countries
Elfeky, Abdellah Ibrahim Mohammed; Elbyaly, Marwa Yasien Helmy – Interactive Learning Environments, 2021
Little studies have been conducted on the question of the use of augmented reality technology in the education field. The effects of augmented reality technology on the educational environment of tertiary students need to be further explored. Therefore, the present study aimed to investigate the effectiveness of augmented reality technology in…
Descriptors: Skill Development, Clothing, Design, Aesthetics
Davy Tsz Kit Ng; Jiahong Su; Jac Ka Lok Leung; Samuel Kai Wah Chu – Interactive Learning Environments, 2024
Artificial intelligence (AI) literacy has emerged to equip students with digital skills for effective evaluation, communication, collaboration, and ethical use of AI in online, home, and workplace settings. Countries are increasingly developing AI curricula to support students' technological skills for future studies and careers. However, there is…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Secondary School Students
Tlili, Ahmed; Denden, Mouna; Essalmi, Fathi; Jemni, Mohamed; Chang, Maiga; Kinshuk; Chen, Nian-Shing – Interactive Learning Environments, 2023
The ability of automatically modeling learners' personalities is an important step in building adaptive learning environments. Several studies showed that knowing the personality of each learner can make the learning interaction with the provided learning contents and activities within learning systems more effective. However, the traditional…
Descriptors: Learning Analytics, Learning Management Systems, Intelligent Tutoring Systems, Bayesian Statistics
Mustafa, Ghulam; Abbas, Muhammad Azeem; Hafeez, Yaser; Khan, Sharifullah; Hwang, Gwo-Jen – Interactive Learning Environments, 2019
During early childhood, children start developing their cognitive, social, emotional, and behavioural skills, laying the foundation for life-long learning. Cognitive skills are usually taught in traditional classrooms through the use of textbooks and worksheets. The learning content in these textbooks and worksheets is static pre-authored content…
Descriptors: Cognitive Development, Preschool Children, Child Development, Skill Development
Hsu, Ting-Chia – Interactive Learning Environments, 2019
This study examines four elements of learner motivation, attention, relevance, confidence, and satisfaction, in an EFL speaking course that uses the computer mediated communication (CMC) tool Google Hangouts. The study found that a preparatory concept mapping task before the CMC sessions improved students' perceived attention, relevance,…
Descriptors: Foreign Countries, Concept Mapping, Teaching Methods, Learning Motivation
Chen, Chih-Ming; Wang, Jung-Ying; Chen, Yong-Ting; Wu, Jhih-Hao – Interactive Learning Environments, 2016
To reduce effectively the reading anxiety of learners while reading English articles, a C4.5 decision tree, a widely used data mining technique, was used to develop a personalized reading anxiety prediction model (PRAPM) based on individual learners' reading annotation behavior in a collaborative digital reading annotation system (CDRAS). In…
Descriptors: Reading Strategies, Prediction, Models, Quasiexperimental Design
Hsu, Wei-Chih; Li, Cheng-Hsiu – Interactive Learning Environments, 2015
This paper presents a new algorithm called competency-based guided-learning algorithm (CBGLA), which can be applied on adaptively guiding e-learning. Computational process analysis and mathematical derivation of competency-based learning (CBL) were used to develop the CBGLA. The proposed algorithm could generate an effective adaptively guiding…
Descriptors: Educational Technology, Competency Based Education, Pretests Posttests, Scores
Rodicio, H. Garcia; Sanchez, E. – Interactive Learning Environments, 2012
Learners are usually provided with support devices because they find it difficult to learn from multimedia presentations. A key question, with no clear answer so far, is how best to present these support devices. One possibility is to insert them into the multimedia presentation (canned support), while another is to have a human agent provide them…
Descriptors: Multimedia Instruction, Computer Assisted Instruction, Tutoring, Intermode Differences
Laureano-Cruces, Ana Lilia; Ramirez-Rodriguez, Javier; Mora-Torres, Martha; de Arriaga, Fernando; Escarela-Perez, Rafael – Interactive Learning Environments, 2010
In this paper behavior during the teaching-learning process is modeled by means of a fuzzy cognitive map. The elements used to model such behavior are part of a generic didactic model, which emphasizes the use of cognitive and operative strategies as part of the student-tutor interaction. Examples of possible initial scenarios for the…
Descriptors: Cognitive Mapping, Educational Technology, Teaching Methods, Cognitive Development
Kenny, Claire; Pahl, Claus – Interactive Learning Environments, 2009
Active learning facilitated through interactive and adaptive learning environments differs substantially from traditional instructor-oriented, classroom-based teaching. We present a web-based e-learning environment that integrates knowledge learning and skills training. How these tools are used most effectively is still an open question. We…
Descriptors: Feedback (Response), Active Learning, Educational Technology, Evaluation Methods
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