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Showing 16 to 30 of 33 results Save | Export
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Xia, Xiaona – Interactive Learning Environments, 2023
Interactive learning environments can generate massive learning behavior data and the support of learning behavior big data can ensure the completeness of data analysis and robustness of relationship verification. In this study, learning behaviors are divided into training set and testing set, BP neural network and recurrent Elman network are…
Descriptors: Interaction, Intervention, Student Behavior, Educational Environment
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Tayebeh Sargazi Moghadam; Ali Darejeh; Mansoureh Delaramifar; Sara Mashayekh – Interactive Learning Environments, 2024
Learners' emotional states might change during the learning process, and unpredictable variations of a person's emotions raise the demand for regular assessment of feelings during learning. In this paper, an AI-based decision framework is proposed and implemented for e-learning systems that identify suitable micro-brake activities based on the…
Descriptors: Artificial Intelligence, Decision Making, Electronic Learning, Psychological Patterns
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Slavko Žitnik; Glenn Gordon Smith – Interactive Learning Environments, 2024
In the recent, and ongoing, COVID-19 pandemic, remote or online K-12 schooling became the norm. Even if the pandemic tails off somewhat, remote K-12 schooling will likely remain more frequent than it was before the pandemic. A mainstay technique of online learning, at least at the college and graduate level, has been the online discussion. Since…
Descriptors: Grade 4, Elementary School Students, Discussion, Automation
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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
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Asselman, Amal; Khaldi, Mohamed; Aammou, Souhaib – Interactive Learning Environments, 2023
Performance Factors Analysis (PFA) is considered one of the most important Knowledge Tracing (KT) approaches used for constructing adaptive educational hypermedia systems. It has shown a high prediction accuracy against many other KT approaches. While, the desire to estimate more accurately the student level leads researchers to enhance PFA by…
Descriptors: Algorithms, Artificial Intelligence, Factor Analysis, Student Behavior
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Siu-Cheung Kong; Wei Shen – Interactive Learning Environments, 2024
Logistic regression models have traditionally been used to identify the factors contributing to students' conceptual understanding. With the advancement of the machine learning-based research approach, there are reports that some machine learning algorithms outperform logistic regression models in terms of prediction. In this study, we collected…
Descriptors: Student Characteristics, Predictor Variables, Comprehension, Computation
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Shu-Hsuan Chang; Po-Jen Kuo; Jia Xin Kao; Lee-Jen Yang – Interactive Learning Environments, 2024
With the development of education technology, Smart classroom has evolved to version 2.0. Currently, the meta-analysis literature on the effects of smart classroom-based instruction on academic achievement ignores the impact of technological changes and time on the effect sizes. This study incorporated the impact of technological changes and time,…
Descriptors: Educational Technology, Technology Integration, Instructional Effectiveness, Academic Achievement
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Noawanit Songkram; Supattraporn Upapong; Heng-Yu Ku; Narongpon Aulpaijidkul; Sarun Chattunyakit; Nutthakorn Songkram – Interactive Learning Environments, 2024
This research proposes the integration of robotic education and scenario-based learning (SBL) paradigm for teaching computational thinking (CT) to enhance the computational abilities of primary school students, based on digital innovation and a teaching assistant robot acceptance model. The sample group consisted of 532 primary school teachers and…
Descriptors: Foreign Countries, Elementary School Students, Elementary School Teachers, Grade 1
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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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Xia, Xiaona – Interactive Learning Environments, 2023
The interactive learning is a continuous process, which is full of a large number of learning interaction activities. The data generated between learners and learning interaction activities can reflect the online learning behaviors. Through the correlation analysis among learning interaction activities, this paper discusses the potential…
Descriptors: Behavior Patterns, Learning Analytics, Decision Making, Correlation
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Xing, Wanli; Pei, Bo; Li, Shan; Chen, Guanhua; Xie, Charles – Interactive Learning Environments, 2023
Engineering design plays an important role in education. However, due to its open nature and complexity, providing timely support to students has been challenging using the traditional assessment methods. This study takes an initial step to employ learning analytics to build performance prediction models to help struggling students. It allows…
Descriptors: Learning Analytics, Engineering Education, Prediction, Design
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Silvia Wen-Yu Lee; Jyh-Chong Liang; Chung-Yuan Hsu; Meng-Jung Tsai – Interactive Learning Environments, 2024
While research has shown that students' epistemic beliefs can be a strong predictor of their academic performance, cognitive abilities, or self-efficacy, studies of this topic in computer education are rare. The purpose of this study was twofold. First, it aimed to validate a newly developed questionnaire for measuring students' epistemic beliefs…
Descriptors: Student Attitudes, Beliefs, Computer Science Education, Programming
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Shian-Shyong Tseng; Tsung-Yu Yang; Wen-Chung Shih; Bo-Yang Shan – Interactive Learning Environments, 2024
In this paper, to handle the problem of the quick evolution of cyber-security attacks, we developed the iMonsters board game and proposed the attack and defense knowledge self-evolving algorithm. Three versions of the iMonsters were launched in 2013, 2017, and 2019, respectively. Accordingly, the cyber-security ontology can be refined by the…
Descriptors: Educational Games, Computer Security, Computer Science Education, Game Based Learning
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Changhao Liang; Rwitajit Majumdar; Yuta Nakamizo; Brendan Flanagan; Hiroaki Ogata – Interactive Learning Environments, 2024
In-class group work activities are found to promote the interpersonal skills of learners. To support the teachers in facilitating such activities, we designed a learning analytics-enhanced technology framework, Group Learning Orchestration Based on Evidence (GLOBE) using data-driven approaches. In this study, we implemented the algorithmic group…
Descriptors: Algorithms, Group Dynamics, Group Activities, Learning Analytics
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Li, Jiansheng; Lin, Yuyu; Sun, Mingzhu; Shadiev, Rustam – Interactive Learning Environments, 2023
This study examined whether socially shared regulation of learning (SSRL) enhances students' algorithmic thinking performance, promotes learning participation and improves students' learning attitudes through game-based collaborative learning. The students learned algorithmic knowledge and completed programing tasks using Kodu, a new visual…
Descriptors: Cooperative Learning, Game Based Learning, Educational Environment, Algorithms
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