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Radosavljevic, Vitomir; Radosavljevic, Slavica; Jelic, Gordana – Interactive Learning Environments, 2022
This paper introduces the smart classroom learning model based on the concept of ambient intelligence. By analyzing a smart classroom, the ambient intelligence system detects a student and determines their level of fatigue based on the data about their previous daily academic activities. This information is then used to assign the student the…
Descriptors: Virtual Classrooms, Educational Technology, Technology Uses in Education, Artificial Intelligence
Lertnattee, Verayuth; Wangwattana, Bunyapa – Interactive Learning Environments, 2021
In the academic year of 2019, the designed personalized learning and assessment was applied to the fourth-year pharmacy students who registered for the Pharmacognosy Laboratory in the Faculty of Pharmacy, Silpakorn University. We allowed all students to do the experiment as they preferred. We created a personalized assessment that allowed the…
Descriptors: Individualized Instruction, Pharmaceutical Education, Laboratory Equipment, Identification
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
Min-Chi Chiu; Gwo-Jen Hwang; Lu-Ho Hsia; Fong-Ming Shyu – Interactive Learning Environments, 2024
In a conventional art course, it is important for a teacher to provide feedback and guidance to individual students based on their learning status. However, it is challenging for teachers to provide immediate feedback to students without any aid. The advancement of artificial intelligence (AI) has provided a possible solution to cope with this…
Descriptors: Art Education, Artificial Intelligence, Teaching Methods, Comparative Analysis
Huang, Anna Y. Q.; Lu, Owen H. T.; Huang, Jeff C. H.; Yin, C. J.; Yang, Stephen J. H. – Interactive Learning Environments, 2020
In order to enhance the experience of learning, many educators applied learning analytics in a classroom, the major principle of learning analytics is targeting at-risk student and given timely intervention according to the results of student behavior analysis. However, when researchers applied machine learning to train a risk identifying model,…
Descriptors: Academic Achievement, Data Use, Learning Analytics, Classification
Ruiz, Samara; Urretavizcaya, Maite; Rodríguez, Clemente; Fernández-Castro, Isabel – Interactive Learning Environments, 2020
A positive emotional state of students has proved to be essential for favouring student learning, so this paper explores the possibility of obtaining student feedback about the emotions they feel in class in order to discover emotion patterns that anticipate learning failures. From previous studies about emotions relating to learning processes, we…
Descriptors: College Students, Computer Science Education, Emotional Response, Student Reaction
Li, Cheng-Hsuan; Wu, Huey-Min; Kuo, Bor-Chen; Yang, Yu-Mao; Lin, Chin-Kai; Wang, Wei-Hsiang – Interactive Learning Environments, 2018
The purpose of this study is to explore the validity of the assessment tool. The purposive sampling method is applied in this research on a total of 551 preschool children between 4 and 6 years old. Their ages range from 46 to 81 months, with an average age of 63.9 months (SD = 7.58). The assessment tool used in this research is the…
Descriptors: Test Validity, Chinese, Psychomotor Skills, Preschool Children
Bahreini, Kiavash; Nadolski, Rob; Westera, Wim – Interactive Learning Environments, 2017
The teaching of communication skills is a labour-intensive task because of the detailed feedback that should be given to learners during their prolonged practice. This study investigates to what extent our FILTWAM facial and vocal emotion recognition software can be used for improving a serious game (the Communication Advisor) that delivers a…
Descriptors: Communication Skills, Skill Development, Training Methods, Computer Software
Yu, Fu-Yun; Sung, Shannon – Interactive Learning Environments, 2016
This study examined the effects of identity revelation and concealment on the number of times students' work was assessed in an online peer assessment context. It also examined the underlying reasons guiding the assessor's targeting behavior. Two fifth-grade classes participated. The one-group pretest-posttest experimental research design coupled…
Descriptors: Foreign Countries, Elementary School Students, Grade 5, Student Evaluation
Girvan, C.; Savage, T. – Interactive Learning Environments, 2012
The combination of features in virtual worlds provides an opportunity to implement and research unique learning experiences. With increasing interest and activity from the educational research community, exploring virtual worlds for teaching and learning, there is a need to identify and understand the ethical implications of conducting research in…
Descriptors: Educational Research, Ethics, Virtual Classrooms, Learning Experience
Hwang, Wu-Yuin; Huang, Yueh-Min; Wu, Sheng-Yi – Interactive Learning Environments, 2011
The use of instant messaging to support e-learning will continue to gain importance because of its speed, effectiveness, and low cost. This study developed an MSN agent to mediate and facilitate students' learning in a Web-based course. The students' acceptance of the MSN agent and its effect on learning community identification and learning…
Descriptors: Electronic Learning, Feedback (Response), Web Based Instruction, Identification
Schellens, T.; Van Keer, H.; De Wever, B.; Valcke, M. – Interactive Learning Environments, 2009
The present study focuses on the use of thinking types as a possible way to structure university students' discourse in asynchronous discussion groups and consequently promote their learning. More specifically, the aim of the study is to determine how requiring students to label their contributions by means of De Bono's (1991) thinking hats…
Descriptors: Discussion Groups, Identification, Critical Thinking, Thinking Skills
Yannibelli, Virginia; Godoy, Daniela; Amandi, Analia – Interactive Learning Environments, 2006
Learning styles encapsulate the preferences of the students, regarding how they learn. By including information about the student learning style, computer-based educational systems are able to adapt a course according to the individual characteristics of the students. In accomplishing this goal, educational systems have been mostly based on the…
Descriptors: Student Characteristics, Mathematical Models, Genetics, Educational Technology
Veen, Jan; Collis, Betty; Jones, Val – Interactive Learning Environments, 2003
Group-based learning is being introduced into many settings in higher education. Is this a sustainable development with respect to the resources required? Under what conditions can group-based learning be applied successfully in distance education and in increasingly flexible campus-based learning? Can networked support facilitate and enrich…
Descriptors: Higher Education, Identification, Sustainable Development, Distance Education
Westera, W.; Hommes, M. A.; Houtmans, M.; Kurvers, H. J. – Interactive Learning Environments, 2003
This paper outlines and discusses a self-contained multimedia-training program on psychological diagnostics. The program aims to play an intermediate role between theory and working practice, while offering students a simulated environment to prepare for practical work with real humans. The program simulates the entire diagnostic cycle in…
Descriptors: Simulated Environment, Program Design, Learning Strategies, Foreign Countries

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