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Andrew Kwok-Fai Lui; Sin-Chun Ng; Stella Wing-Nga Cheung – Interactive Learning Environments, 2024
The technology of automated short answer grading (ASAG) can efficiently process answers according to human-prepared grading examples. Computer-assisted acquisition of grading examples uses a computer algorithm to sample real student responses for potentially good examples. The process is critical for optimizing the grading accuracy of machine…
Descriptors: Grading, Computer Uses in Education, Educational Technology, Artificial Intelligence
Zhang, Lishan; Huang, Yuwei; Yang, Xi; Yu, Shengquan; Zhuang, Fuzhen – Interactive Learning Environments, 2022
Automatic short-answer grading has been studied for more than a decade. The technique has been used for implementing auto assessment as well as building the assessor module for intelligent tutoring systems. Many early works automatically grade mainly based on the similarity between a student answer and the reference answer to the question. This…
Descriptors: Automation, Grading, Models, Artificial Intelligence
Kai Guo; Yuchun Zhong; Danling Li; Samuel Kai Wah Chu – Interactive Learning Environments, 2024
This study proposed a novel approach to classroom debates, in which chatbots that are able to engage in argumentative dialogues are adopted to facilitate students' debate preparation. The approach comprised three stages: first, students interacted with a chatbot named Argumate to help them generate ideas; second, students discussed the ideas with…
Descriptors: Foreign Countries, Undergraduate Students, Debate, Persuasive Discourse
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
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
Jon-Chao Hong; Chien-Hung Lin; Chin-Chieh Juh – Interactive Learning Environments, 2024
Referring to the advantages of intelligent personal assistants, or virtual agents, Charades can be implemented with a Chatbot to enhance students' vocabulary mastery. However, only a few studies have addressed the effectiveness of learning through practice with chatbots based on the Charades approach. We designed a Charades game using Google…
Descriptors: Artificial Intelligence, Computer Uses in Education, Games, Vocabulary Development
Chenchen Liu; Jierui Hou; Yun-Fang Tu; Youmei Wang; Gwo-Jen Hwang – Interactive Learning Environments, 2023
Automated writing feedback supported by artificial intelligence (AI) techniques has attracted the attention of English as Foreign Language (EFL) researchers. However, there is insufficient evidence and inconsistent conclusions on the actual impacts of AI on students' writing skills. In addition, in the field of EFL writing, there are few studies…
Descriptors: Artificial Intelligence, Reflection, English (Second Language), Writing Instruction
Wong, Lung-Hsiang; Looi, Chee-Kit – Interactive Learning Environments, 2012
The notion of a system adapting itself to provide support for learning has always been an important issue of research for technology-enabled learning. One approach to provide adaptivity is to use social navigation approaches and techniques which involve analysing data of what was previously selected by a cluster of users or what worked for…
Descriptors: Electronic Learning, Entomology, Educational Technology, Individualized Instruction
The Social Semantic Web in Intelligent Learning Environments: State of the Art and Future Challenges
Jovanovic, Jelena; Gasevic, Dragan; Torniai, Carlo; Bateman, Scott; Hatala, Marek – Interactive Learning Environments, 2009
Today's technology-enhanced learning practices cater to students and teachers who use many different learning tools and environments and are used to a paradigm of interaction derived from open, ubiquitous, and socially oriented services. In this context, a crucial issue for education systems in general, and for Intelligent Learning Environments…
Descriptors: Models, Interaction, Educational Technology, Design Requirements

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