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Showing all 11 results Save | Export
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Bin Meng; Fan Yang – International Journal of Web-Based Learning and Teaching Technologies, 2025
This paper proposes a computer-aided teaching model using knowledge graph construction and learning path recommendation. It first creates a multimodal knowledge graph to illustrate complex relationships among knowledge. Learning elements and sequences are then used to form time sequences stored as directed graphs, supporting flexible path…
Descriptors: Students, Teachers, Computer Assisted Instruction, Knowledge Representation
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Sri Wahyuni; Nur Hidayanto Pancoro Setyo Putro; Anwar Efendi – Advanced Education, 2024
Notwithstanding the increase in research on artificial intelligence-infused English language learning, several issues remain inadequately addressed. Thus, this paper provides a systematic review and analyzes previous studies to pinpoint fruitful knowledge gaps and outline approaches for future research directions. Two approaches, bibliometric and…
Descriptors: Artificial Intelligence, Educational Trends, Technology Uses in Education, Handheld Devices
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Darmawansah Darmawansah; Dzul Rachman; Febiyani Febiyani; Gwo-Jen Hwang – Education and Information Technologies, 2025
Argumentation is a complex skill essential for English as a Foreign Language (EFL) students to effectively use their English language and reasoning abilities in writing and speaking. Constructing arguments without proper collaborative scaffolding and technological support can be cognitively demanding. Generative artificial intelligence (Gen AI) in…
Descriptors: Artificial Intelligence, Cooperative Learning, Persuasive Discourse, Scripts
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Kuo, Yu-Chen; Chen, Yun-An – Education and Information Technologies, 2023
With the development of science and technology, the demand for programmers has increased. However, learning computer programs is not an easy task. It might cause a significant impact on programming if misconceptions exist at the beginning of the study. Hence, it is important to discover and correct them immediately. Chatbots are effective teaching…
Descriptors: Programming, Artificial Intelligence, Computer Science Education, Misconceptions
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Rasheed, Fareeha; Wahid, Abdul – International Journal of Information and Learning Technology, 2019
Purpose: The purpose of this paper is to identify the different sequence generation techniques for learning, which are applied to a broad category of personalized learning experiences. The papers have been classified using different attributes, such as the techniques used for sequence generation, attributes used for sequence generation; whether…
Descriptors: Sequential Approach, Electronic Learning, Futures (of Society), Student Characteristics
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Jain, G. Panka; Gurupur, Varadraj P.; Schroeder, Jennifer L.; Faulkenberry, Eileen D. – IEEE Transactions on Learning Technologies, 2014
In this paper, we describe a tool coined as artificial intelligence-based student learning evaluation tool (AISLE). The main purpose of this tool is to improve the use of artificial intelligence techniques in evaluating a student's understanding of a particular topic of study using concept maps. Here, we calculate the probability distribution of…
Descriptors: Artificial Intelligence, Concept Mapping, Teaching Methods, Student Evaluation
Benjamin D. Nye; Arthur C. Graesser; Xiangen Hu – Grantee Submission, 2014
AutoTutor is a natural language tutoring system that has produced learning gains across multiple domains (e.g., computer literacy, physics, critical thinking). In this paper, we review the development, key research findings, and systems that have evolved from AutoTutor. First, the rationale for developing AutoTutor is outlined and the advantages…
Descriptors: Intelligent Tutoring Systems, Natural Language Processing, Computer Software, Artificial Intelligence
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Benjamin D. Nye; Arthur C. Graesser; Xiangen Hu – International Journal of Artificial Intelligence in Education, 2014
AutoTutor is a natural language tutoring system that has produced learning gains across multiple domains (e.g., computer literacy, physics, critical thinking). In this paper, we review the development, key research findings, and systems that have evolved from AutoTutor. First, the rationale for developing AutoTutor is outlined and the advantages…
Descriptors: Intelligent Tutoring Systems, Natural Language Processing, Computer Software, Artificial Intelligence
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Barnes, Tiffany, Ed.; Chi, Min, Ed.; Feng, Mingyu, Ed. – International Educational Data Mining Society, 2016
The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…
Descriptors: Data Analysis, Evidence Based Practice, Inquiry, Science Instruction
Smith, Karl A. – Engineering Education, 1987
Differentiates between learning efficiency (enhancing the rate of learning) and learning effectiveness (enhancing the mastery and retention of facts, concepts, and relationships). Discusses some of the contributions of knowledge engineering to metalearning. Provides a concept map for constructing knowledge bases, along with some possible…
Descriptors: Artificial Intelligence, College Science, Concept Formation, Concept Mapping
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers