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Heck, Tanja; Meurers, Detmar; Nuxoll, Florian – Research-publishing.net, 2022
Foreign language teaching achieves best learning outcomes when individual differences of learners are taken into account. While it is difficult for teachers to support internal differentiation in the classroom, digital tools can adaptively propose individual learning paths through activities so that students can practice with appropriately…
Descriptors: Intelligent Tutoring Systems, Outcomes of Education, Second Language Learning, Second Language Instruction
Joe Olsen; Amy Adair; Janice Gobert; Michael Sao Pedro; Mariel O'Brien – Grantee Submission, 2022
Many national science frameworks (e.g., Next Generation Science Standards) argue that developing mathematical modeling competencies is critical for students' deep understanding of science. However, science teachers may be unprepared to assess these competencies. We are addressing this need by developing virtual lab performance assessments that…
Descriptors: Mathematical Models, Intelligent Tutoring Systems, Performance Based Assessment, Data Collection
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Doroudi, Shayan; Aleven, Vincent; Brunskill, Emma – International Journal of Artificial Intelligence in Education, 2019
Since the 1960s, researchers have been trying to optimize the sequencing of instructional activities using the tools of reinforcement learning (RL) and sequential decision making under uncertainty. Many researchers have realized that reinforcement learning provides a natural framework for optimal instructional sequencing given a particular model…
Descriptors: Reinforcement, Learning Processes, Sequential Learning, Decision Making
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Taub, Michelle; Azevedo, Roger – International Journal of Artificial Intelligence in Education, 2019
The goal of this study was to use eye-tracking and log-file data to investigate the impact of prior knowledge on college students' (N = 194, with a subset of n = 30 for eye tracking and sequence mining analyses) fixations on (i.e., looking at) self-regulated learning-related areas of interest (i.e., specific locations on the interface) and on the…
Descriptors: Prior Learning, Eye Movements, Metacognition, Learning Processes
Cai, Zhiqiang; Hu, Xiangen; Graesser, Arthur C. – Grantee Submission, 2019
Conversational Intelligent Tutoring Systems (ITSs) are expensive to develop. While simple online courseware could be easily authored by teachers, the authoring of conversational ITSs usually involves a team of experts with different expertise, including domain experts, linguists, instruction designers, programmers, artists, computer scientists,…
Descriptors: Programming, Intelligent Tutoring Systems, Courseware, Educational Technology
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Zhang, Chuankai; Huang, Yanzun; Wang, Jingyu; Lu, Dongyang; Fang, Weiqi; Stamper, John; Fancsali, Stephen; Holstein, Kenneth; Aleven, Vincent – International Educational Data Mining Society, 2019
"Wheel spinning" is the phenomenon in which a student fails to master a Knowledge Component (KC), despite significant practice. Ideally, an intelligent tutoring system would detect this phenomenon early, so that the system or a teacher could try alternative instructional strategies. Prior work has put forward several criteria for wheel…
Descriptors: Identification, Intelligent Tutoring Systems, Academic Failure, Criteria
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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
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Cheng, Li; Umapathy, Karthikeyan; Rehman, Muhammad; Ritzhaupt, Albert; Antonyan, Kristine; Shidfar, Poorya; Nichols, James; Lee, Minyoung; Abramowitz, Brian – Journal of Interactive Learning Research, 2023
The purpose of this research study is to design, develop, and validate an instrument for measuring undergraduate students' conceptions of artificial intelligence in education. Following systematic procedures, our team created a conceptual framework through an extant literature review and used it to create an initial item pool of 48-items across…
Descriptors: Undergraduate Students, Knowledge Level, Artificial Intelligence, Technology Uses in Education
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Lijuan Feng – Journal of Educational Computing Research, 2025
This study investigates the impact of AI-assisted language learning (AIAL) strategies on cognitive load and learning outcomes in the context of language acquisition. Specifically, the study explores three distinct AIAL strategies: personalized feedback and adaptive learning, interactive exercises with speech recognition, and intelligent tutoring…
Descriptors: Artificial Intelligence, Computer Assisted Instruction, Second Language Learning, Second Language Instruction
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Viktor Wang, Editor – IGI Global, 2025
Artificial Intelligence (AI) integration in andragogical education offers significant enhancements to the learning experience for adult learners. By utilizing AI-powered platforms, instructors can provide personalized learning paths that adapt to the unique needs, interests, and goals of each individual. These systems can analyze performance data…
Descriptors: Andragogy, Artificial Intelligence, Computer Software, Technology Integration
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Morakinyo Akintolu; Akinpelu A. Oyekunle – Journal of Educators Online, 2025
This paper provides a comprehensive overview of the research on the application of artificial intelligence (AI) in primary education to explore its potential to enhance teaching and learning processes. Through a systematic review of the relevant literature, this study identifies key areas in which AI can significantly impact primary education and…
Descriptors: Data Analysis, Learning Analytics, Artificial Intelligence, Computer Software
Rachel Schechter; Michaela Gulemetova; Colin Ackerman; Laura Janakiefski – Online Submission, 2025
This quasi-experimental study examined the impact of Coursemojo's AI-powered teaching platform on sixth-grade English Language Arts achievement in a large, diverse Tennessee school district during the 2024-2025 school year. The study involved 2,203 students across twelve schools, with 1,017 students using Coursemojo and 1,186 serving as comparison…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Technology, English Instruction
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Kai Guo; Yuanke Li; Yongyan Li; Samuel Kai Wah Chu – Education and Information Technologies, 2024
Despite growing interest in exploring the application of chatbots in language education, studies on the process of chatbot-assisted language learning are scant. This qualitative study uses activity theory to understand how English as a foreign language students engage with a chatbot, Argumate, when composing argumentative essays. Five Chinese…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Artificial Intelligence
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Talan, Tarik – International Journal of Research in Education and Science, 2021
The aim of this study is to examine the studies in the literature on the use of artificial intelligence in education in terms of its bibliometric properties. The Web of Science (WoS) database was used to collect the data. Various keywords were used to search the literature, and a total of 2,686 publications on the subject published between…
Descriptors: Artificial Intelligence, Bibliometrics, Teaching Methods, Technology Uses in Education
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Rogerson-Revell, Pamela M. – RELC Journal: A Journal of Language Teaching and Research, 2021
This viewpoint essay considers the current status of computer-assisted pronunciation training (CAPT) before examining some of the current issues and future directions in the field. The underlying premise is the pedagogic potential of CAPT systems and resources for teaching and learning, and the need for greater synergy between technological design…
Descriptors: Computer Assisted Instruction, Pronunciation Instruction, Individualized Instruction, Feedback (Response)
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