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Nguyen, Huy; Wang, Yeyu; Stamper, John; McLaren, Bruce M. – International Educational Data Mining Society, 2019
Knowledge components (KCs) define the underlying skill model of intelligent educational software, and they are critical to understanding and improving the efficacy of learning technology. In this research, we show how learning curve analysis is used to fit a KC model--one that was created after use of the learning technology--which can then be…
Descriptors: Middle School Students, Knowledge Representation, Models, Computer Games
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McCarthy, Kathryn S.; Roscoe, Rod D.; Likens, Aaron D.; McNamara, Danielle S. – Grantee Submission, 2019
This study investigated the effect of incorporating spelling and grammar checking tools within an automated writing tutoring system, Writing Pal. High school students (n = 119) wrote and revised six persuasive essays. After initial drafts, all students received formative feedback about writing strategies. Half of the participants were also given…
Descriptors: Spelling, Grammar, Automation, Writing Instruction
Lippert, Anne; Gatewood, Jessica; Cai, Zhiqiang; Graesser, Arthur C. – Grantee Submission, 2019
One out of six adults in the United States possesses low literacy skills. Many advocates believe that technology can pave the way for these adults to gain the skills that they desire. This article describes an adaptive intelligent tutoring system called AutoTutor that is designed to teach adults comprehension strategies across different levels of…
Descriptors: Intelligent Tutoring Systems, Educational Technology, Adult Literacy, Skill Development
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Saastamoinen, Kalle; Rissanen, Antti – International Baltic Symposium on Science and Technology Education, 2019
Conventional learning guidance systems are typically automated machines for creating teaching materials: quizzes, exercises, examinations etc. In the future, systems will also offer ease of use, attention to sociality, ability to adapt to the pupil's needs and skill levels, and time savings. Ease-of-use and adaptation can be sought using systems…
Descriptors: Teaching Methods, Intelligent Tutoring Systems, Artificial Intelligence, Usability
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Smith, E. Halle; Hollander, John; Graesser, Art C.; Sabatini, John; Hu, Xiangen – English Teaching, 2021
Facing the demands of the pandemic and distance learning, English learners require educational technologies that are accessible, engaging, and effective. Meeting these demands requires educational technology developers to consider learners' sociocultural contexts. Learning theories can be applied to meet individuals' needs to optimize chances for…
Descriptors: Reading Comprehension, English (Second Language), Second Language Learning, Second Language Instruction
Ruiqi Shen – ProQuest LLC, 2021
With the large demand for technology workers all around the world, more people are learning programming. Studies show that human tutoring is the most effective way to learn for novice programmers. However, problems such as the inaccessibility to physical classes, prohibitive costs, and the lack of educators may limit students' opportunities to…
Descriptors: MOOCs, Online Systems, Interactive Video, Computer Assisted Instruction
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Perikos, Isidoros; Grivokostopoulou, Foteini; Hatzilygeroudis, Ioannis – International Journal of Artificial Intelligence in Education, 2017
Logic as a knowledge representation and reasoning language is a fundamental topic of an Artificial Intelligence (AI) course and includes a number of sub-topics. One of them, which brings difficulties to students to deal with, is converting natural language (NL) sentences into first-order logic (FOL) formulas. To assist students to overcome those…
Descriptors: Intelligent Tutoring Systems, Feedback (Response), Natural Language Processing, Logical Thinking
Li, Haiying; Graesser, Art – Grantee Submission, 2017
This study investigated the impact of pedagogical agents' conversational formality on learning and engagement in a trialog-based intelligent tutoring system (ITS). Participants (N = 167) were randomly assigned into one of three conditions to learn summarization strategies with the conversational agents: (1) a "formal" condition in which…
Descriptors: Language Usage, Arousal Patterns, Reading Comprehension, Learner Engagement
Lujie Chen; Artur Dubrawski – Grantee Submission, 2017
We propose a data driven method for decomposing population level learning curve models into mutually exclusive distinctive groups each consisting of similar learning trajectories. We validate this method on six knowledge components from the log data from an online tutoring system ASSISTment. Preliminary analysis reveals interpretable patterns of…
Descriptors: Learning Trajectories, Learning Processes, Intelligent Tutoring Systems, Cluster Grouping
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Tzafilkou, Katerina; Protogeros, Nicolaos – European Educational Researcher, 2020
This study investigates students' mouse behavior during their interaction with a web-based experiential learning environment for Computer Science courses. The research focuses on the detection of correlations between the monitored mouse metrics and students' technology acceptance items of perceived usefulness and ease of use. Findings reveal…
Descriptors: Electronic Learning, Learning Analytics, Student Attitudes, Usability
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Haridas, Mithun; Gutjahr, Georg; Raman, Raghu; Ramaraju, Rudraraju; Nedungadi, Prema – Education and Information Technologies, 2020
In many rural Indian schools, English is a second language for teachers and students. Intelligent tutoring systems have good potential because they enable students to learn at their own pace, in an exploratory manner. This paper describes a 3-year longitudinal study of 2123 Indian students who used the intelligent tutoring system, AmritaITS. The…
Descriptors: Foreign Countries, Predictor Variables, English (Second Language), Second Language Learning
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Turkmen, Gamze; Caner, Sonay – Turkish Online Journal of Distance Education, 2020
This study aims to provide a comprehensive and in-depth investigation of the debugging process in programming teaching in terms of cognitive and metacognitive aspects, based on programming students who demonstrate low, medium, and high programming performance and to propose instructional strategies for scaffolding novice learners in an effective…
Descriptors: Programming, Novices, Electronic Learning, Troubleshooting
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Nofriansyah, Dicky; Ganefri; Ridwan – International Journal of Evaluation and Research in Education, 2020
This research focused on the development a new learning model in Vocational Education to answer the challenges of this Industrial Revolution 4.0 era. The problem identified was the lack of learning outcomes, especially subjects oriented to software engineering for information systems students in particular and other computer science seen in the…
Descriptors: Foreign Countries, Computer Software, Engineering, Vocational Education
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Lin, Michael Pin-Chuan; Chang, Daniel – Educational Technology & Society, 2020
In the present study, we developed a chatbot that helps teachers to deliver writing instructions. By working with the chatbot, the post-secondary writers developed a thesis statement for their argumentative essay outlines, and the chatbot helped the writers to refine their peer review feedback. We conducted a preliminary analysis of the effect of…
Descriptors: Writing Skills, Instructional Effectiveness, Educational Technology, Intelligent Tutoring Systems
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Meng, Qingquan; Jia, Jiyou; Zhang, Zhiyong – Interactive Technology and Smart Education, 2020
Purpose: The purpose of this study is to verify the effect of smart pedagogy to facilitate the high order thinking skills of students and to provide the design suggestion of curriculum and intelligent tutoring systems in smart education. Design/methodology/approach: A smart pedagogy framework was designed. The quasi-experiment was conducted in a…
Descriptors: Thinking Skills, Instructional Effectiveness, Technology Integration, Intelligent Tutoring Systems
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