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Allen, Laura K.; Jacovina, Matthew E.; McNamara, Danielle S. – Grantee Submission, 2016
The development of strong writing skills is a critical (and somewhat obvious) goal within the classroom. Individuals across the world are now expected to reach a high level of writing proficiency to achieve success in both academic settings and the workplace (Geiser & Studley, 2001; Powell, 2009; Sharp, 2007). Unfortunately, strong writing…
Descriptors: Writing Skills, Writing Instruction, Writing Strategies, Teaching Methods
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Rau, Martina A. – International Educational Data Mining Society, 2016
To succeed in STEM, students need to connect visual representations to domain-relevant concepts, which is a difficult task for them. Prior research shows that physical representations (that students manipulate with their hands) and virtual representations (that they manipulate on a computer) have complementary advantages for conceptual learning.…
Descriptors: Visual Aids, Manipulative Materials, STEM Education, Concept Formation
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Lehman, Blair; D'Mello, Sidney; Strain, Amber; Mills, Caitlin; Gross, Melissa; Dobbins, Allyson; Wallace, Patricia; Millis, Keith; Graesser, Art – International Journal of Artificial Intelligence in Education, 2013
Cognitive disequilibrium and its affiliated affective state of confusion have been found to positively correlate with learning, presumably due to the effortful cognitive activities that accompany their experience. Although confusion naturally occurs in several learning contexts, we hypothesize that it can be induced and scaffolded to increase…
Descriptors: Psychological Patterns, Undergraduate Students, Intelligent Tutoring Systems, Learning
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Rouhani, Saeed; Mirhosseini, Seyed Vahid – International Journal of Web-Based Learning and Teaching Technologies, 2015
Today, several educational portals established by organizations to enhance web E-learning. Intelligence agent's usage is necessary to improve the system's quality and cover limitations such as face-to-face relation. In this research, after finding two main approaches in this field that are fundamental use of intelligent agents in systems design…
Descriptors: Intelligent Tutoring Systems, Electronic Learning, Integrated Learning Systems, Computer Software Evaluation
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Jackson, Tanner; Boonthum-Denecke, Chutima; McNamara, Danielle – Journal of Interactive Learning Research, 2015
Intelligent Tutoring Systems (ITSs) are situated in a potential struggle between effective pedagogy and system enjoyment and engagement. iSTART (Interactive Strategy Training for Active Reading and Thinking), a reading strategy tutoring system in which students practice generating self-explanations and using reading strategies, employs two devices…
Descriptors: Intelligent Tutoring Systems, Educational Technology, Reading Strategies, Tutoring
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Jackson, G. Tanner; Boonthum-Denecke, Chutima; McNamara, Danielle S. – Grantee Submission, 2015
Intelligent Tutoring Systems (ITSs) are situated in a potential struggle between effective pedagogy and system enjoyment and engagement. iSTART, a reading strategy tutoring system in which students practice generating self-explanations and using reading strategies, employs two devices to engage the user. The first is natural language processing…
Descriptors: Natural Language Processing, Feedback (Response), Intelligent Tutoring Systems, Reading Strategies
Klingler, Severin; Käser, Tanja; Solenthaler, Barbara; Gross, Markus – International Educational Data Mining Society, 2015
Modeling student knowledge is a fundamental task of an intelligent tutoring system. A popular approach for modeling the acquisition of knowledge is Bayesian Knowledge Tracing (BKT). Various extensions to the original BKT model have been proposed, among them two novel models that unify BKT and Item Response Theory (IRT). Latent Factor Knowledge…
Descriptors: Intelligent Tutoring Systems, Knowledge Level, Item Response Theory, Prediction
Van Inwegen, Eric G.; Adjei, Seth A.; Wang, Yan; Heffernan, Neil T. – International Educational Data Mining Society, 2015
User modelling algorithms such as Performance Factors Analysis and Knowledge Tracing seek to determine a student's knowledge state by analyzing (among other features) right and wrong answers. Anyone who has ever graded an assignment by hand knows that some answers are "more wrong" than others; i.e. they display less of an understanding…
Descriptors: Knowledge Level, Performance Factors, Error Patterns, Mathematics
Matthew E. Jacovina; Erica L. Snow; G. Tanner Jackson; Danielle S. McNamara – Grantee Submission, 2015
To optimize the benefits of game-based practice within Intelligent Tutoring Systems (ITSs), researchers examine how game features influence students' motivation and performance. The current study examined the influence of game features and individual differences (reading ability and learning intentions) on motivation and performance. Participants…
Descriptors: Game Based Learning, Intelligent Tutoring Systems, Learning Motivation, Performance
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Lee, Nancy; Hong, Eunsook – IAFOR Journal of Education, 2017
The study described here explored the differential effects of two learning strategies, self-explanation and reading questions and answers, on learning the computer programming language JavaScript. Students' test performance and perceptions of effectiveness toward the two strategies were examined. An online interactive tutorial instruction…
Descriptors: Computer Science Education, Programming, Introductory Courses, High School Students
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Xin, Yan Ping; Tzur, Ron; Hord, Casey; Liu, Jia; Park, Joo Young; Si, Luo – Learning Disability Quarterly, 2017
The Common Core Mathematics Standards have raised expectations for schools and students in the United States. These standards demand much deeper content knowledge from teachers of mathematics and their students. Given the increasingly diverse student population in today's classrooms and shortage of qualified special education teachers,…
Descriptors: Intelligent Tutoring Systems, Computer Assisted Instruction, Mathematics Instruction, Learning Disabilities
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Michalenko, Joshua J.; Lan, Andrew S.; Waters, Andrew E.; Grimaldi, Philip J.; Baraniuk, Richard G. – International Educational Data Mining Society, 2017
An important, yet largely unstudied problem in student data analysis is to detect "misconceptions" from students' responses to "open-response" questions. Misconception detection enables instructors to deliver more targeted feedback on the misconceptions exhibited by many students in their class, thus improving the quality of…
Descriptors: Data Analysis, Misconceptions, Student Attitudes, Feedback (Response)
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Hooshyar, Danial; Ahmad, Rodina Binti; Yousefi, Moslem; Fathi, Moein; Abdollahi, Abbas; Horng, Shi-Jinn; Lim, Heuiseok – Educational Technology Research and Development, 2016
Nowadays, intelligent tutoring systems are considered an effective research tool for learning systems and problem-solving skill improvement. Nonetheless, such individualized systems may cause students to lose learning motivation when interaction and timely guidance are lacking. In order to address this problem, a solution-based intelligent…
Descriptors: Intelligent Tutoring Systems, Technology Integration, Educational Games, Formative Evaluation
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Crossley, Scott; Ocumpaugh, Jaclyn; Labrum, Matthew; Bradfield, Franklin; Dascalu, Mihai; Baker, Ryan S. – International Educational Data Mining Society, 2018
A number of studies have demonstrated strong links between students' language features (as found in spoken and written production) and their math performance. However, no studies have examined links between the students' language features and measures of their Math Identity. This project extends prior studies that use natural language processing…
Descriptors: Correlation, Speech Communication, Written Language, Mathematics Achievement
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Troussas, Christos; Virvou, Maria; Alepis, Efthimios – Informatics in Education, 2014
This paper proposes a student-oriented approach tailored to effective collaboration between students using mobile phones for language learning within the life cycle of an intelligent tutoring system. For this reason, in this research, a prototype mobile application has been developed for multiple language learning that incorporates intelligence in…
Descriptors: Cooperative Learning, Group Dynamics, Interaction, Intelligent Tutoring Systems
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