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Showing 166 to 180 of 325 results Save | Export
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Vajjala, Sowmya – International Journal of Artificial Intelligence in Education, 2018
Automatic essay scoring (AES) refers to the process of scoring free text responses to given prompts, considering human grader scores as the gold standard. Writing such essays is an essential component of many language and aptitude exams. Hence, AES became an active and established area of research, and there are many proprietary systems used in…
Descriptors: Computer Software, Essays, Writing Evaluation, Scoring
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McCarthy, Kathryn S.; Likens, Aaron D.; Johnson, Amy M.; Guerrero, Tricia A.; McNamara, Danielle S. – International Journal of Artificial Intelligence in Education, 2018
Research suggests that promoting metacognitive awareness can increase performance in, and learning from, intelligent tutoring systems (ITSs). The current work examines the effects of two metacognitive prompts within iSTART, a reading comprehension strategy ITS in which students practice writing quality self-explanations. In addition to comparing…
Descriptors: Metacognition, Difficulty Level, Prompting, Intelligent Tutoring Systems
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Omheni, Nizar; Kalboussi, Anis; Mazhoud, Omar; Kacem, Ahmed Hadj – International Journal of Artificial Intelligence in Education, 2017
Researchers in education are interested in modeling of learner's profile and adapt their learning experiences accordingly. When learners read and interact with their reading materials, they do unconscious practices like annotations which may be, a key feature of their personalities. Annotation activity requires readers to be active, to think…
Descriptors: Personality Traits, Learning Experience, Notetaking, Critical Reading
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Harley, Jason M.; Lajoie, Susanne P.; Frasson, Claude; Hall, Nathan C. – International Journal of Artificial Intelligence in Education, 2017
A growing body of work on intelligent tutoring systems, affective computing, and artificial intelligence in education is exploring creative, technology-driven approaches to enhance learners' experience of adaptive, positively-valenced emotions while interacting with advanced learning technologies. Despite this, there has been no published work to…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Technology Uses in Education, Psychological Patterns
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Fratamico, Lauren; Conati, Cristina; Kardan, Samad; Roll, Ido – International Journal of Artificial Intelligence in Education, 2017
Interactive simulations can facilitate inquiry learning. However, similarly to other Exploratory Learning Environments, students may not always learn effectively in these unstructured environments. Thus, providing adaptive support has great potential to help improve student learning with these rich activities. Providing adaptive support requires a…
Descriptors: Computer Simulation, Models, Educational Environment, Comparative Analysis
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Rau, Martina Angela – International Journal of Artificial Intelligence in Education, 2017
Traditional knowledge-component models describe students' content knowledge (e.g., their ability to carry out problem-solving procedures or their ability to reason about a concept). In many STEM domains, instruction uses multiple visual representations such as graphs, figures, and diagrams. The use of visual representations implies a…
Descriptors: Knowledge Representation, Models, Competence, Learning Processes
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Gonzalez, Avelino J.; Hollister, James R.; DeMara, Ronald F.; Leigh, Jason; Lanman, Brandan; Lee, Sang-Yoon; Parker, Shane; Walls, Christopher; Parker, Jeanne; Wong, Josiah; Barham, Clayton; Wilder, Bryan – International Journal of Artificial Intelligence in Education, 2017
This paper describes an interactive museum exhibit featuring an avatar of Alan Turing that informs museum visitors about artificial intelligence and Turing's seminal Turing Test for machine intelligence. The objective of the exhibit is to engage and motivate visiting children in the hope of sparking an interest in them about computer science and…
Descriptors: Artificial Intelligence, Informal Education, Science Education, Interaction
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Stevenson, Claire E. – International Journal of Artificial Intelligence in Education, 2017
This study contrasted the effects of tutoring, multiple try and no feedback on children's progression in analogy solving and examined individual differences herein. Feedback that includes additional hints or explanations leads to the greatest learning gains in adults. However, children process feedback differently from adults and effective…
Descriptors: Tutoring, Feedback (Response), Children, Short Term Memory
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Ramachandran, Lakshmi; Gehringer, Edward F.; Yadav, Ravi K. – International Journal of Artificial Intelligence in Education, 2017
A "review" is textual feedback provided by a reviewer to the author of a submitted version. Peer reviews are used in academic publishing and in education to assess student work. While reviews are important to e-commerce sites like Amazon and e-bay, which use them to assess the quality of products and services, our work focuses on…
Descriptors: Natural Language Processing, Peer Evaluation, Educational Quality, Meta Analysis
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Wiese, Eliane S.; Koedinger, Kenneth R. – International Journal of Artificial Intelligence in Education, 2017
This paper proposes "grounded feedback" as a way to provide implicit verification when students are working with a novel representation. In grounded feedback, students' responses are in the target, to-be-learned representation, and those responses are reflected in a more-accessible linked representation that is intrinsic to the domain.…
Descriptors: Instructional Design, Feedback (Response), Evaluation Criteria, Instructional Effectiveness
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Goldin, Ilya; Narciss, Susanne; Foltz, Peter; Bauer, Malcolm – International Journal of Artificial Intelligence in Education, 2017
Formative feedback is well known as a key factor in influencing learning. Modern interactive learning environments provide a broad range of ways to provide feedback to students as well as new tools to understand feedback and its relation to various learning outcomes. This issue focuses on the role of formative feedback through a lens of how…
Descriptors: Formative Evaluation, Feedback (Response), Interaction, Technology Uses in Education
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Green, Nancy L. – International Journal of Artificial Intelligence in Education, 2017
This paper describes an educational argument modeling system, GAIL (Genetics Argumentation Inquiry Learning). Using GAIL's graphical interface, learners can select from possible argument content elements (hypotheses, data, etc.) displayed on the screen with which to construct argument diagrams. Unlike previous systems, GAIL uses domain-independent…
Descriptors: Persuasive Discourse, Feedback (Response), Inquiry, Computer Assisted Instruction
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Nguyen, Huy; Xiong, Wenting; Litman, Diane – International Journal of Artificial Intelligence in Education, 2017
A peer-review system that automatically evaluates and provides formative feedback on free-text feedback comments of students was iteratively designed and evaluated in college and high-school classrooms. Classroom assignments required students to write paper drafts and submit them to a peer-review system. When student peers later submitted feedback…
Descriptors: Computer Uses in Education, Computer Mediated Communication, Feedback (Response), Peer Evaluation
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Easterday, Matthew W.; Rees Lewis, Daniel; Gerber, Elizabeth M. – International Journal of Artificial Intelligence in Education, 2017
Intelligent tutors based on expert systems often struggle to provide formative feedback on complex, ill-defined problems where answers are unknown. Hybrid crowdsourcing systems that combine the intelligence of multiple novices in face-to-face settings might provide an alternate approach for providing intelligent formative feedback. The purpose of…
Descriptors: Intelligent Tutoring Systems, Formative Evaluation, Feedback (Response), Novices
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Cutumisu, Maria; Blair, Kristen P.; Chin, Doris B.; Schwartz, Daniel L. – International Journal of Artificial Intelligence in Education, 2017
We introduce a choice-based assessment strategy that measures students' choices to seek constructive feedback and to revise their work. We present the feedback system of a game we designed to assess whether students choose positive or negative feedback and choose to revise their posters in the context of a poster design task, where they learn…
Descriptors: Student Evaluation, Feedback (Response), Games, Task Analysis
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