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Hosseini, Roya; Akhuseyinoglu, Kamil; Brusilovsky, Peter; Malmi, Lauri; Pollari-Malmi, Kerttu; Schunn, Christian; Sirkiä, Teemu – International Journal of Artificial Intelligence in Education, 2020
This research is focused on how to support students' acquisition of program construction skills through worked examples. Although examples have been consistently proven to be valuable for student's learning, the learning technology for computer science education lacks program construction examples with interactive elements that could engage…
Descriptors: Programming, Computer Science Education, Problem Solving, Learner Engagement
Price, Thomas W.; Dong, Yihuan; Zhi, Rui; Paaßen, Benjamin; Lytle, Nicholas; Cateté, Veronica; Barnes, Tiffany – International Journal of Artificial Intelligence in Education, 2019
In the domain of programming, a growing number of algorithms automatically generate data-driven, next-step hints that suggest how students should edit their code to resolve errors and make progress. While these hints have the potential to improve learning if done well, few evaluations have directly assessed or compared the quality of different…
Descriptors: Comparative Analysis, Programming Languages, Data Analysis, Evaluation Methods
Yazdanian, Ramtin; West, Robert; Dillenbourg, Pierre – International Journal of Artificial Intelligence in Education, 2021
The Fourth Industrial Revolution has considerably sped up the pace of skill changes in many professional domains, with scores of new skills emerging and many old skills moving towards obsolescence. For these domains, identifying the new necessary skills in a timely manner is a difficult task, where existing methods are inadequate. Understanding…
Descriptors: Electronic Learning, Personnel Selection, Computer Software, Computer Mediated Communication
Dermeval, Diego; Paiva, Ranilson; Bittencourt, Ig Ibert; Vassileva, Julita; Borges, Daniel – International Journal of Artificial Intelligence in Education, 2018
Authoring tools have been broadly used to design Intelligent Tutoring Systems (ITS). However, ITS community still lacks a current understanding of how authoring tools are used by non-programmer authors to design ITS. Hence, the objective of this work is to review how authoring tools have been supporting ITS design for non-programmer authors. In…
Descriptors: Intelligent Tutoring Systems, Programming, Computer Software, Evidence
Murray, Tom – International Journal of Artificial Intelligence in Education, 2016
Intelligent Tutoring Systems authoring tools are highly complex educational software applications used to produce highly complex software applications (i.e. ITSs). How should our assumptions about the target users (authors) impact the design of authoring tools? In this article I first reflect on the factors leading to my original 1999 article on…
Descriptors: Usability, Programming, Computer Software, Intelligent Tutoring Systems
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
Miller, L. D.; Soh, Leen-Kiat; Samal, Ashok; Nugent, Gwen – International Journal of Artificial Intelligence in Education, 2012
Learning objects (LOs) are digital or non-digital entities used for learning, education or training commonly stored in repositories searchable by their associated metadata. Unfortunately, based on the current standards, such metadata is often missing or incorrectly entered making search difficult or impossible. In this paper, we investigate…
Descriptors: Computer Science Education, Metadata, Internet, Artificial Intelligence
Lynch, Collin; Ashley, Kevin D.; Pinkwart, Niels; Aleven, Vincent – International Journal of Artificial Intelligence in Education, 2009
In this paper we consider prior definitions of the terms "ill-defined domain" and "ill-defined problem". We then present alternate definitions that better support research at the intersection of Artificial Intelligence and Education. In our view both problems and domains are ill-defined when essential concepts, relations, or criteria are un- or…
Descriptors: Definitions, Artificial Intelligence, Problem Solving, Educational Research
Baschera, Gian-Marco; Gross, Markus – International Journal of Artificial Intelligence in Education, 2010
We present an inference algorithm for perturbation models based on Poisson regression. The algorithm is designed to handle unclassified input with multiple errors described by independent mal-rules. This knowledge representation provides an intelligent tutoring system with local and global information about a student, such as error classification…
Descriptors: Foreign Countries, Spelling, Intelligent Tutoring Systems, Prediction
Aleven, Vincent; McLaren, Bruce M.; Sewall, Jonathan; Koedinger, Kenneth R. – International Journal of Artificial Intelligence in Education, 2009
The Cognitive Tutor Authoring Tools (CTAT) support creation of a novel type of tutors called example-tracing tutors. Unlike other types of ITSs (e.g., model-tracing tutors, constraint-based tutors), example-tracing tutors evaluate student behavior by flexibly comparing it against generalized examples of problem-solving behavior. Example-tracing…
Descriptors: Feedback (Response), Student Behavior, Intelligent Tutoring Systems, Problem Solving
Kazi, Hameedullah; Haddawy, Peter; Suebnukarn, Siriwan – International Journal of Artificial Intelligence in Education, 2009
In well-defined domains such as Physics, Mathematics, and Chemistry, solutions to a posed problem can objectively be classified as correct or incorrect. In ill-defined domains such as medicine, the classification of solutions to a patient problem as correct or incorrect is much more complex. Typical tutoring systems accept only a small set of…
Descriptors: Foreign Countries, Problem Based Learning, Problem Solving, Correlation
Blessing, Stephen B.; Gilbert, Stephen B.; Ourada, Stephen; Ritter, Steven – International Journal of Artificial Intelligence in Education, 2009
Intelligent Tutoring Systems (ITSs) that employ a model-tracing methodology have consistently shown their effectiveness. However, what evidently makes these tutors effective, the cognitive model embedded within them, has traditionally been difficult to create, requiring great expertise and time, both of which come at a cost. Furthermore, an…
Descriptors: Intelligent Tutoring Systems, Cognitive Processes, Models, Expertise
Hayashi, Yusuke; Bourdeau, Jacqueline; Mizoguchi, Riichiro – International Journal of Artificial Intelligence in Education, 2009
This paper describes the achievements of an innovative eight-year research program first introduced in Mizoguchi and Bourdeau (2000), which was aimed at building a theory-aware authoring system by using ontological engineering. To date, we have proposed OMNIBUS, an ontology that comprehensively covers different learning/instructional theories and…
Descriptors: Foreign Countries, Theory Practice Relationship, Engineering, Teaching Methods
Mitrovic, Antonija; Martin, Brent; Suraweera, Pramuditha; Zakharov, Konstantin; Milik, Nancy; Holland, Jay; McGuigan, Nicholas – International Journal of Artificial Intelligence in Education, 2009
Over the last decade, the Intelligent Computer Tutoring Group (ICTG) has implemented many successful constraint-based Intelligent Tutoring Systems (ITSs) in a variety of instructional domains. Our tutors have proven their effectiveness not only in controlled lab studies but also in real classrooms, and some of them have been commercialized.…
Descriptors: Foreign Countries, Investment, Intelligent Tutoring Systems, Artificial Intelligence
Ogan, Amy; Aleven, Vincent; Jones, Christopher – International Journal of Artificial Intelligence in Education, 2009
Most successes in intelligent tutoring systems have come in well-defined domains like algebra or physics. We investigate how to support students in acquiring ill-defined skills of intercultural competence using an online environment that employs clips of feature films from a target culture. To test the effectiveness of a set of attention-focusing…
Descriptors: Foreign Countries, Intelligent Tutoring Systems, Perspective Taking, Cultural Awareness