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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
Matsuda, Noboru – International Journal of Artificial Intelligence in Education, 2022
This paper demonstrates that a teachable agent (TA) can play a dual role in an online learning environment (OLE) for learning by teaching--the teachable agent working as a synthetic peer for students to learn by teaching and as an interactive tool for cognitive task analysis when authoring an OLE for learning by teaching. We have developed an OLE…
Descriptors: Artificial Intelligence, Teaching Methods, Intelligent Tutoring Systems, Feedback (Response)
Jennings, Jay; Muldner, Kasia – International Journal of Artificial Intelligence in Education, 2021
When students are first learning to program, they not only have to learn to write programs, but also how to trace them. Code tracing involves stepping through a program step-by-step, which helps to predict the output of the program and identify bugs. Students routinely struggle with this activity, as evidenced by prior work and our own experiences…
Descriptors: Scaffolding (Teaching Technique), Tutors, Tutoring, Programming
Albó, Laia; Barria-Pineda, Jordan; Brusilovsky, Peter; Hernández-Leo, Davinia – International Journal of Artificial Intelligence in Education, 2022
Over the last 10 years, learning analytics have provided educators with both dashboards and tools to understand student behaviors within specific technological environments. However, there is a lack of work to support educators in making data-informed design decisions when designing a blended course and planning appropriate learning activities. In…
Descriptors: Learning Analytics, Visual Aids, Design, Learning Activities
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
Bosch, Nigel; D'Mello, Sidney – International Journal of Artificial Intelligence in Education, 2017
Novice students (N = 99) participated in a lab study in which they learned the fundamentals of computer programming in Python using a self-paced computerized learning environment involving a 25-min scaffolded learning phase and a 10-min unscaffolded fadeout phase. Students provided affect judgments at approximately 100 points (every 15 s) over the…
Descriptors: Employees, Programming, Computers, Novices
Rivers, Kelly; Koedinger, Kenneth R. – International Journal of Artificial Intelligence in Education, 2017
To provide personalized help to students who are working on code-writing problems, we introduce a data-driven tutoring system, ITAP (Intelligent Teaching Assistant for Programming). ITAP uses state abstraction, path construction, and state reification to automatically generate personalized hints for students, even when given states that have not…
Descriptors: Programming, Coding, Computers, Data
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
Weragama, Dinesha; Reye, Jim – International Journal of Artificial Intelligence in Education, 2014
Programming is a subject that many beginning students find difficult. The PHP Intelligent Tutoring System (PHP ITS) has been designed with the aim of making it easier for novices to learn the PHP language in order to develop dynamic web pages. Programming requires practice. This makes it necessary to include practical exercises in any ITS that…
Descriptors: Intelligent Tutoring Systems, Programming, Computer Science Education, Programming Languages
Devedzic, Vladan – International Journal of Artificial Intelligence in Education, 2016
If you ask me "Will Semantic Web 'ever' happen, in general, and specifically in education?", the best answer I can give you is "I don't know," but I know that today we are still far away from the hopes that I had when I wrote my paper "Education and The Semantic Web" (Devedzic 2004) more than 10 years ago. Much of the…
Descriptors: Web 2.0 Technologies, Semantics, Web Based Instruction, Visual Aids
Matsuda, Noboru; Cohen, William W.; Koedinger, Kenneth R. – International Journal of Artificial Intelligence in Education, 2015
SimStudent is a machine-learning agent initially developed to help novice authors to create cognitive tutors without heavy programming. Integrated into an existing suite of software tools called Cognitive Tutor Authoring Tools (CTAT), SimStudent helps authors to create an expert model for a cognitive tutor by tutoring SimStudent on how to solve…
Descriptors: Intelligent Tutoring Systems, Programming, Computer Simulation, Models
Aleven, Vincent; McLaren, Bruce M.; Sewall, Jonathan; van Velsen, Martin; Popescu, Octav; Demi, Sandra; Ringenberg, Michael; Koedinger, Kenneth R. – International Journal of Artificial Intelligence in Education, 2016
In 2009, we reported on a new Intelligent Tutoring Systems (ITS) technology, example-tracing tutors, that can be built without programming using the Cognitive Tutor Authoring Tools (CTAT). Creating example-tracing tutors was shown to be 4-8 times as cost-effective as estimates for ITS development from the literature. Since 2009, CTAT and its…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Programming, Educational Technology
Sottilare, Robert A.; Shawn Burke, C.; Salas, Eduardo; Sinatra, Anne M.; Johnston, Joan H.; Gilbert, Stephen B. – International Journal of Artificial Intelligence in Education, 2018
The goal of this research was the development of a practical architecture for the computer-based tutoring of teams. This article examines the relationship of team behaviors as antecedents to successful team performance and learning during adaptive instruction guided by Intelligent Tutoring Systems (ITSs). Adaptive instruction is a training or…
Descriptors: Meta Analysis, Teaching Methods, Teamwork, Outcomes of Education
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
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