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Rebecka Weegar; Peter Idestam-Almquist – International Journal of Artificial Intelligence in Education, 2024
Machine learning methods can be used to reduce the manual workload in exam grading, making it possible for teachers to spend more time on other tasks. However, when it comes to grading exams, fully eliminating manual work is not yet possible even with very accurate automated grading, as any grading mistakes could have significant consequences for…
Descriptors: Grading, Computer Assisted Testing, Introductory Courses, Computer Science Education
Leitner, Maxyn; Greenwald, Eric; Wang, Ning; Montgomery, Ryan; Merchant, Chirag – International Journal of Artificial Intelligence in Education, 2023
Artificial Intelligence (AI) permeates every aspect of our daily lives and is no longer a subject reserved for a select few in higher education but is essential knowledge that our youth need for the future. Much is unknown about the level of AI knowledge that is age and developmentally appropriate for high school, let alone about how to teach AI…
Descriptors: Instructional Design, Game Based Learning, High School Students, Artificial Intelligence
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
Touretzky, David; Gardner-McCune, Christina; Seehorn, Deborah – International Journal of Artificial Intelligence in Education, 2023
This article provides an in-depth look at how K-12 students should be introduced to Machine Learning and the knowledge and skills they will develop as a result. We begin with an overview of the AI4K12 Initiative, which is developing national guidelines for teaching AI in K-12, and briefly discuss each of the "Five Big Ideas in AI" that…
Descriptors: Electronic Learning, Artificial Intelligence, Elementary School Students, Secondary School Students
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
Behera, Ardhendu; Matthew, Peter; Keidel, Alexander; Vangorp, Peter; Fang, Hui; Canning, Susan – International Journal of Artificial Intelligence in Education, 2020
Learning involves a substantial amount of cognitive, social and emotional states. Therefore, recognizing and understanding these states in the context of learning is key in designing informed interventions and addressing the needs of the individual student to provide personalized education. In this paper, we explore the automatic detection of…
Descriptors: Nonverbal Communication, Intelligent Tutoring Systems, Eye Movements, Learning Processes
Gerdes, Alex; Heeren, Bastiaan; Jeuring, Johan; van Binsbergen, L. Thomas – International Journal of Artificial Intelligence in Education, 2017
Ask-Elle is a tutor for learning the higher-order, strongly-typed functional programming language Haskell. It supports the stepwise development of Haskell programs by verifying the correctness of incomplete programs, and by providing hints. Programming exercises are added to Ask-Elle by providing a task description for the exercise, one or more…
Descriptors: Intelligent Tutoring Systems, Automation, Feedback (Response), Programming Languages
Howard, Cynthia; Jordan, Pamela; Di Eugenio, Barbara; Katz, Sandra – International Journal of Artificial Intelligence in Education, 2017
Despite a growing need for educational tools that support students at the earliest phases of undergraduate Computer Science (CS) curricula, relatively few such tools exist--the majority being Intelligent Tutoring Systems. Since peer interactions more readily give rise to challenges and negotiations, another way in which students can become more…
Descriptors: Computer Science Education, Undergraduate Study, Intelligent Tutoring Systems, Artificial Intelligence
Westerfield, Giles; Mitrovic, Antonija; Billinghurst, Mark – International Journal of Artificial Intelligence in Education, 2015
We investigate the combination of Augmented Reality (AR) with Intelligent Tutoring Systems (ITS) to assist with training for manual assembly tasks. Our approach combines AR graphics with adaptive guidance from the ITS to provide a more effective learning experience. We have developed a modular software framework for intelligent AR training…
Descriptors: Intelligent Tutoring Systems, Computer Simulation, Computer Science Education, Instructional Effectiveness
Mostafavi, Behrooz; Barnes, Tiffany – International Journal of Artificial Intelligence in Education, 2017
Deductive logic is essential to a complete understanding of computer science concepts, and is thus fundamental to computer science education. Intelligent tutoring systems with individualized instruction have been shown to increase learning gains. We seek to improve the way deductive logic is taught in computer science by developing an intelligent,…
Descriptors: Artificial Intelligence, Problem Solving, Educational Technology, Technology Uses in Education
Roll, Ido; Russell, Daniel M.; Gaševic, Dragan – International Journal of Artificial Intelligence in Education, 2018
Learning at Scale is a fast growing field that affects formal, informal, and workplace education. Highly interdisciplinary, it builds on solid foundations in the learning sciences, computer science, education, and the social sciences. We define learning at scale as the study of the technologies, pedagogies, analyses, and theories of learning and…
Descriptors: Interdisciplinary Approach, Computer Science Education, Social Sciences, Learning
Paquette, Luc; Lebeau, Jean-François; Beaulieu, Gabriel; Mayers, André – International Journal of Artificial Intelligence in Education, 2015
Model-tracing tutors (MTTs) have proven effective for the tutoring of well-defined tasks, but the pedagogical interventions they produce are limited and usually require the inclusion of pedagogical content, such as text message templates, in the model of the task. The capability to generate pedagogical content would be beneficial to MTT…
Descriptors: Intelligent Tutoring Systems, Intervention, Instruction, Automation
Broisin, Julien; Venant, Rémi; Vidal, Philippe – International Journal of Artificial Intelligence in Education, 2017
Remote practical activities have been demonstrated to be efficient when learners come to acquire inquiry skills. In computer science education, virtualization technologies are gaining popularity as this technological advance enables instructors to implement realistic practical learning activities, and learners to engage in authentic and…
Descriptors: Laboratories, Artificial Intelligence, Computer Science Education, Scaffolding (Teaching Technique)
Wiggins, Joseph B.; Grafsgaard, Joseph F.; Boyer, Kristy Elizabeth; Wiebe, Eric N.; Lester, James C. – International Journal of Artificial Intelligence in Education, 2017
In recent years, significant advances have been made in intelligent tutoring systems, and these advances hold great promise for adaptively supporting computer science (CS) learning. In particular, tutorial dialogue systems that engage students in natural language dialogue can create rich, adaptive interactions. A promising approach to increasing…
Descriptors: Intelligent Tutoring Systems, Self Efficacy, Computer Science Education, Dialogs (Language)
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
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