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Alshehri, Mohammad; Alamri, Ahmed; Cristea, Alexandra I.; Stewart, Craig D. – International Journal of Artificial Intelligence in Education, 2021
Since their 'official' emergence in 2012 (Gardner and Brooks 2018), massive open online courses (MOOCs) have been growing rapidly. They offer low-cost education for both students and content providers; however, currently there is a very low level of course purchasing (less than 1% of the total number of enrolled students on a given online course…
Descriptors: Instructional Design, Online Courses, Consumer Economics, Student Behavior
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Geden, Michael; Emerson, Andrew; Carpenter, Dan; Rowe, Jonathan; Azevedo, Roger; Lester, James – International Journal of Artificial Intelligence in Education, 2021
Game-based learning environments are designed to provide effective and engaging learning experiences for students. Predictive student models use trace data extracted from students' in-game learning behaviors to unobtrusively generate early assessments of student knowledge and skills, equipping game-based learning environments with the capacity to…
Descriptors: Game Based Learning, Middle School Students, Microbiology, Secondary School Science
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Lodder, Josje; Heeren, Bastiaan; Jeuring, Johan; Neijenhuis, Wendy – International Journal of Artificial Intelligence in Education, 2021
This paper describes LOGAX, an interactive tutoring tool that gives hints and feedback to a student who stepwise constructs a Hilbert-style axiomatic proof in propositional logic. LOGAX generates proofs to calculate hints and feedback. We compare these generated proofs with expert proofs and student solutions, and conclude that the quality of the…
Descriptors: Intelligent Tutoring Systems, Cues, Feedback (Response), Mathematical Logic
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Deane, Paul; Wilson, Joshua; Zhang, Mo; Li, Chen; van Rijn, Peter; Guo, Hongwen; Roth, Amanda; Winchester, Eowyn; Richter, Theresa – International Journal of Artificial Intelligence in Education, 2021
Educators need actionable information about student progress during the school year. This paper explores an approach to this problem in the writing domain that combines three measurement approaches intended for use in interim-assessment fashion: scenario-based assessments (SBAs), to simulate authentic classroom tasks, automated writing evaluation…
Descriptors: Vignettes, Writing Evaluation, Writing Improvement, Progress Monitoring
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Lawson, Alyssa P.; Mayer, Richard E.; Adamo-Villani, Nicoletta; Benes, Bedrich; Lei, Xingyu; Cheng, Justin – International Journal of Artificial Intelligence in Education, 2021
There has been much research on the effectiveness of animated pedagogical agents in an educational context, however there is little research about how the emotions they display contribute to a learner's understanding of the lesson. The positivity principle suggests that learners should learn better from instructors with positive emotions compared…
Descriptors: Psychological Patterns, Animation, Recognition (Psychology), Artificial Intelligence
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Kumar, Vivekanandan S.; Boulanger, David – International Journal of Artificial Intelligence in Education, 2021
This article investigates the feasibility of using automated scoring methods to evaluate the quality of student-written essays. In 2012, Kaggle hosted an Automated Student Assessment Prize contest to find effective solutions to automated testing and grading. This article: a) analyzes the datasets from the contest -- which contained hand-graded…
Descriptors: Automation, Scoring, Essays, Writing Evaluation
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Zapata-Rivera, Diego – International Journal of Artificial Intelligence in Education, 2021
Research in the area of Open Student Models (OSMs) has shown that external representations of the student model can be used to facilitate educational processes such as student reflection, knowledge awareness, learning, collaboration, negotiation, and student model diagnosis. OSMs can be integrated into existing learning systems or become a…
Descriptors: Models, Student Characteristics, Access to Information, Educational Research
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Katz, Sandra; Albacete, Patricia; Chounta, Irene-Angelica; Jordan, Pamela; McLaren, Bruce M.; Zapata-Rivera, Diego – International Journal of Artificial Intelligence in Education, 2021
Jim Greer and his colleagues argued that student modelling is essential to provide adaptive instruction in tutoring systems and showed that effective modelling is possible, despite being enormously challenging. Student modelling plays a prominent role in many intelligent tutoring systems (ITSs) that address problem-solving domains. However,…
Descriptors: Physics, Science Instruction, Pretests Posttests, Scores
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Brooks, Christopher; Quintana, Rebecca M.; Choi, Heeryung; Quintana, Chris; NeCamp, Timothy; Gardner, Joshua – International Journal of Artificial Intelligence in Education, 2021
In this article we describe our experiences building a large-scale data science program aimed at supporting diversity in online data science learning. This program was built to support a set of introductory skills-based, higher education courses. We are motivated by work done in project-based learning contexts and culturally responsive pedagogies…
Descriptors: Introductory Courses, Culturally Relevant Education, Higher Education, Student Projects
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Winne, Philip H. – International Journal of Artificial Intelligence in Education, 2021
Learner modeling systems so far formulated model learning in three main ways: a learner's "position" within a lattice of declarative and procedural knowledge about highly structured disciplines such as geometry or physics, a learner's path through curricular tasks compared to milestones, or profiles of a learner's achievements on a set…
Descriptors: Models, Student Characteristics, Access to Information, Learning Processes
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Lajoie, Susanne P. – International Journal of Artificial Intelligence in Education, 2021
I first met Jim Greer at the NATO Advanced Study Institute on Syntheses of Instructional Sciences and Computing Science for Effective Instructional Computing Systems in 1990 in Calgary, Canada. It was during this meeting that I came to realize that Jim was one of those rare individuals that could help "translate" computer science…
Descriptors: Models, Student Characteristics, Artificial Intelligence, Computer Uses in Education
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Mousavi, Amin; Schmidt, Matthew; Squires, Vicki; Wilson, Ken – International Journal of Artificial Intelligence in Education, 2021
Greer and Mark's (2016) paper suggested and reviewed different methods for evaluating the effectiveness of intelligent tutoring systems such as Propensity score matching. The current study aimed at assessing the effectiveness of automated personalized feedback intervention implemented via the Student Advice Recommender Agent (SARA) in a first-year…
Descriptors: Automation, Feedback (Response), Intervention, College Freshmen
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Bull, Susan – International Journal of Artificial Intelligence in Education, 2021
For the special issue of the International Journal of Artificial Intelligence in Education dedicated to the memory of Jim Greer, this paper highlights some of Jim's extensive and always-timely contributions to the field: from his early AI-focussed research on intelligent tutoring systems, through a variety of applications deployed to support…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Educational Research, College Students
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Arruarte, Josu; Larrañaga, Mikel; Arruarte, Ana; Elorriaga, Jon A. – International Journal of Artificial Intelligence in Education, 2021
In order to be effective, a learning process requires the use of valid and suitable educational resources. However, measuring the quality of an educational resource is not an easy task for a teacher. The data of the performance of the students can be used to measure how appropriate the didactic resources are. Besides this data, adequate metrics…
Descriptors: Educational Resources, Educational Quality, Learning Analytics, Tests
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du Boulay, Benedict – International Journal of Artificial Intelligence in Education, 2021
Mark and Greer's ("International Journal of Artificial Intelligence in Education," 4(2/3), 129-153, 1993) review was very influential in setting out effective goals and methods for evaluating adaptive educational systems of all kinds. A later review brought the story up to date (Greer, "International Journal of Artificial…
Descriptors: Artificial Intelligence, Computer Uses in Education, Evaluation Methods, Student Satisfaction
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