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Cody, Christa; Maniktala, Mehak; Lytle, Nicholas; Chi, Min; Barnes, Tiffany – International Journal of Artificial Intelligence in Education, 2022
Research has shown assistance can provide many benefits to novices lacking the mental models needed for problem solving in a new domain. However, varying approaches to assistance, such as subgoals and next-step hints, have been implemented with mixed results. Next-Step hints are common in data-driven tutors due to their straightforward generation…
Descriptors: Comparative Analysis, Prior Learning, Intelligent Tutoring Systems, Problem Solving
Linking Dialogue with Student Modelling to Create an Adaptive Tutoring System for Conceptual Physics
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
Fabic, Geela Venise Firmalo; Mitrovic, Antonija; Neshatian, Kourosh – International Journal of Artificial Intelligence in Education, 2019
The overarching goal of our project is to design effective learning activities for PyKinetic, a smartphone Python tutor. In this paper, we present a study using a variant of Parsons problems we designed for PyKinetic. Parsons problems contain randomized code which needs to be re-ordered to produce the desired effect. In our variant of Parsons…
Descriptors: Telecommunications, Handheld Devices, Cues, Intelligent Tutoring Systems
Leite, Walter L.; Kuang, Huan; Shen, Zuchao; Chakraborty, Nilanjana; Michailidis, George; D'Mello, Sidney; Xing, Wanli – Grantee Submission, 2022
Previous research has shown that providing video recommendations to students in virtual learning environments implemented at scale positively affects student achievement. However, it is also critical to evaluate whether the treatment effects are heterogeneous, and whether they depend on contextual variables such as disadvantaged student status and…
Descriptors: Algebra, Teaching Methods, Mathematics Instruction, COVID-19
Nagashima, Tomohiro; Bartel, Anna N.; Silla, Elena M.; Vest, Nicholas A.; Alibali, Martha W.; Aleven, Vincent – Grantee Submission, 2020
Many studies have shown that visual representations can enhance student understanding of STEM concepts. However, prior research suggests that visual representations alone are not necessarily effective across a broad range of students. To address this problem, we created a novel, scaffolded form of diagrammatic self-explanation in which students…
Descriptors: Algebra, Teaching Methods, Visual Aids, Concept Formation
Chen, Xingliang; Mitrovic, Antonija; Mathews, Moffat – International Journal of Artificial Intelligence in Education, 2019
Agency refers to the level of control the student has over learning. Most studies on agency in computer-based learning environments have been conducted in the context of educational games and multimedia learning, while there is little research done in the context of learning with Intelligent Tutoring Systems (ITSs). We conducted a study in the…
Descriptors: Problem Solving, Intelligent Tutoring Systems, Educational Games, Independent Study
Hooshyar, D.; Ahmad, R. B.; Yousefi, M.; Yusop, F. D.; Horng, S.-J. – Journal of Computer Assisted Learning, 2015
Intelligent tutoring and personalization are considered as the two most important factors in the research of learning systems and environments. An effective tool that can be used to improve problem-solving ability is an Intelligent Tutoring System which is capable of mimicking a human tutor's actions in implementing a one-to-one personalized and…
Descriptors: Flow Charts, Intelligent Tutoring Systems, Educational Technology, Teaching Methods
Liu, Ran; Koedinger, Kenneth R. K – International Educational Data Mining Society, 2017
Research in Educational Data Mining could benefit from greater efforts to ensure that models yield reliable, valid, and interpretable parameter estimates. These efforts have especially been lacking for individualized student-parameter models. We collected two datasets from a sizable student population with excellent "depth" -- that is,…
Descriptors: Data Analysis, Intelligent Tutoring Systems, Bayesian Statistics, Pretests Posttests
Roll, Ido; Baker, Ryan S. J. d.; Aleven, Vincent; Koedinger, Kenneth R. – Journal of the Learning Sciences, 2014
Seeking the right level of help at the right time can support learning. However, in the context of online problem-solving environments, it is still not entirely clear which help-seeking strategies are desired. We use fine-grained data from 38 high school students who worked with the Geometry Cognitive Tutor for 2 months to better understand the…
Descriptors: Help Seeking, Comparative Analysis, Behavior Patterns, Intelligent Tutoring Systems
Rau, Martina A. – Chemistry Education Research and Practice, 2015
Multiple representations are ubiquitous in chemistry education. To benefit from multiple representations, students have to make connections between them. However, connection making is a difficult task for students. Prior research shows that supporting connection making enhances students' learning in math and science domains. Most prior research…
Descriptors: College Science, Undergraduate Study, Correlation, Concept Formation
Lintean, Mihai; Rus, Vasile; Azevedo, Roger – International Journal of Artificial Intelligence in Education, 2012
This article describes the problem of detecting the student mental models, i.e. students' knowledge states, during the self-regulatory activity of prior knowledge activation in MetaTutor, an intelligent tutoring system that teaches students self-regulation skills while learning complex science topics. The article presents several approaches to…
Descriptors: Semantics, Intelligent Tutoring Systems, Prior Learning, Mathematics
Abramovich, Samuel; Schunn, Christian; Higashi, Ross Mitsuo – Educational Technology Research and Development, 2013
Educational Badges are touted as an alternative assessment that can increase learner motivation. We considered two distinct models for educational badges; merit badges and videogame achievements. To begin unpacking the relationship between badges and motivation, we conducted a study using badges within an intelligent-tutor system for teaching…
Descriptors: Student Motivation, Prior Learning, Alternative Assessment, Expertise
Rus, Vasile; Lintean, Mihai; Azevedo, Roger – International Working Group on Educational Data Mining, 2009
This paper presents several methods to automatically detecting students' mental models in MetaTutor, an intelligent tutoring system that teaches students self-regulatory processes during learning of complex science topics. In particular, we focus on detecting students' mental models based on student-generated paragraphs during prior knowledge…
Descriptors: Data Analysis, Prior Learning, Cognitive Structures, College Students
Peer reviewedWaern, Yvonne; Ramberg, Robert – Computers in Human Behavior, 1996
Discusses users' perceptions of computers versus human beings as advice givers in problem-solving situations based on two studies conducted at Stockholm University (Sweden). Examines people's self-confidence and perception of advice, and concludes that perception relates to existing attitudes, experience, and domain knowledge. (Author/LRW)
Descriptors: Analysis of Variance, Comparative Analysis, Foreign Countries, Higher Education
Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed. – International Working Group on Educational Data Mining, 2009
The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…
Descriptors: Data Analysis, Educational Research, Conferences (Gatherings), Foreign Countries
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