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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
Wang, Dongqing; Han, Hou – Journal of Computer Assisted Learning, 2021
With the development of a technology-supported environment, it is plausible to provide rich process-oriented feedback in a timely manner. In this paper, we developed a learning analytics dashboard (LAD) based on process-oriented feedback in iTutor to offer learners their final scores, sub-scale reports, and corresponding suggestions on further…
Descriptors: Learning Analytics, Educational Technology, Feedback (Response), Intelligent Tutoring Systems
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
Sullins, Jeremiah; Acuff, Samuel; Neely, Daniel; Hu, Xiangen – Journal of Educational Multimedia and Hypermedia, 2018
Is it possible to teach a learner to become a better question asker in as little as 25 minutes? Given that many teachers and school districts do not have the resources to provide individualized question training to students, the current study sought to explore the benefits of using animated pedagogical agents to teach question-asking skills in a…
Descriptors: Prior Learning, Questioning Techniques, Training, Intelligent Tutoring Systems
Mao, Ye; Lin, Chen; Chi, Min – Journal of Educational Data Mining, 2018
Bayesian Knowledge Tracing (BKT) is a commonly used approach for student modeling, and Long Short Term Memory (LSTM) is a versatile model that can be applied to a wide range of tasks, such as language translation. In this work, we directly compared three models: BKT, its variant Intervention-BKT (IBKT), and LSTM, on two types of student modeling…
Descriptors: Prediction, Pretests Posttests, Bayesian Statistics, Short Term Memory
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
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
Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Grantee Submission, 2016
A commonly held belief among educators, researchers, and students is that high-quality texts are easier to read than low-quality texts, as they contain more engaging narrative and story-like elements. Interestingly, these assumptions have typically failed to be supported by the literature on writing. Previous research suggests that higher quality…
Descriptors: Role, Writing (Composition), Natural Language Processing, Hypothesis Testing
Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Journal of Educational Psychology, 2016
A commonly held belief among educators, researchers, and students is that high-quality texts are easier to read than low-quality texts, as they contain more engaging narrative and story-like elements. Interestingly, these assumptions have typically failed to be supported by the literature on writing. Previous research suggests that higher quality…
Descriptors: Role, Writing (Composition), Natural Language Processing, Hypothesis Testing
Wijekumar, Kausalai; Meyer, Bonnie J. F.; Lei, Puiwa; Cheng, Weiyi; Ji, Xuejun; Joshi, R. M. – Journal of Educational Computing Research, 2017
Reading and comprehending content area texts require learners to effectively select and encode with hierarchically strategic memory structures in order to combine new information with prior knowledge. Unfortunately, evidence from state and national tests shows that children fail to successfully navigate the reading comprehension challenges they…
Descriptors: Evidence, Intelligent Tutoring Systems, Memory, Expository Writing
Roscoe, Rod D.; Jacovina, Matthew E.; Harry, Danielle; Russell, Devin G.; McNamara, Danielle S. – Grantee Submission, 2015
Multimedia instructional materials require learners to select, organize, and integrate information across multiple modalities. To facilitate these comprehension processes, a variety of multimedia design principles have been proposed. This study further explores the redundancy principle by manipulating the degree of partial redundancy between…
Descriptors: Multimedia Instruction, Multimedia Materials, High School Students, Writing Instruction
Bringula, Rex P.; Basa, Roselle S.; Dela Cruz, Cecilio; Rodrigo, Ma. Mercedes T. – Journal of Educational Computing Research, 2016
This study attempted to determine the influence of prior knowledge in mathematics of students on learner-interface interactions in a learning-by-teaching intelligent tutoring system. One hundred thirty-nine high school students answered a pretest (i.e., the prior knowledge in mathematics) and a posttest. In between the pretest and posttest, they…
Descriptors: Mathematics, Tutoring, Mathematics Instruction, Foreign Countries
Inan, Fethi A.; Flores, Raymond; Ari, Fatih; Arslan-Ari, Ismahan – Journal of Interactive Learning Research, 2011
The purpose of this study was to document the design and development of an adaptive system which individualizes instruction such as content, interfaces, instructional strategies, and resources dependent on two factors, namely student motivation and prior knowledge levels. Combining adaptive hypermedia methods with strategies proposed by…
Descriptors: Electronic Learning, Educational Strategies, Learning Theories, Instructional Design

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