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Mao, Ye – ProQuest LLC, 2021
Intelligent Tutoring Systems (ITSs) have emerged as valuable systems to promote active learning. It is critical to build accurate student models to support the learning process. In order to provide efficient and effective personalized instructions for students, tracking a student's time-varying knowledge state is essential to an ITS. Prior…
Descriptors: Time Perspective, STEM Education, Intelligent Tutoring Systems, Learning Processes
Conrad Borchers; Alex Houk; Vincent Aleven; Kenneth R. Koedinger – Grantee Submission, 2025
Active learning promises improved educational outcomes yet depends on students' sustained motivation to engage in practice. Goal setting can enhance learner engagement. However, past evidence of the effectiveness of setting goals tends to be limited to non-digital learning settings and does not scale well as it requires active teacher or parent…
Descriptors: Learner Engagement, Educational Benefits, Goal Orientation, Rewards
Meng Xia; Robin Schmucker; Conrad Borchers; Vincent Aleven – Grantee Submission, 2025
Mastery learning improves learning proficiency and efficiency. However, the overpractice of skills--students spending time on skills they have already mastered--remains a fundamental challenge for tutoring systems. Previous research has reduced overpractice through the development of better problem selection algorithms and the authoring of focused…
Descriptors: Mastery Learning, Skill Development, Intelligent Tutoring Systems, Technology Uses in Education
Balaban, Igor; Filipovic, Danijel; Peras, Marko – International Association for Development of the Information Society, 2019
This paper deals with a problem of digital competence acquisition and certification. In order to overcome the problem of still inadequate number of digitally competent students and the tools that merely focus on skills acquisition, this paper proposes the CRISS platform which is a unique cloud-based digital learning solution, based on the most…
Descriptors: Computer Software, Integrated Learning Systems, Technological Literacy, Teaching Methods
Miller, Chyna J.; Bernacki, Matthew L. – High Ability Studies, 2019
The ability to self-regulate learning (SRL) is a skill theorized to transfer across learning environments. Students with this ability can consider a learning task, identify a goal, develop a plan to achieve it, execute that plan, and monitor and adapt learning until the goal is met. This paper examines the educational implications of developing…
Descriptors: Case Studies, Mathematics Achievement, Metacognition, Learning Strategies
Streeter, Matthew – International Educational Data Mining Society, 2015
We show that student learning can be accurately modeled using a mixture of learning curves, each of which specifies error probability as a function of time. This approach generalizes Knowledge Tracing [7], which can be viewed as a mixture model in which the learning curves are step functions. We show that this generality yields order-of-magnitude…
Descriptors: Probability, Error Patterns, Learning Processes, Models
Wan, Hao; Beck, Joseph Barbosa – International Educational Data Mining Society, 2015
The phenomenon of wheel spinning refers to students attempting to solve problems on a particular skill, but becoming stuck due to an inability to learn the skill. Past research has found that students who do not master a skill quickly tend not to master it at all. One question is why do students wheel spin? A plausible hypothesis is that students…
Descriptors: Skill Development, Problem Solving, Knowledge Level, Learning Processes
McNamara, Danielle S.; Jacovina, Matthew E.; Snow, Erica L.; Allen, Laura K. – Grantee Submission, 2015
Work in cognitive and educational psychology examines a variety of phenomena related to the learning and retrieval of information. Indeed, Alice Healy, our honoree, and her colleagues have conducted a large body of groundbreaking research on this topic. In this article we discuss how 3 learning principles (the generation effect, deliberate…
Descriptors: Learning Processes, Instructional Design, Intelligent Tutoring Systems, Writing Instruction
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
Baker, Ryan S.; Hershkovitz, Arnon; Rossi, Lisa M.; Goldstein, Adam B.; Gowda, Sujith M. – Journal of the Learning Sciences, 2013
We present a new method for analyzing a student's learning over time for a specific skill: analysis of the graph of the student's moment-by-moment learning over time. Moment-by-moment learning is calculated using a data-mined model that assesses the probability that a student learned a skill or concept at a specific time during learning (Baker,…
Descriptors: Learning Processes, Intelligent Tutoring Systems, Probability, Skill Development
Kert, Serhat Bahadir; Kurt, Adile Askim – Interactive Learning Environments, 2012
Electronic performance support systems (EPSSs) are the software programs commonly used in commercial environments since the early 1990s. These software programs are generally called performance-based systems and focus on the complete job rather than providing individual development. For that reason, the usage of these systems in learning…
Descriptors: Foreign Countries, Web Based Instruction, Program Effectiveness, Learning Strategies

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