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Showing all 12 results Save | Export
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Natalie Brezack; Melissa Lee; Kelly Collins; Wynnie Chan; Mingyu Feng – Grantee Submission, 2025
Students' effort and emotions are important contributors to math learning. In a recent study evaluating the efficacy of MathSpring, a scalable web-based intelligent tutoring system that provides students with personalized math problems and affective support, system usage data were collected for 804 U.S. 10-12-year-olds. To understand the patterns…
Descriptors: Intelligent Tutoring Systems, Problem Solving, Behavior Patterns, Student Behavior
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Melissa Lee; Chun-Wei Huang; Kelly Collins; Mingyu Feng – Grantee Submission, 2025
Math anxiety has been found to negatively correlate with math achievement, affecting students' choices to take fewer math classes and avoid math educational opportunities. Educational technology tools can ameliorate some of the negative effects of math anxiety. We examined students' math anxiety, effort in an educational technology platform, and…
Descriptors: Correlation, Mathematics Anxiety, Mathematics Achievement, Outcomes of Education
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del Olmo-Muñoz, Javier; González-Calero, José Antonio; Diago, Pascual D.; Arnau, David; Arevalillo-Herráez, Miguel – British Journal of Educational Technology, 2022
Problem solving is often regarded as one of the most essential cognitive functions in our daily lives, and, for that reason, educational theorists have long stressed the need for its development. As cognitive flexibility is a fundamental characteristic necessary throughout the problem-solving process, the purpose of this study is to analyse…
Descriptors: Problem Solving, Arithmetic, Grade 5, Grade 6
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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
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Mingyu Feng; Natalie Brezack; Chunwei Huang; Melissa Lee; Megan Schneider; Kelly Collins; Wynnie Chan – Society for Research on Educational Effectiveness, 2024
Background/Context: Math education remains a critical focus for national education improvement. As a solution, districts in the U.S. are investing in math education technologies. Research has demonstrated the potential of these technologies to close achievement gaps (e.g., Pape et al., 2012; Roschelle et al., 2016). Student math achievement is…
Descriptors: Mathematics Education, Problem Solving, Educational Technology, Technology Uses in Education
Tomohiro Nagashima; Anna N. Bartel; Stephanie Tseng; Nicholas A. Vest; Elena M. Silla; Martha W. Alibali; Vincent Aleven – Grantee Submission, 2021
Although visual representations are generally beneficial for learners, past research also suggests that often only a subset of learners benefits from visual representations. In this work, we designed and evaluated anticipatory diagrammatic self- explanation, a novel form of instructional scaffolding in which visual representations are used to…
Descriptors: Visual Aids, Scaffolding (Teaching Technique), Mathematics Instruction, Algebra
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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
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Aguerrebere, Cecilia; Cobo, Cristóbal; Whitehill, Jacob – International Educational Data Mining Society, 2018
When implementing large-scale educational computing initiatives (e.g., One Laptop Per Child) it is vital to allocate resources for training, support, and device deployment judiciously. One question that arises is how learners' engagement with online educational resources is affected by receiving a new computer; do the benefits justify the costs?…
Descriptors: Management Systems, Foreign Countries, Resource Allocation, Learner Engagement
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Chin, Doris B.; Blair, Kristen P.; Wolf, Rachel C.; Conlin, Luke D.; Cutumisu, Maria; Pfaffman, Jay; Schwartz, Daniel L. – Journal of the Learning Sciences, 2019
Educators aim to equip students with learning strategies they can apply when approaching new problems on their own. Teaching design-thinking strategies may support this goal. A first test would show that the strategies are good for learning and that students spontaneously transfer them beyond classroom instruction. To examine this, we introduce…
Descriptors: Problem Solving, Learning Strategies, Teaching Methods, Design
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Rau, Martina A.; Aleven, Vincent; Rummel, Nikol – Journal of Educational Psychology, 2015
Research shows that multiple external representations can significantly enhance students' learning. Most of this research has focused on learning with text and 1 additional graphical representation. However, real instructional materials often employ multiple "graphical" representations (MGRs) in addition to text. An important open…
Descriptors: Graphs, Instructional Materials, Instructional Effectiveness, Educational Experiments
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Baker, Ryan S. J. D.; Goldstein, Adam B.; Heffernan, Neil T. – International Journal of Artificial Intelligence in Education, 2011
Intelligent tutors have become increasingly accurate at detecting whether a student knows a skill, or knowledge component (KC), at a given time. However, current student models do not tell us exactly at which point a KC is learned. In this paper, we present a machine-learned model that assesses the probability that a student learned a KC at a…
Descriptors: Intelligent Tutoring Systems, Mastery Learning, Probability, Knowledge Level
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection