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Showing 1 to 15 of 116 results Save | Export
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Corey Schimpf; Ruby Castellani; Molly H. Goldstein – International Journal of Technology and Design Education, 2025
Worldwide, engineering design is seeing an increase in pre-college settings due to changing educational policies and standards. Additionally, these projects can help students develop critical skills for a broad range of problem settings, such as design thinking and reflection. In design and other contexts, reflection is a mental process where…
Descriptors: Engineering Education, Reflection, Educational Technology, Learning Analytics
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Halim Acosta; Seung Lee; Daeun Hong; Wookhee Min; Bradford Mott; Cindy Hmelo-Silver; James Lester – International Educational Data Mining Society, 2025
Understanding the relationship between student behaviors and learning outcomes is crucial for designing effective collaborative learning environments. However, collaborative learning analytics poses significant challenges, not only due to the complex interplay between collaborative problem-solving and collaborative dialogue but also due to the…
Descriptors: Learning Analytics, Cooperative Learning, Student Behavior, Prediction
Juliana Irene Owen Thompson – ProQuest LLC, 2023
Aurelius School District used Curriculum Associates' i-Ready program, which was philosophically aligned to the science of reading and included i-Ready Diagnostic, i-Ready Instruction, and Teacher Toolbox, to improve Cole Middle School students' reading achievement. Because of the high monetary cost of i-Ready, the school district was considering…
Descriptors: Middle Schools, Learning Management Systems, Learning Analytics, Reading Achievement
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Nicole M. Hutchins; Gautam Biswas – British Journal of Educational Technology, 2024
This paper provides an experience report on a co-design approach with teachers to co-create learning analytics-based technology to support problem-based learning in middle school science classrooms. We have mapped out a workflow for such applications and developed design narratives to investigate the implementation, modifications and temporal…
Descriptors: Problem Based Learning, Teaching Methods, Science Instruction, Learning Analytics
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Conrad Borchers; Jeroen Ooge; Cindy Peng; Vincent Aleven – Grantee Submission, 2025
Personalized problem selection enhances student practice in tutoring systems. Prior research has focused on transparent problem selection that supports learner control but rarely engages learners in selecting practice materials. We explored how different levels of control (i.e., full AI control, shared control, and full learner control), combined…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Learner Controlled Instruction, Learning Analytics
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Wenyi Lu; Joseph Griffin; Troy D. Sadler; James Laffey; Sean P. Goggins – Journal of Learning Analytics, 2025
Game-based learning (GBL) is increasingly recognized as an effective tool for teaching diverse skills, particularly in science education, due to its interactive, engaging, and motivational qualities, along with timely assessments and intelligent feedback. However, more empirical studies are needed to facilitate its wider application in school…
Descriptors: Game Based Learning, Predictor Variables, Evaluation Methods, Educational Games
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Conrad Borchers; Cindy Peng; Qianru Lyu; Paulo F. Carvalho; Kenneth R. Koedinger; Vincent Aleven – Grantee Submission, 2025
Many AIED systems support self-regulated learning, yet, support for setting and achieving practice goals has received little attention. We examine how middle school students respond to system-recommended practice goals, building on the success of similar data-driven recommendations in other domains. We introduce an adaptive dashboard in an…
Descriptors: Goal Orientation, Student Attitudes, Self Control, Intelligent Tutoring Systems
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Matthieu Cisel – Canadian Journal of Education, 2024
Over the last decade, teachers in France have been increasingly pressured to use digital learning environments, and to shift from grade-based to skill-based assessment. Educational dashboards, which measure student input electronically, could foster such a transition by providing insights into learners' performances. However, such dashboards could…
Descriptors: Foreign Countries, Computer Assisted Testing, Summative Evaluation, Elementary School Students
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Echeverria, Vanessa; Yang, Kexin; Lawrence, LuEttaMae; Rummel, Nikol; Aleven, Vincent – IEEE Transactions on Learning Technologies, 2023
Combining individual and collaborative learning is common, but dynamic combinations (which happen as-the-need arises, rather than in preplanned ways, and may happen on an individual basis) are rare. This work reports findings from a technology probe study exploring alternative designs for classroom co-orchestration support for dynamically…
Descriptors: Man Machine Systems, Artificial Intelligence, Cooperative Learning, Educational Technology
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Knezek, Gerald; Gibson, David; Christensen, Rhonda; Trevisan, Ottavia; Carter, Morgan – British Journal of Educational Technology, 2023
This article reports on a trace-based assessment of approaches to learning used by middle school aged children who interacted with NASA Mars Mission science, technology, engineering and mathematics (STEM) games in "Whyville," an online game environment with 8 million registered young learners. The learning objectives of two games…
Descriptors: Learning Analytics, Nonparametric Statistics, Multidimensional Scaling, STEM Education
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Hanife Merve Erdogan; Nazan Sezen Yüksel – Acta Didactica Napocensia, 2023
The aim of this study is to classify the subjects and skills of middle school mathematics course in the context of MATH Taxonomy and to determine their relations. For this purpose, the questions and answers related to the mathematics subtest of a national exam were analyzed over the answers of 20154 students. The study continued with the analysis…
Descriptors: Mathematics Skills, Taxonomy, Computer Software, Probability
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Halim Acosta; Seung Lee; Bradford Mott; Haesol Bae; Krista Glazewski; Cindy Hmelo-Silver; James Lester – International Educational Data Mining Society, 2024
Collaborative game-based learning offers opportunities for students to participate in small group learning experiences that foster knowledge sharing, problem solving, and engagement. Student satisfaction with their collaborative experiences plays a pivotal role in shaping positive learning outcomes and is a critical factor in group success during…
Descriptors: Cooperative Learning, Game Based Learning, Learning Analytics, Prediction
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Sergio Tirado-Olivares; Rocio Minguez-Pardo; Javier del Olmo-Munoz; Jose A. Gonzalez-Calero – IEEE Transactions on Learning Technologies, 2025
Decimal misconceptions are a persistent challenge in mathematics education, often hindering students' long-term understanding. This study examines how learning analytics (LA) can be effectively integrated into instructional sequences to address these misconceptions, providing teachers with real-time insights for formative assessment. Despite the…
Descriptors: Learning Analytics, Elementary School Students, Elementary School Mathematics, Mathematics Education
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Yu-Jie Wang; Chang-Lei Gao; Xin-Dong Ye – Education and Information Technologies, 2024
The continuous development of Educational Data Mining (EDM) and Learning Analytics (LA) technologies has provided more effective technical support for accurate early warning and interventions for student academic performance. However, the existing body of research on EDM and LA needs more empirical studies that provide feedback interventions, and…
Descriptors: Precision Teaching, Data Use, Intervention, Educational Improvement
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Eran Hadas; Arnon Hershkovitz – Journal of Learning Analytics, 2025
Creativity is an imperative skill for today's learners, one that has important contributions to issues of inclusion and equity in education. Therefore, assessing creativity is of major importance in educational contexts. However, scoring creativity based on traditional tools suffers from subjectivity and is heavily time- and labour-consuming. This…
Descriptors: Creativity, Evaluation Methods, Computer Assisted Testing, Artificial Intelligence
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