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Hyeongdon Moon; Richard Lee Davis; Seyed Parsa Neshaei; Pierre Dillenbourg – International Educational Data Mining Society, 2025
Knowledge tracing models have enabled a range of intelligent tutoring systems to provide feedback to students. However, existing methods for knowledge tracing in learning sciences are predominantly reliant on statistical data and instructor-defined knowledge components, making it challenging to integrate AI-generated educational content with…
Descriptors: Artificial Intelligence, Natural Language Processing, Automation, Information Management
Miguel Eduardo Uribe-Moreno; Iván Felipe Medina-Arboleda; Alfredo Guzmán-Rincón; Suelen Emilia Castiblanco-Moreno – International Journal of Educational Psychology, 2024
Grit, the passion for achieving long-term goals, has been conceived as a two-dimensional construct (Consistency of interest and Perseverance of effort). The construct is well known for its easy measurement and its relationship with performance, including academic performance. However, there have been different criticisms, such as the overlap of…
Descriptors: Academic Achievement, Psychometrics, Measures (Individuals), Resilience (Psychology)
Singelmann, Lauren Nichole – ProQuest LLC, 2022
To meet the national and international call for creative and innovative engineers, many engineering departments and classrooms are striving to create more authentic learning spaces where students are actively engaging with design and innovation activities. For example, one model for teaching innovation is Innovation-Based Learning (IBL) where…
Descriptors: Engineering Education, Design, Educational Innovation, Models
Onoue, Akira; Shimada, Atsushi; Minematsu, Tsubasa; Taniguchi, Rin-Ichiro – International Association for Development of the Information Society, 2019
This study aimed to cluster learners based on the structures of the knowledge maps they created. Learners drew their own knowledge maps to reflect their learning activities. Our system collected individual knowledge maps from many learners and clustered them to generate an integrated version of the knowledge maps of each cluster. We applied the…
Descriptors: Concept Mapping, Learning Processes, Cluster Grouping, Graphs
Käser, Tanja; Schwartz, Daniel L. – International Educational Data Mining Society, 2019
Open-ended learning environments (OELEs) allow students to freely interact with the content and to discover important principles and concepts of the learning domain on their own. However, only some students possess the necessary skills for efficient and effective exploration. Guidance in the form of targeted interventions or feedback therefore has…
Descriptors: Educational Environment, Interaction, Cluster Grouping, Models
Eakins, Amanda; Eakins, Sheldon L., Sr. – Journal of Learning in Higher Education, 2017
Recently the US have seen a movement of African American students demonstrating dissatisfaction with their treatment and presence at predominantly white institutions. Some of the common discrepancies from the students' perspectives have included the lack of student and faculty representation of color on these campuses. The model of cohort…
Descriptors: African American Students, Teacher Recruitment, Diversity (Faculty), Cluster Grouping
Vanwynsberghe, Griet; Vanlaar, Gudrun; Van Damme, Jan; De Fraine, Bieke – School Effectiveness and School Improvement, 2017
Although the importance of primary schools in the long term is of interest in educational effectiveness research, few studies have examined the long-term effects of schools over the past decades. In the present study, long-term effects of primary schools on the educational positions of students 2 and 4 years after starting secondary education are…
Descriptors: Secondary Education, School Effectiveness, Elementary Secondary Education, Followup Studies
Riofrio-Luzcando, Diego; Ramirez, Jaime; Berrocal-Lobo, Marta – IEEE Transactions on Learning Technologies, 2017
Data mining is known to have a potential for predicting user performance. However, there are few studies that explore its potential for predicting student behavior in a procedural training environment. This paper presents a collective student model, which is built from past student logs. These logs are first grouped into clusters. Then, an…
Descriptors: Student Behavior, Predictive Validity, Predictor Variables, Predictive Measurement

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