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Blanton, Maria – North American Chapter of the International Group for the Psychology of Mathematics Education, 2022
Learning progressions have become an important construct in educational research, in part because of their ability to inform the design of coherent standards, curricula, assessments, and instruction. In this paper, I discuss how a learning progressions approach has guided our development of an early algebra innovation for the elementary grades and…
Descriptors: Learning Trajectories, Access to Education, Algebra, Mathematics Education
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Rho, Jihyun; Rau, Martina A.; Van Veen, Barry D. – International Educational Data Mining Society, 2022
Instruction in many STEM domains heavily relies on visual representations, such as graphs, figures, and diagrams. However, students who lack representational competencies do not benefit from these visual representations. Therefore, students must learn not only content knowledge but also representational competencies. Further, as learning…
Descriptors: Learning Processes, Models, Introductory Courses, Engineering Education
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Ellis, Amy B. – North American Chapter of the International Group for the Psychology of Mathematics Education, 2022
The development and use of learning trajectories is a body of research that has made enormous contributions to the field of mathematics education, offering insight into the teaching and learning of topics at all levels. Simultaneously, the work of building learning trajectories can benefit from explicitly adopting an anti-deficit stance,…
Descriptors: Learning Trajectories, Mathematics Education, Teaching Methods, Learning Processes
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Dawkins, Paul Christian; Roh, Kyeong Hah; Eckman, Derek; Cho, Young Kee – North American Chapter of the International Group for the Psychology of Mathematics Education, 2021
This report documents how one undergraduate student used set-based reasoning to reinvent logical principles related to conditional statements and their proofs. This learning occurred in a teaching experiment intended to foster abstraction of these logical relationships by comparing the predicate and inference structures among various proofs (in…
Descriptors: Mathematics Instruction, Validity, Mathematical Logic, Learning Trajectories
Lujie Chen; Artur Dubrawski – Grantee Submission, 2017
We propose a data driven method for decomposing population level learning curve models into mutually exclusive distinctive groups each consisting of similar learning trajectories. We validate this method on six knowledge components from the log data from an online tutoring system ASSISTment. Preliminary analysis reveals interpretable patterns of…
Descriptors: Learning Trajectories, Learning Processes, Intelligent Tutoring Systems, Cluster Grouping
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Chu, Wei; Pavlik, Philip I., Jr. – International Educational Data Mining Society, 2023
In adaptive learning systems, various models are employed to obtain the optimal learning schedule and review for a specific learner. Models of learning are used to estimate the learner's current recall probability by incorporating features or predictors proposed by psychological theory or empirically relevant to learners' performance. Logistic…
Descriptors: Reaction Time, Accuracy, Models, Predictor Variables