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Chenglu Li; Wanli Xing; Walter Leite – Interactive Learning Environments, 2024
As instruction shifts away from traditional approaches, online learning has grown in popularity in K-12 and higher education. Artificial intelligence (AI) and learning analytics methods such as machine learning have been used by educational scholars to support online learners on a large scale. However, the fairness of AI prediction in educational…
Descriptors: Artificial Intelligence, Prediction, Mathematics Achievement, Algorithms
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Garcia Coppersmith, Jeannette; Star, Jon R. – Journal of Numerical Cognition, 2022
This study explores student flexibility in mathematics by examining the relationship between accuracy and strategy use for solving arithmetic and algebra problems. Core to procedural flexibility is the ability to select and accurately execute the most appropriate strategy for a given problem. Yet the relationship between strategy selection and…
Descriptors: Mathematics Skills, Learning Strategies, Problem Solving, Arithmetic
Karen E. B. Elliott – ProQuest LLC, 2024
When the purpose and meaning of grades is not well-defined by an organization, there is a disconnect between curricular/assessment practices and student engagement. This study sought to investigate origins and find solutions in regards to discerning a student's knowledge and mastery of a subject and how this is reflected in the grade, and how…
Descriptors: Curriculum Based Assessment, Grading, Disclosure, Grades (Scholastic)
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Asselman, Amal; Khaldi, Mohamed; Aammou, Souhaib – Interactive Learning Environments, 2023
Performance Factors Analysis (PFA) is considered one of the most important Knowledge Tracing (KT) approaches used for constructing adaptive educational hypermedia systems. It has shown a high prediction accuracy against many other KT approaches. While, the desire to estimate more accurately the student level leads researchers to enhance PFA by…
Descriptors: Algorithms, Artificial Intelligence, Factor Analysis, Student Behavior
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Anika Alam; A. Brooks Bowden – Society for Research on Educational Effectiveness, 2024
Background: The importance of high school completion for jobs and postsecondary opportunities is well- documented. Combined with federal laws where high school graduation rate is a core performance indicator, school systems and states face pressure to actively monitor and assess high school completion. This proposal employs machine learning…
Descriptors: Dropout Characteristics, Prediction, Artificial Intelligence, At Risk Students