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David Arthur; Hua-Hua Chang – Journal of Educational and Behavioral Statistics, 2024
Cognitive diagnosis models (CDMs) are the assessment tools that provide valuable formative feedback about skill mastery at both the individual and population level. Recent work has explored the performance of CDMs with small sample sizes but has focused solely on the estimates of individual profiles. The current research focuses on obtaining…
Descriptors: Algorithms, Models, Computation, Cognitive Measurement
Manuel B. Garcia – Education and Information Technologies, 2025
The global shortage of skilled programmers remains a persistent challenge. High dropout rates in introductory programming courses pose a significant obstacle to graduation. Previous studies highlighted learning difficulties in programming students, but their specific weaknesses remained unclear. This gap exists due to the predominant focus on the…
Descriptors: Programming, Introductory Courses, Computer Science Education, Mastery Learning
Jiangyue Liu; Jing Ma; Siran Li – Education and Information Technologies, 2025
This study developed a school-based AI curriculum suitable for senior high school students, with the primary objective of enhancing their mastery of knowledge and proficiency in AI, as well as their computational thinking abilities. The curriculum was designed with an awareness of the practical challenges encountered by the subject school in their…
Descriptors: Artificial Intelligence, Technology Uses in Education, Curriculum Design, Computation
Zhongzhou Chen; Tom Zhang; Michelle Taub – Journal of Learning Analytics, 2024
The current study measures the extent to which students' self-regulated learning tactics and learning outcomes change as the result of a deliberate, data-driven improvement in the learning design of mastery-based online learning modules. In the original design, students were required to attempt the assessment once before being allowed to access…
Descriptors: Learning Analytics, Algorithms, Instructional Materials, Course Content
Anderson, Lorin W.; And Others – 1978
Clinchy and Rosenthal's error classification scheme was applied to test results to determine its ability to differentiate the effectiveness of instruction in two elementary schools. Mathematics retention tests matching the instructional objectives of both schools were constructed to measure the understanding of arithmetic concepts and the ability…
Descriptors: Academic Achievement, Algorithms, Computation, Elementary Education

Canino, Casilda; Cicchelli, Terry – Journal of Educational Computing Research, 1988
Describes aptitude treatment interaction study that used the cognitive styles field dependence and independence matched with computerized algorithmic and discovery treatments to determine mathematics achievement on a criterion-referenced test. Posttest mathematics scores and student responses to the computer are analyzed, and mastery learning is…
Descriptors: Algorithms, Analysis of Covariance, Aptitude Treatment Interaction, Computer Assisted Instruction