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Yun Huang; Christian Dieter Schunn; Julio Guerra; Peter L. Brusilovsky – ACM Transactions on Computing Education, 2024
Programming skills are increasingly important to the current digital economy, yet these skills have long been regarded as challenging to acquire. A central challenge in learning programming skills involves the simultaneous use of multiple component skills. This article investigates why students struggle with integrating component skills--a…
Descriptors: Programming, Computer Science Education, Error Patterns, Classification
Paulsen, Justin; Valdivia, Dubravka Svetina – Journal of Experimental Education, 2022
Cognitive diagnostic models (CDMs) are a family of psychometric models designed to provide categorical classifications for multiple latent attributes. CDMs provide more granular evidence than other psychometric models and have potential for guiding teaching and learning decisions in the classroom. However, CDMs have primarily been conducted using…
Descriptors: Psychometrics, Classification, Teaching Methods, Learning Processes
Wanxue Zhang; Lingling Meng; Bilan Liang – Interactive Learning Environments, 2023
With the continuous development of education, personalized learning has attracted great attention. How to evaluate students' learning effects has become increasingly important. In information technology courses, the traditional academic evaluation focuses on the student's learning outcomes, such as "scores" or "right/wrong,"…
Descriptors: Information Technology, Computer Science Education, High School Students, Scoring
Attali, Yigal; Arieli-Attali, Meirav – ETS Research Report Series, 2019
Learning progressions (LPs) have seen a growing interest in recent years due to their potential benefits in the development of formative assessments for classroom use. Using an LP as the backbone of an assessment can yield diagnostic classifications of students that can guide instruction and remediation. In operationalizing an LP, assessment items…
Descriptors: Classification, Mastery Learning, Learning Processes, Sequential Approach
Tang, Hengjun; Seah, Wee Tiong; Zhang, Qiaoping; Zhang, Weizhong – ECNU Review of Education, 2021
Purpose: Given that prior research has confirmed that students' mathematics values significantly affect their mathematics learning, understanding how students' values form and change, especially during different learning stages, is an important topic. Design/Approach/Methods: This study administered a questionnaire to investigate the values of…
Descriptors: Factor Structure, Mathematics Education, Student Attitudes, High School Students
Kai, Shimin; Almeda, Ma. Victoria; Baker, Ryan S.; Heffernan, Cristina; Heffernan, Neil – Journal of Educational Data Mining, 2018
Research on non-cognitive factors has shown that persistence in the face of challenges plays an important role in learning. However, recent work on wheel-spinning, a type of unproductive persistence where students spend too much time struggling without achieving mastery of skills, show that not all persistence is uniformly beneficial for learning.…
Descriptors: Decision Making, Models, Intervention, Computer Assisted Instruction
Chen, Fu; Zhang, Shanshan; Guo, Yanfang; Xin, Tao – Research in Science Education, 2017
We used the Rule Space Model, a cognitive diagnostic model, to measure the learning progression for thermochemistry for senior high school students. We extracted five attributes and proposed their hierarchical relationships to model the construct of thermochemistry at four levels using a hypothesized learning progression. For this study, we…
Descriptors: Chemistry, High School Students, Secondary School Science, Correlation