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Grover, Shuchi; Basu, Satabdi; Bienkowski, Marie; Eagle, Michael; Diana, Nicholas; Stamper, John – ACM Transactions on Computing Education, 2017
Systematic endeavors to take computer science (CS) and computational thinking (CT) to scale in middle and high school classrooms are underway with curricula that emphasize the enactment of authentic CT skills, especially in the context of programming in block-based programming environments. There is, therefore, a growing need to measure students'…
Descriptors: Learning Analytics, Thinking Skills, Computation, Programming
An Investigation of High School Students' Errors in Introductory Programming: A Data-Driven Approach
Qian, Yizhou; Lehman, James – Journal of Educational Computing Research, 2020
This study implemented a data-driven approach to identify Chinese high school students' common errors in a Java-based introductory programming course using the data in an automated assessment tool called the Mulberry. Students' error-related behaviors were also analyzed, and their relationships to success in introductory programming were…
Descriptors: High School Students, Error Patterns, Introductory Courses, Computer Science Education
Emara, Mona; Hutchins, Nicole M.; Grover, Shuchi; Snyder, Caitlin; Biswas, Gautam – Journal of Learning Analytics, 2021
The integration of computational modelling in science classrooms provides a unique opportunity to promote key 21st century skills including computational thinking (CT) and collaboration. The open-ended, problem-solving nature of the task requires groups to grapple with the combination of two domains (science and computing) as they collaboratively…
Descriptors: Cooperative Learning, Self Management, Metacognition, Computer Science Education
Edwards, John; Hart, Kaden; Shrestha, Raj – Journal of Educational Data Mining, 2023
Analysis of programming process data has become popular in computing education research and educational data mining in the last decade. This type of data is quantitative, often of high temporal resolution, and it can be collected non-intrusively while the student is in a natural setting. Many levels of granularity can be obtained, such as…
Descriptors: Data Analysis, Computer Science Education, Learning Analytics, Research Methodology