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Download full textFein, Benedikt; Graßl, Isabella; Beck, Florian; Fraser, Gordon – International Educational Data Mining Society, 2022
The recent trend of embedding source code for machine learning applications also enables new opportunities in learning analytics in programming education, but which code embedding approach is most suitable for learning analytics remains an open question. A common approach to embedding source code lies in extracting syntactic information from a…
Descriptors: Artificial Intelligence, Learning Analytics, Programming, Programming Languages
Direct linkYadav, Aman; Gretter, Sarah; Good, Jonathon – AERA Online Paper Repository, 2017
The gender gap in computer science is worst amongst any of the STEM fields. At the secondary school level, only 18.6% of AP computer science test-takers in the United States were girls. In order to address the persistent gender gaps in computer science, it is important to understand K-12 students' views about computer science and programming. The…
Descriptors: Computer Science, Sex Role, Gender Differences, Middle School Students
Kim, Sunha; Chang, Mido; Park, Jeehyun – AERA Online Paper Repository, 2017
The objective of the study was to examine the direct, indirect, and total effects of computer uses on math achievements, by paying particular attention to immigrant students. The study focused on two types of computer uses: computer use for programming and computer use for practice. By using the data from Program for International Student…
Descriptors: Mathematics Achievement, Computer Uses in Education, Immigrants, Secondary School Students
