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Ainsley Miller; Kate Pyper – Journal of Statistics and Data Science Education, 2024
R is becoming the standard for teaching statistics due to its flexibility, and open-source nature, replacing software programs like Minitab and SPSS. The main driver for reform within Scottish statistical undergraduate programs is the creation of the Scottish Qualification Authority's Higher Applications of Mathematics course which has statistics…
Descriptors: College Freshmen, Undergraduate Study, Anxiety, Programming Languages
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Guangrui Fan; Dandan Liu; Rui Zhang; Lihu Pan – International Journal of STEM Education, 2025
Purpose: This study investigates the impact of AI-assisted pair programming on undergraduate students' intrinsic motivation, programming anxiety, and performance, relative to both human-human pair programming and individual programming approaches. Methods: A quasi-experimental design was conducted over two academic years (2023-2024) with 234…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Programming
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Christine Eith; Denise Zawada – Impacting Education: Journal on Transforming Professional Practice, 2025
This paper proposes a framework for integrating generative artificial intelligence (AI) tools into statistical training for Doctor of Education (EdD) students. The rigorous demands of doctoral education, coupled with the challenges of learning complex statistical software and coding language, often lead to anxiety and frustration among students,…
Descriptors: Doctoral Programs, Artificial Intelligence, Technology Integration, Statistics Education
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Custer, Gordon F.; van Diepen, Linda T. A.; Seeley, Janel – Natural Sciences Education, 2021
Quantitative literacy is necessary to keep pace with the exponentially increasing magnitude of biological data and the complexity of statistical tools. However, statistical programming can cause anxiety in new learners and educators alike. In order to produce graduates that are well-prepared for quantitative research, overcoming the initial…
Descriptors: Programming Languages, Computer Science Education, Student Attitudes, Time Management