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Gerbing, David W. – Journal of Statistics and Data Science Education, 2021
R and Python are commonly used software languages for data analytics. Using these languages as the course software for the introductory course gives students practical skills for applying statistical concepts to data analysis. However, the reliance upon the command line is perceived by the typical nontechnical introductory student as sufficiently…
Descriptors: Statistics Education, Teaching Methods, Introductory Courses, Programming Languages
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Brown, Neil C. C.; Altadmri, Amjad – ACM Transactions on Computing Education, 2017
Teaching is the process of conveying knowledge and skills to learners. It involves preventing misunderstandings or correcting misconceptions that learners have acquired. Thus, effective teaching relies on solid knowledge of the discipline, but also a good grasp of where learners are likely to trip up or misunderstand. In programming, there is much…
Descriptors: Novices, Programming Languages, Programming, Error Patterns
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Hubbard, Aleata – Grantee Submission, 2017
The results of educational research studies are only as accurate as the data used to produce them. Drawing on experiences conducting large-scale efficacy studies of classroom-based algebra interventions for community college and middle school students, I am developing practice-based data cleaning procedures to support scholars in conducting…
Descriptors: Educational Research, Mathematics Education, Algebra, Intervention
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El-khateeb, Mahmoud M. A. – Journal of Education and Learning, 2015
The purpose of this study was to investigate the misperceptions and performance of king Saud University students' about concept and finding the limit of same partial functions given in the form of both graphical and symbolic. In the collection of the data, the researcher employed the open-ended question test consisted of four items. Firstly,…
Descriptors: Foreign Countries, College Students, Student Attitudes, Misconceptions
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Boyer, Kristy Elizabeth, Ed.; Yudelson, Michael, Ed. – International Educational Data Mining Society, 2018
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…
Descriptors: Data Collection, Data Analysis, Computer Science Education, Program Proposals
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Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis
Fredrich, Barbara E.; Griffin, Ernst C. – 1976
College students from colleges and universities throughout the United States were surveyed about the location of the world's 50 most populous countries. Over 3,300 responses were examined to determine the perceived geographic range of given countries, the regional degree of accuracy among students, and the overall significance of response errors.…
Descriptors: Area Studies, College Students, Data Analysis, Error Patterns