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Shao-Heng Ko; Kristin Stephens-Martinez – ACM Transactions on Computing Education, 2025
Background: Academic help-seeking benefits students' achievement, but existing literature either studies important factors in students' selection of all help resources via self-reported surveys or studies their help-seeking behavior in one or two separate help resources via actual help-seeking records. Little is known about whether computing…
Descriptors: Computer Science Education, College Students, Help Seeking, Student Behavior
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Gabriella Roby Dodd; Cedric Gondro; Tasia M.Taxis; Margaret Young; Breno Fragomeni – NACTA Journal, 2024
The objectives of this study were to identify gaps in educational training for undergraduate and graduate students in agricultural data science, propose paths for filling these gaps, and provide an annotated list of resources currently available to different training levels. Data in this study was collected through three voluntary surveys catered…
Descriptors: Data Science, Statistics Education, Agriculture, Genetics
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Nick Hopwood; Tracey-Ann Palmer; Gloria Angela Koh; Mun Yee Lai; Yifei Dong; Sarah Loch; Kun Yu – International Journal of Research & Method in Education, 2025
Student emotions influence assessment task behaviour and performance but are difficult to study empirically. The study combined qualitative data from focus group interviews with 22 students and 4 teachers, with quantitative real-time learning analytics (facial expression, mouse click and keyboard strokes) to examine student emotional engagement in…
Descriptors: Psychological Patterns, Student Evaluation, Learning Analytics, Learner Engagement
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Ram B. Basnet; David J. Lemay; Paul Bazelais – Knowledge Management & E-Learning, 2024
Academic and practitioner interest in data science has increased considerably. Yet scholarly understanding of what motivates students to learn data science is still limited. Drawing on the theory of planned behavior, we propose a research model to examine the determinants of behavioral intentions to learn data science. In the proposed research…
Descriptors: Student Attitudes, Intention, Data Science, Statistics Education
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Beth Chance; Andrew Kerr; Jett Palmer – Journal of Statistics and Data Science Education, 2024
While many instructors are aware of the "Literary Digest" 1936 poll as an example of biased sampling methods, this article details potential further explorations for the "Digest's" 1924-1936 quadrennial U.S. presidential election polls. Potential activities range from lessons in data acquisition, cleaning, and validation, to…
Descriptors: Publications, Public Opinion, Surveys, Bias
Yim Register – ProQuest LLC, 2024
The field of Data Science has seen rapid growth over the past two decades, with a high demand for people with skills in data analytics, programming, statistics, and ability to visualize, predict from, and otherwise make sense of data. Alongside the rise of various artificial intelligence (AI) and machine learning (ML) applications, we have also…
Descriptors: Artificial Intelligence, Ethics, Algorithms, Data Science
Clement Chimezie Aladi – ProQuest LLC, 2024
This dissertation explores technological affordances in blended learning, their influence on the flexibility of statistics and data science curricula, and students' satisfaction with learning. While blended learning is often perceived as a flexible learning approach, its correlation with flexibility lacks substantial evidence in existing…
Descriptors: Affordances, Higher Education, Blended Learning, Technology Uses in Education
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Jo Boaler; Kira Conte; Ken Cor; Jack A. Dieckmann; Tanya LaMar; Jesse Ramirez; Megan Selbach-Allen – Journal of Statistics and Data Science Education, 2025
This article reports on a multi-method study of a high school course in data science, finding that students who take data science take more mathematics courses than those who do not, there are more under-represented students in data science than is typical for other advanced mathematics courses; that the students who take data science are more…
Descriptors: Mathematics Instruction, Opportunities, High School Students, Data Science
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Alex Duran-Riquelme; Cherie Flores-Fernández; Judith Riquelme-Ríos – Education for Information, 2024
A professional practice is a type of internship, a practicum, that encompasses a supervised hands-on training experience for students to develop and identify the core and enabling competencies required in a professional environment. It also allows them to identify the developed and underdeveloped skills that are important in the labour environment…
Descriptors: Graduate Students, Library Science, Internship Programs, Practicums
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Azzah Al-Maskari; Thuraya Al Riyami; Sami Ghnimi – Journal of Applied Research in Higher Education, 2024
Purpose: Knowing the students' readiness for the fourth industrial revolution (4IR) is essential to producing competent, knowledgeable and skilled graduates who can contribute to the skilled workforce in the country. This will assist the Higher Education Institutions (HEIs) to ensure that their graduates own skill sets needed to work in the 4IR…
Descriptors: Career Readiness, Technological Literacy, Student Attitudes, Information Technology
Andrew Kent Shealy Jr. – ProQuest LLC, 2024
The increasing prevalence of data emphasizes the importance of statistical literacy. Educational systems are charged with developing students who are statistically literate before entering higher education or the workforce. Adequate teaching and learning of statistics in K-12 education faces challenges, due to limited statistical content knowledge…
Descriptors: Preservice Teacher Education, Preservice Teachers, Mathematics Education, Mathematics Teachers
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Jose L. Salas; Xinran Wang; Mary C. Tucker; Ji Y. Son – Online Learning, 2024
Students believe mathematics is best learned by memorization; however, endorsing memorization as a study strategy is associated with a decrease in learning (Schoenfeld, 1989). When the world changed with the onset of the COVID-19 global pandemic, instruction transitioned to fully remote instruction where many assignments and examinations became…
Descriptors: Distance Education, Memorization, Pandemics, COVID-19
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Amanda Barany; Andi Danielle Scarola; Alex Acquah; Sayed Mohsin Reza; Michael A. Johnson; Justice Walker – Information and Learning Sciences, 2024
Purpose: There is a need for precollege learning designs that empower youth to be epistemic agents in contexts that intersect burgeoning areas of computing, big data and social media. The purpose of this study is to explore how "sandbox" or open-inquiry data science with social media supports learning. Design/methodology/approach: This…
Descriptors: Student Empowerment, Data Science, Social Media, Open Education