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Wole Michael Olatokun; Oluyemi Folorunso Ayanbode; Sunday Oluwadare Oladipo – Education and Information Technologies, 2025
This study examined the data science career preference, data science skills, and core competencies of 416 students from fourteen Nigerian universities using a Google Forms-created structured online questionnaire. A convenience sampling technique was adopted to select the participants. Data were analysed using both descriptive and inferential…
Descriptors: Data Science, Preferences, College Students, Foreign Countries
Gaoxia Zhu; Chew Lee Teo; Aloysius Kian-Keong Ong; Katherine Guangji Yuan; Chin Lee Ker; Yuqin Yang – Education and Information Technologies, 2025
Preparing the new generation to be data-literate citizens is a pressing challenge, and some explorations have been made to cultivate K-12 students' data science skills and attitudes. However, there is a lack of instructional models to guide the design of data science programs in K-12 due to its complex and interdisciplinary nature as well as the…
Descriptors: Data Science, Skill Development, Secondary School Students, Cooperative Learning
Komp, Evan A.; Pelkie, Brenden; Janulaitis, Nida; Abel, Michael; Castillo, Ivan; Chiang, Leo H.; Peng, You; Beck, David C.; Valleau, Stéphanie – Chemical Engineering Education, 2023
We present a two-week active learning chemical engineering hackathon event specifically designed to teach undergraduate chemical engineering students of any skill level data science through Python and directly apply this knowledge to a real problem provided by industry. The event is free and optional to the students. We use self-evaluation surveys…
Descriptors: Data Science, Undergraduate Students, Learning Activities, Chemical Engineering
Allison S. Theobold; Megan H. Wickstrom; Stacey A. Hancock – Journal of Statistics and Data Science Education, 2024
Despite the elevated importance of Data Science in Statistics, there exists limited research investigating how students learn the computing concepts and skills necessary for carrying out data science tasks. Computer Science educators have investigated how students debug their own code and how students reason through foreign code. While these…
Descriptors: Computer Science Education, Coding, Data Science, Statistics Education
David Rae; Edward Cartwright; Mario Gongora; Chris Hobson; Harsh Shah – Industry and Higher Education, 2024
This paper demonstrates how the innovative application of a Collective Intelligence approach enhanced Local Skills Improvement Planning information for employers, education and skills training organisations and regional economic policy organisations. This took place within a Knowledge Transfer Partnership between a Chamber of Commerce and a…
Descriptors: Cooperative Learning, Intelligence, Knowledge Management, Skill Development
Reem Khojah; Alexandra Werth; Kelly W. Broadhead; Lawrence W. Dobrucki; Chris Geiger; David A. Rubenstein – Biomedical Engineering Education, 2025
The integration of generative artificial intelligence (GenAI) is reshaping biomedical engineering (BME) education. This paper presents insights from "The Fifth Biomedical Engineering Education Summit", which brought together educators from across the U.S. to address challenges and opportunities in integrating GenAI into BME curricula.…
Descriptors: Artificial Intelligence, Technology Uses in Education, Technology Integration, Educational Technology
Toshiya Arakawa; Haruki Miyakawa – Technology, Knowledge and Learning, 2025
Data science education in Japan extends from elementary to high school students. However, some studies show that this has not enhanced interest or curiosity in data science. Therefore, gamification appears to be an efficient method for encouraging high school students' interest in data science, with research indicating that video games are…
Descriptors: Data Science, Educational Games, Statistics Education, Foreign Countries
Yang, Yuqin; Zheng, Zhizi; Zhu, Gaoxia; Salas-Pilco, Sdenka Zobeida – British Journal of Educational Technology, 2023
Preparing data-literate citizens and supporting future generations to effectively work with data is challenging. Engaging students in Knowledge Building (KB) may be a promising way to respond to this challenge because it requires students to reflect on and direct their inquiry with the support of data. Informed by previous studies, this research…
Descriptors: Elementary School Students, Grade 6, Information Literacy, Data
Tiago Carvalho; Ana Correia Simões; Vasco Teles; António Henrique Almeida – European Journal of Engineering Education, 2024
Previous studies show that digital transition brings several benefits and challenges for companies. Among those challenges, particularly for Small and Medium-sized Enterprises (SMEs), the main one is increased capacitation, from technical roles to management. Considering this, the main objective of this study is to identify the training needs and…
Descriptors: Small Businesses, Educational Needs, Ecology, Job Skills
Integrating Computational Data Science in University Curriculum for the New Generation of Scientists
Renu, N.; Sunil, K. – Higher Education for the Future, 2023
Integration of computational data science (CDS) into the university curriculum offers several advantages for students, faculty and the institution. This article discusses the benefits to students of introducing CDS into the university curriculum with a focus on developing skills in cheminformatics, data analysis, structure--activity relationships,…
Descriptors: Data Science, Higher Education, College Students, Skill Development

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