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Maria Eftychia Angelaki; Fragkiskos Bersimis; Theodoros Karvounidis; Christos Douligeris – IEEE Transactions on Education, 2024
Contributions: This article explores the impact of environmental education interventions about e-waste recycling and management practices as well as about the energy usage of data centers (DCs) into the Information and Communication Technologies (ICTs) university curricula. Intended Outcomes: An education program was implemented aiming to raise…
Descriptors: Information Technology, Communications, Conservation Education, Sanitation
Ozyurt, Ozcan – Education and Information Technologies, 2023
This study presents topic modeling based bibliometric characteristics of the articles related to the flipped classroom. The corpus of the study consists of 2959 articles published in the Scopus database as of the end of 2021. In addition to the bibliometric characteristics of the field, research interests and trends were also revealed with the…
Descriptors: Bibliometrics, Educational Research, Educational Trends, Flipped Classroom
Crystal Goldman; Erik T. Mitchell – portal: Libraries and the Academy, 2024
The intersection of Data Science (DS) and Library and Information Science (LIS) is rapidly developing, with a notable need for ongoing transdisciplinary training between practitioners in these two fields. The LIS Education and Data Science Integrated Network Group (LEADING) fellowship program and its ancillary community of practice (CoP) showcase…
Descriptors: Library Science, Information Science Education, Data Science, Interdisciplinary Approach
Gemma F. Mojica; Emily Thrasher; Adrian Kuhlman; Bruce Graham; Hollylynne S. Lee; Michelle Pace – North American Chapter of the International Group for the Psychology of Mathematics Education, 2023
In this study, 82 middle and high school teachers engaged with the InSTEP online professional learning platform to develop their expertise in teaching data science and statistics. We investigated teachers' engagement within the platform, aspects of the platform that were most and least effective in building teachers' expertise, and the extent to…
Descriptors: Middle School Teachers, High School Teachers, Faculty Development, Data Science
Sy-Miin Chow; Jungmin Lee; Jonathan Park; Prabhani Kuruppumullage Don; Tracey Hammel; Michael N. Hallquist; Eric A. Nord; Zita Oravecz; Heather L. Perry; Lawrence M. Lesser; Dennis K. Pearl – Journal of Statistics and Data Science Education, 2024
Personalized educational interventions have been shown to facilitate successful and inclusive statistics, mathematics, and data science (SMDS) in higher education through timely and targeted reduction of heterogeneous training disparities caused by years of cumulative, structural challenges in contemporary educational systems. However, the burden…
Descriptors: Individualized Instruction, Instructional Design, Science Education, Higher Education
Ismaila Temitayo Sanusi; Fred Martin; Ruizhe Ma; Joseph E. Gonzales; Vaishali Mahipal; Solomon Sunday Oyelere; Jarkko Suhonen; Markku Tukiainen – ACM Transactions on Computing Education, 2024
As initiatives on AI education in K-12 learning contexts continues to evolve, researchers have developed curricula among other resources to promote AI across grade levels. Yet, there is a need for more effort regarding curriculum, tools, and pedagogy, as well as assessment techniques to popularize AI at the middle school level. Drawing on prior…
Descriptors: Artificial Intelligence, Middle School Students, Learner Engagement, Technology Uses in Education
Preel-Dumas, Camille; Hendra, Richard; Denison, Dakota – MDRC, 2023
This brief explores data science methods that workforce programs can use to predict participant success. With access to vast amounts of data on their programs, workforce training providers can leverage their management information systems (MIS) to understand and improve their programs' outcomes. By predicting which participants are at greater risk…
Descriptors: Labor Force Development, Programs, Prediction, Success