NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 4 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Alison Wallum; Zetai Liu; Joy Lee; Subhojyoti Chatterjee; Lawrence Tauzin; Christopher D. Barr; Amberle Browne; Christy F. Landes; Amy L. Nicely; Martin Gruebele – Journal of Chemical Education, 2023
As data science and instrumentation become key practices in common careers ranging from medicine to agriscience, chemistry as a core introductory course must introduce such topics to students early and at an accessible level. Advanced data acquisition and data science generally require expensive precision instrumentation and massive computation,…
Descriptors: Undergraduate Study, Data Science, Science Laboratories, Laboratory Equipment
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Salleh, Tuan Salwani; Zakaria, Effandi – Turkish Online Journal of Educational Technology - TOJET, 2016
The objective of this research is to investigate the effectiveness of a learning strategy using Maple in integral calculus. This research was conducted using a quasi-experimental nonequivalent control group design. One hundred engineering technology students at a technical university were chosen at random. The effectiveness of the learning…
Descriptors: Foreign Countries, Learning Strategies, Calculus, Engineering Education
Smith, Vernon C.; Lange, Adam; Huston, Daniel R. – Journal of Asynchronous Learning Networks, 2012
Community colleges continue to experience growth in online courses. This growth reflects the need to increase the numbers of students who complete certificates or degrees. Retaining online students, not to mention assuring their success, is a challenge that must be addressed through practical institutional responses. By leveraging existing student…
Descriptors: Academic Achievement, At Risk Students, Prediction, Community Colleges
Schaffhauser, Dian – Campus Technology, 2009
Using data to track and manage student enrollment is steadily becoming a standard practice on both two-year and four-year campuses. Data mining enables colleges to create predictive models for identifying behaviors that put students at risk for dropping out, flag students who engage in these behaviors, and help identify practices that work in…
Descriptors: Community Colleges, Educational Strategies, Academic Support Services, Attendance Patterns