Publication Date
In 2025 | 0 |
Since 2024 | 1 |
Since 2021 (last 5 years) | 3 |
Descriptor
Large Group Instruction | 3 |
Learning Analytics | 3 |
Algorithms | 1 |
Artificial Intelligence | 1 |
Assignments | 1 |
Biology | 1 |
Case Studies | 1 |
College Freshmen | 1 |
Computer Software | 1 |
Criterion Referenced Tests | 1 |
Data Analysis | 1 |
More ▼ |
Author
Abigail T. Panter | 1 |
Beasley, Zachariah J. | 1 |
Chaewon Lee | 1 |
Christopher J. Urban | 1 |
Jeffrey A. Greene | 1 |
Kathleen M. Gates | 1 |
Kelly A. Hogan | 1 |
Matthew L. Bernacki | 1 |
Mladen Rakovic | 1 |
Piegl, Les A. | 1 |
Robert D. Plumley | 1 |
More ▼ |
Publication Type
Journal Articles | 2 |
Reports - Research | 2 |
Dissertations/Theses -… | 1 |
Education Level
Higher Education | 2 |
Postsecondary Education | 2 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Robert D. Plumley; Matthew L. Bernacki; Jeffrey A. Greene; Shelbi Kuhlmann; Mladen Rakovic; Christopher J. Urban; Kelly A. Hogan; Chaewon Lee; Abigail T. Panter; Kathleen M. Gates – British Journal of Educational Technology, 2024
Even highly motivated undergraduates drift off their STEM career pathways. In large introductory STEM classes, instructors struggle to identify and support these students. To address these issues, we developed co-redesign methods in partnership with disciplinary experts to create high-structure STEM courses that better support students and produce…
Descriptors: Learning Analytics, Prediction, Undergraduate Study, Biology
Taylor V. Williams – ProQuest LLC, 2022
Clustering, a prevalent class of machine learning (ML) algorithms used in data mining and pattern-finding--has increasingly helped engineering education researchers and educators see and understand assessment patterns at scale. However, a challenge remains to make ML-enabled educational inferences that are useful and reliable for research or…
Descriptors: Multivariate Analysis, Data Analysis, Student Evaluation, Large Group Instruction
Beasley, Zachariah J.; Piegl, Les A.; Rosen, Paul – IEEE Transactions on Learning Technologies, 2021
Accurately grading open-ended assignments in large or massive open online courses is nontrivial. Peer review is a promising solution but can be unreliable due to few reviewers and an unevaluated review form. To date, no work has leveraged sentiment analysis in the peer-review process to inform or validate grades or utilized aspect extraction to…
Descriptors: Case Studies, Online Courses, Assignments, Peer Evaluation