Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 1 |
Since 2016 (last 10 years) | 4 |
Descriptor
Author
Lynch, Collin F. | 4 |
Barnes, Tiffany | 3 |
Gitinabard, Niki | 3 |
Heckman, Sarah | 3 |
Gaweda, Adam M. | 1 |
Sheshadri, Adithya | 1 |
Xu, Yiqiao | 1 |
Publication Type
Reports - Research | 4 |
Speeches/Meeting Papers | 3 |
Journal Articles | 1 |
Education Level
Higher Education | 3 |
Postsecondary Education | 3 |
Audience
Location
North Carolina | 3 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Gaweda, Adam M.; Lynch, Collin F. – International Educational Data Mining Society, 2021
There are a number of novel exercise types that students can utilize while learning Computer Science, each with its own level of complexity and interaction as outlined by the ICAP Framework [10]. Some are "Interactive," like solving coding problems; "Constructive," like explaining code; "Active," like retyping source…
Descriptors: Computer Science Education, Learning Activities, Student Behavior, Study Habits
Sheshadri, Adithya; Gitinabard, Niki; Lynch, Collin F.; Barnes, Tiffany; Heckman, Sarah – International Educational Data Mining Society, 2018
Online tools provide unique access to research students' study habits and problem-solving behavior. In MOOCs [Massive Open Online Courses], this online data can be used to inform instructors and to provide automatic guidance to students. However, these techniques may not apply in blended courses with face to face and online components. We report…
Descriptors: Online Courses, Large Group Instruction, Educational Technology, Technology Uses in Education
Gitinabard, Niki; Xu, Yiqiao; Heckman, Sarah; Barnes, Tiffany; Lynch, Collin F. – IEEE Transactions on Learning Technologies, 2019
Blended courses that mix in-person instruction with online platforms are increasingly common in secondary education. These platforms record a rich amount of data on students' study habits and social interactions. Prior research has shown that these metrics are correlated with students performance in face-to-face classes. However, predictive models…
Descriptors: Blended Learning, Educational Technology, Technology Uses in Education, Prediction
Gitinabard, Niki; Barnes, Tiffany; Heckman, Sarah; Lynch, Collin F. – International Educational Data Mining Society, 2019
Students' interactions with online tools can provide us with insights into their study and work habits. Prior research has shown that these habits, even as simple as the number of actions or the time spent on online platforms can distinguish between the higher performing students and low-performers. These habits are also often used to predict…
Descriptors: Blended Learning, Student Adjustment, Online Courses, Study Habits