Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 0 |
| Since 2016 (last 10 years) | 1 |
| Since 2006 (last 20 years) | 3 |
Descriptor
| Data Interpretation | 3 |
| Science Education | 2 |
| Science Process Skills | 2 |
| Undergraduate Students | 2 |
| Abstract Reasoning | 1 |
| Case Studies | 1 |
| Chemistry | 1 |
| Coaching (Performance) | 1 |
| Coding | 1 |
| Cognitive Ability | 1 |
| College Students | 1 |
| More ▼ | |
Author
| Bolger, Molly S. | 1 |
| Cunningham, Jim | 1 |
| Heisterkamp, Kimberly | 1 |
| Meddleton, Shanice | 1 |
| Talanquer, Vicente | 1 |
| Zagallo, Patricia | 1 |
Publication Type
| Reports - Research | 3 |
| Journal Articles | 2 |
| Speeches/Meeting Papers | 1 |
Education Level
| Higher Education | 3 |
| Postsecondary Education | 3 |
Audience
Location
| Arizona | 3 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkZagallo, Patricia; Meddleton, Shanice; Bolger, Molly S. – CBE - Life Sciences Education, 2016
We present our design for a cell biology course to integrate content with scientific practices, specifically data interpretation and model-based reasoning. A 2-year research project within this course allowed us to understand how students interpret authentic biological data in this setting. Through analysis of written work, we measured the extent…
Descriptors: Undergraduate Students, Science Education, Cytology, Instructional Design
Download full textCunningham, Jim – International Educational Data Mining Society, 2015
In this paper, I describe preliminary work on a new research project in learning analytics at Arizona State University. In conjunction with an innovative remedial mathematics course using Khan Academy and student coaches, this study seeks to measure the effectiveness of visualized data in assisting student coaches as they help remedial math…
Descriptors: Research Projects, Remedial Mathematics, Coaching (Performance), Visual Aids
Heisterkamp, Kimberly; Talanquer, Vicente – Journal of Chemical Education, 2015
The central goal of this study was to characterize major patterns of reasoning exhibited by college chemistry students when analyzing and interpreting chemical data. Using a case study approach, we investigated how a representative student used chemical models to explain patterns in the data based on structure-property relationships. Our results…
Descriptors: College Students, Science Education, Chemistry, Data Interpretation
