Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 0 |
| Since 2007 (last 20 years) | 2 |
Descriptor
| Scientific Concepts | 2 |
| Visual Aids | 2 |
| Visualization | 2 |
| Active Learning | 1 |
| Automation | 1 |
| Bias | 1 |
| Biological Sciences | 1 |
| Comparative Analysis | 1 |
| Computer Assisted Testing | 1 |
| Computer Simulation | 1 |
| Concept Mapping | 1 |
| More ▼ | |
Author
| Linn, Marcia C. | 2 |
| Chang, Hsin-Yi | 1 |
| Chiu, Jennifer L. | 1 |
| McElhaney, Kevin W. | 1 |
| Ryoo, Kihyun | 1 |
Publication Type
| Journal Articles | 2 |
| Reports - Research | 2 |
| Information Analyses | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Ryoo, Kihyun; Linn, Marcia C. – Journal of Research in Science Teaching, 2016
Advances in automated scoring technologies have the potential to support student learning during inquiry instruction by providing timely and adaptive guidance on individual students' responses. To identify which forms of automated guidance can be beneficial for inquiry learning, we compared reflective guidance to directive guidance for…
Descriptors: Active Learning, Inquiry, Computer Assisted Testing, Scoring
McElhaney, Kevin W.; Chang, Hsin-Yi; Chiu, Jennifer L.; Linn, Marcia C. – Studies in Science Education, 2015
Dynamic visualisations capture aspects of scientific phenomena that are difficult to communicate in static materials and benefit from well-designed scaffolds to succeed in classrooms. We review research to clarify the impacts of dynamic visualisations and to identify instructional scaffolds that mediate their success. We use meta-analysis to…
Descriptors: Science Curriculum, Science Materials, Visualization, Evidence

Peer reviewed
Direct link
