Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 1 |
| Since 2007 (last 20 years) | 2 |
Descriptor
| Mathematical Models | 2 |
| Multivariate Analysis | 2 |
| Chemistry | 1 |
| College Science | 1 |
| College Students | 1 |
| Higher Education | 1 |
| Intellectual Property | 1 |
| Introductory Courses | 1 |
| Learning | 1 |
| Logical Thinking | 1 |
| Mathematical Formulas | 1 |
| More ▼ | |
Author
| Becker, Nicole M. | 1 |
| Brandriet, Alexandra | 1 |
| Lazenby, Katherine | 1 |
| Leach, Ryan C. | 1 |
| Rummel, Nikol | 1 |
| Rupp, Charlie A. | 1 |
| Wiedmann, Michael | 1 |
| Wiley, Jennifer | 1 |
Publication Type
| Journal Articles | 2 |
| Reports - Research | 2 |
Education Level
| Higher Education | 2 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
| Test of Logical Thinking | 1 |
What Works Clearinghouse Rating
Peer reviewed
Direct linkBrandriet, Alexandra; Rupp, Charlie A.; Lazenby, Katherine; Becker, Nicole M. – Chemistry Education Research and Practice, 2018
Analyzing and interpreting data is an important science practice that contributes toward the construction of models from data; yet, there is evidence that students may struggle with making meaning of data. The study reported here focused on characterizing students' approaches to analyzing rate and concentration data in the context of method of…
Descriptors: Mathematical Models, Multivariate Analysis, Qualitative Research, Introductory Courses
Wiedmann, Michael; Leach, Ryan C.; Rummel, Nikol; Wiley, Jennifer – Instructional Science: An International Journal of the Learning Sciences, 2012
Schwartz and Martin ("Cogn Instr" 22:129-184, 2004) as well as Kapur ("Instr Sci", this issue, 2012) have found that students can be better prepared to learn about mathematical formulas when they try to invent them in small groups before receiving the canonical formula from a lesson. The purpose of the present research was to investigate how the…
Descriptors: Mathematical Formulas, Intellectual Property, Learning, Multivariate Analysis
