Dana Gnesdilow
Biographic Data
| ID | 4636377 |
|---|---|
| NAME | Dana Gnesdilow |
| GIVEN NAMES | Dana |
| FAMILY NAME | Gnesdilow |
| SIGNATURE | GNESDILOW D |
| AFFILIATIONS | Wisconsin Center for Education Research School of Education, University of Wisconsin–Madison Madison Wisconsin USA |
| ORCID | 0000-0001-8977-6187 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
NLP ‐enabled automated assessment of scientific explanations
As use of artificial intelligence (AI) has increased, concerns about AI bias and discrimination have been growing. This paper discusses an application called PyrEval in which natural language processing (NLP) was used to automate assessment and provide feedback on middle school science writing without linguistic discrimination. Linguistic discrimination in this study was operationalized as unfair assessment of scientific essays based on writing f…
Middle School Students' Application of Science Learning From Physical Versus Virtual Labs to New Contexts
Even though virtual labs help students learn science content, little is known about how well students can later apply this learning to other contexts or tasks when compared to students who performed physical labs. The goal of this study was to understand how students who perform physical versus virtual labs were able to later apply what they learn to a new context and a more intricate physical lab. We also explored whether reducing the complexity…
Supporting middle school students’ science talk
Research exploring students’ learning from physical and virtual labs has suggested that on the whole, students learn science content just as well, if not better from virtual labs as they do from physical labs. However, the affordances of physical labs might support the learning of specific skills and competencies that are just as crucial for learning science. In this study, we examined students’ discussions as they worked on physical and virtual …
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Supporting middle school students’ science talk
Research exploring students’ learning from physical and virtual labs has suggested that on the whole, students learn science content just as well, if not better from virtual labs as they do from physical labs. However, the affordances of physical labs might support the learning of specific skills and competencies that are just as crucial for learning science. In this study, we examined students’ discussions as they worked on physical and virtual …
Middle School Students' Application of Science Learning From Physical Versus Virtual Labs to New Contexts
Even though virtual labs help students learn science content, little is known about how well students can later apply this learning to other contexts or tasks when compared to students who performed physical labs. The goal of this study was to understand how students who perform physical versus virtual labs were able to later apply what they learn to a new context and a more intricate physical lab. We also explored whether reducing the complexity…
NLP ‐enabled automated assessment of scientific explanations
As use of artificial intelligence (AI) has increased, concerns about AI bias and discrimination have been growing. This paper discusses an application called PyrEval in which natural language processing (NLP) was used to automate assessment and provide feedback on middle school science writing without linguistic discrimination. Linguistic discrimination in this study was operationalized as unfair assessment of scientific essays based on writing f…
Computer Science (3 works) · Psychology (3 works) · Experimental Learning in Engineering (2 works) · Mathematics education (2 works) · Multimedia (2 works) · Online and Blended Learning (2 works) · Physical science (2 works) · Science education (2 works) · Virtual lab (2 works) · Affordance (1 works)