Measuring and teaching problem-solving practices in digital learning environments
Abstract/Contents
- Abstract
- Digital learning environments are becoming increasingly ubiquitous as a wide range of EdTech products and services enter classrooms and households across the globe. One salient attribute of these environments is their capacity to generate large amounts of data as students interact with the technology. These data logs can help construct a detailed picture of how students work on a task and provide valuable insights into their underlying competencies. At the same time, the sheer volume of interaction data poses challenges, such as how to extract meaningful behavioral patterns from the raw data and model them to assess specific constructs. This dissertation contributes to the efforts of educational researchers and practitioners in harnessing the data generated by digital technology to support teaching and learning, with an emphasis on using interactive tasks to assess and teach problem-solving practices.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2023; ©2023 |
| Publication date | 2023; 2023 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Wang, Karen Dan |
|---|---|
| Degree supervisor | Schwartz, Daniel L |
| Degree supervisor | Wieman, C. E. (Carl Edwin) |
| Thesis advisor | Schwartz, Daniel L |
| Thesis advisor | Wieman, C. E. (Carl Edwin) |
| Thesis advisor | Domingue, Ben |
| Thesis advisor | Salehi, Shima |
| Degree committee member | Domingue, Ben |
| Degree committee member | Salehi, Shima |
| Associated with | Stanford University, Graduate School of Education |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Karen Dan Wang. |
|---|---|
| Note | Submitted to the Graduate School of Education. |
| Thesis | Thesis Ph.D. Stanford University 2023. |
| Location | https://purl.stanford.edu/gq140rw8478 |
Access conditions
- Copyright
- © 2023 by Dan Wang
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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