
Karen D. Wang
Postdoctoral Scholar, Education
Bio
My research is situated at the intersection of machine learning and human cognition. In my work, I apply learning analytics and data mining techniques to students’ interaction data in technology-based learning environments. The goal is to translate fine-grained behavioral data into meaningful evidence about students’ cognitive and metacognitive processes. These enhanced understandings of students’ mental processes and competencies are then used to guide the design of and evaluate instructional materials embedded in educational technology.
2021-22 Courses
- Learning Design and Technology Seminar
EDUC 229A (Aut) - Learning Design and Technology Seminar
EDUC 229B (Win) - Learning Design and Technology Seminar
EDUC 229C (Spr) - Learning Design and Technology Seminar
EDUC 229D (Sum)
All Publications
-
Impact of Prompting Engineering Undergraduates to Reflect on Their Problem-Solving Skills
INTERNATIONAL JOURNAL OF ENGINEERING EDUCATION
2023; 39 (2): 653-667
View details for Web of Science ID 000994170200015
-
A systematic review of empirical studies using log data from open-ended learning environments to measure science and engineering practices
BRITISH JOURNAL OF EDUCATIONAL TECHNOLOGY
2022
View details for DOI 10.1111/bjet.13289
View details for Web of Science ID 000891715500001
-
Validated diagnostic test for introductory physics course placement
PHYSICAL REVIEW PHYSICS EDUCATION RESEARCH
2021; 17 (1)
View details for DOI 10.1103/PhysRevPhysEducRes.17.010127
View details for Web of Science ID 000643695100001
-
Examining the Links between Log Data and Reflective Problem-solving Practices in An Interactive Task
ASSOC COMPUTING MACHINERY. 2021: 525-532
View details for DOI 10.1145/3448139.3448193
View details for Web of Science ID 000883342500054
-
Can Majoring in Computer Science Improve General Problem-solving Skills?
ASSOC COMPUTING MACHINERY. 2020: 156-161
View details for DOI 10.1145/3328778.3366808
View details for Web of Science ID 000810169400024
-
Factors Contributing to Anesthesia Residents' Learner Engagement and Learning Experience in a Mobile App: A Mixed-Method Design Study
LIPPINCOTT WILLIAMS & WILKINS. 2017: 102–3
View details for Web of Science ID 000404667000044