Kathleen Scalise

Kathleen Scalise profile picture

Biography

Kathleen Scalise is a professor at the University of Oregon in the Department of Methodology, Policy and Leadership. Her main research areas are technology-enhanced assessments in science and mathematics education, item response models with innovative item types, dynamically delivered content in e-learning, computer adaptive and multi-stage testing, and applications to equity studies. She serves currently as director of the National Assessment of Educational Progress (NAEP) Science for ETS. Her projects have included research on 21st Century Skills Assessments with Cisco, Intel and Microsoft; STEM Virtual Performance Assessments with Harvard University; and technology-enhanced assessments with Smarter Balanced and NGSS science assessment designs. She has served internationally on OECD’s PISA, and IEA’s eTIMSS and ICILS. She has extensive journal publications and served on the NRC committee report on assessment of the Next Generation Science Standards. She holds K-12 teaching credentials (California) for physical sciences and life sciences, a B.A. in biochemistry, and the Ph.D. from UC Berkeley.

Education

Ph.D., 2004, University of California, Berkeley
Major: Quantitative Measurement
 
M.A., 2004, University of California, Berkeley
Major: Policy, Organization, Measurement and Evaluation with a disciplinary focus in Cognition
 
B.A., 1982, University of California, Berkeley
Major: Biochemistry

Honors and Awards

2018 Faculty Research Excellence Award, University of Oregon

2017 Journal of Educational Measurement (JEDM) Top Downloaded Publication, “Modeling Data From Collaborative Assessments: Learning in Digital Interactive Social Networks”

2016 Online Learning Journal, 8th Most Downloaded Article for 2016, “Assessment of Learning in Digital Interactive Social Networks: A Learning Analytics Approach ”

2015 Assessment for e-Learning for paper on “Assessment for e-Learning: Case studies of an emerging field”

2014 JCE Most Read Articles 2014, Journal of Chemical Education: “What Does a Student Know Who Earns a Top Score on the Advanced Placement Chemistry Exam?”

2014 ACS Editors' Choice Selection, American Chemical Society

2014 National Council on Measurement in Education, Program Co-Chair

2012 National Association for Research in Science Teaching, Top Five Articles for 2012

2011 U.S. Department of Education, Certification of Recognition for Outstanding Work for the Department’s Race to the Top Assessment Program

2007 Early Career Teaching Award, University of Oregon

Publications

Scalise, K., & Clarke-Midura, J. (2018). The many faces of scientific inquiry: Effectively measuring what students do and not only what they say, Journal of Research in Science Teaching, Sept. 3 (early release), https://doi.org/10.1002/tea.21464.

 

Wilson, M, Scalise, K., and Gochyyev, P. (2018). Domain modelling for advanced learning environments: the BEAR Assessment System Software, Educational Psychology, July 24 (early release), https://doi.org/10.1080/01443410.2018.1481934.

 

Scalise, K., Douskey, M., Stacy, A. (2018). Measuring learning gains and examining implications for student success in STEM, Higher Education Pedagogies, 3(1), 10-22.

 

Scalise, K., Irvin, P.S., Alresheed, F., Yim, H., Park, S., Landis, B., Meng, P., Kleinfelder, B., Halladay, L., Partsafas, A. (2018). Accommodations in computer-based, interactive assessment tasks: Promising practices for enhancing accessibility for students with disabilities, Journal of Special Educational Technology (JOSET), https://doi.org/10.1177/0162643418759340.

 

Wilson, M., Scalise, K., Gochyyev, P. (2017). Modeling data from collaborative assessments: Learning in digital interactive social networks, Journal of Educational Measurement54(1), 85-102.

 

Scalise, K., & Felde, M. (2017). Why neuroscience matters in the classroom: Principles of brain-based instructional design for teachers. Columbus, OH: Pearson, Prentice Hall.

 

Wilson, M., Scalise, K., & Gochyyev, P. (2016). Assessment of learning in digital interactive social networks: A learning analytics approach. Online Learning Journal20(2), DOI: http://dx.doi.org/10.24059/olj.v20i2.799.

Research

Professor Scalise’s main research areas are science and mathematics education, including instructional technology and interactive activities in STEM, data science, technology-enhanced measurement and assessment, evidence in simulations and serious gaming including process data, item response models with innovative item types, dynamically delivered content in e-learning, computer adaptive and multi-stage testing, and applications to equity studies. She works in K-16 and also teams as a methodologist with applied researchers in many other areas.