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Kathleen Scalise

Professor
College of Education, Education Policy and Leadership, LEADS, Quantitative Research Methods in Education
Phone: 541-346-0893
Office: 102B Lokey Education Bldg

Biography

Kathleen Scalise is a professor at the University of Oregon in the Department of Methodology, Policy and Leadership. Dr. Scalise employs data science at the intersection with measurement and assessment for applied and theoretical research, including for learning in digital social networks and science/engineering education, as well as for network analyses of leadership and collaboration. She has extensive research in the areas of learning, e-learning, large-scale assessment, and instructional technology in the context of STEM education (science, technology, engineering, and mathematics) and also in emergent language, second language acquisition, digital literacy, social collaboration, leadership, and 21st century skills. In addition to data analytics, she is interested in new models for dynamic delivery of differentiated content to support the needs of all learners, innovative item types, and equity, opportunity and access in education. She serves currently as director of the National Assessment of Educational Progress (NAEP) Science for ETS. She is co-lead for the University of Oregon Social Systems Data Science Network. 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. focusing on Quantitative Measurement from UC Berkeley.

Education

Ph.D., 2004, University of California, Berkeley
Focus: Quantitative Measurement

M.A., 2004, University of California, Berkeley
Area: 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

De Boeck, P. & Scalise K. (2019). Collaborative problem solving: Processing time, actions, and performance. Frontiers in Psychology 10: 1280, Section: Educational Psychology. Research Topic Title: Advancements in Technology-Based Assessment: Emerging Item Formats, Test Designs, and Data Sources, https://doi.org/ 10.3389/fpsyg.2019.01280.

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.

Scalise, K. (2018). Next Wave for Integration of Educational Technology into the Classroom: Collaborative Technology Integration Planning Practices, In Griffin, P., & Care,E. (Eds.), Assessment and teaching of 21st century skills, Volume 3 – research & applications. Dordrecht: Springer.

Wilson, M., Scalise, K., & Gochyyev, P. (2018). ICT Literacy in Digital Networks, In Griffin, P., Wilson, M. & Care, E. (Eds.), Assessment and teaching of 21st century skills, Volume 3 – research & applications. Dordrecht: Springer.

Wilson, M., Scalise, K., & Gochyyev, P. (2018). ICT literacy as a 21st century skill: Learning in Digital Networks with Agile Development approaches. In R. W. Lissitz & H. Jiao (Eds.), Technology enhanced innovative assessment: Development, modeling, and scoring from an interdisciplinary perspective. Charlotte, NC: Information Age Publisher.

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.

Scalise, K. (2017). Hybrid measurement models for technology-enhanced assessments through mIRT-bayes, International Journal of Statistics and Probability, 6(3), 168-182.

Wilson, M., Scalise, K., & Gochyyev, P. (2016). Assessment of learning in digital interactive social networks: A learning analytics approach. Online Learning Journal, 20(2), DOI: http://dx.doi.org/10.24059/olj.v20i2.799.Wilson, M., Scalise, K., & Gochyyev, P. (2018). Issues Arising in the Context of ICT Literacy Assessment, In Griffin, P., Wilson, M. & Care, E. (Eds.), Assessment and teaching of 21st century skills, Volume 3 – research & applications. Dordrecht: Springer

Scalise, K. (2016). Student collaboration and school educational technology: Technology integration practices in the classroom. Journal on School Educational Technology, 11(4), 39-49.

Scalise, K. (2016). Intellectual capital in the context of STEM assessment, Measurement: Interdisciplinary Research and Perspectives, 14(4), pp. 156–157.

Scalise, K., Mustafic, M., & Greiff, S. (2016). Dispositions for collaborative problem solving. In S. Kuger, E. Klieme, N. Jude & D. Kaplan (Eds.), Assessing context of learningworld-wide (Methodology of educational measurement and assessment series). Dordrecht: Springer.

Wilson, M., & Scalise, K. (2016). Learning analytics: Negotiating the intersection of measurement technology and information technology. In J. M. Spector, B. B. Lockee & M.D. Childress (Eds.), Learning, design, and technology. An international compendium of theory, research, practice, and policy. Dordrecht: Springer.

Research

Dr. Kathleen Scalise employs data science at the intersection with measurement and assessment for applied and theoretical research, including for learning in digital social networks and science/engineering education, as well as for network analyses of leadership and collaboration. She has extensive research in the areas of learning, e-learning, large-scale assessment, and instructional technology in the context of STEM education (science, technology, engineering, and mathematics) and also in emergent language, second language acquisition, digital literacy, social collaboration, leadership, and 21st century skills. In addition to data analytics, she is interested in new models for dynamic delivery of differentiated content to support the needs of all learners, innovative item types, and equity, opportunity and access in education.