
Marcia C. Linn
· Distinguished ProfessorUniversity of California, Berkeley · Education
Active 1972–2026
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About
Marcia C. Linn is the Evelyn Lois Corey Professor of Instructional Science at the University of California, Berkeley, within the Berkeley School of Education. Her specialization is in science and technology education. She is a member of the National Academy of Education and a Fellow of several prestigious organizations, including the American Association for the Advancement of Science (AAAS), the American Psychological Association, the Association for Psychological Science, and the International Society of the Learning Sciences (ISLS). Linn has served as President of the ISLS, Chair of the AAAS Education Section, and has been involved with various boards such as the Educational Testing Service Graduate Record Examination, the McDonnell Foundation Cognitive Studies in Education Practice, and the National Science Foundation Education and Human Resources Directorate. Her research interests encompass assessment and educational measurement, cognitive development, computer-mediated learning, curriculum design, diversity and educational equity, educational media, gender equity, information technology, participatory research, policy analysis, professional development for educators, research methods, school and non-school learning contexts, school-university collaboration, science education, simulation learning environments, teacher development, testing, urban schooling, cluster learning sciences, and social research methodologies. Linn earned her Ph.D. in Educational Psychology from…
Research topics
- Computer Science
- Psychology
- Mathematics education
- Pedagogy
- Artificial Intelligence
- Medicine
- Human–computer interaction
Selected publications
Let's talk evidence – The case for combining inquiry-based and direct instruction
Educational Research Review · 2023 · 147 citations
Many studies investigating inquiry learning in science domains have appeared over the years. Throughout this period, inquiry learning has been regularly criticized by scholars who favor direct instruction over inquiry learning. In this vein, Zhang, Kirschner, Cobern, and Sweller (2022) recently asserted that direct instruction is overall superior to inquiry-based instruction and reproached policy makers for ignoring this fact. In the current article we reply to this assertion and the premises on…
Computer-based guidance to support students’ revision of their science explanations
Computers & Education · 2021 · 48 citations
As they encounter new ideas, students need to make integrated revisions to their science explanations, a key aspect of science learning. This involves filling gaps, resolving inconsistencies with evidence, and strengthening connections among ideas. Rather than making integrated revisions, even after automated, adaptive guidance, students typically add disconnected ideas or fix mechanical errors. The knowledge integration framework, supported by new technologies including natural language process…
Self-directed Science Learning During COVID-19 and Beyond
Journal of Science Education and Technology · 2021 · 36 citations
Senior authorCorrespondingPrompted by the sudden shift to remote instruction in March 2020 brought on by the COVID-19 pandemic, teachers explored online resources to support their students learning from home. We report on how twelve teachers identified and creatively leveraged open educational resources (OERs) and practices to facilitate self-directed science learning. Based on interviews and logged data, we illustrate how teachers' use of OER starkly differed from the typical uses of technology for transmitting informat…
Educational Research Review · 2024-07-26 · 28 citations
reviewOpen accessWe recently published a paper in this journal (de Jong et al., 2023) that presented an overview of the literature on learning in science domains through direct instruction and guided inquiry-based learning. This paper was, in part, a response to Zhang et al. (2022) who argued that the evidence firmly supported the superiority of direct instruction over inquiry learning. Sweller et al. (2024) recently replied by repeating this claim and also argued that we had ignored evidence against our positio…
British Journal of Educational Technology · 2023-09-08 · 25 citations
articleOpen accessSenior authorAbstract This paper describes a Human‐Centred Learning Analytics (HCLA) design approach for developing learning analytics (LA) dashboards for K‐12 classrooms that maintain both contextual relevance and scalability—two goals that are often in competition. Using mixed methods, we collected observational and interview data from teacher partners and assessment data from their students' engagement with the lesson materials. This DBR‐based, human‐centred design process resulted in a dashboard that sup…
Recent grants
NSF · $1.7M · 2003–2007
CLASS: Continuous Learning and Automated Scoring in Science
NSF · $3.1M · 2011–2017
Mentored and Online Development of Educational Leaders for Science (MODELS)
NSF · $2.4M · 2005–2011
Frequent coauthors
- 80 shared
Libby Gerard
University of California, Berkeley
- 29 shared
Marian Rice
University of California, Berkeley
- 28 shared
Jonathan M. Vitale
- 25 shared
Camillia Matuk
- 21 shared
Michael Clancy
- 20 shared
Kevin W. McElhaney
- 20 shared
Allison Bradford
University of California, Berkeley
- 18 shared
Nancy Butler Songer
University of Utah
Education
Ph, D. M.A. B,A,
Stanford University
Awards & honors
- National Association for Research in Science Teaching Award…
- American Educational Research Association Willystine Goodsel…
- Council of Scientific Society Presidents first award for Exc…
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