Mark Warschauer

About

Mark Warschauer is a Professor of Education at the University of California, Irvine, with affiliated appointments in the Department of Informatics, the Department of Language Science, and the Department of Psychological Science. He is also the director of the Digital Learning Lab at UC Irvine, where he collaborates with colleagues and students on research projects related to digital media and artificial intelligence in education. He is a member of the National Academy of Education, reflecting his significant contributions to the field of educational research and digital learning.

Research topics

• Computer Science
• Psychology
• Pedagogy
• Mathematics education
• Data science
• World Wide Web
• Medical education
• Medicine
• Artificial Intelligence
• Political Science

Selected publications

• Mining Big Data in Education: Affordances and Challenges

  Review of Research in Education · 2020 · 389 citations

  Senior authorCorresponding

  The emergence of big data in educational contexts has led to new data-driven approaches to support informed decision making and efforts to improve educational effectiveness. Digital traces of student behavior promise more scalable and finer-grained understanding and support of learning processes, which were previously too costly to obtain with traditional data sources and methodologies. This synthetic review describes the affordances and applications of microlevel (e.g., clickstream data), mesol…

  DOI

• Same benefits, different communication patterns: Comparing Children's reading with a conversational agent vs. a human partner

  Computers & Education · 2020-10-23 · 164 citations

  articleOpen accessSenior author
  PublisherOA PDFDOI

• Educational Research and AI-Generated Writing: Confronting the Coming Tsunami

  2023 · 140 citations

  Senior authorCorresponding

  The public release and surprising capacity of ChatGPT has brought AI-enabled text generation into the forefront for educators and academics. ChatGPT and similar text generation tools raise numerous questions for educational practitioners, policymakers, and researchers. We begin by first describing what large language models are and how they function, and then situate them in the history of technology’s complex interrelationship with literacy, cognition, and education. Finally, we discuss implica…

  DOI

• The benefits and caveats of using clickstream data to understand student self-regulatory behaviors: opening the black box of learning processes

  International Journal of Educational Technology in Higher Education · 2020 · 95 citations

  Abstract Student clickstream data—time-stamped records of click events in online courses—can provide fine-grained information about student learning. Such data enable researchers and instructors to collect information at scale about how each student navigates through and interacts with online education resources, potentially enabling objective and rich insight into the learning experience beyond self-reports and intermittent assessments. Yet, analyses of these data often require advanced analyti…

  DOI

• “ChatGPT seems too good to be true”: College students’ use and perceptions of generative AI

  Computers and Education Artificial Intelligence · 2024-09-12 · 94 citations

  articleOpen accessSenior author

  This study investigates how U.S. college students (N = 1001) perceive and use ChatGPT, exploring its relationship with societal structures and student characteristics. Regression results show that gender, age, major, institution type, and institutional policy significantly influenced ChatGPT use for general, writing, and programming tasks. Students in their 30s–40s were more likely to use ChatGPT frequently than younger students. Non-native English speakers were more likely than native speakers…

  PublisherDOI

Recent grants

• Collaborative Network of Grades 3-5 Educators for Computational Thinking for English Learners

  NSF · $1.1M · 2019–2023

• Developing Conversational Videos to Support Children's STEM Learning and Engagement

  NSF · $3.0M · 2021–2027

• Using Conversational Agents to Foster Preschool Children's Science Learning and Engagement from Interactive Science Videos

  NSF · $300k · 2019–2022

Frequent coauthors

• Sharin Jacob

  Digital Promise

  45 shared

• Tamara Tate

  36 shared

• Ying Xu

  23 shared

• Binbin Zheng

  Uniformed Services University of the Health Sciences

  21 shared

• Christian Fischer

  University of Tübingen

  17 shared

• Penelope Collins

  Changwon National University

  16 shared

• Santiago Ojeda-Ramirez

  University of California, Irvine

  16 shared

• Fernando Rodriguez

  University of California, Irvine

  14 shared

Education

• Ph.D., Second Language Acquisition

  University of Hawaii at Manoa

  1997

• M.A., English: Teaching English as a Second Language

  San Francisco State University

  1991

• B.A., Psychology

  University of California, Santa Cruz

  1975

Awards & honors

• Member of the National Academy of Education

Similar researchers at University of California, Irvine

• Stephen Schuellerh-65
• Sean Youngh-48
• Anne Marie Piperh-44