Message from Sciences of Learning Strategic Research Theme, Faculty of Education

Research Seminar:
Accountable Talk: How Structured Academic Discussion Builds the Mind

Abstract
Recent evidence from several countries suggests that long- term, “far” transfer from one academic discipline to another is possible under certain conditions of teaching and learning. For example: a) English students who discussed middle school science problems under teacher guidance repeatedly outperformed other students on the British national exam in English three years later; b) American elementary school pupils from poor families who learned math through teacher-led discussion later scored at the highest levels on national and state standard tests of reading; and c) Scottish elementary students who discussed problems in the Philosophy for Children program later outperformed control groups on standard math and reading tests. Experimental results like these are becoming more frequent. Yet very little standard teaching includes the guided discussion that appears essential to the “transfer effect.” Teachers avoid discussion methods because they believe that basic information must first be taught “directly,” and because they believe that only a few students are capable of the kind of “accountable talk” that appears to produce transfer. Thus, a major new challenge for education is to find ways to “break the discussion barrier” in all types of classes and schools.

Workshop: Measuring Classroom Talk

Abstract
The speakers will consider the requirements of measuring classroom talk for two related but separable purposes: 1) Research aimed at understanding and documenting the role of Accountable Talk and related classroom discussion systems in student learning. The speakers will examine examples of coding systems for interactive classrooms. These can range from qualitative anthropological-style descriptions to quantitative sociolinguistic analyses. 2) Research aimed at developing tools for teacher development in the skills of discussion-based teaching. The speakers will describe relatively new efforts to create “mirrors” that allow teachers to examine and analyze aspects of their own teaching within a few days (perhaps eventually hours) of the teaching event. These can range from visual displays of sequences of “turn taking” to quick-take videos with guidelines for professional analysis and discussion. The speakers will discuss how the requirements for these two uses (research reporting and mirrors for improving teaching) overlap and differ and how technologies for both are developing. These technologies range from relatively simple graphing techniques to (semi)-automated coding systems to speech recognition.

Participants are encouraged to bring examples of classroom data they are analyzing or interested in analyzing.

About the speakers

Lauren Resnick is a Distinguished University Professor of Psychology and Cognitive Science and also of Learning Sciences and Education Policy at the University of Pittsburgh. She is an internationally known scholar in the cognitive science of learning and instruction and was Director of the Learning Research and Development Center at the University of Pittsburgh from 1977 to 2008. She has researched and written widely on the learning and teaching of literacy, mathematics, and science. Her recent work focuses on school reform, assessment, effort-based education, the nature and development of thinking abilities, and the role of talk and discourse in learning. Dr. Resnick is founder and Co-Director of the Institute for Learning, which bridges the domains of research and practice by conveying to educators the best of current knowledge about learning processes, principles of instruction, and the design of school systems. Dr. Resnick also co- founded the New Standards Project (1990-1999), which developed performance-based standards and assessments that widely influenced state and school district practice. Dr. Resnick is a prolific author, a respected editor, and a frequent consultant, with appointments to many national education boards, commissions, and associations. Recognized both nationally and internationally, Dr. Resnick has received multiple awards for her research. Educated at Radcliffe and Harvard, Dr. Resnick has been an Overseer of Harvard University and a member of the Smithsonian Council. She is also an elected member of the American Academy of Arts and Sciences.

Gaowei Chen is an assistant professor in the Faculty of Education, University of Hong Kong. Before joining HKU, Dr. Chen spent three years as a postdoctoral associate in the Learning Research and Development Center, University of Pittsburgh and also in Pittsburgh Science of Learning Center. By applying statistical and machine learning models to studies of classroom and online discussions, he examined how teacher-student and student-student interactions help produce strong effects on learning. His research interests include teacher-student interaction and classroom processes, teacher professional development, educational statistics, learning analytics, and computer supported collaborative learning. Dr. Chen received his PhD in educational psychology from the Chinese University of Hong Kong.