Keynote Speakers
Professor Nilanjana Buju Dasgupta (University of Massachusetts, USA)
STEMing the Tide: How communal contexts, own-group peers, and professionals act as 'social vaccines' protecting underrepresented students' persistence in in STEM
Individuals' motivation to pursue one academic or professional path over another may feel like a free choice fueled by intrinsic factors, but it is often constrained by subtle cues in learning environments that signal who naturally belong there and who don’t. What factors release these constraints and enhance individuals’ real freedom to pursue academic and professional paths despite stereotypes to the contrary? Coming from a social psychological perspective, I will show how the power of situations impacts young people’s learning, motivation, persistence, and career aspiration in STEM in the face of implicit stereotypes casting doubt on their ability. Our research identifies the types of people and local communities that function as ‘social vaccines’ in high stakes learning environments and inoculate young women, students of color, and first-generation students against implicit stereotypes. Informed by these data, I will propose some research-driven remedies that promise to enhance learning and persistence of diverse groups in STEM educational and professional pathways and reflect on their implications for learning analytics.
Nilanjana Buju Dasgupta is a Professor of Psychology and the inaugural Director of the Institute of Diversity Sciences at the University of Massachusetts, Amherst. She received her Bachelor’s degree from Smith College and a PhD in psychology from Yale University. Her research is on implicit bias with emphasis on the how to change such forms of bias. She is particularly interested in evidence-based solutions to overcome implicit biases in ways that allow girls, women, and underrepresented students to thrive in academic and career trajectories in science, technology, and engineering.
Dasgupta’s research has been funded by the National Science Foundation, including the NSF CAREER award, and several other grants from the National Institutes of Health and the American Psychological Foundation. She received the Application of Personality and Social Psychology Award from the Society for Personality & Social Psychology, the Distinguished Academic Outreach Award in Research, the Chancellor’s Award for Outstanding Accomplishments in Research and Creative Activity, and the Hidden Bias Research Prize awarded by the Level Playing Field Institute, a private foundation based in Silicon Valley. She has given a distinguished faculty lecture at the NSF and an invited presentation at a White House roundtable during the Obama administration on the inclusion of underrepresented youth in science and technology. In 2015 Dasgupta was invited to participate at a White House Next Gen High School Summit convened by the White House Domestic Policy Council and Office of Science and Technology Policy. Dasgupta serves on the National Science Foundation’s Advisory Committee for Social, Behavioral, and Economic Sciences.
She has a passion for translating scientific research to inform and help solve social problems such as gender and race disparities in STEM pathways. She has presented this work to K-12 audiences, university leaders, tech leaders, policymakers on Capitol Hill, and at a White House roundtable during the Obama administration. Dasgupta’s research has been featured in the New York Times, Boston Globe, The Atlantic, International Herald Tribune, London Times, National Public Radio, PBS, ABC News, Scientific American Mind, Slate.com, and many other popular news outlets.
Professor Samuel Greiff (University of Luxembourg, Luxembourg)
Combining Perspectives: A View at Learning Analytics from the Outside
Learning Analytics is an umbrella term for different approaches that collect, analyze, and embed diverse forms and formats of digital data to find traces of learning and to better understand learning processes. In this, Learning Analytics is inherently cross-disciplinary with ties to a number of research fields housing researchers with various background. But, as a field that has not established itself as a discipline in its own right, Learning Analytics has also been viewed skeptically by educationalists, practitioners, and policy makers alike. In this talk, I will view the field of Learning Analytics with different outside lenses and explore potential, limitations, and concrete connecting points for adjacent research fields. Specifically, I will focus on the role that Learning Analytics might play in (1) describing and potentially facilitating complex psychological constructs such as problem solving (cognitive psychology perspective); in (2) assessing and understanding non-cognitive components related to learning such as self-regulation (personality psychology perspective); in (3) supporting teachers in their everyday classroom activities, their teaching and instruction (educational psychology perspective); in (4) augmenting the reporting and the policy relevance of educational large-scale assessments such as the Programme for International Student Assessment (PISA) that tests 15-year old students in over 70 countries worldwide (educational policy perspective). While necessary selective in content and scope, this talk wants to initiate a discussion of the potential implications across of Learning Analytics for students, teachers, institutions, and policy makers.
Prof Dr Samuel Greiff is head of research group, principal investigator, and Full Professor of Educational Assessment and Psychology at University of Luxembourg. He holds a PhD in cognitive and experimental psychology from the University of Heidelberg, Germany. Prof Greiff has been awarded several national and international research funds by diverse funding organizations and has published articles in national and international scientific journals and books He has been and continues to be involved in the Programme for International Student Assessment (PISA) and in the Programme for the International Assessment of Adult Competencies (PIAAC). He has been working for several years in the field of educational assessment and educational technology. In this, he also takes strong interest into the use of log file data and learning analytics for summative and formative assessment purposes.
Professor Scott Freeman (University of Washington, USA)
The evidence-basis for inclusive teaching in undergraduate STEM majors
Low-income, female, and ethnic and racial minority students are underrepresented in STEM careers because they drop out of undergraduate STEM majors at disproportionately high rates--often due to bad experiences in introductory courses. Our research has shown, however, that across STEM, the broad class of teaching innovations characterized as active learning not only supports better performance by all students, but closes performance gaps between students from underrepresented and overrepresented groups. Our current focus is on exploring why minoritized students experience disproportionate benefits in active learning classrooms--specifically, testing what we call the Heads and Hearts hypothesis.
Scott Freeman grew up in Wisconsin and received a B.A. in Biology from Carleton College in 1978. After working in environmental education and international conservation for six years, he did graduate work at the University of Washington on the molecular systematics and morphological evolution of blackbirds and received a PhD in zoology in 1991. He had a Sloan Fellowship to support a post-doctoral fellowship in molecular evolution at Princeton University, then returned to the University of Washington as Director of Public Programs at the Burke Museum. Since the mid-1990s his focus has been on textbook writing, teaching, and discipline-based education research. He co-authored Evolutionary Analysis and was sole author of Biological Science, each through four editions—the texts are now in their 6th editions—and recently published his first book for a general audience, Saving Tarboo Creek. He is currently Lecturer Emeritus in Biology at the UW, where he conducts research on how active learning techniques impact student performance. He is a recipient of a UW Distinguished Teaching Award.