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Social Metacognition and Big Data Network
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Social Metacognition and Big Data Network


IRN Start Date: 1 May 2019



Although people often benefit from cooperating (learn more, solve complex problems, ...), some interactions are more effective than others. Hence, understanding how people influence one another’s emotions, thinking and actions (social metacognition) to achieve their goals and avoid pitfalls can improve their interactions. To develop social metacognition theory, we use artificial intelligence and advanced statistics to analyze complex, big data, specifically talk/action sequences, both face-to-face (e.g., discussions to improve teaching, technicians’ problem solving) and online (debates, mathematics problem solving forums).   

1)      How do people’s recent cognitive (e.g., new idea) and social metacognitive talk/action sequences (e.g., disagree, question) influence other’s talk/actions?

2)      How do sequences of people’s cognitive and social metacognitive actions influence their outcomes (learning, teaching, problem solving, debates)?

We situate our social metacognition theory within micro-time-, activity-, and society-contexts. Our Assessment Research Centre’s network of 28 researchers includes students, post-doctoral fellows, and professors at each rank from 9 countries/regions. 



Ming Ming Chiu, PhD

Chair Professor of Analytics and Diversity
Director, Assessment Research Centre
Department of Special Education and Counselling
Education University of Hong Kong



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