Overview

Psychology and educational research have long created a sharp divide between affect and cognition, the hot and the cold of learning. However, the world is not so easliy divided, and the two influence each other in important ways over the pathways a learning might follow. Efficacy and self-efficacy are loosely coupled. Interest and opportunity-to-learn are similalry bidirectionally loosely coupled. Through deep dives into the nature of both motivational constructs and learning processes in STEM contexts, we build new accounts of learning towards a discipline unfolding over the scale of months to years.

   
         
 
Recent Results
  • A mixture of skills, knolwedge, and dispositions are required to produce science learners who choose optional science learning experiences, engage more productively during those science learning experiences (both in schools and in informal learning contexts), and learn more science content.
  • Badges appear to have both positive and negative effects on student motivation, depending critically upon the type of badges and the type of learner.
  • Different motivational factors appear to predict persistence for students and teachers participating in a MOOC.
   
   

 

 

   
 
The Team
   
       
 
Schunn Lab: Meghan Bathgate, Paulette Vincent-Ruz, Ross Higashi,, Christopher Matthis
   
 
Collaborators: Rena Dorph (UC Berkeley), Mac Cannady (UC Berkeley), Patrick Sheilds, Rip Correnti, Kevin Crowley, Liz Richey, Jennifer Cromley, Joe Merlino, Nora Newcombe, Li Sha, Lou Alfieri
   
           

 

 

 


 

 
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Current Projects

Science Learning Activation Lab (ActLab). The Science Learning Activation Lab is a national research and design effort to learn and demonstrate how to activate children in ways that ignite persistent engagement in science learning and inquiry. Led by the Learning Research Development Center at the University of Pittsburgh and the Lawrence Hall of Science at the University of California Berkeley, the Lab is conducting research to identify the characteristics of young children that are predictive of successful science learning and future participation in science, as well as to design learning environments that promote such outcomes. Working with a team of national experts, the Activation Lab has developed a theoretical framework to guide our investigation in systematic ways across learning settings. Our research will explore and define the elements of an activated learner, the trajectory of predicted outcomes, and the learning experiences that support or maintain activation.

Badges for Learning Computer Science. Educational badges represent a new vision of learning that combines the hot and cold of learning. On the one hand, badges are meant to represent what learners actually can do, based on rich evidence that is more authentic than test performance alone. On the other hand, badges are meant to shape learner motivations (potentially in positive and negative ways). Despite all the attention to badges for a half-decade, very little is known empirically about their validity nor their affects. We are studying and refining a badge ecosystem embedded with an online teaching environment for formal and informal robotics instruction (with embedded computer science and mathematics instructional goals): cs2n.org.

 


   
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