Systemic Approaches in Learning Science Research

Researchers must undertake systemic and elemental approaches to investigating questions about learning and learning science (LS). Research in LS:

  1. attempts to bridge the divide between research and practice.
  2. is motivated by limitations of theories of learning and cognition for specifying instruction.
  3. embraces the importance of analyzing and assessing complex interventions through both experimental and design-based research.
  4. emphasizes the learning and behavior of the individual in interaction with the physical, social, and cultural world, as well as with semiotic and technical resources.

Some LS researchers have explored alternative methods for analyzing and assessing the impact of interventions. One approach is to adopt a design-oriented philosophy more commonly associated with engineering fields than with social science. The design-based influences can be traced back in part to the Intelligent Tutoring Systems and Artificial Intelligence and Education (AI & Ed) communities, whose work inspired early LS research on learning environment development that later spawned research in educationa…

Design experiments allow for a vastly expanded tool kit of data collection and analysis methods that have been developed to address questions about settings, people, and phenomena that do not lend themselves easily to classic experimental methods.

These four themes unified under a time scale framework can function together along with their disparate research traditions and methods to capture how learning and complex behavior arises. Aggregated or higher time scale research on cognitive tutors constrains research at lower levels, providing it a target phenomenon that needs further explication, such as the work on classroom interactions among peers and the teacher, on visual processes used in attending to hints from the tutor, and on neural processes in…

This integrated research then informs theories of learning that constrain the design of future learning environments, leading to a virtuous cycle of scaling up and down to further the science of learning.