Metacognition and self-regulated learning in manipulative robotic problem-solving task

TL;DR

This paper explores how metacognition influences self-regulated learning in robotic problem-solving, highlighting the regulation of exploration and exploitation in ill-defined tasks using educational robots.

Contribution

It introduces a metacognitive and interactionist approach to analyze problem-solving with educational robots, including a case study on knowledge emergence during exploration.

Findings

Metacognitive regulation guides exploration and exploitation in robotic problem-solving.

Knowledge emerges through metacognitive regulation of exploration and exploitation.

Robots facilitate understanding of complex problem-solving processes.

Abstract

Metacognition is an important aspect in creative problem solving (CPS) and through this chapter we analyse the meta-reasoning aspects applied in the different processes of monitoring the progress of learners' reasoning and CPS activities. Meta-reasoning monitors the way that problem-solving processes advance and regulate time and efforts towards a solution. In the context of an ill-defined problem, exploration is required to develop a better-defined problem space and advance towards the solution space. The way learners engage in exploration and exploitations is regulated by the meta-reasoning within the CPS activity. The objective of this chapter is to examine and identify the CPS process with educational robots through a metacognitive and interactionist approach. This chapter presents a case study, where, to solve a problem, a participant had to explore a set of robot cubes to develop the technological knowledge associated with each single component of the system, but also conceptualize a system-level behaviour of the cubes when they are assembled. The chapter presents the emergence of knowledge through the metacognitive regulation of the process of exploration and exploitation of prior knowledge and emergent knowledge until finding a solution