Cognitive Load Theory: Instructional Implications of the Interaction between Information Structures and Cognitive Architecture

Within the cognitive load theory research community it has become customary to report theoretical and empirical progress at international conference symposia and in special issues of journals (e.g., Educational Psychologist 2003; Learning and Instruction 2002). The continuation of this custom at the 10th European Conference for Research on Learning and Instruction, 2003, in Padova, Italy, has materialized in this special issue of Instructional Science on the instructional implications of the interaction between information structures and cognitive architecture. Since the 1990s this interaction has begun to emerge as an explicit field of study for instructional designers and researchers. In this introduction, we describe the basics of cognitive load theory, sketch the origins of the instructional implications, introduce the articles accepted for this special issue as a representative sample of current research in this area, and discuss the overall results in the context of the theory. It is generally accepted that performance degrades at the cognitive load extremes of either excessively low load (underload) or excessively high load (overload) – see e.g., Teigen (1994). Under conditions of both underload and overload, learners may cease to learn. So, whereas learning situations with low processing demands will benefit from practice conditions that increase the load and challenge the learner, learning situations with an extremely high load will benefit from practice conditions that reduce the load to more manageable levels (Wulf and Shea 2002). Cognitive load theory (CLT; Paas, Renkl and Sweller 2003; Sweller 1988, 1999) is mainly concerned with the learning of complex cognitive tasks, where learners are often overwhelmed by the number of information elements and their interactions that need to be processed simultaneously before meaningful learning can commence. Instructional control of this (too) high load, in order to attain meaningful learning in complex cognitive domains, has