Cognitive Load Theory (CLT) is one of the major current instructional theories, describing a capacity model of learning. Since it conceptualizing in the 1980s, CLT has gone through several major modifications. These modifications included revisions to sources of cognitive load, the addition of evolutionary foundations, and the consideration of neuropsychological correlates. As capacity model, CLT has often been used in conjunction with processing theories, such as Mayer’s (2001) Cognitive Theory of Multimedia Learning (CTML). These processing theories have recently undergone major revisions based on research showing the effect of motivation and emotion on learning. I will discuss two expansions of CTML that added affective and motivational components, and will explore how adding affective processing can expand the concept of cognitive load.
(Authors: Detlev Leutner, Ferdi Stebner, Corinna Schuster, Joachim Wirth)
Self-regulated learning (SRL) has been a hot research topic for many years. In the keynote, a specific view on SRL will be presented. The basic idea is that successful SRL forces high-quality application of cognitive learning strategies. That is, when learning to learn, students have not only to learn how to perform the steps of a specific learning strategy (such as text highlighting) but also how to apply the strategy on a high level of quality. In other words, besides learning the mechanics of a strategy, they have to acquire metacognitive knowledge and skills so that they can plan, monitor and regulate the use of the strategy in order to meet its quality standards. From a CLT perspective, the main question is to what extent learners (can) transfer metacognitive knowledge and skills acquired with one cognitive learning strategy to another cognitive learning strategy in order to learn more successful. Thus, the keynote extends a passionate discussion about SRL and CLT at the Wollongong ICLTC 2017.
In our work on the research and design of mobile learning activities, we have brought some of such practices to K-12 schools as pedagogical frameworks for enabling the notion of seamless learning. In this talk, we consider a key challenge for further research lies in bringing our understanding of cognitive load theory (CLT) to the design of mobile learning as well as seamless learning. The learning processes with mobile devices tend to be more spontaneous with students interacting with the 'open' environment, compared to other learning environments which are more scripted or structured such as in the classrooms. We review the literature of where mobile learning may meet CLT, and postulate the areas in which the general framework of CLT is applicable to mobile learning.
Repeated practice leads to acquisition of skills, which requires adapting brain function to achieve mastery. In this talk, I will present two types of brain plasticity for effective learning. At the regional level, the activation pattern stability is considered as a general neural marker of effective learning. For example, the improvement of activation pattern stability in the fusiform cortex contributes to perceptual learning of face views. Similarly, fear conditioning of associative learning increases activation pattern stability for the reinforced stimuli, but not the unreinforced stimuli. The increased activation pattern stability after learning possibly reflects more reliable and refined neural representation on regional level. On the other hand, accumulating evidence indicates that learning is a complex process involving multiple cognitive functions, which causes global brain reorganization across distributed regions. Indeed, motor learning increases the stability of whole-brain functional connectivity pattern of the primary motor cortex, which is related to participants’ improvement in behavioral performance. In short, learning to be skillful may rely not only on reliable neural representation on regional level, but more importantly, on reliable network organization that allows for efficient information transmission in distributed brain networks.