Informing: A Cognitive Load Perspective

Abstract

Introduction Informing science investigates how to provide clientele with information in a form, format, and schedule that maximizes its effectiveness (Cohen, 1999; 2009). According to its general, cross-disciplinary definition, information is a feature of objects of different nature that describes their structural aspects represented by patterns attributed to their organization (e.g., Stonier, 1997). Consequently, informing could be regarded as spreading structural patterns (patterns in form) among objects of different nature (Gackowski, 2009). In case of complex information systems such as living organisms (including humans), the aim of informing has been defined as expanding their control over environment (Gackowski, 2009) or, in evolutionary terms, enhancing their chances of survival. When informing is considered at the level of human information processing, the structure and characteristics of human cognitive architecture could have significant implications for the informing process. Cognitive aspects of human information processing may critically affect both the informing (informer) and perceiving (client) ends of the informing process. The intersection of cognitive and informing sciences has been related to the area of cognitive informatics (Cohen, 2009). Cognitive load theory as a branch of instructional psychology (see Sweller, 2003; Sweller, Ayres, & Kalyuga, 2011, for recent overviews) has applied cognitive science to enhance effectiveness and efficiency of instructional design. Since the major aim of instructional design is providing instructional formats and procedures that maximize learning, this could be regarded as a specific area of application of general principles of informing science with learners as clientele. Therefore, instructional and informing sciences are inherently connected. Theoretical frameworks and recommendations of informing science should be applied to instructional design, and established principles of cognitive load theory could also be potentially generalized to advance certain aspects of informing science. This paper explores a possibility of extending the established conceptual framework and principles of cognitive load theory to broader and more general situations than those in teaching and learning with the aim of enhancing the effectiveness of informing. The paper begins with an overview of major assumptions and principles of cognitive load theory based on a recently proposed evolutionary perspective, describes a corresponding model of human cognitive architecture, followed first by general implications of this architecture to informing science, and then by specific recommendations for improving processes of informing. Human Cognitive Architecture Cognitive load theory describes educational implications of human cognitive architecture (Sweller, 2003, 2004). In its basic assumptions, the theory uses the information processing aspects of biological evolution by natural selection as analogical to basic characteristics of human cognition (Sweller & Sweller, 2006). It considers both biological evolution and human cognition as examples of a broader category of natural information processing systems. It is assumed that such systems function based on the following five fundamental principles (Sweller, 2003; for an overview, see Sweller et al., 2011): * The information store principle: natural information processing systems include large stores of information that govern their activities. In human cognitive architecture, long-term memory provides this function. * The borrowing and reorganizing principle: information in the store is mostly borrowed from other information stores; however, it is reorganized in the process rather than copied exactly. For example, humans imitate other people, listen, and read in order to build long-term memory. * The randomness as genesis principle: all truly novel (not borrowed) information is acquired by a random generate-and-test process. …