TL;DR: In this article, the authors present a literature review identifying thirteen distinct definitions of task complexity, then synthesize these into a new five-class framework, referred to as the Comprehensive Task Complexity Classes (CTCC).
Abstract: Task complexity is a construct widely used in the behavioral sciences to explore and predict the relationship between task characteristics and information processing. Because the creation and use of IT in the performance of tasks is a central area of informing science (IS) research, it follows that better understanding of task complexity should be of great potential benefit to IS researchers and practitioners. Unfortunately, applying task complexity to IS is difficult because no complete, consistent definition exists. Furthermore, the most commonly adopted definition, objective task complexity, tends to be of limited use in situations where discretion or learning is present, or where information technology (IT) is available to assist the task performer. These limitations prove to be severe in many common IS situations. The paper presents a literature review identifying thirteen distinct definitions of task complexity, then synthesizes these into a new five-class framework, referred to as the Comprehensive Task Complexity Classes (CTCC). It then shows the potential relevance of the CTCC to IS, focusing on different ways it could be applied throughout a hypothetical information systems lifecycle. In the course of doing so, the paper also illustrates how the interaction between different classes of task complexity can serve as a rich source of questions for future investigations.
TL;DR: In this paper, a range of methods that can be used to find solutions to practical and theoretical problems using geological prior information, and the nature of geological information can be so employed.
Abstract: Geological prior information represents a new and emerging field within the geosciences. Prior information is the term used to describe previously existing knowledge that can be brought to bear on a new problem. This volume describes a range of methods that can be used to find solutions to practical and theoretical problems using geological prior information, and the nature of geological information that can be so employed. As such, this volume defines how geology can be influential far beyond the confines of its own definition.
TL;DR: This research highlights the need to understand more fully the rationale behind the rapid adoption of EMMARM, as well as its applications in medicine and information technology.
Abstract: Published version of an article from the journal:Issues in Informing Science and Information Technology. Also available from the publisher: http://iisit.org/Vol8/IISITv8p431-449Hadjerrouit224.pdf
TL;DR: 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 is explored.
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. …
TL;DR: Using a combination of informing science models and simulations of complex landscapes, the paper demonstrates how imitating nearby neighbors proves to be a highly effective strategy as complexity grows.
Abstract: Where shared knowledge, beliefs, attitudes and artifacts exist within a group, we have a culture. Culture plays a central role in informing research with two key themes being dominant: 1) the challenges presented by communicating across cultures, and 2) the impact of shared attributes, such as receptiveness to novel ideas, on a culture’s readiness to be informed. Recent research in organizational behavior suggests another perspective: that having a strong culture that is also adaptable can significantly improve an organization’s performance across a broad range of possible attributes. In other words, culture itself—independent of specifics—can exert a positive influence. The paper considers this proposition in the context of complex environments, finding considerable theoretical justification. Complex environments present major challenges to individuals seeking to improve their personal fitness; rules tend to be highly localized and fitness drops between states are often sharp. Using a combination of informing science models and simulations of complex landscapes, the paper demonstrates how imitating nearby neighbors proves to be a highly effective strategy as complexity grows. A strong culture fosters similarities across individuals or entities within a group, ensuring that participants have many self-similar neighbors to observe. The shared values can also serve to reduce the distortion we experience when we relate our own experiences and listen to the experiences of others. Encouraging the development of strong culture is not without risk, however. It is already well established that certain cultural traits—such as the unwillingness to attend to individuals outside the cultural grouping—can impede informing. There is also the danger that the underlying processes that produce strong culture—such as homophily and social contagion—may succeed too well in static environments, leading to values that are over-constrained and therefore do not adapt well. By understanding the informing implications of culture, we may be able to better avoid such obstacles in the future.