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Pew and Mavor (1998) called for an integrative representation of human behavior for use in models of individual combatants and organizations. Models with integrated representation of behavior have only been achieved at rudimentary levels according to those performing the studies (e.g. Pew & Mavor, 1998; Tulving, 2002) and those building the models (e.g. Warwick et al., 2002). This chapter will address aspects of cognitive performance that are important to incorporate into models of combat based on acceptance of theory, strength of empirical data, or for other reasons such as to bridge gaps where incomplete knowledge exists about cognitive behavior and performance. As a starting point, this chapter will assess which of Pew and Mavor’s recommendations are still appropriate as determined by a review of selected literature on cognition and its representation. We will also provide some review and extensions of key literature on cognition and modeling and suggest a way ahead to close the remaining gaps. Different aspects of cognition are described with recent findings, and most are followed by an example of how they have been represented in computer models or a discussion of challenges to their representation in modeling.

Different images of teacher knowledge and of teaching are described using the conceptual structure of Cochran-Smith and Lytle (1999a), in which knowledge and practice are viewed as either formal, practical, or transformative. Instructional design (ID) represents a formal image of knowledge and frames the teacher as a problem-solver. Teachers, however, have been resistant to the use of ID. In a graduate ID course, students were given the task of drawing their own representation of the ID process. Two research questions framed the study, including How might these models be categorized? and What views of teaching were found in the models? From 13 deliveries of the course, 123 models and explanatory narratives were analyzed from students who were teachers. The course and ID model task are described. A recursive cycle of categorization and theme-building were used. Types of models included those characterized by Human Activity (51 models), Components (23), Artifacts (20), Organic (15), and Flow Charts (14). Views of teaching included Teacher-centered (47 models), Designer-centered (36 models), Co-centered (18), Learner-centered (16), and De-centered (6). Analysis revealed that for teachers ID activity is a human activity and the principal focus for design activity is teacher needs. Implications are summarized in terms of teacher knowledge and expertise, as well as limitations to our methodology.

The purpose of this chapter is to characterize knowledge organization (KO) as a field that is affected by geographic and diachronic variations in such a way that the recognition of a slanted KO could be considered an ethical option in the KO theory and practice. KO can be considered a dynamic social product that reflects a construction that is altered in space and time. Slants are inherent to any organization of knowledge and are manifested in multiple dimensions. There is a need to find a balance between the respect for the local specificities and the necessity of global access to information. Conceptual and terminological time and space slants in KO are presented. Examples of possible day-by-day searches are analyzed in order to evidence the different cultures that are involved in the different social-linguistic characteristics. The recognition of time and space as operational axes for an ethical approach to a slanted KO is important because: (a) it tries to intervene in represented and possibly disseminated biases that are practiced so far; (b) it recognizes the coexistence of diverse groups and communities, with local characteristics, meanings, and idiosyncrasies, that will need to communicate with each other in global information systems of information; and (c) it can promote an intercultural ethics of mediation, culturally warranted, in order to avoid cultural damages and to guarantee that descriptions can reflect the past while keeping an eye in the future, based on KOS whose functionality remains over time.

This chapter makes a case for extending institutional preservation strategies to the entire landscape of knowledge capital. First, the authors define the three primary types of capital – physical, financial, and knowledge. Knowledge capital is further broken down into three categories – human, structural, and relational. The individual types of knowledge capital are defined, along with their variant economic properties and behaviors. The challenges these variations present for preservation are discussed. The authors also highlight these assets’ significant opportunities for curating new knowledge. Each type of knowledge capital is described, along with the preservation challenges and the curation opportunities.

Having considered various types of pedagogy as well as technology affordances and multimedia learning principles, this chapter focuses on issues surrounding the representation and sharing of content using technology. Anderson & Krathwohl’s (2001) Taxonomy of Learning, Teaching and Assessing is examined as a means of conceptualizing different types of thinking processes in a way that can be applied across discipline areas. The representational requirements of different subject areas (English, mathematics, science, history, geography, and computing) are explored by means of examples, with reference to the role of technology and the range of possible tasks that may be utilized. Assessment issues as they relate to the representation of content are also considered. The broader contextual shift toward open education and sharing is discussed, including key drivers such as learning object repositories, open educational resources, Creative Commons licensing, and massive open online courses.

Learning to teach subject matter topics that emerge as challenging for culturally and linguistically diverse students remains a key goal for prospective teachers. Teacher education needs multiple ways to guide preservice teachers (PSTs) for this work. One context for such teacher development is classroom-based teacher inquiry. I describe an innovation in teacher inquiry pedagogy that mentors PSTs in (a) mining multiple sources of knowledge for teaching challenging areas of content learning, (b) systematically analyzing knowledge gleaned from these sources, and (c) mediating through visual representations the overlapping, reinforcing, and sometimes conflicting ideas gleaned from sources, in order to advance conceptions and practice in content-based learning for diverse youth. I describe the pedagogy in practice, then use a case of one PST to illustrate how her knowledge evolved in learning to teach persuasive writing to early adolescent English language learners. It was in the knowledge sources interface, mediated by visual representations and written reflections, that this PST’s developing knowledge gained texture and depth.

This chapter briefly reviews the research related to the construct of pedagogical content knowledge (PCK) over the past 25 years. Despite the remarkable implications of the PCK conceptualization, questions remain concerning the vagueness of the construct and the studies conducted on the PCK research line, questions which may lead to new developments in defining the nature of the conceptualization, its validity, and its utility. However, agreement exists concerning the need to portray specific cases of PCK of successful teaching. The work argues for a need to develop models of teacher learning and professional development that are subject matter specific. The chapter ends with a call for basing professional development on the conceptualization of PCK.

With the continuous development of intelligent technologies, knowledge graph, the backbone of artificial intelligence, has attracted much attention from both academic and industrial communities due to its powerful capability of knowledge representation and reasoning. Besides, knowledge graph has been widely applied in different kinds of applications, such as semantic search, question answering, knowledge management, and so on. In recent years, knowledge graph techniques in China are also developing rapidly and different Chinese knowledge graphs have been built to support various applications. Under the background of “One Belt One Road (OBOR)” initiative, cooperating with the countries along OBOR on studying knowledge graph techniques and applications will greatly promote the development of artificial intelligence. At the same time, the accumulated experience of China on developing knowledge graph is also a good reference. Thus, in this chapter, the authors mainly introduce the development of Chinese knowledge graphs and their applications. The authors first describe the background of OBOR, and then introduce the concept of knowledge graph and three typical Chinese knowledge graphs, including Zhishi.me, CN-DBpedia, and XLORE. Finally, the authors demonstrate several applications of Chinese knowledge graphs.

Through a theoretical review of the literature, this chapter assesses the potential of different knowledge organisation systems (KOS) to support corporate knowledge management systems (KMS), namely digital libraries (DL) in companies and other institutions. Questions are framed through which the chapter discusses how classical KOS, such as nomenclatures, classification systems, thesauri and ontologies, are able to reflect explicit knowledge in sense of the Semantic Web and also introduces persons as documents along with folksonomies as a means for externalising implicit knowledge in sense of the Web 2.0.