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In this chapter, each of the completed models of curriculum is presented and evaluated using criteria from the attributes of effective curricula discussed in Chapter 1. Explanations of the design strategies that are used to demonstrate each attribute in a differentiated manner are included. The evaluation process provides an evaluation methodology to demonstrate the effectiveness of each model of a curriculum in a credible and trustworthy way.

In the previous chapters, the individual parts of the curricula were configured, aligned, and interconnected to deliver specific outcomes in each learning module. In this chapter, the components of each curriculum are assembled into one table to exhibit the order contained within each learning module within the overall curriculum. The standards for curricular attributes adopted at the beginning of the design process are the criteria for the evaluation of the completed curriculum. The strategies used to configure the components of each curriculum provide evidence of the curriculum’s characteristics, which demonstrate compliance with each criterion.

The evaluation of these attributes within a curriculum serves several purposes. First, they provide a checklist to guide the design process toward curricula that reflect these standards as developed by the profession of curriculum design in higher education. Second, they provide a measurement of the attributes of the curriculum to demonstrate the compliance of each curricular design with conventional standards. Third, these measurements can be compared with other institutional data to uncover correlations between the design assumptions and learner performance. These correlations often reveal unanticipated results, which inform the effectiveness of the instructional system.

These criteria are applied to the evaluation of the curriculum for each module to demonstrate the diverse manner in which each can be achieved in a discipline-specific manner. The compliance with these criteria is explained to be a matter of demonstration, as used in the discipline of qualitative research. These qualitative evaluations can then be compared with other operational data to understand the effectiveness of the design assumptions for each curriculum.

The study this chapter reports focuses on how network theory contributes to the understanding of the internationalization process of SMEs and measures the effect of network capability on performance in international trade and has three research objectives.

The first objective of the study relates to providing new insights into the international market development activities through the application of a network perspective. The chapter reviews the international business literature to ascertain the development of thought, the research gaps, and the shortcomings. This review shows that the network perspective is a useful and popular theoretical domain that researchers can use to understand international activities, particularly of small, high technology, resource-constrained firms.

The second research objective is to gain a deeper understanding of network capability. This chapter presents a model for the impact of network capability on international performance by building on the emerging literature on the dynamic capabilities view of the firm. The model conceptualizes network capability in terms of network characteristics, network operation, and network resources. Network characteristics comprise strong and weak ties (operationalized as foreign-market entry modes), relational capability, and the level of trust between partners. Network operation focuses on network initiation, network coordination, and network learning capabilities. Network resources comprise network human-capital resources, synergy-sensitive resources (resource combinations within the network), and information sharing within the network.

The third research objective is to determine the impact of networking capability on the international performance of SMEs. The study analyzes 11 hypotheses through structural equations modeling using LISREL. The hypotheses relate to strong and weak ties, the relative strength of strong ties over weak ties, and each of the eight remaining constructs of networking capability in the study. The research conducts a cross-sectional study by using a sample of SMEs drawn from the telecommunications industry in Ireland.

The study supports the hypothesis that strong ties are more influential on international performance than weak ties. Similarly, network coordination and human-capital resources have a positive and significant association with international performance. Strong ties, weak ties, trust, network initiation, synergy-sensitive resources, relational capability, network learning, and information sharing do not have a significant association with international performance. The results of this study are strong (R2=0.63 for performance as the outcome) and provide a number of interesting insights into the relations between collaboration or networking capability and performance.

This study provides managers and policy makers with an improved understanding of the contingent effects of networks to highlight situations where networks might have limited, zero, or even negative effects on business outcomes. The study cautions against the tendency to interpret networks as universally beneficial to business development and performance outcomes.

As a company that has continuously achieved business innovation, Apple in the United States has successfully applied strategic knowledge creation to produce a series of products that integrate various digital devices as well as diverse contents and applications, such as the iPod, iPhone, and iPad, based on a corporate vision of a digital hub concept. At the same time, the redefining of corporate boundaries that expanded Apple’s business in a horizontal direction from the Macintosh PC business to the delivery of music, smartphones, and tablets is also an indication of the evolution of a corporate vision involving Apple’s strategic transformation. This chapter presents the strategic and creative processes that enabled practitioners, including the late Steve Jobs, to demonstrate “strategic innovation capability” by “holistic leadership” at every level of management at Apple and successfully achieve a business ecosystem strategy through “creative collaboration” across diverse boundaries within and outside the company.

This chapter provides an overview of the Department of Defense (DoD) laboratory structure to help equipment designers, modelers, and manufacturers determine where research, testing programs, or relevant findings can be found. The chapter includes a discussion of the performance measures and metrics typically used in DoD laboratories and concludes by considering the current state-of-the-art as well as the state-of-the-possible for human performance measurement.

This chapter outlines potential steps to take in designing active learning experiences based on several theories underlying the learning process. The chapter examines theories of learning and instruction including information processing, schema acquisition, and cognitive load theory. Next follows an explanation of how these theories support problem-centered learning as well as a rationale for the need to help learners develop domain-general, flexible problem-solving skills that will transfer to future needs and contexts. The second half of the chapter focuses on designing active learning experiences based on the selection of real-world problems as the foundation for learning, activating prior knowledge, demonstration of the process or concept, multiple opportunities for practice with relevant scaffolding, and the chance to integrate that knowledge into the learners’ own context based on M. D. Merrill’s (2002) First Principles of Instruction. Examples of assessments, strategies, and activities to foster active, problem-centered learning drawn from the literature are also provided.

Several criteria were used for this study to determine the relevance of the literature for the purpose of the review. First, all articles were required to be published in peer-reviewed journals. Next, all articles were required to be primary sources. Reviews of the literature found throughout the search procedures were used as supporting information, as well as the basis for this review. Only quantitative studies were included in this review; opinion papers and qualitative studies were not incorporated into the results. The participants in each study had to be identified as having a learning disability. Studies that included regular education students as a control or comparative group were included as long as the treatment group included students with learning disabilities. The students with learning disabilities were required to possess verbal deficits. Those studies that examined students with non-verbal learning disabilities were excluded from this review. All studies were required to be in English and conducted in the United States.

E-learning programs exist in a wide variety of formats. Without a framework for distinguishing between different e-learning programs, it is a challenge for researchers to compare their effectiveness or identify characteristics of e-learning that contribute to learning effectiveness. Based on general theories of learning, we develop a typology that compares e-learning programs in terms of the nature of the learning interactions they provide for learners in three dimensions: degree of interaction, learner control of interactions, and informational value of interactions. The typology dimensions apply to learner–instructor, learner–learner, and learner–instructional material interactions. We also discuss important theoretical implications of the typology. First, we show the utility of the typology for comparing the effectiveness of different e-learning programs. Second, we apply the typology dimensions to develop a theoretical framework for e-learning research that provides a foundation for examining factors that influence learning effectiveness in an e-learning program. The framework identifies e-learning program characteristics, learner characteristics, and contextual factors that impact learning effectiveness in different e-learning environments. It also shows how the typology dimensions align with learning goals to influence learning effectiveness.