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Increased interest in team dynamics has resulted in new methods for measuring teamwork over time. The primary purpose of this chapter is to provide a survey of recent developments in teamwork/collaboration measurement in an educational context. Key topics include conceptual frameworks, large-scale assessments, and innovative measurement techniques.

A range of methods for collecting and analyzing teamwork data are discussed, and five frameworks for measuring collaborative problem solving (CPS) over time are compared. Frameworks from Programme for International Student Assessment (PISA), Assessment and Teaching of 21st Century Skills (ATC21S) project, Educational Testing Service (ETS), ACT, and von Davier and Halpin (2013) are discussed. Results of assessments developed from these frameworks are also considered.

New techniques for measuring team dynamics over time have great potential to improve education and work outcomes. Preliminary results of the assessments developed from these frameworks show that important advances in teamwork measurement have been enabled by innovative task designs, data-mining techniques, and novel applications of stochastic models.

This novel overview and comparison of interdisciplinary approaches will help to indicate where progress has been made and what challenges are ahead.

The pursuit of entrepreneurial opportunities is not always successful. On the one hand, entrepreneurial failure offers an invaluable opportunity for entrepreneurs to learn about their ventures and themselves. On the other hand, entrepreneurial failure is associated with substantial financial, psychological, and social costs. When entrepreneurs fail to learn from failure, the potential value of this experience is not fully utilized and these costs will have been incurred in vain. In this chapter, the authors investigate how the stigma of failure exacerbates the various costs of failure, thereby making learning from failure much more difficult. The authors combine an analysis of interviews of 20 entrepreneurs (who had, at the time of interview, experienced failure) with an examination of archival data reflecting the legal and cultural environment around their ventures. The authors find that stigma worsens the entrepreneurs’ experience of failure, hinders their transformation of failure experience, and eventually prevents them from utilizing the lessons learnt from failure in their future entrepreneurial activities. The authors discuss the implications of the findings for the entrepreneurship research and economic policies.

This chapter focuses on the state-of-the-art modeling approaches used in Intelligent Tutoring Systems (ITSs) and the frameworks for researching and operationalizing individual and group models of performance, knowledge, and interaction. We adapt several ITS methodologies to model team performance as well as individuals’ performance of the team members. We briefly describe the point processes proposed by von Davier and Halpin (2013), and we also introduce the Competency Architecture for Learning in teaMs (CALM) framework, an extension of the Generalized Intelligent Framework for Tutoring (GIFT) (Sottilare, Brawner, Goldberg, & Holden, 2012) to be used for team settings.

This chapter describes how conversational computer agents have been used in collaborative problem-solving environments. These agent-based systems are designed to (a) assess the students’ knowledge, skills, actions, and various other psychological states on the basis of the students’ actions and the conversational interactions, (b) generate discourse moves that are sensitive to the psychological states and the problem states, and (c) advance a solution to the problem. We describe how this was accomplished in the Programme for International Student Assessment (PISA) for Collaborative Problem Solving (CPS) in 2015. In the PISA CPS 2015 assessment, a single human test taker (15-year-old student) interacts with one, two, or three agents that stage a series of assessment episodes. This chapter proposes that this PISA framework could be extended to accommodate more open-ended natural language interaction for those languages that have developed technologies for automated computational linguistics and discourse. Two examples support this suggestion, with associated relevant empirical support. First, there is AutoTutor, an agent that collaboratively helps the student answer difficult questions and solve problems. Second, there is CPS in the context of a multi-party simulation called Land Science in which the system tracks progress and knowledge states of small groups of 3–4 students. Human mentors or computer agents prompt them to perform actions and exchange open-ended chat in a collaborative learning and problem-solving environment.

The increasing threat of global warming and climate change has been a major worldwide concern for more than two decades. As the achievement of sustainable economic growth has gradually become a major global concern both policy makers and researchers have given considerable attention over the years on the link among energy consumption, emissions and economic growth. In this study, following a solovian growth structure, the authors assume that the aggregate output depends on the stock of physical as well as human capital and energy or power. Depending on the sources, the energy can be categorised into cleaner input generated from renewable sources and a dirty input extracted from non-renewable resources having by-products like pollution. This study finds that less-developed countries (LDCs) failing to afford sufficient access to clean energy which in turn has deleterious impact on the human capital which cascades into low level of production, low saving and low per capita output forming a vicious loop. On the other side, the developed nations are better poised with access to clean energy and this is what is reflected in having larger reserve of human capital yielding higher production, higher income, higher saving and higher per capita capital stock in a circular process. This hence posits a clinching picturing divergence in per capital output and income between developed and less-developed nation mediated through degree of access to clean energy and thereof, the capacity to control emission. The convergence situation between the developed and the less-developed nations shows that each ends up with the relative energy mix below the threshold and it is not desirous for the world as a whole. In case of per capita emission, the divergence situation with the global level of emission is bit ambiguous.

The objective of the research is to explore the importance of online reputation management through some core concepts: technologies and entrepreneurship. Specifically, the research will explore how in a tourism ecosystem context, it is strategically relevant through the use of Big Data Analytics (BDA) to manage and improve online reputation management. An emphasis will also be placed on the concept of entrepreneurship and dynamic capabilities. Finally, the research also explores empowerment issue to shed some considerations on the development of tourists' online reviews.