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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.

Team cognition research continues to evolve as the need for understanding and improving complex problem solving itself grows. Complex problem solving requires members to engage in a number of complicated collaborative processes to generate solutions. This chapter illustrates how the Macrocognition in Teams model, developed to guide research on these processes, can be utilized to propose how intelligent tutoring systems (ITSs) could be developed to train collaborative problem solving. Metacognitive prompting, based upon macrocognitive processes, was offered as an intervention to scaffold learning these complex processes. Our objective is to provide a theoretically grounded approach for linking intelligent tutoring research and development with team cognition. In this way, team members are more likely to learn how to identify and integrate relevant knowledge, as well as plan, monitor, and reflect on their problem-solving performance as it evolves. We argue that ITSs that utilize metacognitive prompting that promotes team planning during the preparation stage, team knowledge building during the execution stage, and team reflexivity and team knowledge sharing interventions during the reflection stage can improve collaborative problem solving.

In a variety of domains, teams represent the main mechanism for dealing with change, complexity, and uncertainty in organizations. Consequently, teams need to be able to adapt and effectively use shared and complementary cognitive processing while collaborating to deal with these challenges.

A conceptual review is provided that addresses this type of complex collaborative cognition via discussion of macrocognition and the processes contributing to effective team problem-solving.

Despite extensive research on problem-solving, research and theories regarding how problem-solving changes over time as teams develop is missing. With this review, we extend research on team problem-solving and team development through integration of existing theory and concepts from the team literature.

This review provides a theoretical foundation for understanding and studying the developmental dynamic of team problem-solving.

A team problem-solving development model is described which outlines the degree to which the primary elements of team development are likely to affect macrocognitive processes within problem-solving phases. A set of propositions is offered in order to guide research on team development in collaborative problem-solving.

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.

This chapter looks at how Goal 17 on partnerships can be a lever of change. It discusses the partnership approach to achieving the SDGs and unravels the key functions of networks and partnerships, such as knowledge sharing, coordination, and collaborative governance. It carefully explains why we need to shift the focus of the global debate from collaborative governance to the cocreation of public value outcomes. It then provides a schematic account of the different steps in the process of cocreating outcomes, which include initiation, design, implementation, and evaluation. Finally, the chapter identifies the key merits of cocreation and looks its dark side straight in the eye.

Over the past decade the policy debate over improving U.S. public education has focused on market solutions (charter schools, privatization, and vouchers) and teacher evaluation through high stakes standardized testing of students. In this debate, teachers and their unions are often characterized as the problem. Our research offers an alternate path in the debate, a perspective that looks at schools as systems – the way schools are organized and the way decisions are made. We focus on examples of collaboration through the creation of long-term labor-management partnerships among teachers’ unions and school administrators that improve and restructure public schools from the inside to enhance planning, decision-making, problem solving, and the ways teachers interact and schools are organized. We analyzed how these efforts were created and sustained in six public school districts over the past two decades, and what they can teach us about the impact of significant involvement of faculty and their local union leadership, working closely with district administration. We argue that collaboration between teachers, their unions, and administrators is both possible and necessary for any meaningful and lasting public school reform.

Despite the existence of legislation and policy, the inclusion of students with special needs remains a challenge for teachers when research-based pedagogies and collaboration are not translated into practice. Given emerging Indexes for inclusion, perhaps we should be attending to measuring school and classroom indicators of inclusive education to allow for professional development for teachers in an empirical and guided manner. Following a brief introduction to the importance of inclusive practice in schools, this chapter will address teacher use of research-based pedagogies and curriculum differentiation required to enhance success with students in schools; teachers’ capacity to communicate about learning using professional language and collaborative problem-solving processes; teachers’ sense of self-efficacy when working with students who have special needs; and translation of these research-based skills into actual classroom practice.

This chapter reports on the design-based research study aimed at the re- and codesign of the third-year course “Introduction to Biostatistics,” part of the Bachelor program in Medicine. The authors aimed to make teaching more interactive, student-based and future-proof by empirically testing theoretical assumptions during iterative studies, including both quantitative and qualitative results from the perspective of the students and the teacher. The authors’ conclusion is that teacher–researcher collaboration can be an effective approach for professional development and improving innovative practices. At the same time, it allows to get a better theoretical understanding of effective teaching and learning practices. The authors hope that this chapter can inspire others to transform toward a progressive institution and looking for concrete innovative classroom practices in the context of innovative learning spaces.