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The question facing sociology is whether it is a field or a discipline. If it is a field, then there is no need for theorizing. However, if sociology is a discipline, then problem-solving cannot be disentangled from theorizing without a loss of intelligibility – the inability to explain the social as the concept of the discipline. Through the quasi-realism of problem-solving as a course of activity, this chapter presents cognitive sociology as a paradigm appropriate to the concept of the social understood as an ongoing course of activity. In doing so, it is shown how bounded rationality and expertise play a crucial role in how communication interacts with the division of cognitive labor, especially through the idea of representational representationality. Representational representationality is an idea that reveals how the degree of clarity among language, meaning, and thought is relative to the issues of audience and ignorance. Representational representationality is significant because it demonstrates how the relationship among meaning, language, and thought is subject to communicative errors – errors arising from a predicament of intelligibility and not merely arising from issues of computational skill, as described by Herbert Simon's model of bounded rationality and expertise in human problem-solving. The argument that follows from this shows how the means for adapting to ambiguity amounts to the difference between Simon's model and a quasi-real model in terms of its principle of rationality, principle of efficiency, and its cognitive style of problem-solving for deliberate practice. These dimensions are shown to effect what “examples” are good for in the problem-solving process, thereby revealing the politics of expertise. The politics of expertise demonstrates how the conflicts in sociological explanations of strategy are not merely conflicts that can be set aside as a pluralism of values. Rather, the conflicting explanations of theory and theorizing can only be resolved when the situational rationality of sociology as a discipline realizes the quasi-realism of problem-solving as a course of activity.

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.

The goal of this study was to examine individual, relational, and organizational determinants of negotiation behavior (problem solving, contending, yielding, and avoiding) between planning and marketing departments in manufacturing organizations. Results from a study among 41 managers and 85 planning and marketing employees within 11 firms showed that individual personality, perceived interdepartmental interdependence, and organizational strategy were each related to the negotiation behavior of department members. Desirable negotiation behavior—specifically, the problem‐solving approach—was more likely when individuals were extraverted and agreeable, when employees perceived high interdepartmental interdependence, and when organizations did not have a low‐cost strategy. Contending was more likely when individuals were extraverted and disagreeable, and yielding was more likely when department members perceived a power advantage vis‐à‐vis the other department. All four styles of negotiation behavior were more likely the less the organizations had a low‐cost strategy. These findings provide guidance to organizations in their efforts to encourage constructive negotiation behavior between departments.

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.

This study investigated the problem-solving strategies used in solving problems in the learning domain of numbers and operations in mathematics textbooks for Turkish middle schools.

To this end, four middle school mathematics textbooks published by the Ministry of National Education of Turkey (MEB in Turkish), one from each grade level (Grades 5–8), were examined. The data in this document analysis study were analyzed using semantic content analysis.

The findings revealed that mathematics textbooks' most used problem-solving strategies for each level were drawing a figure (diagram), writing equality and inequality, making a table and making a systematic list. Drawing a diagram (figure) strategy was the most used strategy at each grade level, while working backwards was the least used one. Another finding was that finding a pattern and solving a simpler analogous problem strategies were rarely used at each grade level.

This study points out how problem-solving strategies used Grades 5-8 mathematics textbooks in a different culture like Türkiye. So, it may also give some important clues for applying problem-solving strategies in mathematics classrooms in a different culture.

This study may draw the attention of educational stakeholders and textbook authors who want to understand and implement problem-solving strategies in mathematics classrooms by considering a different cultural perspective.

This study may point to the importance of using problem-solving strategies in mathematics and daily and social learning environments due to the nature of mathematical problem-solving and problem-solving strategies.

This document review study examined the problem-solving strategies used in Turkish middle school mathematics textbooks, and the data were analyzed using semantic content analysis. The findings revealed that mathematics textbooks' most used problem solving strategies for each level were drawing a figure (diagram), writing equality and inequality, making a table and making a systematic list. Drawing a diagram (figure) strategy was the most used strategy at each grade level, while working backwards was the least used one. Another finding was that finding a pattern and solving a simpler analogous problem strategies were rarely used at each grade level.

This paper aims to delve into the complexity and multiplicity of consumer experiences in relation to mobile and virtual technology, and provides a lived-experience account of the Consumer Immediacy Pandemic (CIP) and related consumer experiences and responses.

Using open-ended, in-depth interviews, as well as personal essays, the research questions are addressed through the interpretive hermeneutic approach.

The CIP is an important, multifaceted consumer shift, whose ramifications are traceable in consumer behavior. It encompasses three consumer problem-solving styles (i.e. real-time, mobile and virtual problem-solving). Consumers adapt to the CIP through such strategies as unbundling of presence, temporal gain and synchronization, task continuity, work-fun integration and multi-tasking.

With conventional theories ineffectively explaining consumer experiences with such products as smart phone, social media and selfie stick, this paper provides fruitful directions for studying consumer-technology relationships.

The findings point to untapped and novel needs rooted in consumer experience with mobile and virtual technology such as the needs for personal information management and/or professional counseling.

The paper provides evidence as to a deep-seated shift in the role of technology in consumer life. Underestimating the ongoing and future success and power of mobile and virtual technology can be too costly for society at large.

This study exposes the dialogical interplay between consumer agency and structural influences that compels consumers to internalize immediacy as a taken-for-granted expectation. Such pandemic alters the ways consumers go about satisfying their needs and wants. The findings can help understand the twenty-first century consumer, theorize product agency and chart marketing and policy directions.

This study examined the impact of perceived threat and cohesion on the ability of groups to solve problems in a situation of social conflict. The self‐reports and behaviors of 31 groups of college males were studied within a comprehensive, strategic simulation of intergroup conflict. The simulation was based on both a value conflict and an economic competition over scarce resources. A coding scheme for group problem solving was created based in part on Janis' seven symptoms of groupthink. Change scores were calculated over different points in time to assess the relationships among perceived threat, group cohesion, and dysfunctional group problem solving. Large increases in perceived threat were significantly related to decrements in problem‐solving effectiveness regardless of whether cohesion was stable or increased. Groups who reported high and increasing levels of cohesion experienced a decrement in problem solving regardless of the increase in perceived threat, while groups who showed small changes in cohesion demonstrated decreased problem solving under high perceived threat. The results were consistent with Janis' model of groupthink, and Fisher's eclectic model of intergroup conflict.

The purpose of this study is to develop an intelligent tutoring system (ITS) for programming learning based on information tutoring feedback (ITF) to provide real-time guidance and feedback to self-directed learners during programming problem-solving and to improve learners’ computational thinking.

By analyzing the mechanism of action of ITF on the development of computational thinking, an ITF strategy and corresponding ITS acting on the whole process of programming problem-solving were developed to realize the evaluation of programming problem-solving ideas based on program logic. On the one hand, a lexical and syntactic analysis of the programming problem solutions input by the learners is performed and presented with a tree-like structure. On the other hand, by comparing multiple algorithms, it is implemented to compare the programming problem solutions entered by the learners with the answers and analyze the gaps to give them back to the learners to promote the improvement of their computational thinking.

This study clarifies the mechanism of the role of ITF-based ITS in the computational thinking development process. Results indicated that the ITS designed in this study is effective in promoting students’ computational thinking, especially for low-level learners. It also helped to improve students’ learning motivation, and reducing cognitive load, while there’s no significant difference among learners of different levels.

This study developed an ITS based on ITF to address the problem of learners’ difficulty in obtaining real-time guidance in the current programming problem-solving-based computational thinking development, providing a good aid for college students’ independent programming learning.

This paper aims to investigate the effect of parent–adolescent conflict in step versus biological families on family communication patterns (FCPs) and the conflict resolution strategy adopted by adolescents during family destinations or holiday planning (where to visit?).

The literature on family conflict (i.e. parent–adolescent conflict) and the different types of families (step vs nuclear) supported the proposed framework. The survey was conducted in the Indian subcontinent with a sample size of 437 adolescents. SPSS 22.0 was used for factor analysis (exploratory and confirmatory factor analysis) and structural equation modelling was used through AMOS 26.0 for data analysis.

Significant relationship was observed between the types of families (step and biological), FCP and the resolution strategy chosen by Indian adolescents. Adopting a resolution strategy by adolescents in both families depends on the type of FCP in the family. Adolescents in stepfamilies have socio-oriented FCP and use “positive problem-solving” and “conflict withdrawal” as a resolution strategy. In contrast, adolescents in biological families have concept-oriented families and use “conflict enhancement” as a resolution strategy. It has also been found that adolescents who fall into high-stress categories used conflict enhancement strategies. In contrast, those who fall under low-stress categories used positive problem-solving and withdrawal strategies.

This study will add a new chapter to adolescents’ decision-making literature in line with the previous research. It has practical implications for tourism marketers, academicians/researchers and policymakers. Marketers can segment adolescents into step versus biological families, and the choice of resolution strategies may introduce efficient and competent marketing strategies and promotional campaigns.

This study favours that family type is a robust construct to predict adolescents’ choice of resolution strategy. So, it is one of the most influential variables in adolescents’ resolution strategy adoption.