The co-construction of campaign argumentation on U.S.A. late-night talk shows

This study shows that when presidential candidates visit, late-night talk show discourse is argumentative, and that this argumentation is co-constructed by the host and the candidate. Through their questions, hosts implicitly invoke arguments by casting doubt on the candidate’s presidential bid. By treating the host’s questions as critical questions expressing skepticism whether people should vote for the candidate, politicians prototypically use two types of argument schemes to defend their case. First, to argue that their policy proposals are needed, candidates use complex problem-solving argumentation. Second, to maintain that they have the skills and character to succeed as president, candidates use symptomatic argumentation. In their response, candidates also deal with other critical questions belonging to the argument scheme invoked through the host’s question. Which critical questions of that argument scheme the candidate addresses in addition to the one posed by the host depends on the type of question the host has asked.

Analyzing Complex Problem Solving by Dynamic Brain Networks

Complex problem solving is a high level cognitive task of the human brain, which has been studied over the last decade. Tower of London (TOL) is a game that has been widely used to study complex problem solving. In this paper, we aim to explore the underlying cognitive network structure among anatomical regions of complex problem solving and its subtasks, namely planning and execution. A new computational model for estimating a brain network at each time instant of fMRI recordings is proposed. The suggested method models the brain network as an Artificial Neural Network, where the weights correspond to the relationships among the brain anatomic regions. The first step of the model is preprocessing that manages to decrease the spatial redundancy while increasing the temporal resolution of the fMRI recordings. Then, dynamic brain networks are estimated using the preprocessed fMRI signal to train the Artificial Neural Network. The properties of the estimated brain networks are studied in order to identify regions of interest, such as hubs and subgroups of densely connected brain regions. The representation power of the suggested brain network is shown by decoding the planning and execution subtasks of complex problem solving. Our findings are consistent with the previous results of experimental psychology. Furthermore, it is observed that there are more hubs during the planning phase compared to the execution phase, and the clusters are more strongly connected during planning compared to execution.

Do social identity and cognitive diversity correlate in environmental stakeholders? A novel approach to measuring cognitive distance within and between groups

Groups with higher cognitive diversity, i.e. variations in how people think and solve problems, are thought to contribute to improved performance in complex problem-solving. However, embracing or even engineering adequate cognitive diversity is not straightforward and may even jeopardize social inclusion. In response, those that want to promote cognitive diversity might make a simplified assumption that there exists a link between identity diversity, i.e. range of social characteristics, and variations in how people perceive and solve problems. If this assumption holds true, incorporating diverse identities may concurrently achieve cognitive diversity to the extent essential for complex problem-solving, while social inclusion is explicitly acknowledged. However, currently there is a lack of empirical evidence to support this hypothesis in the context of complex social-ecological systems—a system wherein human and environmental dimensions are interdependent, where common-pool resources are used or managed by multiple types of stakeholders. Using a fisheries example, we examine the relationship between resource stakeholders’ identities and their cognitive diversity. We used cognitive mapping techniques in conjunction with network analysis to measure cognitive distances within and between stakeholders of various social types (i.e., identities). Our results empirically show that groups with higher identity diversity also demonstrate more cognitive diversity, evidenced by disparate characteristics of their cognitive maps that represent their understanding of fishery dynamics. These findings have important implications for sustainable management of common-pool resources, where the inclusion of diverse stakeholders is routine, while our study shows it may also achieve higher cognitive coverage that can potentially lead to more complete, accurate, and innovative understanding of complex resource dynamics.

Thai information and communication technology student teacher complex problem-solving skills

From the study’s qualitative analysis, 5 latent variables and 21 observed variables concerning complex problem-solving (CPS) skills were identified and subsequently used in a questionnaire on a sample of 214 Thai education professionals teaching information and communication technology (ICT)-related student teachers in one of 31 Thai Rajabhat (teaching) Universities. Goodness-of-fit and descriptive statistical analysis (mean and standard deviation) were analysed by using IBM® Statistical Package for the Social Sciences® for Windows version 21, while the second-order confirmatory factor analysis used LISREL 9.10. The results revealed that the educators perceived information literacy (1.00), analytical thinking (0.96), self-control (0.93), knowledge application (0.90) and planning ability (0.85) as the most important for the student teachers’ CPS skills. Moreover, the results revealed that each teacher’s opinion on CPS skill indicators was at a ‘high agreement’ level. Therefore, it suggested that the results can be used by Thailand’s Ministry of Education and other ICT-related education agencies in developing CPS skill programmes for Thai student teachers. Keywords: CPS, ICT, Information literacy, preservice teachers, Thailand

Teaching Systems Thinking in Higher Education

Systems thinking is recognized as an essential skill for understanding complex problem solving and decision making associated with many of the contemporary issues faced by individuals and communities. In this article, our goal is to contribute to the knowledge of curriculum and pedagogy of formal systems thinking teaching in higher education. We believe that accumulating this knowledge can provide a better foundation for including systems thinking in higher-educational programs. To achieve this goal, the purpose of this study is to examine whether the use of a set of systems thinking concepts and methods can effectively promote systems thinking in higher-education settings. The study shows that systems thinking skills can be promoted effectively through the delivery of a combination of systems thinking methods and concepts.

Assessing Complex Problem-Solving Skills in Under 20 Minutes

Rationale: Assessing complex problem-solving skills (CPS) is of great interest to many researchers. However, existing assessments require long testing times making them difficult to include in many studies and experiments. Here, we propose a specific composition of microworlds based on the MicroDYN approach, which allows for valid estimation of CPS in a substantially reduced amount of time (<20 min). Methods: Based on the reanalysis of a sample of N = 232 university students who worked on 11 microworlds of increasing difficulty, we conducted multiple confirmatory factor analyses to test all possible combinations of microworlds, which were theoretically justified in advance. Results/Discussion: We demonstrate one best fitting set with five microworlds, which shows excellent factorial validity and relates to both conventional measures of intelligence and to school grades. We hope that this will allow other researchers to include CPS into their study designs even when testing time is limited.