scholarly journals Deep Flow: Scientific Schema for Complex Problem Solving

2020 ◽  
Author(s):  
Divya Sethi
Keyword(s):  
Problem Solving ◽  
Ad Hoc ◽  
Complete Solution ◽  
Complex Problem ◽  
Complex Problem Solving ◽  
Complex Problems ◽  
Problem Solvers ◽  
Information Streams ◽  
Intuitive Sense ◽  
At Will

Complex problem solvers are occasionally able to solve the problem by framing the problem properly and by engaging deeply to solve them. But there are times when the solvers experience an impasse and the problem just can’t be solved. We propose this as a pivoting point in complex problem solving, which requires the solver to, counter-intuitively, detach from the problem (instead of spending more effort in framing the problem and/or focusing on solving it). This disengagement prepares the ground for willful synthesis of both processed and unprocessed information streams – either automatically or through an interactive process. The outcome of synthesis is an aggregated solution which transcends the impasse and enables the solver to find an innovative and complete solution. This is often accompanied with a feeling of attunement, an intuitive sense of completeness. While it is possible to solve complex problems in an ad-hoc way, we outline a scientifically underpinned schema that governs this process. This process, which we refer to as Deep Flow, has four steps: (1) Frame, (2) Engage, (3) Disengage and (4) Synthesize. Deep Flow culminates in a feeling of attunement and creates positive affect. As solvers intentionally engage with Deep Flow, they can invoke the necessary steps at will. It empowers solvers to solve complex complex problems efficiently; also, the sense of attunement inspires them to tackle more complex problems in a comprehensive manner.

scholarly journals Interdisciplinarity and transdisciplinarity

2021 ◽  
Vol 45 (1) ◽  
pp. 67-73
Author(s):  
Igor Toš
Keyword(s):  
Problem Solving ◽  
Scientific Knowledge ◽  
Interdisciplinary Collaboration ◽  
Complex Problem ◽  
Complex Problem Solving ◽  
Cultural Traditions ◽  
Research And Practice ◽  
Complex Problems ◽  
Transdisciplinary Collaboration ◽  
General Culture

The production of new scientific knowledge and practical solutions to complex problems require increasing amounts of interdisciplinary collaboration, while requirements for transdisciplinary cooperation have recently likewise become more frequent. In practice, however, they are rarely implemented adequately; what occurs instead is merely multidisci­plinary collaboration. True implementation of inter- and/or transdisciplinary collaboration is often met with certain difficulties and obstacles: problems due to limited disciplinary competence, problems due to protecting knowledge and power, the problem of competence required for inter- and transdisciplinary collaboration, complexity problems, method­ological problems and problems caused by differences in cultural traditions. It is necessary to acquire clear general defi­nitions of the concepts of multidisciplinarity, interdisciplinarity and transdisciplinarity, to define and implement general guidelines for the development of multidisciplinary and transdisciplinary practice and to develop a new general culture of collaboration in research and practice of complex problem-solving.

scholarly journals Development of Perceived Complex Problem-Solving Instrument in Domain of Complex Systems

Systems ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 51
Author(s):  
Morteza Nagahi ◽  
Alieh Maddah ◽  
Raed Jaradat ◽  
Mohammad Mohammadi
Keyword(s):  
Problem Solving ◽  
Complex Systems ◽  
Systems Thinking ◽  
21St Century ◽  
Complex Problem ◽  
Complex Problem Solving ◽  
Final Model ◽  
Complex Problems ◽  
High Level ◽  
The Relationship

The ability to solve modern complex systems becomes a necessity of the 21st century. The purpose of this study is the development of an instrument that measures an individual’s perception toward solving complex problems. Based on literature and definitions, an instrument with four stages named perceived complex problem-solving (PCPS) was designed through exploratory and confirmatory stages. The instrument is validated and scaled through different models, and the final model is discussed. After completing validation and scale development of the PCPS instrument, the final model of the PCPS instrument was introduced to resolve the gap in the literature. The final model of the PCPS instrument is able to find and quantify the degree of perception an individual holds in dealing with complex problems and can be utilized in different settings and environments. Further research about the relationship between Systems Thinking and CPS revealed individuals with a high level of systems thinking have a better understanding of the characteristics of complex problems and so better perception of CPS.

Promoting Effective Student Problem Solving

2007 ◽  
Author(s):  
J. C. Bennett
Keyword(s):  
Problem Solving ◽  
Engineering Education ◽  
Student Development ◽  
Engineering Students ◽  
Complex Problem ◽  
Course Development ◽  
Complex Problem Solving ◽  
Problem Solvers ◽  
Student Problem ◽  
Effective Problem

If one were to ask most anyone what engineers do, they would say “solve problems.” And indeed, engineers do [but I would suggest that all people solve problems regardless of their chosen careers]. What are less obvious are [a] whether engineering students and graduates are effective problem solvers; [b] whether engineering education is facilitated effectively as a “problem to be solved” and [c] whether that engineering education intentionally facilitates the development by students of an effective problem solving approach. In this paper, it is argued that instructors use of effective problem solving in course development, preparation, and facilitation must include the explicit attention to the student development of effective problem solving procedures. In this paper, it is argued that students will become more effective problem solvers if instructors encourage them to use procedures that embrace ambiguity and if instructors more consistently expect them to apply the procedures to open-ended problems throughout the curriculum. As students move from well-defined problem solving to more complex problem solving, they will benefit from one general and effective problem-solving procedure that is sufficiently flexible to include the various and more specific procedures that students will encounter. With career paths continually evolving and with information generation growth ever expanding, such skills are absolutely critical to success, again regardless of career choice.

Extending the Assessment of Complex Problem Solving to Finite State Automata

2015 ◽  
Vol 31 (3) ◽  
pp. 181-194 ◽  
Author(s):  
Jonas C. Neubert ◽  
André Kretzschmar ◽  
Sascha Wüstenberg ◽  
Samuel Greiff
Keyword(s):  
Problem Solving ◽  
Complex Problem ◽  
Assessment Instruments ◽  
Finite State Automata ◽  
Complex Problem Solving ◽  
Domain Specific ◽  
Complex Problems ◽  
Specific Subset ◽  
Formal Framework ◽  
Finite State

Abstract. Recent advancements in the assessment of Complex Problem Solving (CPS) build on the use of homogeneous tasks that enable the reliable estimation of CPS skills. The range of problems featured in established instruments such as MicroDYN is consequently limited to a specific subset of homogeneous complex problems. This restriction is problematic when looking at domain-specific examples of complex problems, which feature characteristics absent from current assessment instruments (e.g., threshold states). We propose to utilize the formal framework of Finite State Automata (FSA) to extend the range of problems included in CPS assessment. An approach based on FSA, called MicroFIN, is presented, translated into specific tasks, and empirically investigated. We conducted an empirical study (N = 576), (1) inspecting the psychometric features of MicroFIN, (2) relating it to MicroDYN, and (3) investigating the relations to a measure of reasoning (i.e., CogAT). MicroFIN (1) exhibited adequate measurement characteristics and multitrait-multimethod models indicated (2) the convergence of latent dimensions measured with MicroDYN. Relations to reasoning (3) were moderate and comparable to the ones previously found for MicroDYN. Empirical results and corresponding explanations are discussed. More importantly, MicroFIN highlights the feasibility of expanding CPS assessment to a larger spectrum of complex problems.

Complex Problem Solving and Worked Examples

2009 ◽  
Vol 23 (2) ◽  
pp. 129-138 ◽  
Author(s):  
Florian Schmidt-Weigand ◽  
Martin Hänze ◽  
Rita Wodzinski
Keyword(s):  
Problem Solving ◽  
Cognitive Load ◽  
Learning Experience ◽  
Worked Examples ◽  
Complex Problem ◽  
Complex Problem Solving ◽  
Strategic Learning ◽  
Learning Behavior ◽  
Worked Example ◽  
8Th Grade

How can worked examples be enhanced to promote complex problem solving? N = 92 students of the 8th grade attended in pairs to a physics problem. Problem solving was supported by (a) a worked example given as a whole, (b) a worked example presented incrementally (i.e. only one solution step at a time), or (c) a worked example presented incrementally and accompanied by strategic prompts. In groups (b) and (c) students self-regulated when to attend to the next solution step. In group (c) each solution step was preceded by a prompt that suggested strategic learning behavior (e.g. note taking, sketching, communicating with the learning partner, etc.). Prompts and solution steps were given on separate sheets. The study revealed that incremental presentation lead to a better learning experience (higher feeling of competence, lower cognitive load) compared to a conventional presentation of the worked example. However, only if additional strategic learning behavior was prompted, students remembered the solution more correctly and reproduced more solution steps.

The Prediction of Problem-Solving Assessed Via Microworlds

2016 ◽  
Vol 32 (4) ◽  
pp. 298-306 ◽  
Author(s):  
Samuel Greiff ◽  
Katarina Krkovic ◽  
Jarkko Hautamäki
Keyword(s):  
Working Memory ◽  
Problem Solving ◽  
Complex Problem ◽  
Two Dimensions ◽  
Assessment Instruments ◽  
Complex Problem Solving ◽  
Visual Spatial ◽  
Rule Knowledge ◽  
Rule Application ◽  
Fluid Reasoning

Abstract. In this study, we explored the network of relations between fluid reasoning, working memory, and the two dimensions of complex problem solving, rule knowledge and rule application. In doing so, we replicated the recent study by Bühner, Kröner, and Ziegler (2008) and the structural relations investigated therein [ Bühner, Kröner, & Ziegler, (2008) . Working memory, visual-spatial intelligence and their relationship to problem-solving. Intelligence, 36, 672–680]. However, in the present study, we used different assessment instruments by employing assessments of figural, numerical, and verbal fluid reasoning, an assessment of numerical working memory, and a complex problem solving assessment using the MicroDYN approach. In a sample of N = 2,029 Finnish sixth-grade students of which 328 students took the numerical working memory assessment, the findings diverged substantially from the results reported by Bühner et al. Importantly, in the present study, fluid reasoning was the main source of variation for rule knowledge and rule application, and working memory contributed only a little added value. Albeit generally in line with previously conducted research on the relation between complex problem solving and other cognitive abilities, these findings directly contrast the results of Bühner et al. (2008) who reported that only working memory was a source of variation in complex problem solving, whereas fluid reasoning was not. Explanations for the different patterns of results are sought, and implications for the use of assessment instruments and for research on interindividual differences in complex problem solving are discussed.

Sign in / Sign up

Export Citation Format

Share Document