External information sources in computer programming. The role of textual and graphical representations in support of complex problem solving activities

1996 ◽  
Author(s):  
S.P. Davies
2014 ◽  
Vol 19 (1-2) ◽  
pp. 127-146 ◽  
Author(s):  
Sascha Wüstenberg ◽  
Matthias Stadler ◽  
Jarkko Hautamäki ◽  
Samuel Greiff

2020 ◽  
Vol 4 (3) ◽  
pp. 58
Author(s):  
Vitalii Epishin ◽  
Nataliya Bogacheva

Current studies of complex problem-solving do not commonly evaluate the regulatory role of such personality-based variables as tolerance for uncertainty, risk-readiness, and patterns for coping with decisional conflict. This research aims to establish the contribution of those traits into individual parameters of complex problem-solving strategies. The study was conducted on 53 healthy individuals 17 to 29 years old (M = 20.42; SD = 2.34). Our own computerized complex problem task “The Anthill” was developed for this research. We identified five measurable parameters of the participants’ problem-solving strategies: preferred orientational level (POL); orientational level variability (OLV); class quotas‘ range (R); mean and median quotas shift (MS and MeS); and abrupt changes of strategy (AC). Psychodiagnostic methods included: new questionnaire of tolerance/intolerance for uncertainty; personal decision-making factors questionnaire; Melbourne Decision Making Questionnaire; Subjective Risk Intelligence Scale; Eysencks’ Impulsiveness Scale. The study showed the role of tolerance for uncertainty, risk-readiness, negative attitude toward uncertainty, and decision-making styles in the regulation of complex problem-solving strategies. Specifically, procrastination, tolerance for uncertainty, and risk-readiness were significant predictors of individual strategy indicators, such as POL, OLV, and MeS. Thus, personality traits were shown to regulate resource allocation strategies and the required level of orientation in a complex problem.


2017 ◽  
Vol 6 (1) ◽  
pp. 27-43 ◽  
Author(s):  
Bart Garssen

Abstract This paper focuses on the role of the argument by example in the argumentation put forward by Members of the European Parliament. The argumentative patterns that come into being in legislative debates in the European Parliament depend for the most part on the problem-solving argumentation that is put forward in the opening speech by the rapporteur of the parliamentary committee report. Complex problem-solving argumentation consists of a premise stating that there is a problem (the problem statement) and a premise stating that the proposed legislation will solve the problem (the causal statement). In their contributions, MEPs who are in favor of the proposal will either defend the problem statement or the causal statement. This paper examines how an argument by example is used in order to defend the problem statement. The argument by example can be used to defend the existential presupposition as well as the normative presupposition in the problem-statement.


2017 ◽  
Vol 8 ◽  
Author(s):  
C. Dominik Güss ◽  
Madison Lee Burger ◽  
Dietrich Dörner

2019 ◽  
Vol 128 ◽  
pp. 1-12 ◽  
Author(s):  
Beate Eichmann ◽  
Frank Goldhammer ◽  
Samuel Greiff ◽  
Liene Pucite ◽  
Johannes Naumann

2009 ◽  
Vol 23 (2) ◽  
pp. 129-138 ◽  
Author(s):  
Florian Schmidt-Weigand ◽  
Martin Hänze ◽  
Rita Wodzinski

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.


2016 ◽  
Vol 32 (4) ◽  
pp. 298-306 ◽  
Author(s):  
Samuel Greiff ◽  
Katarina Krkovic ◽  
Jarkko Hautamäki

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.


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