scholarly journals Statistical Analysis of Complex Problem-Solving Process Data: An Event History Analysis Approach

2019 ◽  
Vol 10 ◽  
Author(s):  
Yunxiao Chen ◽  
Xiaoou Li ◽  
Jingchen Liu ◽  
Zhiliang Ying
Keyword(s):  
Statistical Analysis ◽  
Problem Solving ◽  
Event History Analysis ◽  
Complex Problem ◽  
Event History ◽  
Analysis Approach ◽  
Complex Problem Solving ◽  
Process Data ◽  
History Analysis ◽  
Problem Solving Process

Game Design as a Complex Problem Solving Process

2017 ◽  
pp. 217-233 ◽  
Author(s):  
Mete Akcaoglu ◽  
Antonio P. Gutierrez ◽  
Charles B. Hodges ◽  
Philipp Sonnleitner
Keyword(s):  
Problem Solving ◽  
Middle School Students ◽  
Game Design ◽  
Formal Education ◽  
Complex Problem ◽  
Complex Problem Solving ◽  
School Students ◽  
Daily Lives ◽  
Problem Solving Process ◽  
System Knowledge

Problem solving is one of the most essential skills for individuals to be successful at their daily lives and careers. When problems become complex, solving them involves identifying relationships among a multitude of interrelated variables, to achieve multiple different possible solutions. Teaching Complex Problem Solving (CPS) skills in formal education contexts is challenging. In this research, we examined if through an innovative game-design course middle school students improved in their CPS skills. Our results showed that students showed significant improvements in their CPS skills, especially in terms of system exploration, t(10) = 2.787, p = .019; system knowledge, t(10) = 2.437, p = .35; system application, t(10) = 2.472, p = .033. In addition, there was a statistically significant change in students' interest for CPS after attending the GDL program, t(6) = 3.890, p = .008. We discuss implications regarding use of game-design tasks as contexts to teach CPS skills in formal and informal educational contexts.

Using process data to explain group differences in complex problem solving.

2020 ◽  
Vol 112 (8) ◽  
pp. 1546-1562
Author(s):  
Beate Eichmann ◽  
Frank Goldhammer ◽  
Samuel Greiff ◽  
Liene Brandhuber ◽  
Johannes Naumann
Keyword(s):  
Problem Solving ◽  
Complex Problem ◽  
Group Differences ◽  
Complex Problem Solving ◽  
Process Data

scholarly journals Latent Class Analysis of Recurrent Events in Problem-Solving Items

2018 ◽  
Vol 42 (6) ◽  
pp. 478-498 ◽  
Author(s):  
Haochen Xu ◽  
Guanhua Fang ◽  
Yunxiao Chen ◽  
Jingchen Liu ◽  
Zhiliang Ying
Keyword(s):  
Problem Solving ◽  
Latent Class Analysis ◽  
Recurrent Events ◽  
Latent Class ◽  
Complex Problem ◽  
Class Analysis ◽  
Complex Problem Solving ◽  
Climate Control ◽  
Process Data ◽  
International Student Assessment

Computer-based assessment of complex problem-solving abilities is becoming more and more popular. In such an assessment, the entire problem-solving process of an examinee is recorded, providing detailed information about the individual, such as behavioral patterns, speed, and learning trajectory. The problem-solving processes are recorded in a computer log file which is a time-stamped documentation of events related to task completion. As opposed to cross-sectional response data from traditional tests, process data in log files are massive and irregularly structured, calling for effective exploratory data analysis methods. Motivated by a specific complex problem-solving item “Climate Control” in the 2012 Programme for International Student Assessment, the authors propose a latent class analysis approach to analyzing the events occurred in the problem-solving processes. The exploratory latent class analysis yields meaningful latent classes. Simulation studies are conducted to evaluate the proposed approach.

Event History Analysis in Demography

1995 ◽  
Vol 49 (2) ◽  
pp. 355-357
Author(s):  
Johannes Huinink
Keyword(s):  
Event History Analysis ◽  
Event History ◽  
History Analysis

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.

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