Dissertation/Thesis Abstract

How Children Solve Engineering Design Problems: A Study of Design Process Patterns Using Sequential Analysis
by Sung, Euisuk, Ph.D., Purdue University, 2018, 214; 10843627
Abstract (Summary)

The ability to solve problems in creative and innovative ways is more critical than ever in today’s rapidly-changing society. To support these demands, the educational curricula in the U.S. and other countries adopted engineering design as a learning platform to promote students’ creativity, communication and design skills, and innovative problem-solving abilities. When using engineering design, many educators use a variety of engineering design process models. However, little is known about the problem-solving processes in terms of design cognition. Therefore, in this study, the researcher examined the problem-solving patterns of students who engage in engineering design using a cognitive pattern approach.

This study was conducted as part of the NSF-funded Science Learning through Engineering Design (SLED) project for elementary science students’ grades three to six. The researcher adopted the sequential analysis method to identify students' problem-solving patterns. Sequential analysis is a statistical research method to detect behavioral or psychological patterns by analyzing repeated cognitive events. The researcher sampled a total of 48 Concurrent Think-Aloud (CTA)sessions to examine the statistical significance of the sequential analysis. Two coders independently conducted data coding using Halfin’s codes and confirmed a high range of inter-rater reliability with 97.22 % overall agreements and .86 Kappa coefficients.

The first research question aimed to identify the common cognitive strategies used by elementary science students in engineering design. The researchers pooled 48 CTA sessions to investigate the common cognitive strategies. The results indicated that the students largely concentrated on idea generation (DE) and sketching (MO) while less emphasized on questioning (QH), predicting (PR), managing (MA), and analyzing (AN). Moreover, the researcher confirmed that the upper level graders showed higher frequencies of cognitive strategies than lower graders.

The second research question aimed to investigate the common problem-solving sequential patterns of the engineering design process. After pooling the 48 CTA sessions, the researcher analyzed the statistical significances of two-event sequential patterns using GSEQ software. The statistical analysis yielded 14 significant two-event sequential patterns at the right-tailed 0.05 level and two-sided z distribution. Using the significant sequential patterns, the researcher built a pattern-based design process model. The model illustrates various iterations between the problem and solution strategies. The iterations in the problem strategies showed recursive cycles between defining the problem, analyzing, and managing. The solution focused iterations often began with questioning and proceeded to designing and modeling or designing and predicting. Moreover, the pattern model shows that managing and questioning played a key role in bridging problem and solution strategies.

The third research question was to identify how the cognitive strategies vary by design tasks. The researcher compared eight engineering design tasks used in the SLED project and confirmed that the structure of design problems was associated with the students’ problem-solving strategies. The results of data analysis showed that the participant students commonly emphasized on Designing and Modeling strategies. However, the researcher found that the modeling-driven design tasks required accurate mechanical designing lead students’ high concentrations on the Modeling strategy.

The last research question was to identify the differences of cognitive problem-solving patterns by design tasks. The study analyzed eight engineering design tasks and each task pooled six CTA sessions. The results confirmed that higher graders’ design tasks showed more complicated design pathways than younger graders’ design tasks. Additionally, the researcher found that each design task yielded distinct problem-solving pattern models.

Based on these results, the researcher suggested that engineering and technology educators need to highlight the multiple pathways of the engineering design process. The results showed many alternative problem-solving pathways rather than the standardized process models. The researcher also proposed that when adopting an engineering design approach in elementary curriculum, the program developers need to align its design procedure with learners’ sequential patterns of the design process. Engineering design problems provide rich opportunities to develop the cognitive abilities of young students. Additionally, the researcher encourages engineering and technology education programs to adopt multiple design process models aligned with the corresponding design problem types.

Indexing (document details)
Advisor: Kelley, Todd Richard
Commitee: Mentzer, Nathan, Samarapungavan, Ala, Strimel, Greg
School: Purdue University
Department: Technology Leadership and Innovation
School Location: United States -- Indiana
Source: DAI-A 80/01(E), Dissertation Abstracts International
Subjects: Design, Elementary education, Engineering, Science education
Keywords: Design process, Problem solving, STEM, Sequential analysis, Technology education, Think-aloud
Publication Number: 10843627
ISBN: 978-0-438-36019-8
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