Advancing research on engineering design using e-Journal

Febrian, Andreas; Lawanto, Oenardi; Cromwell, Matthew

doi:10.1109/fie.2015.7344191

Cited by 6 publications

(3 citation statements)

References 3 publications

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“…Precisely, the BCM imposes that all self-regulation activities are influenced by multiple layers of context , 2005Butler et al, 2017;, such as students' awareness of themselves (e.g., their experience or strengths), academic culture, computer science (CS) as a discipline, and concepts, standards, and best practices in programming. This contextual characteristic makes BCM flexible because it can be and has been used to describe CS and engineering students' SR (Febrian, Lawanto, & Cromwell, 2015;Lawanto, 2010;Santoso, 2013).…”

Section: Self-regulation and Task Interpretationmentioning

confidence: 99%

Do Computer Science Students Understand Their Programming Task?—A Case Study of Solving the Josephus Variant Problem

Febrian¹,

Lawanto²

2018

IES

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The ability of students to problem solve begins with interpreting the problem. When they interpret the problem inaccurately, they will likely use ineffective strategies or fail to solve the problem. Studies reported students are often incapable of identifying and articulating the problem goal, requirements/constraints, and expected output. In other words, students lack self-regulation skills, especially related to task understanding. In this study, two male and two female senior computer science students from Utah State University, USA, were recruited as research participants to learn more about their task understanding skills while engage in programming tasks. The participants were asked to answer five programming problems while thinking aloud, and their responses were video- and audio-recorded. This report focuses on one of the problems, which was a variant of the Josephus problem. Three research questions were used to guide the analysis: (a) what were the participants’ initial task understanding; (b) how did it change during the problem-solving endeavor; and (c) why did it change. All participants identified the problem goal inaccurately and as a result, selected ineffective problem-solving strategies. The analysis suggested their inaccurate task interpretations were caused by their confidence bias (i.e., a systematic cognitive error), in which they drew knowledge and strategies from irrelevant experience. Out of four participants, only one was able to defeat the confidence bias and acquired an accurate task understanding; the influencing factors and possible interventions to overcome confidence bias are discussed.

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Section: Self-regulation and Task Interpretationmentioning

confidence: 99%

Do Computer Science Students Understand Their Programming Task?—A Case Study of Solving the Josephus Variant Problem

Febrian¹,

Lawanto²

2018

IES

Self Cite

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“…This has yielded insights into the psychological processes involved in design, however it is time consuming, and is not always appropriate for data collection or analysis of design classes [10], nor useful for instructors attempting to evaluate their own classes. A design-specific e-journal is available to collect project-based design data from authentic class projects [11]. The data is very rich in context as the students treat it like an electronic design notebook, however it requires researchers and expert designers to retrospectively code the tasks that were documented in the journal, and does not collect quantitative data regarding time distribution of students on design processes, or gather data on student self-efficacy in design.…”

Section: Introductionmentioning

confidence: 99%

An Evaluation of an Engineering Design Class using Mixed Methods Techniques

Moyne¹,

Herman²,

Walsh³

et al.

2018 ASEE Annual Conference &Amp; Exposition Proceedings

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“…Using the eJ, we collected participants' plan, design journal, design artifacts, and eJ-related activities (i.e., checking the teams' progress on designing wheelchair assist). For the participants, the eJ could serve as a communication channel among the team members that allowed them to update and access design progress anytime at anywhere [53]. Prior to the data collections, all teams received an hour workshop about the eJ and its potential.…”

Section: Data Collection and Analysismentioning

confidence: 99%

Students' Self-regulation in a Senior Capstone Design Context: A Comparison Between Mechanical and Biological Engineering Design Projects

Febrian¹,

Lawanto²

2017 ASEE Annual Conference &Amp; Exposition Proceedings

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He received his bachelor and master degree in computer science (CS) from Universitas Indonesia, one of the top university in Indonesia. He was an active student who involved in various activities, such as research, teaching assistantship, and student organizations in the campus. He developed various CS skills through courses and research activities, especially in computer architecture, robotics, and web development. Through being a teaching assistant and joining student organizations, he developed an interest in psychology and Affective Computing. Currently, pursuing the Doctoral degree in Engineering Education at Utah State University with focuses in self-regulated learning in engineering design. Self-regulated learning (SRL), which is often called self-regulation, is a complex repository of knowledge and skills for planning, implementing, monitoring, evaluating, and continually improving the learning process. Studies suggest that the recursive, dynamic, multidirectional, and complex nature of self-regulated learning always occur in a context. This study intent to learn about the influence of contexts on students' self-regulation during the Capstone design course by comparing the biological engineering (BE) and the mechanical & aerospace engineering (MAE) students' self-regulation activities. We recruited four senior student groups. They worked in four different Capstone design projects at a public university in the mountain west of the United States of America. Two groups were recruited from the BE department, and another two groups were recruited from the MAE department. Various qualitative and quantitative data was collected. The analyses were framed using Butler & Cartier's model of self-regulation in context and Dym & Little's prescriptive design process frameworks. Four engineering experts, two from each respective engineering discipline, were recruited to help code the design process. The interrater agreement yields an almost perfect agreement. Additionally, the data was also coded based on SRL constructs. Our findings suggest that all groups shared numerous similarities in regulating their activities throughout the design process and project management. Any dissimilarities found were due to the nature of the sub-discipline, problem, design, and team.

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Advancing research on engineering design using e-Journal

Cited by 6 publications

References 3 publications

Do Computer Science Students Understand Their Programming Task?—A Case Study of Solving the Josephus Variant Problem

Do Computer Science Students Understand Their Programming Task?—A Case Study of Solving the Josephus Variant Problem

An Evaluation of an Engineering Design Class using Mixed Methods Techniques

Students' Self-regulation in a Senior Capstone Design Context: A Comparison Between Mechanical and Biological Engineering Design Projects

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