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Findings indicated stronger scores for task interpretation than for planning, cognitive, and monitoring/fix-up strategies, with higher performers using more effective cognitive and monitoring/fix-up approaches.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & 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9-12  \nOenardi Lawanto, Utah State University, USA Deborah Butler, University of British Columbia, Canada Sylvie Cartier, University de Montreal, Canada  \nHarry Santoso, Utah State University, USA  \nKevin Lawanto, Utah State University, USA David Clark, Monarch High School, Colorado, USA  \nAbstract  \nThis exploratory study evaluated self-regulated learning (SRL) strategies of 27 students in grades 9-12 during an engineering design project. The specific focus of the study was on student task interpretation and its relation to planning and cognitive strategies in design activities. Two research questions guided the study: (1) To what degree was students’ task interpretation reflected in their working plans and SRL strategies use across the design process?; and (2) How did relatively lower-and higher-achieving design-performing students differ in interpreting tasks and deploying SRL strategies? Survey instruments and Webbased design notebook writing were used to capture students’ reported use of SRL strategies. On the survey,  \nstudents reported use of SRL strategies at the early, middle, and final stages of the design task, with a focus on task interpretation, planning, cognitive, monitoring/fix-up strategies, and performance criteria.  \nThe findings suggested that students scored higher on task interpretation than on planning, cognitive, and monitoring/fix-up strategies. Students’ relatively high awareness of task interpretation-related-issues was also reflected in what they considered to be good design performance. Our findings were suggestive that higher performing students scored significantly higher than their lower-performing peer on cognitive and monitoring and fix-up strategies. On the other hand, lower-performing students reported greater use of planning strategies. Moreover, higher-performing students seemed to be able to convey more detailed and specific descriptions than did their relatively-lower performing peers. This article discusses potential implications for design instruction in grades 9-12.  \nKey words  \ndesign, grades 9-12, metacognition, self-regulated learning  \nIntroduction  \nThere is a widely accepted theory among Science, Technology, Engineering, and Mathematics (STEM) educators that teaching concepts and skills in the context  \nof solving engineering design-type problems will enable students to more easily grasp and retain those concepts (Katehi et al, 2009). Although there is a strong push among educators to emphasise engineering design in K-12 engineering education either in Australia, Europe, or United States (Eder, 1993; Göl et al, 2004; Katehi et al, 2009), few studies have assessed how students’ selfregulated learning (SRL) strategies are selected and deployed to solve complex problems (De Corte et al, 2011) . Having a better understanding about those strategies is essential, however, because consistency in employing SRL strategies is highly correlated with student achievement (Zimmerman and Schunk, 2011), particularly in the kinds of complex, ill-structured tasks so ubiquitous in Engineering education and practice.  \nSRL can be defined essentially as a form of iterative, goaldirected activity that involves interpreting tasks, setting goals, selecting, adapting or even inventing strategies effective for achieving those goals, monitoring progress, and adjusting approaches as needed (Zimmerman, 2008) . Effective SRL is invited by and particularly critical in complex or ill-structured tasks, such as engineering design (Lawanto, 2010; Lawanto and Johnson, 2012) . As stated by Dym and Little,“Designing is about people planning and creating ways to produce things that achieve some known goals”(2009: 5) . The design process is not linear; at any phase of the process, students must identify, plan, act, evaluate, and make necessary adjustments. Students’development of SRL strategies is part","cbCaieiEuTXZA9XA","https://ap.wps.com/l/cbCaieiEuTXZA9XA","pdf",199698,14,"English","# Abstract\n# Introduction\n# Relevant Literature Review\n## Insights into metacognition in a self-regulated learning context","[{\"question\":\"What was the main purpose of the exploratory study?\",\"answer\":\"The study evaluated how students in grades 9-12 used self-regulated learning (SRL) strategies during an engineering design project, with a specific focus on task interpretation and its links to planning and cognitive strategies.\"},{\"question\":\"How were students’ SRL strategies measured?\",\"answer\":\"The researchers used survey instruments and web-based design notebook writing to capture students’ reported use of SRL strategies across early, middle, and final stages of the design task.\"},{\"question\":\"What differences appeared between lower- and higher-achieving students?\",\"answer\":\"Higher-performing students scored significantly higher on cognitive and monitoring/fix-up strategies and could provide more detailed and specific descriptions, while lower-performing students reported greater use of planning strategies.\"}]","An Exploratory Study of Self-Regulated Learning Strategies in a Design Project by Students in Grades 9-12 | PDF",1792091032,35]