Knowledge Surveys in Engineering Statics
Author(s) -
Eric Davishahl
Publication year - 2018
Language(s) - English
Resource type - Conference proceedings
DOI - 10.18260/1-2--28602
Subject(s) - formative assessment , summative assessment , context (archaeology) , computer science , engineering education , curriculum , survey data collection , mathematics education , class (philosophy) , knowledge survey , medical education , psychology , engineering , engineering management , pedagogy , artificial intelligence , medicine , paleontology , statistics , mathematics , biology
Knowledge surveys ask students to report on their confidence that they can perform specific tasks aligned with course learning outcomes instead of asking students to complete said tasks. This approach allows these surveys to cover a broad range of course topics and cognitive levels while requiring a relatively short amount of time to complete. Administering the surveys multiple times during a course offers a context for students to reflect on their own learning progress and provides useful assessment data to the instructor. Knowledge survey applications documented in the science education literature include their use for both formative and summative assessment of student learning, their use by faculty in assessing the effectiveness of teaching methods, and their use by programs and departments in evaluating curriculum. Reporting on the use of these types of self-assessment surveys; however, is generally absent in the engineering education literature. This paper seeks to introduce this potentially useful tool to the engineering education community by reporting on the development and implementation of a knowledge survey for an engineering statics course. The survey consists of 122 specific success criteria mapped to eight course-level learning outcomes. Students completed the survey three times during the term; once during the first week of class; once before the first exam; and once before the second exam. The paper explores several potential uses of the survey data, examines correlation of the survey responses with exam scores, and concludes that these surveys show promise as a tool for engineering educators. Their effectiveness toward multiple teaching goals warrants further development and investigation.
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