Insights Into Students' Conceptual Understanding Using Textual Analysis: A Case Study in Signal Processing

Concept inventory tests are one method to evaluate conceptual understanding and identify possible misconceptions. The multiple-choice question format, offering a choice between a correct selection and common misconceptions, can provide an assessment of students' conceptual understanding in vari...

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Veröffentlicht in:IEEE transactions on education 2016-08, Vol.59 (3), p.216-223
Hauptverfasser: Goncher, Andrea M., Jayalath, Dhammika, Boles, Wageeh
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creator Goncher, Andrea M.
Jayalath, Dhammika
Boles, Wageeh
description Concept inventory tests are one method to evaluate conceptual understanding and identify possible misconceptions. The multiple-choice question format, offering a choice between a correct selection and common misconceptions, can provide an assessment of students' conceptual understanding in various dimensions. Misconceptions of some engineering concepts exist due to a lack of mental frameworks, or schemas, for these types of concepts or conceptual areas. This study incorporated an open textual response component in a multiple-choice concept inventory test to capture written explanations of students' selections. The study's goal was to identify, through text analysis of student responses, the types and categorizations of concepts in these explanations that had not been uncovered by the distractor selections. The analysis of the textual explanations of a subset of the discrete-time signals and systems concept inventory questions revealed that students have difficulty conceptually explaining several dimensions of signal processing. This contributed to their inability to provide a clear explanation of the underlying concepts, such as mathematical concepts. The methods used in this study evaluate students' understanding of signals and systems concepts through their ability to express understanding in written text. This may present a bias for students with strong written communication skills. This study presents a framework for extracting and identifying the types of concepts students use to express their reasoning when answering conceptual questions.
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subjects Assessments
Australia
Case Studies
Classification
Coding
Cognition
Comparative Analysis
Computational Linguistics
Computer Software
Concept Formation
Concept inventories
conceptual understanding
Difficulty Level
Encoding
Engineering Education
Inventories
Inventory
Manuals
Mathematical analysis
Mathematical Concepts
Misconceptions
Multiple Choice Tests
Signal processing
Software
Statistical Analysis
Stockpiling
Students
Teaching Methods
Text analysis
Texts
Training
Transaction processing
Undergraduate Students
Writing (Composition)
title Insights Into Students' Conceptual Understanding Using Textual Analysis: A Case Study in Signal Processing
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