TY - JOUR
T1 - Insights into students conceptual understanding using textual analysis
T2 - A case study in signal processing
AU - Goncher, Andrea
AU - Jayalath, Dhammika
AU - Boles, Wageeh
N1 - Includes bibliographical references.
PY - 2016
Y1 - 2016
N2 - 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.
AB - 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.
KW - Conceptual questions
KW - Conceptual understanding
KW - Discrete-time signals
KW - Engineering concepts
KW - Engineering controlled terms: Education
KW - Engineering main heading: Students
KW - Engineering main heading: StudentsConceptual questions
KW - Mathematical concepts
KW - Multiple choice questions
KW - Signal processing
KW - Signals and systems
KW - Written communication skills
U2 - 10.1109/TE.2016.2515563
DO - 10.1109/TE.2016.2515563
M3 - Article
VL - 59
SP - 216
EP - 223
JO - IRE Transactions on Education
JF - IRE Transactions on Education
SN - 0018-9359
IS - 3
ER -