TY - JOUR
T1 - Text analysis in education
T2 - A review of selected software packages with an application for analysing students’ conceptual understanding
AU - Cunningham-Nelson, Samuel
AU - Mukherjee, Michelle
AU - Goncher, Andrea
AU - Boles, Wageeh
N1 - Includes bibliographical references.
PY - 2018/7/29
Y1 - 2018/7/29
N2 - Using text analysis, computers can find patterns to determine and extract useful information from a set of text. Exploiting the capabilities of text analysis software can efficiently provide educators with the ability to analyse students’ answers and make better judgement on their performance. Such ability would otherwise be impossible to practically gain, especially for large classes. Because of the availability of a wide range of text analysis software, with varied features, an important question to ask is which software to use, that best suits a certain application, and users’ educational technology skills. This paper evaluates seven selected software packages which can be used for textual analysis. The graphical abstract, Figure 1, shows the outputs of one of the software packages (Leximancer), using the text from this paper as input. The data set and results presented use responses from a university-level test in an electrical engineering topic, which are included in this paper. The test was designed to assess students’ conceptual understanding. Students were asked to provide an explanatory text justifying their selection of a multiple-choice option. The principles, ideas and software evaluation criteria discussed, although applied to our dataset, can be extended to many other areas and fields.
AB - Using text analysis, computers can find patterns to determine and extract useful information from a set of text. Exploiting the capabilities of text analysis software can efficiently provide educators with the ability to analyse students’ answers and make better judgement on their performance. Such ability would otherwise be impossible to practically gain, especially for large classes. Because of the availability of a wide range of text analysis software, with varied features, an important question to ask is which software to use, that best suits a certain application, and users’ educational technology skills. This paper evaluates seven selected software packages which can be used for textual analysis. The graphical abstract, Figure 1, shows the outputs of one of the software packages (Leximancer), using the text from this paper as input. The data set and results presented use responses from a university-level test in an electrical engineering topic, which are included in this paper. The test was designed to assess students’ conceptual understanding. Students were asked to provide an explanatory text justifying their selection of a multiple-choice option. The principles, ideas and software evaluation criteria discussed, although applied to our dataset, can be extended to many other areas and fields.
KW - Conceptual understanding
KW - Machine learning
KW - Software review
KW - Text analysis
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U2 - 10.1080/22054952.2018.1502914
DO - 10.1080/22054952.2018.1502914
M3 - Article
AN - SCOPUS:85057010893
SN - 1324-5821
VL - 23
SP - 25
EP - 39
JO - Australasian Journal of Engineering Education
JF - Australasian Journal of Engineering Education
IS - 1
ER -