Using Leximancer to Identify Themes and Patterns in the Talk of Three High-Distinction Students

View/ Open
Author(s)
Grimbeek, Peter
Bartlett, Brendan
Loke, Kit-Ken
Year published
2004
Metadata
Show full item recordAbstract
Three graduate students were asked a series of questions about what they did to get either distinctions or high distinctions. The interviewer focused on the student's understanding of assessment requirements, motivation, interest levels, and the relevance of the set task. Other questions queried prior knowledge, course learnt knowledge, the lecturer's input, and peer input. Finally, these students were asked for advice that might assist students in getting high distinctions, or that might assist lecturers in helping students to achieve these outcomes. The transcribed interview with one of these students was entered into ...
View more >Three graduate students were asked a series of questions about what they did to get either distinctions or high distinctions. The interviewer focused on the student's understanding of assessment requirements, motivation, interest levels, and the relevance of the set task. Other questions queried prior knowledge, course learnt knowledge, the lecturer's input, and peer input. Finally, these students were asked for advice that might assist students in getting high distinctions, or that might assist lecturers in helping students to achieve these outcomes. The transcribed interview with one of these students was entered into Leximancer for text analysis. Leximancer provides an automated procedure that computes the distance between each of the terms and presents the results in a two-dimensional spatial representation. The authors in the current study report and comment on the outcome of separate and merged Leximancer analyses of the talk of one of these three students in ways that illustrate the strengths and weaknesses of text analysis.
View less >
View more >Three graduate students were asked a series of questions about what they did to get either distinctions or high distinctions. The interviewer focused on the student's understanding of assessment requirements, motivation, interest levels, and the relevance of the set task. Other questions queried prior knowledge, course learnt knowledge, the lecturer's input, and peer input. Finally, these students were asked for advice that might assist students in getting high distinctions, or that might assist lecturers in helping students to achieve these outcomes. The transcribed interview with one of these students was entered into Leximancer for text analysis. Leximancer provides an automated procedure that computes the distance between each of the terms and presents the results in a two-dimensional spatial representation. The authors in the current study report and comment on the outcome of separate and merged Leximancer analyses of the talk of one of these three students in ways that illustrate the strengths and weaknesses of text analysis.
View less >
Conference Title
Educating: Weaving Research into Practice
Copyright Statement
© The Author(s) 2004. The attached file is posted here with permission of the copyright owners for your personal use only. No further distribution permitted. For information about this conference please refer to the publisher's website or contact the authors.