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Automating insights: Analysing the National Student Survey data using NVivo

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Chapter

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Automating insights: Analysing the National Student Survey data using NVivo. / Wright, Steve.
Analysing Student Feedback in Higher Education: Using Text-Mining to Interpret the Student Voice. ed. / Elena Zaitseva; Beatrice Tucker; Elizabeth Santhanam. London: Routledge, 2021. p. 19-36.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Chapter

Harvard

Wright, S 2021, Automating insights: Analysing the National Student Survey data using NVivo. in E Zaitseva, B Tucker & E Santhanam (eds), Analysing Student Feedback in Higher Education: Using Text-Mining to Interpret the Student Voice. Routledge, London, pp. 19-36. <https://www.routledge.com/Analysing-Student-Feedback-in-Higher-Education-Using-Text-Mining-to-Interpret/Zaitseva-Tucker-Santhanam/p/book/9780367687229>

APA

Wright, S. (2021). Automating insights: Analysing the National Student Survey data using NVivo. In E. Zaitseva, B. Tucker, & E. Santhanam (Eds.), Analysing Student Feedback in Higher Education: Using Text-Mining to Interpret the Student Voice (pp. 19-36). Routledge. https://www.routledge.com/Analysing-Student-Feedback-in-Higher-Education-Using-Text-Mining-to-Interpret/Zaitseva-Tucker-Santhanam/p/book/9780367687229

Vancouver

Wright S. Automating insights: Analysing the National Student Survey data using NVivo. In Zaitseva E, Tucker B, Santhanam E, editors, Analysing Student Feedback in Higher Education: Using Text-Mining to Interpret the Student Voice. London: Routledge. 2021. p. 19-36

Author

Wright, Steve. / Automating insights : Analysing the National Student Survey data using NVivo. Analysing Student Feedback in Higher Education: Using Text-Mining to Interpret the Student Voice. editor / Elena Zaitseva ; Beatrice Tucker ; Elizabeth Santhanam. London : Routledge, 2021. pp. 19-36

Bibtex

@inbook{0b7bbb8ff2ec4e06b1e26d1e76bec8db,
title = "Automating insights: Analysing the National Student Survey data using NVivo",
abstract = "This chapter demonstrates how two different research traditions: computational linguistics and qualitative content analysis can be productively brought together using recent innovations in Computer Assisted Qualitative Data Analysis Software (CAQDAS) packages. It details the criteria used to evaluate available software and outlines the development of a method using NVivo to analyse the National Student Survey comments at a UK university. Automated coding of the content and sentiment, combined with human interpretation, gave insights into patterns of positive and negative student feedback related to teaching, learning and assessment. The key value of synthesising this data is in gaining insight into the processes that may drive correlations in the numeric data. Additionally, it can support identifying the atypical and exceptional practices that can have significant effect on the student experience. It concludes with notes of caution about barriers to impact in practice. The chapter is practice-focussed and extends to consider adapting the approaches for other software and surveys.",
keywords = "Nvivo, text mining, mixed method approaches, National Student Survey",
author = "Steve Wright",
year = "2021",
month = dec,
day = "30",
language = "English",
isbn = "9780367687229",
pages = "19--36",
editor = "Elena Zaitseva and Beatrice Tucker and Elizabeth Santhanam",
booktitle = "Analysing Student Feedback in Higher Education",
publisher = "Routledge",

}

RIS

TY - CHAP

T1 - Automating insights

T2 - Analysing the National Student Survey data using NVivo

AU - Wright, Steve

PY - 2021/12/30

Y1 - 2021/12/30

N2 - This chapter demonstrates how two different research traditions: computational linguistics and qualitative content analysis can be productively brought together using recent innovations in Computer Assisted Qualitative Data Analysis Software (CAQDAS) packages. It details the criteria used to evaluate available software and outlines the development of a method using NVivo to analyse the National Student Survey comments at a UK university. Automated coding of the content and sentiment, combined with human interpretation, gave insights into patterns of positive and negative student feedback related to teaching, learning and assessment. The key value of synthesising this data is in gaining insight into the processes that may drive correlations in the numeric data. Additionally, it can support identifying the atypical and exceptional practices that can have significant effect on the student experience. It concludes with notes of caution about barriers to impact in practice. The chapter is practice-focussed and extends to consider adapting the approaches for other software and surveys.

AB - This chapter demonstrates how two different research traditions: computational linguistics and qualitative content analysis can be productively brought together using recent innovations in Computer Assisted Qualitative Data Analysis Software (CAQDAS) packages. It details the criteria used to evaluate available software and outlines the development of a method using NVivo to analyse the National Student Survey comments at a UK university. Automated coding of the content and sentiment, combined with human interpretation, gave insights into patterns of positive and negative student feedback related to teaching, learning and assessment. The key value of synthesising this data is in gaining insight into the processes that may drive correlations in the numeric data. Additionally, it can support identifying the atypical and exceptional practices that can have significant effect on the student experience. It concludes with notes of caution about barriers to impact in practice. The chapter is practice-focussed and extends to consider adapting the approaches for other software and surveys.

KW - Nvivo

KW - text mining

KW - mixed method approaches

KW - National Student Survey

M3 - Chapter

SN - 9780367687229

SN - 9780367678388

SP - 19

EP - 36

BT - Analysing Student Feedback in Higher Education

A2 - Zaitseva, Elena

A2 - Tucker, Beatrice

A2 - Santhanam, Elizabeth

PB - Routledge

CY - London

ER -