Analysing Student Feedback in Higher Education (Using Text-Mining to Interpret the Student Voice) - 9780367687229

ISBN: 9780367687229
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$49.99
SKU:
9780367687229
Availability:
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Minimum Purchase:
25 units
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Product Details

Author:
Elena Zaitseva, Beatrice Tucker, Elizabeth Santhanam
Format:
Paperback
Pages:
238
Publisher:
Taylor & Francis (December 30, 2021)
Language:
English
ISBN-13:
9780367687229
Weight:
13.125oz
Dimensions:
6.125" x 9.1875"
File:
TAYLORFRANCIS-TayFran_250322054040178-20250322.xml
Folder:
TAYLORFRANCIS
List Price:
$49.99
Case Pack:
10
As low as:
$43.99
Publisher Identifier:
P-CRC
Discount Code:
H
Country of Origin:
United States
Audience:
College/higher education
Pub Discount:
30
Imprint:
Routledge

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Overview

Analysing Student Feedback in Higher Education provides an in-depth analysis of ‘mining’ student feedback that goes beyond numerical measures of student satisfaction or engagement. By including authentic student voices for understanding the student experience, this book will inform strategies for quality improvement in higher education globally.

With contributions, representing an international community of academics, educational developers, institutional data analysts and student-researchers, this book reflects on the role of computer-aided text analysis in gaining insight of student views. The chapters explore the applications of text-mining in different forms, these include varied institutional contexts, using a range of instruments and pursuing different institutional aims and objectives. Contributors provide insights enabled by computer-aided analysis in distilling the student voice and turning large volumes of data into useful information and knowledge to inform actions. Practical tips and core principles are explored to assist academic institutions when embarking on analysing qualitative student feedback.

Written for a wide audience, Analysing Student Feedback in Higher Education provides those making informed decisions about how to approach analyses of large volumes of student narratives, with the benefit of learning from the experiences of those who already started treading this path. It enables academic developers, institutional researchers, academics, and administrators to see how bringing text mining to their institutions can help them in better understanding and using the student voice to improve practice.

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