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Analysing Student Feedback in Higher Education
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Analysing Student Feedback in Higher Education : Using Text-Mining to Interpret the Student Voice

Book Details

Format Hardback or Cased Book
ISBN-10 0367678381
ISBN-13 9780367678388
Publisher Taylor & Francis Ltd
Imprint Routledge
Country of Manufacture GB
Country of Publication GB
Publication Date Dec 30th, 2021
Print length 222 Pages
Weight 453 grams
Ksh 27,900.00
Werezi Extended Catalogue 0 in stock

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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.

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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