Future educational environment – Identification of smart campus topic trends using text mining

Abstract

Purpose

Recent attention to the developments focusing on the educational services has been noteworthy, with the educational environment specifically the smart campus emerging both as a domain and as an opportunity. As a domain worthy of exploration, a number of research efforts are being conceptualized around smart campus initiatives. The existing bouquet of research publications on smart campus provides a testimony of the enthusiasm and also exposes the heterogeneous attempts the domain has witnessed to date. The available evidence is still inadequate to provide clarity on the thrust areas of research around smart campus.

Design/methodology/approach

Given the understanding, this study intends to decode the domain to get an early impression of the focus of the research concentration around smart campus. Thereby the study resorts to an automated text-mining approach using Python on contents shortlisted systematically, and published between the period 2010 and May 2022, from select databases.

Findings

Based on the analysis it was possible to identify eight themes (i.e. smart campus characteristics, smart campus stakeholders, smart campus frameworks, smart campus technologies, smart campus infrastructure, smart campus evaluation, smart learning environment and smart campus applications) characterizing research efforts within the smart campus literature.

Originality/value

The themes around the smart campus showcase the thrust areas receiving attention. These characterize extant research endeavours in the smart campus domain and can offer useful pointers to researchers going forward. This awareness can also be beneficial to institutional leadership and technology providers intending to implement smart campus initiatives, contributing to the development of the educational environment.

Citation

Joshy, K.X., Thakurta, R. and Sekh, A.A. (2023), "Future educational environment – Identification of smart campus topic trends using text mining", International Journal of Educational Management, Vol. 37 No. 4, pp. 884-906. https://doi.org/10.1108/IJEM-01-2023-0005