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This study explores the factors that promote university teachers' switching intention from a traditional classroom to a smart classroom based on the push–pull–mooring (PPM) framework to enrich the theoretical research on the smart classroom and provide a reference for smart classroom promotion.

The proposed conceptual framework was developed from a comprehensive review of the related literature. This study tested and validated the proposed framework using a partial least square structural equation model based on 269 valid questionnaires.

(1) Perceived inefficiency, inquiry-based learning, future expectation and technical self-efficacy had significant effects on switching intention, while low participation, perceived usefulness and habit had no significant effects on university teachers’ switching intention in the smart classroom. (2) In the process of decision-making, the course category significantly moderates the impact of perceived inefficiency and technical self-efficacy on switching intention, while the user experience of smart classrooms significantly moderates the impact of perceived inefficiency on switching intention.

This study explains university teachers' switching intention from a traditional classroom to the smart classroom, which enriches the application area of the PPM framework.

Smart campuses can be seen as the future of higher education efforts, especially for their contributions to sustainability and to encourage innovation. This paper aims to present the benefits of smart practices in a Higher Education Institutions and highlights its connections to the sustainable development goals (SDGs).

The methodology is divided into three steps: first, an international search and assessment of smart practices at universities; second, the identification of smart practices in a university campus in southern Brazil; and third, the presentation of the benefits of smart practices and their relationship with the SDGs.

The results showed that globally, the area most covered by smart practices in universities is the environment and, specifically, focused on waste reduction. in the context of this case study, the benefits of implementing smart practices mainly reach SDGs 4 and SDG 9, especially due to aspects of teaching technologies for the new classroom models and the optimization of campus infrastructure management.

The study encourages other universities to implement smart practices in their campuses, to becoming smart campuses while they also collaborate in achieving the SDGs while raising the discussion on the importance of committed actions taken on a university campus with the UN SDGs, to leverage synergies on campus operations at universities.

This paper presents a set of smart practices that universities are applying both globally and locally (in southern Brazil). In addition, it contributes to sustainability research by showing how smart practices have the potential to promote SDGs in universities, especially through campus operations.

The purpose of this study is to generate knowledge about the use of smart campus tools to improve the effective and efficient use of campuses. Many universities are facing a challenge in attuning their accommodation to organisational demand. How can universities invest their resources as effectively as possible and not in space that will be poorly utilized? The hypothesis of this paper is that by using smart campus tools, this problem can be solved.

To answer the research question, previous survey at 13 Dutch universities was updated and compared with a survey of various universities and other organizations. The survey consisted of interviews with structured and semi-structured questions, which resulted in a unified output for 27 cases.

Based on the output of the cases, the development of smart campus tools at Dutch universities was compared to that of international universities and other organizations. Furthermore, the data collection led to insights regarding the reasons for initiating smart campus tools, user and management information, costs and benefits and foreseen developments.

Although the use of smart tools in practice has gained significant momentum in the past few years, research on the subject is still very technology-oriented and not well-connected to facility management and real estate management. This paper provides an overview of the ways in which universities and organizations are currently supporting their users, improving the use of their buildings and reducing their energy footprint through the use of smart tools.

Higher education institutions are widely known both for their promotion to education for sustainable development (ESD) and for their contribution as living labs to urban management strategies. As for strategies, smart and learning campuses have recently gained significant attention. This paper aims to report an air quality monitoring experience with focus on the smart and learning campus and discuss its implications for the university context with regard to ESD and sustainable development goal (SDG) integration.

The air quality monitoring was held at the main campus of University of Passo Fundo and focused on three pollutants directly related to vehicle emissions. The air quality index (AQI) was presented on a website, along with information regarding health problems caused by air pollution, main sources of emissions and strategies to reduce it.

The results showed how the decrease in air quality is related to the traffic emissions and the fact that exposing students to a smart and learning environment could teach them about sustainability education.

This case study demonstrated how monitoring air quality in a smart environment could highlight and communicate the impact of urban mobility on air quality and alerted to the need for more sustainable choices, including transports.

This paper contributes to the literature by showing the potential of a smart-learning campus integration and its contribution towards the ESD and the UN SDGs.

The objective of corporate real estate management is to optimally attune corporate accommodation to organisational performance. At universities, the dynamic process to match supply and demand is often hindered by difficulties in the allocation and use of space. This is a challenge for the Dutch universities and perhaps also European universities, which own large and ageing real estate portfolio’s in need of (re)investment: how can universities invest their resources as effectively as possible and not in space that will be poorly used? The purpose of this paper is to explore the use of smart campus tools to improve space use on campus.

First, a survey at 13 Dutch universities is conducted, consisting of a questionnaire and semi-structured interviews with Dutch campus managers. Then, semi-structured interviews are held with a number of parties in other industries to explore the use of smart tools in other contexts.

The universities’ demand for smart tools is mainly directed at the automatic and continuous collection of real-time space use data for education spaces and giving students insight into the availability of study places on campus. The tools at the Dutch universities focus largely on effectiveness: helping their users in their search to find a space that supports their activities. In other industry sectors, the results suggest that the use of smart tools is more directed towards efficiency: maximizing the use of existing space or optimising the operations of the organisation.

Although the use of smart tools in practice has gained significant momentum in the past few years, research on the subject is still sparse. By providing a framework for smart tools, as well as exploring the work done in theory and in practice, the authors hope to increase discussion and research on the subject from the perspective of corporate real estate.

Smart libraries are the result of the application of smart technologies in the era of digital intelligence. The establishment and improvement of its service evaluation system serve as indicators for evaluating the growth of smart libraries.

This study introduces and improves the capability maturity model (CMM), creatively constructs a service maturity model specifically designed for smart libraries and combines the Delphi method with the analytic hierarchy process (AHP) to establish a service maturity evaluation system for smart libraries while calculating indicator weights. Finally, two representative smart libraries are selected as case studies, and an empirical application is conducted using the fuzzy comprehensive evaluation method.

The empirical study shows that the developed smart libraries service maturity evaluation system holds significant theoretical and practical value in evaluating smart libraries.

Enhances the CMM and creatively constructs a service maturity model for smart libraries. Combines the Delphi method with AHP to establish a service maturity evaluation system while calculating indicator weights. Uses a fuzzy comprehensive evaluation method to evaluate two representative smart libraries. Demonstrates that the smart library services maturity evaluation system holds significant theoretical and practical value.

In this chapter, we explore an actual incident of cyberbullying that occurred at a large Canadian university. In our analysis, we frame cyberbullying as part of the more general phenomena of classroom incivility. We focus on the sociocultural context and demonstrate how the structures and processes within the classroom environment can enable incivility as well as cyberbullying.

This study aims to present the post-occupancy evaluation (POE) of a smart building on a university campus.

Literature review was conducted to report on the smart building concept and POE. A total of 49 performance indicators, classified according to the technical, functional and behavioral elements, were investigated. A case study of a smart building in a university campus was selected to assess the users’ satisfaction through POE. A total of 90 users from the academic and administrative staff of the building were contacted through a Web-based questionnaire survey, while 35 usable responses were obtained.

The findings revealed that the occupants were satisfied with several aspects of the building performance indicators; however, issues related to ventilation, control of thermostats, amount of natural lighting through low-E windows and privacy were identified. Ultimately, the study reveals that, although the adoption of smart technologies has the potential to provide an excellent and comfortable work environment, the efficient selection and/or maintenance of the adopted technologies is crucial.

The concept of smart buildings is perceived to be the future of the industry. Despite this growing need for “smartization,” the performance of a building ultimately depends on how it satisfies the needs of those who use them. The value and implication of this study is inherent in its emphasis on the satisfaction of buildings users in futuristic designs of buildings. The study shows that POEs can be used to assess the satisfaction of users of smart buildings to understand what works, as well as what needs redesign or improvement.

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.

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.

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.

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.

The purpose of this study is to determine the characteristics of the studies in terms of country, participant profile and methodology, as well as to determine what the Internet of Things (IoT) is currently contributing to higher education.

The study was developed following the methodology supported by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement and the PICOS strategy, retrieving scientific literature from Web of Science, Scopus, ERIC and Google Scholar. Of the 237 studies that the search yielded, 11 were included.

The results showed that among the opportunities offered by IoT is that it not only brings the introduction of information and communication technology into the classroom, but also enhances student interest, thus, improving the quality of teaching in higher education. On the other hand, one of the challenges it faces is the attitude of teachers towards its adoption, as well as the level of digital competence of teachers.

This study presents how higher education institutions are including the IoT in their educational activities. The IoT refers to a network of digital interconnectivity between devices, people and the internet itself that enables the exchange of data between them, allowing key information about the use and performance of devices and objects to be captured to detect patterns, make recommendations, improve efficiency and create better user experiences.