Campus Management Research Articles

Bim-based Digital Twin development for university Campus management. Case study ETSICCP

Bim-based Digital Twin development for university Campus management. Case study ETSICCP

Vicarious Acquisition of Learned Helplessness During the COVID-19 Campus Epidemics in China: Interactions Between Embodied and Mediated Experiences

ABSTRACT Numerous universities nationwide announced urgent implementation of closed campus management due to the epidemics of COVID-19 in Chinese universities since March 2022, and a large number of students were under quarantine. This study aims to explore how embodied experiences (i.e., centralized quarantine and self-quarantine) and mediated experiences (i.e., exposure to media sources, pandemic information overload, and online help seeking) influence the acquisition of learned helplessness during the campus epidemics among the Chinese university students, besides, how do these two types of experiences interact with each other to elicit learned helplessness is another interested research question. The data was collected nationwide via an online survey platform from March 22nd to April 16 2022 immediately after the outbreak of campus epidemics. A total of 1267 valid student samples were retained. Hierarchical regression analysis showed that embodied experience of centralized quarantine is positively related to learned helplessness. Mediated experience of information access from friends on social media and government official media as well as online help seeking are negatively related to learned helplessness. Information access from overseas media and pandemic information overload are positively related to learned helplessness. Besides, the interaction between self-quarantine and pandemic information overload is positively related to learned helplessness. Theoretical contributions and intervention strategies aimed at enhancing authoritative communication and managing information overload during public health crisis were discussed.

Smart Building Digital Twin for Interior Water Distribution System Management

Abstract. A smart campus integrates the Internet of Things, artificial intelligence, and real-time sensor data to optimize campus functions and create a context-aware decision-support platform for effective campus management. A crucial aspect of a smart campus is the water distribution system, which faces several challenges due to bursts, leaks, and water quality issues. This study uses Digital Twin technology to address these challenges through real-time monitoring, detection, and management of campus water distribution networks. A building-level digital twin is developed for the interior water networks of the Daphne Cockwell Complex at Toronto Metropolitan University. The major components include a 3D network model capable of analysis and simulations, a smart water management system, and real-time visualization. A 3D static model of the interior water utility network is created using the Industrial Foundation Class data. The semantic and topological models based on graph models are developed for network analysis. The models are integrated into the ESRI ArcGIS Pro to facilitate BIM-GIS integration. A dynamic model is created by incorporating automatic meter readings based on IoT. Combined with the 3D model of the utility network, the digital twin monitors and visualizes building water consumption, facilitating anomaly detection and real-time maintenance by the facilities management department. This study provides practical guidance for managing water distribution systems in university buildings, with potential applications in other complex environments. Future work aims to develop a system for detecting complex event processes by integrating different utilities.

Assessing Trends of Vehicle Ownership and Use Among Tertiary Students in Kwame Nkrumah University of Science and Technology Campus, Ghana

The study aims to assess trends of car ownership and usage among tertiary students on campus, with an emphasis on Kwame Nkrumah University of Science and Technology (KNUST). The research design employed in this study was descriptive survey, aiming to gather information from a sample population through their responses to specific questions. Data analysis was conducted using descriptive statistics, summarizing the responses quantitatively through bar charts, pie charts, frequencies, percentages as well as means and tables, created using Microsoft Excel. The results revealed that, a majority (70 percent) of the cars being used by students on the KNUST campus are owned by Ghanaian students with foreign students making up the minority of this number. The major challenges faced by students who own or use vehicles on campus are a lack of filling stations on and around campus, lack of student parking lots, and excess traffic. From the findings, it can be concluded that, students' psychological make-up is a major determinant of vehicle ownership among students. Moreover, the findings further revealed that most of the students who have vehicles on the campus exhibit or develop mostly negative habits after vehicle ownership and this in the long run may have negative effects on academic performance which is the sole purpose of being on campus. The study provides insights into the environmental and health impacts of increased vehicle use on university campuses, offering valuable insights for policy decisions, future research, and campus management, thereby enhancing student mobility.

Evaluasi Heuristik E-Learning Institut Agama Hindu Negeri Tampung Penyang Palangka Raya

Institute of Hindu Religion (IAHN) Tampung Penyang Palangka Raya has e-learning in an e-campus with complex features. Many e-learning features become ineffective, and make users unable to maximize their use. Therefore, a heuristic evaluation approach from Nielsen's is needed to find out the extent of usability in the e-learning. The heuristic evaluation method is a method used to find usability problems of a product using 10 heuristic evaluation principles. In this research, the assessment was carried out by 4 expert usability evaluators. The calculation of usability heuristic evaluation using severity ratings scale has been done. The results of the assessment based on heuristic evaluation on the IAHN-TP Palangka Raya e-campus application resulted in 24 problem findings. The highest value of the average severity rating (SR) is on the principle of error prevention and as much as 92% of the largest percentage is on the principle of visibility of system status. This research also provides recommendations for design improvements ranging from adding functions, changing appearance, and layout according to the results of the heuristic evaluation. These recommendations can be used as a consideration for the IAHN-TP campus management in improving the application.

Study path analyses for quality assurance and support of study planning

AbstractUtilizing student lifecycle data provided by campus management systems yields the opportunity to conduct study path analyses. Methods of artificial intelligence (AI) and data science can be used to analyze study paths, identify indicators for success, and gain insights into problems and issues of student cohorts following different study paths. Meanwhile, AI can also be used to support students through informed study planning. This article presents the project AIStudyBuddy with its focus on utilizing rule-based AI and process mining to support study planning and cohort monitoring. The concept of a reference architecture and data model for study path analytics as well as details on the development of the two user applications, StudyBuddy for students and BuddyAnalytics for study program designers, are presented. By exploring how AI and process mining can be applied in the scope of the two applications, the article addresses the question of how AI can be used for quality assurance in study planning and student cohort monitoring.

Towards Entrepreneurial Campus Sustainability: Integrating Artificial Intelligence for Resource Allocation in Business Management

This research delves into the utilization of artificial intelligence (AI) within the framework of campus resource allocation, with a primary focus on enhancing business management practices and fostering entrepreneurial sustainability within educational institutions. Through an innovative amalgamation of AI technology and SmartPLS methodology, the study constructs a comprehensive analytical framework aimed at tackling the multifaceted challenges inherent in resource allocation within campus environments. The findings underscore the transformative potential of AI integration in optimizing resource utilization, identifying efficiency gains, and nurturing entrepreneurial endeavors. This paper distinguishes itself from existing studies by presenting a novel approach that emphasizes the unique contributions of AI-driven solutions in both methodological innovation and practical application. By harnessing SmartPLS alongside AI, the research facilitates more accurate resource demand forecasting and enables adaptive decision-making processes, thereby contributing to the Sustainable Development Goals (SDGs), particularly in promoting quality education and sustainable management practices. The study also provides a detailed technical implementation of AI algorithms, offering valuable insights into their development and application within campus settings. The broader implications for the educational sector are explored, considering the scalability and adaptability of the proposed solutions in various educational contexts. Furthermore, the research contributes to theoretical advancements by pioneering the integration of AI and SmartPLS in campus management research, offering a fresh perspective on economic, environmental, and social impact assessments of AI-driven solutions.

Sustainable University Campuses: Temporal and Spatial Characteristics of Lightscapes in Outdoor Spaces

A lightscape, as a special visual landscape, has unique temporal and spatial characteristics that traditional photometric measurements and descriptions struggle to capture accurately. Despite their significance, there is a lack of in-depth understanding of the on-site perception of lightscapes’ temporal and spatial characteristics, including in outdoor university campus spaces. This study aims to explore the temporal and spatial characteristics of outdoor lightscapes on university campuses and their potential perceptual influencing factors, providing sustainable design, planning, and management suggestions for campus lightscapes. This study was conducted in the Wushan Campus of the South China University of Technology. It employs a “lightwalk” method for on-site perception evaluation, combining qualitative and quantitative approaches to investigate the temporal and spatial characteristics of lightscapes in outdoor university campus spaces and the effect of temporal and spatial factors on lightscape perception. The main findings are as follows: (1) Meteorological, architectural, and biophilic lightscape dominate the outdoor campus lightscapes. (2) The temporal and spatial characteristics of the lightscapes are affected by changes in natural light, the transition of light sources from day to night, human activity patterns, and the functional characteristics of the site. (3) The correlation between meteorological and traffic lightscape types and lightscape perception is diminished during the evening periods. This method should be a good way to optimize water and architectural lightscape at night to alleviate discomfort. (4) In green-shaded spaces, the association between meteorological, architectural, and traffic lightscape types and the evaluations of emotional, luminous, and eventful aspects is significantly enhanced, suggesting an increase in such spaces to improve lightscape experience quality. This study advocates that the construction of buildings and environments should be “human-oriented”, paying attention to the scientific foundation that humans perceive the habitat environment through the “five senses”. Research on lightscapes’ temporal and spatial characteristics, exploration of the temporal and spatial modes of lightscape perception, and avoiding energy waste and light pollution are conducive to the design and construction of university campuses in line with the principles of sustainable development. The lightscape optimization strategies derived from this study can not only provide practical guidance for the design and management of campus but also may offer valuable recommendations for planning sustainable campus development.

Exploring the campus managers’ challenges in managing educational resources in a TVET college

Exploring the campus managers’ challenges in managing educational resources in a TVET college

Research on the Application of Big Data and Cloud Computing Technology in Smart Campus

The current education field is experiencing an innovation driven by big data and cloud technologies, and these advanced technologies play a central role in the construction of smart campuses. Big data technology has a wide range of applications in student learning behavior analysis, teaching resource management, campus safety monitoring, and decision support, which improves the quality of education and management efficiency. Cloud computing technology supports the integration, distribution, and optimal use of educational resources through cloud resource sharing, virtual classrooms, intelligent campus management systems, and Infrastructure-as-a-Service (IaaS) models, which reduce costs and increase flexibility. This paper comprehensively discusses the practical application of big data and cloud computing technologies in smart campuses, showing how these technologies can contribute to the development of smart campuses, and laying the foundation for the future innovation of education models.

A perspective on smart universities as being downsized smart cities: a technological view of internet of thing and big data

The integration of internet of things (IoT) and big data technologies is transforming the overall perspective of managing various sectors of modern life; with higher educational sectors being no exception of this transformation. This paper explores the idea of a “smart university” as an extension of the overarching “smart city” framework, emphasizing the blending of IoT and big data technologies within higher education institutions. The study investigates the incorporation of IoT technologies throughout university campuses, including intelligent classrooms, smart infrastructure, and device networking. Moreover, the paper delves into the substantial role played by big data analytics in processing and extracting meaningful insights from extensive data generated by IoT devices in a Smart University. The use of predictive analytics, machine learning algorithms, and data-driven decision-making contributes to personalized learning experiences, adaptive campus management, and proactive maintenance of university facilities. Furthermore, this paper not only emphasizes the potential benefits of deploying IoT and big data in a university setting but also addresses challenges related to security, privacy, and ethical considerations. By embracing a comprehensive approach to technology integration, universities can leverage the capabilities of IoT and big data to establish intelligent, interconnected, and flexible educational environments that align with the broader vision of a smart city.

Pengaruh Penghargaan Ekstrinsik, Penghargaan Intrinsik, Keterlibatan Kerja Terhadap Kesejahteraan Psikologis pada Institut Bisnis IT&B

This study aims to investigate how extrinsic rewards, intrinsic rewards, and levels of work engagement contribute to the psychological well-being of employees in the campus environment of the ITB Business Institute. The research method used is a survey using questionnaires distributed to employees in various departments and units on campus. Extrinsic awards are evaluated through financial recognition and other material awards, while intrinsic awards include recognition of achievement, personal development, and a sense of accomplishment. Job engagement is measured through job satisfaction, commitment to work, and identification with organizational values. The collected data was analyzed using regression techniques to identify the relationship between independent variables (extrinsic rewards, intrinsic rewards, and work engagement) and dependent variables (psychological well-being). The findings of this study are expected to provide in-depth insights into the factors that affect the psychological well-being of employees on the campus of the ITB Business Institute. The results of this study are expected to provide recommendations to campus management in improving reward strategies and work engagement management to support the psychological well-being of employees. The practical implications of this research are expected to help create a more satisfying and productive work environment for all campus members.

The impact of social isolation on smartphone addiction among college students: the multiple mediating effects of loneliness and COVID-19 anxiety.

The widespread use of smartphones has significantly increased smartphone addiction among college students, especially during the COVID-19 pandemic. Since the COVID-19 outbreak, university campuses in mainland China have strictly followed the Chinese government's strict quarantine policy, including closed campus management, prohibitions against gatherings, and social distancing, increasing student loneliness and anxiety and thus increasing the risk of smartphone addiction. Extant Studies have revealed that social isolation is a prominent predictor of smartphone addiction but have failed to systematically explore the complex relationship between social isolation and smartphone addiction in the context of COVID-19; therefore, the underlying mechanisms of these factors in the post-pandemic era are unclear. This study is the first attempt to consider loneliness, COVID-19 anxiety and social isolation as a whole and to clarify the underlying mechanisms of social isolation and smartphone addiction by constructing a multiple mediating model. This study included students enrolled at eight higher education institutions in Conghua District (Guangzhou city). Quota proportional sampling was adopted, 900 self-report questionnaires were distributed through the WeChat groups of these universities from December 10 to December 15, 2022, and 868 valid questionnaires (620 females, 248 males) were ultimately obtained. The direct effect of social isolation on smartphone addiction was significant, and loneliness and COVID-19 anxiety mediated the association between social isolation and smartphone addiction in both parallel and sequential ways. Moreover, a reverse mediation model with COVID-19 anxiety as the first mediator and loneliness as the second mediator was found. College students who experience social isolation are at greater risk for smartphone addiction, and the core factor leading to their smartphone addiction is the subjective psychological state triggered by campus isolation and social distancing, such as loneliness and anxiety. These risky behaviors of people should receive extra attention, and psychological factors such as loneliness and COVID-19 anxiety should be considered in future therapies aimed at reducing addiction.

Integrating Renewable Energy Produced by a Library Building on a University Campus in a Scenario of Collective Self-Consumption

Rising fossil fuel costs and environmental concerns are driving the search for new energy sources, particularly renewable energy. Among these sources, solar photovoltaic (PV) is the most promising in southern European countries, mainly through the use of decentralised PV systems designed to produce electricity close to the point of demand and primarily to meet local energy needs. In an urban scenario, a decentralised energy system usually operates in parallel with the grid, allowing excess power generated to be injected into the grid. Solar carports and rooftop systems are excellent examples of distributed photovoltaic systems, which are far more sustainable than large centralised systems because they do not compete for land use. Despite their operational advantages, these decentralised photovoltaic production plants, which are in most cases financed by specific energy efficiency programs, present challenges in a regulated market where the injection of energy into the electricity grid is restricted by law and support programs. The aim of this work is to integrate two different photovoltaic systems within an academic campus where the only PV source currently available is a solar car park, a solution designed both to provide shaded space for vehicles and to produce energy to be consumed within the facilities. Due to legal restrictions, surplus electricity cannot be sold to the national grid, and solar batteries to store the generated energy are expensive and have a short lifespan. Therefore, since the campus has two different grid connections and a 102.37 kWp PV system, the newly designed system to be installed on the library roof must be calculated to support the installed electricity system during the most critical working hours, determining the specific angle and orientation of the solar panels. On this basis, the energy management of a school campus is fundamental to creating a collective self-consumption system, the basis of a local energy community that can meet energy, environmental, and social objectives.

Assessment of the End Users' Perceptions About the Campus Management System: A Case Study of Kohat University of Science & Technology

Assessment of the End Users' Perceptions About the Campus Management System: A Case Study of Kohat University of Science & Technology

Review of Digital Campus Construction Led by Virtual Reality Technology

In recent years, the government has issued a series of documents to promote the construction of digital campuses. This initiative serves to encourage the deep integration of information technology and intelligent technology education and digital reform, the combination of virtual reality and campus management is the need for innovative thinking and economic and social development, and then better change our learning style and living environment. The construction of the digital campus is based on virtual reality technology, BIM, GIS, and three-dimensional modeling technology to provide an immersive platform for students, promote the integration of virtual reality technology and education, help teachers, students, and parents to understand all kinds of education information and resources, to achieve their interoperability. From the off-campus environment to the school teaching equipment, teachers to teaching quality certification, and learning, to extracurricular entertainment, opening ceremonies to graduation parties, to bring more efficient, convenient, and safe campus life for teachers, students, and staff in school, and break the traditional information restrictions.

The Relationship between Green Management of Organizational Culture, Green Behavior and Green Campus in Private Universities: A Conceptual Paper

The Relationship between Green Management of Organizational Culture, Green Behavior and Green Campus in Private Universities: A Conceptual Paper

Autonomous communication with normative information facilitates positive spillover: promoting pro-environmental behaviors in a local setting

ABSTRACT A pro-environmental behavior (PEB) intervention may increase the adoption of other PEBs that were not targeted by the intervention, leading to a positive spillover effect. Communication that both support autonomy, as defined by self-determination theory, and compliance with descriptive norms may promote the targeted PEBs and positive spillover effect. Such communication may enhance autonomous motivation to adopt PEBs. A pilot study (N = 350) about waste management in a university campus found that autonomous communication supplemented by normative information influenced both targeted and non-targeted behavioral intentions, compared to autonomous-only and controlling communication. Findings were replicated in a main study (N = 629). An intervention combining autonomy support and descriptive norms increased the likelihood of a positive spillover effect in contrast to an intervention combining controlling communication and descriptive norms. In both studies, autonomous motivation mediated the positive spillover effect. Results suggest that communication that promotes autonomous motivation by fulfilling basic self-determination needs may have a broader effect on a wider range of PEBs.

Keystone - A Smart Campus

Abstract: Increasing numbers of institutes have set up facilities on their Web portal as a way of providing users (i.e. Students and Faculties) with information about their facilities and features. Generally in colleges, things are done manually such as submission, handouts, notice, results, records, examinations, etc. so to avoid this we are designing a web portal for our institute, which will be helpful in following features like time saving, easy access and user friendly. In this project, we developed a Smart Campus Web Portal called Keystone App. Keystone App offers campus management solutions with the collaboration of smart features, the Internet and computer applications. The system has many features; these are Online Attendance System, Online Noticeboard, providing study materials and many more. It is a digitalization of campus resources in the real world, allowing different resources to be integrated and generating an ecology. The virtual campus interacts powerfully with the physical campus, improving the efficiency of campus operations and promoting the university's long-term development.

AI student success predictor: Enhancing personalized learning in campus management systems

Campus Management Systems (CMSs) are vital tools in managing educational institutions, handling tasks like student enrollment, scheduling, and resource allocation. The increasing adoption of CMS for online and mixed-learning environments highlights their importance. However, inherent limitations in conventional CMS platforms hinder personalized student guidance and effective identification of academic challenges. Addressing this crucial gap, our study introduces an AI Student Success Predictor empowered by advanced machine learning algorithms, capable of automating grading processes, predicting student risks, and forecasting retention or dropout outcomes. Central to our approach is the creation of a standardized dataset, meticulously curated by integrating student information from diverse relational databases. A Convolutional Neural Network (CNN) feature learning block is developed the extract the hidden patterns in the student data. This classification model stands as an ensemble masterpiece, incorporating SVM, Random Forest, and KNN classifiers, subsequently refined by a Bayesian averaging model. The proposed ensemble model shows the ability to predict the student grades, retention, and risk levels of dropout. The accuracy achieved by the proposed model is assessed using test data, culminating in a commendable 93% accuracy for student grade prediction and student risk prediction, and a solid 92% accuracy for the complex domain of retention and dropout forecasting. The proposed AI system seamlessly integrates with existing CMS infrastructure, enabling real-time data retrieval and swift, accurate predictions, enhancing academic decision-making efficiency. Our study's pioneering AI Student Success Predictor bridges the chasm between traditional CMS limitations and the growing demands of modern education.