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With the deepening of education informationization, the importance of a college education quality evaluation system has become increasingly prominent. This paper aims to research and develop a quality evaluation system for college students based on an integrated learning algorithm and support vector machine (SVM). By integrating multiple learning algorithms and the classification ability of SVM, the system comprehensively evaluates students’ learning outcomes. First, we preprocess the educational data, including data cleaning, feature selection and standardization. Then, using integrated learning algorithms, such as random forest and gradient lift tree, the system design adopts a modular architecture, including a data preprocessing module, feature engineering module, model training module and evaluation output module. The experimental results show that the system has high evaluation accuracy and stability on several university education data sets. Compared with the traditional single algorithm, ensemble learning combined with SVM has obvious advantages in dealing with high dimensional and nonlinear educational evaluation problems. In addition, the system also provides a user-friendly interface for educators and students to operate and query. It provides a new technical means for the evaluation of college education quality and also provides data support and decision-making reference for personalized education and precision teaching. In the future, the system will further integrate more machine learning algorithms and explore deeper data analysis techniques to achieve more accurate and comprehensive student quality evaluations.

The accuracy and completeness of data preprocessing are crucial to the performance of models. If the pretreatment is not done properly, it may lead to degradation of model performance and even produce misleading results. Therefore, a multi-dimensional evaluation method of collaborative learning quality in higher education based on random forest is proposed. By introducing the student achievement data spanning 2020–2023, the stack denoising autoencoder is applied to the feature extraction of higher education collaborative learning images, and the external information sensitivity matrix and influence weight matrix are introduced. A random forest algorithm based on MapReduce distributed computing framework is proposed, and the convolutional neural network model in deep learning is adopted. Construct the index system of higher education collaborative learning quality evaluation, and introduce GoldenSA algorithm to carry out global search and fast optimization of SVM model parameters, so as to achieve multi-dimensional evaluation of learning quality. The experimental outcomes indicate that the designed method achieves an accuracy of 0.75, a precision of 0.74, a recall rate of 0.73, and an F1-score of 0.77. When the number of iterations only reaches 5 times, the proposed method begins to converge. In D1 data, the proposed method takes 5.87s, and the mean square error is lower than 5%.

The application of IoT technology not only brings abundant data resources and intelligent management tools to higher education institutions, but also promotes innovation in academic research and efficient dissemination of knowledge. When the expansion of higher education scale is combined with IoT-based structural optimization, its driving effect on economic growth is significantly enhanced. On the one hand, the expansion of scale provides a vast experimental field and infinite possibilities for IoT-based structural optimization. On the other hand, the structural optimization driven by the Internet of Things ensures the accuracy and efficiency of scale expansion, effectively avoiding resource waste and low efficiency caused by blind expansion. This paper constructs a dynamic collaborative model between higher education and economic development in the context of IoT integration, and uses econometric methods to analyze in depth the specific impact of the expansion of higher education scale, IoT-driven structural optimization, and their synergistic effects on economic growth. The model results show that the expansion of higher education scale has a significant positive effect on economic growth with the help of IoT integration, and IoT-driven structural optimization has also become an important driving force for economic growth. It is particularly important that when these two work together, their driving effect on economic growth shows a clear nonlinear growth trend, further highlighting the key role of synergy and IoT integration in promoting high-quality economic development.

We apply the contingent valuation method to estimate how much a specific group of society, which is relatively prone to falling victim to crime, is willing to pay to reduce the likelihood of being the victim of violent crime. Based on responses from 1122 students, we found that younger and female students revealed that they are more inclined to pay so as to avoid violent crime. Students' field of study, cautious behavior and a strong opinion about policies and payment vehicles with potential to reduce the risk of crime are key determinants of the willingness to pay.

Successful entrepreneurial activities are a function of human venture and environmental conditions, since the key to improving entrepreneurial perceptions and attitudes within society and within Higher Education (HE) institutions lies in education.

The purpose of this paper is to address issues surrounding entrepreneurial education in HE in Greece, and describes the delivery and evaluation of two programs. The programs were offered by a public university and a public technological & educational institute designed to create opportunities for learning entrepreneurial capacities, in order to develop a framework for the design and implementation of such activities.

Research results, concerning (i) the programs' concept and (ii) the degree that the programs influence the students' knowledge, skills and attitudes towards the undertaking of entrepreneurial activities, provide useful information for academicians, educators, educational managers and policy makers, concerning the design of similar programs. The methodology used brings in the description of each program's structure (in terms of its formation, development, implementation and evaluation) and the evaluation of its effectiveness, based on a pre- and post-analysis of students' perceptions from each institution. Data were collected from 904 students, with both business and scientific-technological studies background.

The analysis of data provides useful conclusions in relation to (i) the design of entrepreneurial education, (i.e. emphasis should be placed on the networking with the business world, the laboratory assistance, the mentoring process, the participants' scientific background) and (ii) the accomplishment of the two programs' objectives in "developing potential entrepreneurs", which seems to be moderately positive.

Despite progress in recognising the popularity of explaining a university’s entrepreneurial orientation (EO), the literature still lacks clear and systematic means of evaluating and measuring university EO. This study seeks to assess the different ways of measuring university EO and develop recommendations for future research to address this gap. Based on a systematic EO review of empirical research were identified three thematic groups: (i) EO and academic entrepreneurship, (ii) EO and entrepreneurial universities, and (iii) EO and academic spinoffs. These results allow for a greater understanding of the research topics and develop an integrated framework, thus helping to measure and refine operationalisations of EO that can help formulate future quantitative studies and increase the empirical accuracy of the field.

The purpose of this article is to uncover the trend of developing education courses for social entrepreneurship in higher education institutions in Hong Kong. The author had searched the syllabi or course descriptions across the websites of the higher education institutions in Hong Kong with the keywords of entrepreneurship, social entrepreneurship and social innovation. It was found that most of the social entrepreneurship courses offered were one-off single subject for undergraduate students, General Education courses, and minor courses, with only a few courses targeting postgraduates. It was also found that curricular differences among the courses offered by various schools or faculties were not that obvious. To understand this, the author had undertaken an analysis of the schools where these courses resided, course objectives, course content, and teaching and learning strategies among these various social entrepreneurship courses. Discussion of these has given insights to arguing for the need of multidisciplinary collaborations among social entrepreneurship educators.

The integrated chatbot for artificial intelligence customizes the learning experience for the students in higher education platform. The chatbot tests the answers of the students and offers insights for the students to improve their learning skills. Further, It helps to improve students’ thinking ability and expectations in higher education platform. The demanding factors for the students in the higher education platform include the need for interactive learning in a non-linear world, enhancing the thinking ability and expectations of the students. This paper proposes Artificial Intelligence Based Inquiry Evaluation Student Learning System (AI-IESLS) to increase interactive learning experience in a non-linear environment. The principal aim of this system is to improve the learning ability of the student on a specific subject using concept mapping in the chatbot. In addition, mapping has been validated for students based on the probability distribution analysis using a concept mapping. Besides, the probability graph’s curve generated by this system assesses the student’s understanding of the topic. The simulation results have been analyzed among students based on concept mapping using the AI-IESLS system in correlation with the traditional approach based on assessment ratio, feedbacks, reciprocity, timing analysis, expectation ratio, and active learning factor.

Higher education plays an important role in the construction of a new growth engine of China’s economy under the new normal state. If innovation is likened to a new engine of economic growth in China, higher education is equivalent to energy and fuel provided by the engine energy for intellectual support and knowledge support. Based on Denison factor analysis, the panel data of 30 provinces in the east, middle and west of China from 1997 to 2014 was used to conduct the Cognitive computing for decision-making and choice about the impact of higher education level of human resources on China’s economic growth. The results show that the output elasticity of material capital gradually decreases from west to east, while the output effect of higher education increases gradually from west to east.

Group work can inspire students, encourage constructive learning, and improve essential critical thinking, communication, and decision-making in the present competitive world. The risk factors in group learning include students who prefer working alone and strongly despise dealing with things created by gathering in teams. Online learners often have problems locating lasting peace times for group therapy sessions are considered an essential factor. A predictive Group Learning Behavior Approach (PGLBA) has been proposed. Students who commute to college agree to group conferences and workgroup learning and Inquiry learning for higher education. The grounded Inquiry Learning Approach is invented to strengthen students’ enjoyment of active group learning, and the students find times for group meetings that are often mutually advantageous. The simulation analysis is performed based on performance, accuracy, and efficiency proves the proposed framework’s reliability. The experimental results show that the proposed PGLBA-IL model enhances the accuracy ratio of 81.2%, an efficiency ratio of the number of students 86.4%, and the overall performance analysis ratio of 85.1% compared to others existing approaches.

This study explores the strategic issues related to the mobile learning quality in Taiwanese higher education during the COVID-19 pandemics. While much previous study determined the factors affecting mobile learning quality, seldom research works discussed the influence weights of the elements and their interrelations in the higher education through a comprehensive view. Hence, the purpose of this research is to explore the interrelationships and feedback between the factors affecting mobile learning quality via a combined multiple attribute decision-making (MADM) method, which will include decision-making trial and evaluation laboratory (DEMATEL), and DEMATEL-based ANP (DANP) approaches. This recommended approach can offer guidance to prioritize the influence elements in the enhancement plans for mobile learning quality. This research uses the recommended approach in the higher education in Taiwan as an empirical study during COVID-19. These findings results state which service quality needs to be enhanced primarily, and learning ability is the most important factor influencing mobile learning quality during COVID-19. Furthermore, the results show that system quality perspective has the strongest impact on the relations and it also has an important effect on other perspectives. The results can provide guidance on assigning resources of limit to improve this mobile learning quality in Taiwanese higher education in the COVID-19 pandemics.

Knowledge Management (KM) has recently received considerable attention in the computer information systems community and is continuously gaining interest by industry, enterprises and academia. As we are moving into an era of "knowledge capitalism", knowledge management in combination with information management will play a fundamental role towards the success of transforming individual knowledge into organizational knowledge. Higher education (HE) institutions are in the knowledge business, since they are involved in knowledge creation, dissemination and learning. The increasing economic importance of knowledge, which nowadays redefines the links among education, work and learning, makes the role of KM in HE crucial.

In this framework, this paper presents the key concepts of human-computer interaction in knowledge management, discusses their applicability to HE and proposes the creation of learning organisations in HE institutions, as an innovative way to apply KM to HE.

Private and academic institutions are embracing E-learning as an attempt to improve the learning process, encourage knowledge transfer and compliment their existing learning environment. For many countries with a large population, limited resources and remote geographical areas like Indonesia, E-learning holds the key to better education and provide better access to knowledge resources. E-learning is still new in Indonesia and there are not many studies reported in the literature. This study aimed to provide some ideas about the state of E-learning in Indonesia, specifically in higher education institutions. A survey was carried out to reveal the state of E-learning in higher education institutions in Indonesia. Sample of the population consists of lecturers, developers and researchers who work for higher education institutions in Indonesia. While the study showed that most of the E-learning projects are new and the level of participation is slow, the quality of E-learning courses is perceived as fair. As E-learning development in Indonesia is still in its early stages, serious efforts are needed to facilitate E-learning in higher institutions. The study identified infrastructure problems and staffs' reluctance to adopt E-learning as the main problems for the slow implementation and adoption of E-learning. Despite these problems, E-learning is expected to gain momentum in Indonesia as it is perceived as an effective way to educate the population of Indonesia.

This study aimed to analyse the implementation form and the maturity level of knowledge management (KM) and formulate recommendations of KM implementation strategies for improvement of academic services at universities in Indonesia. The analysis of the KM implementation was conducted at four top universities in Indonesia based on the ranking of the Indonesian Ministry of Research, Technology and Higher Education 2016, viz., ITB, UGM, UI and IPB. Primary data were obtained from the library of ITB, UGM, UI, and IPB and from 510 academicians of IPB, while secondary data was obtained by content analysis. The result showed that the top four universities in Indonesia have had the basic infrastructure for KM implementation; their management have been actively participating in the promotion of KM initiatives by articulating KM strategy and providing budgetary allocations and rewards system. Several pilot projects were undertaken to develop KM application into a higher level. The utilisation of KM application has not been optimal; knowledge sharing has not yet become a culture. The KM maturity implementation in the library of ITB, UGM, UI and IPB is at the third level. The result of the measurement of interoperability maturity level of seven IPB academic service applications just on the average reaches third level and is still in the stage of data integration. The KM implementation strategies that were recommended to improve the academic services at IPB, among other things, the reinforcement of the role of chief knowledge officer, the promotion of knowledge sharing culture with the knowledge repository optimisation, the formation of a community of practices, the development of knowledge portal, the optimisation of e-learning system and the improvement of rewards system.

Enterprise Resource Planning (ERP) system is a very powerful solution to many academic and non-academic institutions in case it has been implemented and used effectively. Otherwise, the system will interrupt several business processes. This research paper investigates the impact of ERP system on academic performance at Sohar University. A survey questionnaire is distributed to several academic stakeholders to investigate the impact of ERP system on academic performance within the University context. A total of 110 questionnaires was received from the key academic stakeholders to examine the relationship between the three core ERP modules i.e. the students’ information module, the financial module, and human resource module. The research outcomes indicate that there is a relationship between the three modules and the academic performance. However, only students’ information module and financial management module demonstrate a significant impact on academic performance, though the human resource module shows no impact on the academic performance at Sohar University. This study is a single case study approach, which might limit the findings to be generalized on other education institutes, but it gives a chance to other researchers to do multiple case studies in other Universities in the region.

The importance of innovation (INNO) towards organisational performance (OP) is acknowledged in extant literature. There is substantial evidence about INNO playing the determinant role in OP. However, there are few studies providing empirical evidence of this relationship especially in academic settings. By looking at INNO from administrative and technical perspectives, this paper purposefully explores the impacts of INNO on OP in public higher education institutions (HEIs) of Vietnam. Quantitative research was deployed, and results of the study were produced based on a survey data collected in 30 public universities equally located in three regions of Vietnam during 2018. Structural Equation Modelling (SEM) was used to facilitate model testing. We find that each type of innovation exerts its impacts on different aspects of OP in a HEI. Besides enriching the literature on this rapport, this study is also of value in managerial perspective as it helps increase HEIs’ knowledge on how to strengthen their organisational innovativeness, and then enhance performance. A list of measurement scales serving as a checklist for leadership of any HEI desire to embark on INNO journey then boost OP is provided by this study.

Blended Learning (BL) essentially fuses high-tech digital learning with traditional ones to involve students in “network learning”, which helps in transcending physical boundaries. Especially during the ongoing COVID-19 pandemic, BL has been embraced as a realistic possibility to ensure seamless knowledge distribution regardless of time and space. Knowledge Management (KM)-based approaches are typically used to collect, coordinate, and control processes that may be utilised efficiently to both recognise and address customer needs. This study aims to explain how to apply KM techniques within the BL environment to increase educational excellence and quality. We used a quantitative approach, specifically by adopting an online questionnaire circulated to about 272 undergraduate students, primarily from the Department of Information Science and Library Management (ISLM) of the University of Dhaka, Bangladesh. We received completed answers from 74 students; the data gathered were analysed using Statistical Package for the Social Sciences (SPSS) version 20. The findings reveal that KM can be used with BL, especially during crisis times like the one we have today, as it includes integrated tasks and online and e-learning. Finally, the study also proposed an intuitive model for applying BL through KM. Importantly, this study seems to be among the first to examine the students’ perceptions about BL and KM integration during a pandemic. Therefore, this research would possibly prompt further research on different aspects of the combined learning process at different universities, especially within Bangladesh.

Higher education aims to inculcate teamwork and leadership, the two primary management skills that empower students to achieve competency. Despite the fact that students gain domain knowledge through higher education, many organisations report that freshmen have a severe lack of collaborative skills. These skills are essential for today’s graduates to compete in the world of tomorrow. Collaborative learning is a set of strategies that help the students achieve management skills in an effective way, leading to deeper learning. It increases the critical thinking level, communication, leadership, and employability skills, as well as responsibility, and prepares the students for real-life social and economic environments. As collaborative learning practises are so important, this study focuses on assessing the impact they have on competency development, specifically in entrepreneurship programs. A qualitative and quantitative survey has been administered to 536 students pursuing higher education in management in India’s Delhi and the NCR region. A questionnaire has been prepared with 20 questions, comprising 15 closed-ended and 5 open-ended questions. With the results obtained from the survey, it is clear that the collaborative learning practise has a positive relationship with the entrepreneurship programme and competence development among students. The result proved that collaborative learning does benefit the students more in developing competency than individual learning through cultivating essential skills such as communication, teamwork, critical thinking, and responsibility.

The keyword that most effectively describes 21st-century higher education is "expansion," as suggested by Daniel et al. [2009]. The present contribution aims to analyze current higher education requirements, offers a general insight into how to respond to pressing needs by exploiting the added value of networking potentiality, and reports on a successful case: the Licence Professionnelle "Management des Organisations de l'Economie Sociale" course (University Marne-la-Vallée, France).

Higher education and community partnerships have transitioned from casual relationships to more of a mandate with the advancements in technology and globalization. The result of this large-scale change has led to an increase in these efforts, but the relationships are still emerging. Using survey research and the human resource development (HRD) perspective, we explore higher education and community partnerships, assesses their challenges, and discusses potential contributions of such partnerships in community development. This article contributes to our understanding of how these partnerships interact and what strategies the field of HRD may offer to advance such collaborative efforts.