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Despite an enormous growth of the literature and research on inclusive education during the last two and a half decades, theory and practice on inclusive education are still inconsistent across the education systems worldwide. It is defined, conceptualised and practised differently across diverse socioeconomic contexts and groups of scholars and practitioners. While some promote educating all students in a mainstream classroom setting irrespective of their abilities and physical, emotional and behavioural challenges, others emphasise improving the overall quality of education for all children from diverse backgrounds. Given that education is a multidimensional social enterprise, promoting a single perspective at the cost of others or merely emphasising the role of schools and teachers may hardly result in improved education outcomes and guarantee equal learning opportunities for all. This chapter will critically review the relevant theory and discuss the different approaches to inclusive education. Then it will discuss the potential challenges to inclusive education across the education systems. Finally, the chapter will offer an inclusive way forward for improving the quality of education for all children, irrespective of their backgrounds, in mainstream schools in multicultural contexts.

The objective of this chapter is to identify the key characteristics of Global Services businesses that will thrive and achieve success in the future. These factors are integrated into three main pillars, which we refer to as the Triple-Win. The first and most obvious pillar is technology as a tool. The second pillar is the design and sustainability of the business model, without which the previous factor would be merely a cost and not an investment. And last but not the least, there is the purpose which gives meaning to the proposal, focusing on the human being and their environment. The DIDPAGA business model sits at the intersection of these three elements.

The research goal is to understand what factors affect users' knowledge and information learning and sharing on social media platforms. This study focuses on the impact of platform characteristics on users' behavior. Specifically, the purpose of this study is to investigate (1) what factors affect users' learning and dissemination of knowledge and information on social media platforms, (2) whether knowledge and information learning behavior will have a positive effect on sharing behavior and (3) try to establish an impact model of users' learning and sharing behavior about knowledge and information.

This study proposes an impact mechanism model to test these hypotheses. To achieve this, the authors collected data from 430 users who have used the social media platforms to acquire and share knowledge and information to test the hypothesis. The tools SPSS 26.0 and AMOS 23.0 were used to analyze the reliability, validity, model fits and structural equation modeling.

The results show that the learning of knowledge and information can influence the sharing behavior on social media platforms. Users' platform-based trust and platform-based satisfaction affect their knowledge and information learning and sharing on the platform. Factors affecting users' trust in social platforms include privacy protection effectiveness and network effects. And, perceived usefulness and perceived ease of use are related to users' satisfaction with social media platforms.

This study constructs an impact model on the learning and sharing of knowledge and information. The model takes the information system continuance model as the theoretical framework and integrates other factors, including the network effect, the effectiveness of privacy protection and trust. Most of the hypotheses of this research were confirmed. The conclusions provide practical guidance for the dissemination of knowledge information and platform management.

Under emerging social media technology, mobile learners' behavior analysis and legality education have important practical significance. The research aims to detect the mobile learning (M-learning) learners' behavior in legality education under the background of the Internet era and improve the learning and teaching effect of online legality education and law popularization.

This paper proposes a model based on deep learning (DL) fuzzy clustering analysis (FCA), and bidirectional encoder and decoder (ENDEC) of converter model to detect the mobile learners' behaviors in online legality education under the current social media. Then, the effectiveness of the proposed model is tested. The proposed model expects to be applied to multimedia teaching and law popularization activities and provides some theoretical reference and practical value for improving the effectiveness of online teaching.

The experimental results show that in the learner behavior detection process of M-learning-oriented online legality education, the model's accuracy can reach 99.8%. The response time is shorter than other algorithms. Overall, the application effect of the proposed model and algorithm is good and can be applied in practice.

The research results may lack universality due to the selected research methods. Therefore, researchers are encouraged to test the proposed methods further. In the future, it is necessary to expand the type and scale of text data to improve the accuracy of data detection.

The research results provide a specific theoretical reference and practical significance for improving the learning effect of online M-learning-oriented legality education.

This paper meets the needs of mobile learner behavior analysis based on social media.

In the face of major disasters, the Chinese people's willingness to donate has increased and the result is that the donation paths have increased. However, there are certain differences in the choice of donation paths for different types of individuals. It is crucial to pay more attention to the attitude and donation path selection of donors and propose strategies to promote individual donation behavior. The purpose of this study is to propose a conceptualized moderated mediation model for testing the linkage between individual attitude and donation path selection through the mediating effect of donors' behavioral intention and the moderating effect of behavioral difficulty perception or social pressure between donors' attitude and their donation path selection.

Based on a questionnaire survey of 628 community workers during COVID-19 in China. Self-reported measures were used to obtain data on IA, BI, SP, BDP and DPS. Survey data were used to test the proposed model using hierarchical regression analysis. Mediation analyses with bootstrap via PROCESS were used to ascertain the proposed relationship.

The results showed that individual attitude are positively related to donation path selection. Moreover, this study finds that behavioral intention serves as a mediator in the relationships between individual attitude and donation path selection. The social pressure and behavioral difficulty perception negatively moderate the relationship between individual attitude and behavioral intention.

There are still some shortcomings in this study: First, although the data collected at multiple points in this study are all individual data. Future research can add evaluations of relatives, friends or colleagues to individual scheduling of survey subjects to reduce homology errors. Second, although this study has verified the mediating role of the opposite sex, some of the mediating results show that there may be other variables that play a role in the relationship between individual attitudes and donation path selection. In the research on path selection, the integrated theoretical perspective has rich connotations but has not attracted enough attention from the academic community. This research is only based on this single theoretical perspective to construct, verify and explain the model, and there should be other integrated theories. The fit point can be used to analyze the influence mechanism of individual attitudes on the choice of donation path.

First of all, we must deepen our understanding of the connotation and role of individuals' attitudes. In the event of a major epidemic, the following two types of measures will be taken to improve individuals' attitudes toward specific donation paths: First, the sponsors of each donation should do their best to donors and provide more information about donations, because the more information resources they have, the stronger the experience of the corresponding donation path, and the more they will choose the path. The sponsor of the second donation must show concern for major epidemics that are prone to occur and a desire to help people affected by disasters, so as to enhance the emotional identity of the donor, thereby increasing the probability of the donor choosing a specific donation path. Secondly, donation sponsors should be wary of the negative influence of social pressure on the donation path selection of individual donors. Donation sponsors can train individuals who are willing to donate, guide them in social relations, online public opinion and other pressure methods and improve the possibility of individuals choosing specific donation routes.

Deepen the understanding of the content and effectiveness of the behavioral difficulty perception that has a profound impact on the donor. The greater the tendency to make a path choice is often affected by the individual's perception of the difficulty of behavior. The perception of difficulty of a certain donation path will cause the individual to retreat and inhibit the possibility of the individual choosing the path. Therefore, donation sponsors should take all measures to make their own donation channels simpler and more efficient, thereby reducing the individual's perception of the difficulty of donation behavior.

Drawing on TPB theory, a theoretical framework is constructed that specifies the process through which individual attitude affects donation path selection to expand collective understandings of individual attitude in the donation context. Furthermore, the boundary conditions of the underlying process are investigated, which further enhances the contribution of this paper to the extant literature on individual attitude.

Toward the construction of a new paradigm in teacher education in a globalized and digitalized society where it is intended to value knowledge and teacher professional development sustained by collaboration and cooperation, training policies and models based on technology-enhanced active learning will be required. This chapter aims to analyze the dimensions that can affect these training models within a new educational paradigm, at the level of professional development and increase of technological skills, collaborative processes for the creation of communities of practice, and promotion of active learning that contribute to innovative hybrid environments and transformative learning. In the Covid-19 post-pandemic, it is crucial to study and mobilize the experiences developed in the educational field exploring how these can be harnessed to build this new educational paradigm. This work aims to contribute with a reasoned reflection and insights concerning learning models and methodologies in teacher education that contribute to transformative active learning. Focusing on the link between preservice and in-service teacher education, the interrelation among teacher education and evaluation, and the construction of innovative technology-enhanced learning environments, for instance through the active training model.

This study aims to enhance the understanding of the current research landscape regarding the utilisation of telepresence robots (TPRs) in education.

The bibliometric and thematic analysis of research publications on TPRs was conducted using papers in the Scopus database up to 2023. The final analysis focused on 53 papers that adhered to the selection criteria. A qualitative analysis was performed on this set of papers.

The analysis found a rising trend in TPR publications, mostly from the USA as conference papers and journal articles. However, these publications lacked technology integration frameworks, acceptance models and specific learning design models. TPRs have proven effective in various learning environments, fostering accessible education, better communication, engagement and social presence. TPRs can bridge geographical gaps, facilitate knowledge sharing and promote collaboration. Obstacles to implementation include technical, physical, social and emotional challenges. Publications were grouped into four thematic categories: didactic methods of using TPRs, TPRs for educational inclusivity, TPR as a teacher mediator and challenges in using TPRs. Despite the significant potential of TPRs, their broader adoption in education is still facing challenges.

This research solely analysed research papers in the Scopus database, limiting TPR publications with the keywords “telepresence robots”, “learning”, “teaching” and “education”, excluding studies with different other keywords.

This study enhances understanding of TPR research in education, highlighting its pedagogical implications. It identifies a gap in the inclusion of technology integration frameworks, acceptance models and learning design models, indicating a need for further research and development.

With the advent of Internet technologies, shorter product life cycles and increasing competition, organisations have started looking for innovation sources outside the organisational boundaries. The external community of crowds can be used as a valuable source of co-creation in a company's innovation process to generate value. Despite its growing popularity, organisations often face difficulty capturing value from crowdsourcing due to the lack of proper mechanisms behind crowdsourcing-based value co-creation between a crowd and an organisation and their impact on organisational learning and innovation performance. The present study seeks to understand the crowdsourcing-based co-creation mechanism that influences knowledge transfer effectiveness and the organisation's absorptive capacity, resulting in improved innovation performance.

The model was empirically tested using online survey data received from 300 managers of IT firms. Partial least squares structural equation modelling was used to test the model.

The empirical results reveal that crowdsourcing-based value co-creation causes structural, cognitive and relational linkages between a crowd and a firm, among which crowdsourcing-based cognitive linkage contributes more to organisational value capture. Further, an organisation's effective knowledge transfer and absorptive capacity play an important role in influencing the crowdsourcing-based-co-creation organisational learning-innovation performance framework.

This is the first and foremost study that has developed an integrated model using social capital dimensions to understand the entire mechanism behind crowdsourcing-based value co-creation between a crowd and an organisation and their impact on organisational learning and innovation performance. The study provides organisations with theoretical and practical implications of using crowdsourcing as a value co-creation tool and its effects on enhancing organisational learning and value capture.