During the recent years, the issue of preserving the integrity of digital text has become a focus of interest in the transmission of online content on the Internet. Watermarking has a useful tool in the protection of digital text content as it solves the problem of tampering, duplicating, unauthorized access and security breaches. The rapid development currently observable in information transfer and access is the consequences of the widespread usage of the Internet. When it comes to the different types of digital data, text constitutes the most complex and challenging type to which the method of text watermarking can be applied. Text watermarking constitutes a highly complex task, most of all since only limited research has been done in this field. In order to ensure the successful evaluation, analysis and implementation, a comprehensive research needs to be performed. This article studies the theory, methods and applications of text watermarking, which includes the discussion on the definition, embedding and extracting processes, requirements, approaches, and language applications of the established text watermarking methods. The article reviews in detail the new classification of text watermarking, which is through embedding process and its related issues of attacks and language applicability. Open research challenges and future directions are also investigated, with focus on its information integrity, information availability, originality preservation, information confidentiality, protection of sensitive information, document transformation, cryptography application, and language flexibility.

Mobile devices have become an important tool in higher education. Although mobile devices have several benefits for students, the use of these devices is still very limited among students. This low percentage of usage could be attributed to several reasons, both technical and non-technical. Therefore, there is a need to conduct more research in order to understand the necessary factors that would lead to enhanced student usage, thus achieving sustainable mobile learning. In order to achieve that, our study proposes a model by employing the unified theory of acceptance and use of technology (UTAUT) to investigate the necessary factors that influence intention to use mobile learning among university students. To evaluate the proposed model, structural equation modelling (SEM) was employed to analyze data collected from 612 students. The results indicated that factors, such as device connectivity, device compatibility, device memory, device performance, network coverage, and network speed have a significant and positive influence on students’ intention to use mobile learning. This research provides important recommendations for university decision makers and developers on understanding the necessary factors for adopting mobile learning and reflect the students’ requirements.

Social media communication serves as an integral part of the crisis response following a mass emergency (disaster) event. Regardless of the kind of disaster event, whether it is a hurricane, a flood, an earthquake or a man-made disaster event like a riot or a terrorist attack, social media platforms like Facebook, Twitter etc. have proven to be a powerful facilitator of communication and coordination between disaster victims and other communities. Consequently, several research articles have been published on social media utilization for disaster response. Many of those recent research articles discuss automated machine learning approaches to extract disaster indicating posts, useful for coordination from various social media posts. Despite this, there is a scarcity of comprehensive review of all the major research works pertaining to the utilization of machine learning approaches for disaster response using social media posts. Thus, this study reviews academic research articles in the domain and classifies them across three disaster phase dimensions - early warning and event detection, post-disaster coordination and response, damage assessment. This review would help researchers in choosing further research topics pertaining to automated approaches for actionable information classification and disaster coordination and would help the emergency teams to make well-informed decisions in disaster situations.

The implementation of blended learning in higher educational institutions is increasing due to its perceived effectiveness in affording the benefits of both face-to-face traditional mode and the fully online mode of instructions. However, the leading challenge associated with the online component of blended learning is students’ inability to properly self-regulate their learning activities as self-regulation has been an integral competence for the success in online environments. Research on supporting students’ self-regulation in the online component of blended learning has been on the rise, but these approaches have primarily focused on designing systems and techniques to support students self-regulated learning and have not provided solutions to self-regulation strategies, more importantly online peer-learning self-regulation strategy. The lack of online peer learning self-regulation strategy has been the hallmark of the challenges in blended learning instruction. This study proposed an approach for scaffolding students peer-learning self-regulation strategy in the online component of blended learning. The study involves forming online peer-learning groups based on learning potential and affinity structures; leveraging the design of learning system features to instigate group dynamic elements for facilitating and motivating small group peer-learning, as well as promoting pro-social behavior by offering incentives for combating the inherent problems of reluctance to students’ peer-learning participation. An experiment involving 120 university Students shows that effective online peer-learning self-regulation strategy scaffold involves preparing and inspiring students so as to prevent social loafing and refusal to participate; and secondly to facilitate and fully engage students in the actual online peer-learning discussion. The experimental results show significant improvement of students’ academic performance by using this approach. In addition, our study proposed recommendations for future research.