Digital learning environments have offered new opportunities to stream educational materials such as courses, educational videos, forums and provide outcomes of the students, grades, engagement details, and learning patterns. These valuable educational data has emerged with the latest technologies and software tools to provide researchers and decision-makers with a better understanding of students' behaviours. These virtual learning environments can professionally aid struggling students by observing, learning, and identifying different learning patterns. Many researchers have discussed that even if there are instructions and helping tools within these environments, some students remain at risk of negative learning behaviours such as boredom, disengagement, and failure. Particularly when approaching complex or new educational content. Previous researchers have observed that the students exhibit high persistence levels when spending too much time on a particular task when they are learning remotely or too many tries to solve a specific task without reaching the success level. Students' persistence is identified as a prominent learning skill contributing to confirmed success while learning new education materials. Many works of literature recognised the value of persistence. They reached a fundamental fact that not all persistence is considered productive, especially when spending more time and effort without moving toward a state of mastery in learning new skills and topics. This scenario may eventually lead to frustration and disengagement; in the worst-case scenarios, the students will finally drop the course or just quit learning. By examining the most relevant literature, this paper discusses the main factors affecting students' digital learning persistence. Different models performed at each learning opportunity are observed to categorise when involvements may be arranged to best aid the learners facing learning struggles.

A new way of spreading knowledge and collaborating with each other to achieve specific objectives has been introduced with the rise of social media, which is an effective communication tool. A growing number of people are using social media for the search of information relating to religious learning and practices. The younger generation is one of the major users of social media; therefore, many Islamic scholars are reaching out to Muslim youths using this channel. However, as people assimilate themselves to the use of social media in gaining knowledge, questions begin to emerge on the credibility of the Islamic information discovered. Anyone regardless of their background can post or share information or articles on social media, so such information is not always credible or true. Self-proclaimed Islamic scholars could use social media for their own personal gains such as to support and propagate sentiments, misinform, spread rumors, or start up conspiracies. This could confuse social media users, especially the younger generation, whose main information source is social media. Despite the significant importance of this area, limited research has empirically examined the factors that affect the credibility of social media information particularly relating to the Islamic context. In addressing this gap, this study inspects the factors obtained from the literature and classifies the dimensions of social media information credibility. Based on the established credibility theories of the Elaboration Likelihood Model (ELM), Prominence-Interpretation theory, and Social Cognitive theory, a research model is developed to determine Islamic information credibility on social media platforms. It is imperative that the study classifies the credibility dimensions, in order to further validate the factors that influence social media users in confirming the credibility of Islamic information. This study also aims to clear doubts and dispel misinformation regarding the Islamic religion by providing a basis for the society to ascertain Islamic information credibility and authenticity.

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Persona is a method to create a user profile by describing a fictitious user through user experience. This persona study needs to be carried out for the benefit of system design according to the users’ wishes because, so far, electronic resources (e-resources) are not widely used due to cognitive and affective factors such as limited subscription resources, limited user manuals, limited navigation features, and frequent errors when using electronic resources. This leaves the user feeling confused and stressed. The aim of this study is to obtain profiles of e-resource users in college libraries. The method used is an empathy map created with data from 32 users who answered questionnaires and participated in interviews. This study found four e-resource user personas in university libraries: lecturers, students, research assistants, and librarians. Users want a guide for using electronic resources that allows for chat and sharing, and which is fun and can be accessed from any device anytime and anywhere. The benefits of this study will be useful for designing e-resource systems according to users’ wishes.

The primary objective of this study is to examine factors that influence Mobile Learning adoption and effectiveness in the case of higher education, underpinned by the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model. The study was conducted at some of the top Saudi universities. A survey method was used in this study, and the questionnaire includes 12 factors, which include enjoyment, hedonic motivation, and performance expectancy, among others, whose relationships with behavioral intention towards using m-learning and in turn, its actual use, were investigated. Additionally, two mediating factors, namely technostress and exhaustion, were included to examine the effects of students’ engagement with m-learning. The questionnaire was distributed to 500 undergraduate students, and 264 replied. Based on the findings, the traditional UTAUT2 factors had significant effects on students’ intention and use behaviors, which were mediated by technostress and exhaustion. The findings indicated that the effective management of mediators is important to improve student engagement in m-learning and that m-learning strategies can be developed through the information provided. This study validated the UTAUT2 model in the case of m-learning, with a 70% success rate in predicting IT adoption, which exceeded other models. Through the study findings, educators and policymakers can find ways to optimize m-learning platforms. Furthermore, it is recommended that focus is placed on the long-term effects of technostress and exhaustion on the students’ adoption of and engagement with m-learning.