Over the years, technology has become increasingly dominant in every sector of the world, and the impact of digital technology on educational institutions has not been left behind. The concept of “digital education,” which entails using technological tools for both learning and teaching in a classroom context, has changed the traditional classroom environment for both teachers and students. In the present era of technological advancements, digital education is essential because it makes learning efficient through individualized learning, open access to an unlimited amount of information, flexible teaching methods, etc. Digital learning makes it possible for students to communicate and study with a greater variety of materials without having to rely solely on the limited resources available in a traditional classroom setting. Students can study and explore information more easily with the aid of basic digital skills and technology. A student’s academic performance and engagement in active learning both improve with a positive attitude and motivation. Digital education has various pros and cons in the teaching environment and its impact on different beneficiaries. Through a literature search, materials from public, educational, and expert sources were obtained. In this chapter, each of these will be explored and conclusions drawn.

The purpose of this qualitative study was to understand how undergraduate math students perceive their learning in an online learning environment. A review of the literature revealed a need for additional qualitative research on the perceptions of students in the online learning environment. The specific elements of interest were technology, communication, and assessment. The study used a qualitative descriptive case study design. Purposive sampling was used to sample six online undergraduate math students. Online questionnaires and follow-up interviews provided data for analysis. Interpretive analysis highlighted emergent themes to form a true representation of students’ perceptions. The results revealed that students perceived technology as a supportive tool that could not replace the need for teacher–student interaction and engagement. In addition, online students perceived communication as an essential classroom element. Participants considered online assessment measures ineffective without useful feedback. Educational stakeholders could use the study’s findings to make informed instructional design decisions that could increase student success rates in undergraduate online math courses. Also, researchers might use the study findings to identify instructional elements that could potentially lead to increased learning gains.

Despite the significant increase in studies on AI applications in many aspects of life, its applications in mental health services still require further studies. This study aimed to test a proposed structural model of the relationships between AI use, therapeutic alliance, and job engagement by PLS-SEM. The descriptive method was applied. The sample consisted of (382) mental health service providers in Saudi Arabia, including 178 men and 204 women between 25 and 50 (36.32 ± 6.43) years old. The Artificial Intelligence Questionnaire, the Therapeutic Alliance Scale, and the Job Engagement Scale were applied in this study. The results showed the structural model’s predictability for using AI and the therapeutic alliance in predicting job engagement and explaining the causal relationships between them compared to the indicator average and linear models. The study also found a strong positive overall statistically significant effect (p < 0.05) of the use of AI on therapeutic alliance (0.941) and job engagement (0.930) and a positive overall average statistically significant effect (p < 0.05) of the therapeutic alliance on job engagement (0.694). These findings indicated the importance of integrating AI applications and therapeutic alliance skills into training and professional development plans.

There is an increasing number of studies concerned with the study of children with autism spectrum disorder (ASD). At the same time, there is a lack of interest in studies on their families, especially on mothers who represent the first breadwinner for a child who suffers from a deficit in social communication with others, reflected in their well-being (PWB). This study aimed to reveal the possibility of predicting the PWB of autistic spectrum children’s mothers through the variables of coping strategies and psychological capital (PsyCap). The study used a predictive, descriptive research method to reveal the ability of the variables—coping strategies (problem-solving, avoidance, support, re-evaluation, remorse) and PsyCap (self-efficacy, optimism, hope, and resilience)—in predicting the PWB of autistic spectrum children’s mothers. The study sample consisted of (248) mothers, to whom coping strategies, PsyCap, and PWB measures were applied. The results showed that there were statistically significant differences between working and housewife mothers of autistic spectrum children in solving problems (t = 3.162, p < 0.002), avoidance (t = 1.973, p < 0.05), positive coping (t = 2.307, p < 0.022), self-efficacy (t = 3.667, p < 0.000), resilience (t = 3.338, p < 0.001), PsyCap (t = 2.866, p < 0.005), and PWB (t = 2.549, p < 0.011). Meanwhile, there were no statistically significant differences in social support, problem reassessment, remorse, negative coping, optimism, and hope. Also, there were no statistically significant differences due to the number of children in coping strategies, PsyCap, and PWB. The results also showed that there were statistically significant differences at the level of significance (0.05) between mothers whose age was less than 40 years and those 40 years and older in solving problems (t = 2.093, p < 0.037) in favor of mothers of the age group 40 years and older (M = 22.00, SD = 1.22), and avoidance (t = 1.987, p < 0.048) in favor of mothers under 40 years of age (M = 6.228, SD = 0.464). However, there were no statistically significant differences in social support, problem reassessment, remorse, positive coping, negative coping, self-efficacy, optimism, hope, resilience, the total degree of PsyCap, and well-being due to the variable of the mother’s age. The regression analysis results showed that optimism and problem-solving contributed to (39.90%) of the total change in PWB for mothers of children with autism spectrum. The study’s findings indicate the need to develop the ability of autistic spectrum children’s mothers to solve problems and their PsyCap, which is represented in self-efficacy, optimism, hope, and resilience, to enhance their PWB, which may have a positive impact on their autistic spectrum child.

The aim of this quantitative study was to investigate the perceptions of Mathematics teachers working in Abha city, Saudi Arabia, toward using IoT in Mathematics classes for students' acquisition and performance. The sample was selected using the simple random sampling technique, and the researcher collected data using a self-developed scale. The analysis revealed that Mathematics teachers' perception of using IoT is high and integrating IoT in the classroom can improve student participation and help them become more skilled. Also, the findings showed that most of the participants in the survey believe that IoT is a field that is well-equipped to operate effectively. The Pearson correlation coefficient showed a strong and positive relationship between teachers' perception of using IoT and students’ concept acquisition and academic performance. Owing to the vast range of study implications and its ability to boost students' performance and acquisition of new Mathematical concepts, IoT must be implemented in the classroom.

The purpose of this quasi-experimental study was to determine the effectiveness of Twitter when used in conjunction with a non-traditional type of educational approach referred to as the “flipped classroom method” upon the academic achievement of 12th grade students and their learning motivation towards mathematics. The study used a quantitative approach, and the sample consisted of 48 students. The study was conducted during a three-week period in two public high schools in Abha, Saudi Arabia. The first hypothesis was that the use of Twitter would improve academic performance in mathematics. The second hypothesis was that learning in a flipped classroom via Twitter would lead to an improvement in math performance but that this improvement within the flipped classroom would differ across gender. The third hypothesis was that learning in a flipped classroom via Twitter would lead to more positive attitudes towards mathematics. The findings did not support the first or the second hypotheses; when used in the context of a flipped classroom approach, Twitter, did not improve academic achievement: F(1, 46) = .49, p = .486. Improvement in academic achievement from pretest to posttest also did not differ across gender; F(1, 44) = .00, p = .963. However, the results did support the third hypothesis; within the flipped classroom, the improvement in motivation was stronger for girls than it was for boys; F(1, 22) = 51.32, p < .001.