— In the physical education literature, E-learning in terms of online or blended learning has been lacking and facing several challenges which highlighted a need to conduct more research to investigate modern instruction in the context of physical education. This study is one of the few to determine the impact of Mobile Application-Assisted Instruction (MAAI) on intrinsic motivation and sports nutrition knowledge in a blended learning setting. The “KI-coach” app has been used as a state of an art mobile application based on artificial intelligence. This study adopted quasi experimental approach. Students were randomly assigned into a control group (n=25) that received the convolutional instruction method and an experimental group (n=25) that received MAAI. Study groups adopted a blended learning approach. Measures of intrinsic motivation and sports nutrition knowledge were administered to both groups before and after teaching the nutrition and physical performance course. The ANCOVA analysis revealed a statistically significant difference between the mean scores of the two groups on intrinsic motivation and sports nutrition knowledge. These findings indicated that using MAAI in blended learning promoted the development of intrinsic motivation and enhanced sports nutrition knowledge among physical education students. These findings encourage the decision-makers at the Ministry of higher education and physical education instructors to improve blended learning instruction and practice.

This study addresses global concerns surrounding elementary students' science performance following the COVID-19, as a result of international tests such as Trends in International Mathematics and Science Study (TIMSS) highlight the ongoing challenges that urge the exploration of innovative educational approaches to improve science learning. This research employed gamification-assisted instruction and explored its impact on enhancing the understanding of science concepts and attitudes toward science class among fourth graders. The study adopted a quasi-experimental design and included an experimental group (ExG) that was taught using a gamification strategy and a control group (CoG) that was taught using a traditional method with a sample of 38 female elementary students from a public school in Jordan. Data were gathered using valid and reliable tools: the developed scientific concepts test and the Attitude Towards Science class measures. The ANCOVA analysis revealed that gamification significantly improves the acquisition of scientific concepts (η2=.208) and boosts a positive attitude toward science classes among elementary students (η2=.626). These findings encourage decision-makers to incorporate gamification into science teaching practices and methods.

In terms of artificial intelligence (AI) applications, chatbot-based AI such as ChatGPT have the potential to improve students’ academic well-being and success. Despite the wide spread of chatbot-based AI development, no studies have explored their correlation with psychological constructs in the realm of education. This study aimed to measure the academic intensity use of chatbot-based AI and academic well-being among undergraduates and investigate the correlation between these constructs. The data was gathered using a self-administered web-based questionnaire, which includes the Academic Well-Being Scale and the developed academic intensity use of chatbot-based AI scale (AIUCA). The study sample consists of 340 undergraduates from the School of Educational Science. The findings revealed a moderate level of usage of chatbot-based AI and a moderate level of academic well-being among undergraduates. It also demonstrated a significant positive correlation (r = 0.68) between the intensity use of chatbot-based AI and academic well-being (p < 0.01). These results recommend decision-makers in higher education encourage students to integrate chatbot-based AI with their learning processes and activities to improve their academic well-being.

As the digital world grows rapidly, artificial intelligence (AI) tools such as ChatGPT are transforming how students learn, seek support, and manage academic demands. This study aims to fill a gap in the literature regarding ChatGPT’s role in students’ mental health by exploring the relationship between the intensity of using ChatGPT and academic stress among undergraduate students. A quantitative, cross-sectional correlational design was adopted. Data were collected using an online questionnaire that included the Intensity of Using ChatGPT Scale (IUCS) and the Academic Stress Scale (AAS). The sample consisted of 666 undergraduate students. Descriptive results showed that students use ChatGPT at a moderate level (M = 2.94), while their academic stress levels were low (M = 2.25). Pearson correlation analysis revealed a statistically significant negative relationship between the intensity of using ChatGPT and academic stress (r = −0.637, p < 0.01). Furthermore, regression analysis confirmed that ChatGPT use significantly predicted academic stress levels (β = −0.637, R² = 0.405), with higher use contributing to lower stress. These findings suggest that ChatGPT may serve as a supportive digital tool in reducing academic stress and promoting student well-being in higher education.

The tourism sector was the most negatively affected sector due to the COVID-19 pandemic, especially in areas that depend primarily on tourism, such as Petra, Jordan (World Tourism Organization [UNWTO], 2022). The researchers conducted a survey with the goal of measuring the economic impact of the COVID-19 pandemic on the tourism industry in Petra. Data were collected from 484 residents of Petra to survey their views on the degree of the pandemic’s impact. The findings of the study showed that the COVID-19 pandemic increased unemployment in the region, decreased people’s ability to pay bills and buy essential items, and decreased average salaries. The results also showed that businesses decreased the number of their employees, they were expected to make less money, and more businesses were expecting not to make any revenue. There was a larger economic impact on the residential areas of Wadi Musa and Umm Sayhoun because these residential areas are majorly focused on the tourism industry.

Grounded in the Theory of Reasoned Action, this study aims to examine how technology self-efficacy and attitudes toward AI-based mobile applications predict preservice special education teachers’ (SETs) intentions to integrate these applications into teaching students with learning disabilities (SWLD). A stepwise multiple regression analysis assessed the impact of these variables on preservice teachers’ intentions. Data were collected from 173 preservice SETs. The results revealed that preservice teachers exhibited moderate levels of technology self-efficacy, intentions to integrate AI-based mobile applications, and attitudes toward these applications. Furthermore, attitudes toward AI-based mobile applications emerged as the strongest predictor of teachers’ intentions to integrate these technologies (r = 0.878, p < 0.05), while technology self-efficacy also had a significant effect (r = 0.698, p < 0.05). Together, these variables accounted for 76% of the variance in intentions (R2 = 0.77). These findings underscore the important role of technology self-efficacy and positive attitudes in affecting teachers’ adoption of AI-based mobile applications. This study addresses the gap in the literature on integrating AI technologies in special education and emphasizes their potential to enhance teaching practices for SWLD. Based on the findings, the study recommends training and support to improve preservice teachers’ self-efficacy and attitudes toward AI-based mobile applications, facilitating their integration into special education settings.