This study examines the adoption and usability of lifestyle (LS) apps, considering demographic factors like age and education that influence adoption decisions. The study employed a mixed-methods design, combining an experiment (spanning 14 weeks of app use) with semi-structured interviews and periodic measurements. The researchers employed the Mobile Application Usability Questionnaire (MAUQ) to identify pivotal aspects of standalone app usability, interface satisfaction, and usefulness at various stages of use, with a particular emphasis on the experiences of Hungarian students (n = 36). The results demonstrate that health-related factors have a significant impact on students’ behavior and evaluation of lifestyle apps over the 14-week period. Overall, the analyzed LS apps demonstrated positive outcomes in terms of supporting subject health and significantly improving the perceived health state. The findings highlight both practical and theoretical contributions to the field of mobile health applications, suggesting avenues for further research to either confirm or challenge existing theories.

This study examines the impact of education quality and innovative activities on economic growth in Shanghai through international trade and fixed asset formation. The study examines how higher education quality and innovation activities drive regional economic growth, with a focus on the mediating effects of international trade and fixed asset formation in Shanghai. The study adopts a quantitative approach utilizing panel data from 31 provinces in China covering the period from 1999 to 2022. The study incorporates variables such as education quality, innovation capacity, and GDP per capita, as well as control variables like labor, capital, and infrastructure. The methodology involves multiple regression models and robustness tests to verify the relationships between and effects of education quality and innovation with regard to economic growth. This study analyzes the direct and indirect effects of university R&D expenditure and innovation on economic growth using a regression model, based on data from 2014 to 2022 in relation to Shanghai. The model introduces variables such as international trade, capital formation, and urbanization to analyze the relationship between higher education quality and economic growth.

Students from different cultures possess varying levels of skills in learning, remembering, and understanding concepts. Some terms and their explanations may seem easy for one group of students but difficult for another. Therefore, delivering educational content that aligns with student’s learning capabilities is a challenging task based on cultural orientations. This study addresses the learning challenges by developing a Thesaurus Glossary E-learning (TGE) framework method. This study introduces the TGE method which is a multi-language tool with visual associations that adapts to students’ capabilities. It also examines cultural differences and native languages, particularly aiding Arab Native to visualize appropriate terms (thesaurus) and their explanations (glossary) based on students’ learning capabilities. TGE learns from students’ term selection behavior and displays terms at a simple or advanced level that matches their learning ability. Additionally, TGE demonstrated its effectiveness as an e-learning tool, accessible to all students anytime and anywhere. The study analyzed 314 records related to student performance, out of which 114 students were surveyed to evaluate the effectiveness of the TGE method. This work presents TGE as a novel e-learning tool designed to enhance conceptual thinking within the context of modern educational practices during the digital transformation. TGE is based on artificial intelligence algorithms and associative rules that simulate the human brain, establishing logical connections between related key terms and sketching associations among diverse facets of a situation. An experiment was conducted at a private university in the Sultanate of Oman to assess the effectiveness of the proposed TGE tool. TGE was integrated with selected subjects in information systems and used by the students as a resource for e-learning methods and materials. The results show that 85% of students who used TGE improved their performance by 19%. We believe this work could establish a new smart e-learning teaching method and attract modern and digital universities to enhance student learning outcomes linked with conceptual thinking.

The rise of Internet technology has transformed consumer shopping behaviors, offering convenience and a wide range of options, making online shopping increasingly popular. In Saudi Arabia, this trend has grown significantly due to higher internet penetration, technological advancements, and shifting consumer preferences. However, building and maintaining consumer trust remains a crucial challenge. Despite the growing interest, there is limited research on the unique aspects of Saudi consumers’ online shopping behaviors. This study aims to address this gap by identifying key factors influencing these behaviors and examining their impact on purchase intentions, with a focus on the mediating role of consumer trust. This study explores factors influencing online shopping behavior and their impact on purchase intention, with a focus on consumer trust as a mediator. Using a survey of 573 respondents from Jeddah and Medina, Saudi Arabia, key factors identified through literature review include perceived usefulness, ease of use, risk perception, website quality, and social influence. The quantitative analysis revealed that customer service and return policies, information quality, perceived convenience, ease of use, usefulness, cost-saving, product variety, and social influence significantly affect consumer trust, which in turn enhances purchase intention. These findings provide valuable insights for businesses to optimize digital strategies, enhance consumer engagement, and foster long-term customer relationships, thereby boosting satisfaction and online business success.

Language is fundamental to human communication, allowing individuals to express and exchange ideas, thoughts, and emotions. In early childhood, some children experience communication disorders that impede their ability to articulate words correctly, posing significant challenges to their learning and development. This issue is exacerbated in developing countries, where limited resources and a lack of technological tools hinder access to effective speech therapy. Traditional speech therapy remains vital, but the latest technological advancements have introduced robotic assistants to enhance therapy for communication disorders. Despite their potential, these technologies are often inaccessible in developing regions due to high production costs and a lack of sustainable manufacturing models. For these reasons, this paper presents “FONA,” a robotic assistant that employs rule-based expert systems to provide tactile, auditory, and visual stimuli. FONA supports children aged 3 to 6 in speech therapy by delivering exercises such as syllable production, word formation, and pictographic storytelling of various phonemes. Notably, FONA was successfully tested on children with cochlear implants, reducing the number of sessions required to produce isolated phonemes. The paper also introduces an innovative analysis of the Make To Order (MTO) manufacturing system for producing FONA in developing countries. This analysis explores two key perspectives: collaborative networks and entrepreneurship, offering a sustainable production model. In a pilot experiment, FONA significantly improved children’s attention spans, increasing the period by 17 min. Furthermore, the economic analysis demonstrates that producing FONA through collaborative networks can significantly reduce costs, making it more accessible to institutions in developing countries. The findings suggest that the project is viable for a five-year period, providing a sustainable and effective solution for addressing communication disorders in children.