Manfred Man-Fat Wu

Purpose: Research on suffering has been dominated by the healthcare, religious and philosophical perspectives which are based on a narrow perspective of individual subjectivity and well‐being, with the social context largely neglected. This paper aims to complement this inadequacy by highlighting the unique contributions of Hegel's anthropological‐philosophical perspective in bridging the gap between individual subjectivity, that is, personal experience, and the objective collective human entity, that is, the social reality, in the discussions on suffering. This in turn can generate concrete measures especially targeting at the concrete reality, that is, institutions, social structures and public policy. This is especially true for Caring Science because suffering and its alleviation are core notions in this discipline. Method: In this project, the conceptual, textual, and comparative analyses on the major and latest healthcare, philosophical and religious literature were conducted. The Hegelian perspective was proposed as the ideal foundation for research on suffering. It is because despite Hegel never explicitly accounted for suffering in any of his works, suffering surfaces in many occasions in his works describing Spirit's unfolding itself characterized by negation, contradiction and suffering. Given this, the Hegelian perspective offers abundant theoretical resources for re‐conceptualizing suffering. Findings: Evidence from Hegel's various works on different realms of life which include individual psychology, interpersonal relationships, family, and morality converges that suffering is caused by contradictions or gaps between individual subjectivity and the objective reality. Physical suffering is caused by diseases and mental disorders such as dementia, and are part of nature. Conclusion: The conclusion is that the Hegelian perspective can effectively serve as a conceptual bridge for the lack of consideration on the intimate links between individual subjectivity and the objective reality in extant research and discussions on suffering. The contributions of Hegel's philosophy lie in his closely‐knitted nexus connecting human subjectivity and the objective reality operated by dialectic.

Purpose: The proliferation of mobile technologies has transformed language learning in distance education, positioning mobile apps as essential tools for remote and self-directed learners worldwide. This paper presents an evaluation of the feature quality of mobile language learning apps (MLLAs), showing how design, content and pedagogical features of widely used MLLAs can be systematically analysed and compared. Design/methodology/approach: Eight widely used MLLAs – Duolingo, Memrise, Busuu, Falou, LingoDeer, Beelinguapp, FunEasyLearn and Innovative Language Learning – were evaluated using a structured framework. The framework encompasses four dimensions: app background, design, content and pedagogy. Findings: The evaluation results highlight the strengths and limitations of each app, as well as the interplay between design, content and pedagogy in supporting learning processes. The results reveal notable disparities in app performance. Busuu emerged as the top-performing app, particularly in content quality and pedagogical features. Beelinguapp showed limited interactivity and applicability. Duolingo, despite its popularity and innovative gamification elements, had shortcomings in content and pedagogy. Originality/value: This study advances mobile-assisted language learning (MALL) research by situating MLLA evaluation within the context of distance education. It offers a practical, objective and replicable feature-evaluation methodology for selecting apps that align with learner needs and objectives. The results also contribute empirical evidence on app quality disparities, supporting evidence-based tool selection for language learning.

This study explores undergraduate students’ attitudes towards generative AI tools in higher education and their perspectives on the future of jobs. It aims to understand the decision-making processes behind adopting these emerging technologies. A multidimensional model based on the technology acceptance model was developed to assess various factors, including perceived ease of use, perceived benefits, perceived concerns, knowledge of AI, and students’ perceptions of generative AI’s impact on the future of jobs. Data were collected through a survey distributed to 93 undergraduate students at a university in Hong Kong. The findings of multiple regression analyses revealed that these factors collectively explained 23% of the variance in frequency of use [(F(4, 78) = 5.89, p < 0.001), R² = 0.23]. Perceived benefits played the most significant role in determining frequency of use of generative AI tools. While students expressed mixed attitudes toward the role of AI in the future of jobs, those who voiced concerns about AI in education were more likely to view generative AI as a potential threat to job availability. The results provide insights for educators and policymakers to promote the effective use of generative AI tools in academic settings to help mitigate risks associated with overreliance, biases, and the underdevelopment of essential soft skills, including critical thinking, creativity, and communication. By addressing these challenges, higher education institutions can better prepare students for a rapidly evolving, AI-driven workforce.

Mobile-assisted language learning (MALL) has emerged as a powerful tool for language education, offering flexibility, multimedia integration, and personalized learning experiences. Despite its growing adoption, most studies have focused on user perceptions and learning outcomes, with limited attention given to systematically evaluating the design, content, and pedagogical efficacy of mobile language learning apps (MLLAs). To address this gap in the effective design of MALL tools, this study developed an evaluation framework by integrating and refining elements from three established models in the field. The framework is organized into four dimensions: background and characteristics, app design, app content, and app pedagogy. It incorporates objective criteria alongside a standardized scoring system (0–2) to ensure consistent and systematic evaluations. The resulting framework provides researchers and educators with a tool to analyze and compare MLLAs based on their alignment with effective teaching and learning principles. This study contributes to the advancement of MALL app evaluation, supporting their development and improving teaching practices and learner outcomes.