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In the new era, applied economics education is evolving with increasing emphasis on practical training. To cultivate high-quality talents equipped with both theoretical knowledge and practical skills, educational institutions must continuously improve their teaching strategies. This article analyzes the current state of applied economics education, identifies existing challenges, and highlights the importance of practical learning in enhancing students’ abilities and employability. It proposes strategies such as school-enterprise collaboration, simulation training, and real-world project integration. Moreover, advanced computational algorithms—such as machine learning and optimization techniques—are introduced into teaching practices, offering innovative tools that deepen students’ understanding of economic issues and improve problem-solving capabilities, particularly in data analysis, model building, and evidence-based decision-making. © 2025 IGI Global. All rights reserved.

This research investigated the relationship between teachers’ interpersonal variables and EFL students’ willingness to communicate and their mental health. The statistical population of the research was 301 students in different grades and universities. In order to collect the required data, the researchers used standard mental health, willingness to communicate, and teachers’ interaction questionnaires. The collected data were analyzed by SEM statistical analyses to investigate the relationship between the variables. The findings showed that there was a positive and significant relationship between teachers’ interpersonal variables and EFL students’ willingness to communicate and mental health. Interpersonal variables of teachers predict 73% of changes in students’ willingness to communicate and 63% of changes in students’ mental health. The findings of the study emphasized that EFL teachers’ immediacy behaviors empower students, leading to sustained attention and increased interpersonal interaction. This positively influences students’ mental health and willingness to communicate. In addition, language learners’ willingness to communicate is influenced by communication apprehension, self-perceived competence, and emotional intelligence. These factors play a role in shaping the dynamics between teachers and students, impacting mental health and communication willingness. These findings have significant pedagogical implications in an EFL setting. EFL teachers utilize interpersonal projection as a discourse strategy to enhance students’ willingness to communicate. This perspective aligns with a systemic-functional approach, emphasizing the impact of teacher communication on student engagement. The relationship between EFL learners’ emotional intelligence and their willingness to communicate is significant. Teachers should focus on emotional intelligence correlated with communication dynamics, influencing students’ openness to engage in language learning activities. © 2025, Universidad de Granada. All rights reserved.

This study examines key competencies in tourism, highlighting the balanced value of technical (hard) and interpersonal (soft) skills. In tourism, where customer interaction and cultural sensitivity are paramount, a multidimensional skill set enhances employability and organizational competitiveness. Findings show that technical skills, such as operational and financial expertise, are essential for efficiency yet insufficient alone to meet complex industry needs. Soft skills-communication, adaptability, teamwork, and problem-solving-are critical for customer satisfaction and positive client experiences. Moreover, competencies like emotional intelligence and leadership are vital in multicultural settings. The study suggests educational programs should integrate both skill types to better align with industry demands. This competency-based approach benefits not only tourism but also broader workforce development, promoting sustainable growth through adaptable, well-rounded professionals. © 2025, IGI Global Scientific Publishing.

In the era of rapidly evolving technology and digitalization, where everything is connected through the "Internet+", all aspects of people's lives and learning are being profoundly influenced, ushering in a new era of intelligent education in universities. Taking English Practical Writing course as an example, this study integrates the educational philosophy of "Harmony between Education, Practice and Students", leveraging the Unipus Intelligent Platform. Through project-based teaching methods, it activates the new forces in education and teaching in the era of digital intelligence, exploring a deeply integrated "Digital intelligence + Teaching"model characterized by the "12345"framework. This approach aims to create an English Intelligent Classroom for "New Liberal Arts Engineering Training", cultivating students' talents who are proficient in both Chinese and foreign languages, skilled in English practical writing, imbued with a Chinese heart, brimming with Chinese sentiment, filled with Chinese flavor, and capable of creatively inheriting and promoting the cultural heritage of China. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

This study examines the impact of internships on soft skill development among hospitality students, focusing on communication, teamwork, and emotional intelligence. Drawing on Experiential Learning Theory, applied to survey data from over 17,000 students at a U.S. university, analyzed with Partial Least Squares-Structural Equation Modeling (PLS-SEM), results highlight notable gains in communication and organizational skills, with the highest ratings in respect for diversity and adaptability. The findings underscore the importance of internships in bridging theory and practice, urging educators and industry professionals to enhance internship design, align curricula with industry needs, and improve soft skill assessments to better prepare students for career success. © 2025 Elsevier Ltd

In today's world, increasing stress and depression significantly impact cognitive well-being, making early detection of cognitive impairment essential for timely intervention. This work introduces a Multimodal Fusion Cognitive Assessment Framework that leverages advanced deep learning and graph intelligence to enhance early identification accuracy. Traditional tools like the Montreal Cognitive Assessment (MOCA) are limited in adaptability, prompting the need for a more dynamic, data-driven approach. The framework is validated using datasets involving cognitive tests, voice samples, and physiological signals. It enables a scalable, personalized, and adaptive cognitive assessment system that improves early detection and supports targeted intervention strategies. By integrating deep learning and information fusion, this approach addresses the complexity of cognitive health in a modern context. • This paper introduces Multimodal Deep Learning Integration, incorporating MOCA scores, behavioral data, speech signals, and physiological parameters using GAT, TAT, and CNN-LSTM models to capture diverse cognitive indicators. • The proposed model achieves superior performance through Information Fusion via Heterogeneous GNNs, effectively merging cross-domain data to enable holistic cognitive state assessment via inter-modality learning. • This paper applies Reinforcement Learning (RL) to personalize user interactions based on real-time cognitive and stress cues, reducing cognitive overload and enhancing engagement. © 2025 The Author(s)