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Research Article
Investigating Early Warning Signs of Delinquency and the Role of Educators in Identifying At-risk Students
Neha Tanwar*
Issue:
Volume 14, Issue 3, June 2025
Pages:
80-87
Received:
23 January 2025
Accepted:
17 February 2025
Published:
14 May 2025
Abstract: Adolescents and young people have a natural inclination toward exploration and self-assertion through various activities, which can marked in both positive ways—such as art and creativity—and destructive behaviors, including criminal activity, drug abuse, and sexual deviation. Understanding this contrast is crucial in addressing juvenile delinquency and fostering positive youth development. The growth in juvenile delinquency poses significant challenges to society, particularly within educational settings, which are intended to be safe and nurturing but can also facilitate negative behaviours. This study seeks to identify the key factors within educational environments that contribute to juvenile delinquency and explore how social, psychological, and educational influences interact to shape youth behaviour. Employing a mixed-methods approach, the research gathers empirical evidence through surveys and interviews with educators, students, and juvenile counsellors, revealing a complex relationship between educational environments and delinquency characterized by a lack of supportive relationships with educators, poor school climate and safety perceptions, socioeconomic challenges faced by students, and limited access to creative and constructive extracurricular activities. In the long run, the paper concludes that addressing juvenile delinquency requires a holistic approach that integrates educational, social, and psychological perspectives; by fostering supportive educational environments and implementing effective prevention strategies, we can promote positive youth development and mitigate criminal activities among the youth.
Abstract: Adolescents and young people have a natural inclination toward exploration and self-assertion through various activities, which can marked in both positive ways—such as art and creativity—and destructive behaviors, including criminal activity, drug abuse, and sexual deviation. Understanding this contrast is crucial in addressing juvenile delinquenc...
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Research Article
Integrating Generative AI in Higher Education: Practical Applications and Institutional Guidelines
Zhihua Zhang*
Issue:
Volume 14, Issue 3, June 2025
Pages:
88-102
Received:
25 March 2025
Accepted:
30 April 2025
Published:
14 May 2025
Abstract: The rapid advancement of Generative AI (GenAI) presents both opportunities and challenges for higher education. Traditional educational methods often struggle with processing large datasets and facilitating real-time interactions, areas where AI offers potential solutions. This paper examines the development, application, and evaluation of a custom GPTs-based AI teaching assistant, the DS-ASST app, specifically designed for Data Science education within a university liberal arts context. Leveraging Retrieval-Augmented Generation (RAG) technology integrated with course-specific materials, the system aims to enhance both instructor efficiency and student learning experience. The study evaluates the AI assistant's impact across four key areas: teaching preparation efficiency, active learning support, data analysis process enhancement, and the promotion of advanced learning activities. Findings indicate significant improvements in instructor workflow, allowing for more focus on pedagogical refinement rather than routine content creation. For students, the tool provided on-demand concept clarification, guided problem-solving, and personalized learning path suggestions, fostering self-directed learning and engagement, particularly with complex data analysis tasks. The system also aided in developing practical data analysis skills through workflow guidance and interpretation support. Technical challenges inherent in using Large Language Models (LLMs), such as optimizing prompt design for educational relevance and mitigating the risk of AI "hallucinations," were addressed through systematic experimentation and the integration of RAG with a verified knowledge base. Furthermore, the paper discusses the broader implications of GenAI in education, including the redefinition of instructor roles and the evolution of assessment methods. At the same time, based on the implementation experience and existing frameworks, the study proposes practical institutional guidelines and checklists for the ethical and effective use of GenAI by both faculty and students in university settings, emphasizing academic integrity, critical thinking, and AI literacy.
Abstract: The rapid advancement of Generative AI (GenAI) presents both opportunities and challenges for higher education. Traditional educational methods often struggle with processing large datasets and facilitating real-time interactions, areas where AI offers potential solutions. This paper examines the development, application, and evaluation of a custom...
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Research Article
Technologies in the Classroom: Catalysts for Change and Potential Obstacles
Issue:
Volume 14, Issue 3, June 2025
Pages:
103-110
Received:
26 March 2025
Accepted:
30 April 2025
Published:
14 May 2025
Abstract: This article examined how digital and socioeconomic gaps affect the implementation of technologies in education. Unequal access to these tools influences academic performance, especially among low-income students. Studies highlight that students from higher-income families have easier access to devices and the internet, which enhances their educational outcomes. In contrast, those in disadvantaged contexts face limitations that affect their learning. Furthermore, the adaptation of Information and Communication Technologies (ICTs) has fostered innovative methodologies such as the flipped classroom, which promotes collaborative learning. However, resistance to change, especially among older educators, hinders their adoption. A lack of teacher training and adequate resources perpetuate these inequalities. The research specifically addresses the digital divide through multiple perspectives, including device accessibility, connectivity infrastructure, and digital competency development among students and teachers. Our findings indicate that the implementation of ICTs in educational settings varies significantly between urban and rural areas, with rural communities experiencing pronounced disadvantages in technological infrastructure. These disparities are further amplified by socioeconomic factors, as evidenced by research showing that low-income households have significantly less internet access compared to middle and high-income households. The study also explores pedagogical innovations enabled by ICTs, such as constructivist and connectivist approaches that promote student autonomy and active knowledge construction. However, our analysis reveals that these innovations are not equally accessible across different socioeconomic contexts, potentially exacerbating existing educational inequalities. Age-related resistance to technological adoption among educators represents another significant barrier, with research showing that teachers over 50 years old demonstrate greater reluctance to incorporate ICTs into their teaching methods. This research contributes to the ongoing discourse on educational technology by highlighting the complex interplay between technological implementation, socioeconomic factors, and pedagogical practices. In conclusion, although ICTs have the potential to improve educational quality and promote equity, digital and economic gaps limit their impact. It is essential to design inclusive policies and strengthen teacher training to ensure equitable access to digital resources and opportunities for all students, regardless of their socioeconomic background or geographical location.
Abstract: This article examined how digital and socioeconomic gaps affect the implementation of technologies in education. Unequal access to these tools influences academic performance, especially among low-income students. Studies highlight that students from higher-income families have easier access to devices and the internet, which enhances their educati...
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Research Article
Practical Applications of Generative AI in Educational Support
Zhihua Zhang*
Issue:
Volume 14, Issue 3, June 2025
Pages:
111-125
Received:
25 March 2025
Accepted:
2 April 2025
Published:
26 May 2025
Abstract: This paper investigates the practical application and effectiveness of a custom generative AI teaching assistant, developed as a GPTs application named DS-ASST, within a "Data Science" course at Kansai University of International Studies. As generative AI technologies like Large Language Models rapidly advance, their potential to transform educational paradigms becomes increasingly evident, offering solutions to challenges inherent in traditional methodologies, particularly in areas requiring personalized learning and large-scale data interaction. This research utilizes the 'Reconsidering Education in the AI Era' framework, focusing on educational AI alignment and redesigning practices to support both instructors and students. The DS-ASST system was developed using Retrieval-Augmented Generation technology to integrate course-specific materials, including lecture notes and textbook content, ensuring responses are contextually relevant and minimizing factual inaccuracies or "hallucinations". We detail the system architecture, iterative prompt design experiments aimed at optimizing educational value, and strategies employed to mitigate technical challenges like hallucination. The system's effectiveness was evaluated through formative assessment across four key dimensions: enhancing teaching preparation efficiency, supporting active student learning, improving data analysis processes, and promoting advanced learning activities. Key findings indicate significant improvements, including a notable reduction in instructor preparation time (approximately 42%) and increased student engagement in discussions (38%) compared to control groups. The AI assistant effectively provided on-demand concept clarification, guided problem-solving, facilitated interaction with complex data, and supported advanced activities like critical evaluation and ethical reasoning. While demonstrating substantial benefits over traditional methods in scalability and flexibility, limitations related to domain specificity, assessment capabilities, and technical requirements were noted. This research assessed the wider ramifications of generative AI for educational reform, based on its practical implementation in education. It specifically considered the changing roles of teachers, developments in assessment techniques, and the necessity of ethical literacy. The study also outlined potential future research, emphasizing hybrid teaching approaches and the formulation of sound ethical guidelines.
Abstract: This paper investigates the practical application and effectiveness of a custom generative AI teaching assistant, developed as a GPTs application named DS-ASST, within a "Data Science" course at Kansai University of International Studies. As generative AI technologies like Large Language Models rapidly advance, their potential to transform educatio...
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Research Article
Exploring the Structural Logic and Learning Path of Prompt Language in AI-Assisted Interaction Design
Xin Kang,
Xin-Zhu Li*,
Xiaoxia Bai,
Yi Zhang,
Shiyi Chen,
Keying Wang
Issue:
Volume 14, Issue 3, June 2025
Pages:
126-133
Received:
23 April 2025
Accepted:
3 June 2025
Published:
11 June 2025
DOI:
10.11648/j.edu.20251403.15
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Abstract: With the rapid development of generative artificial intelligence (AI), prompt language has emerged as a crucial interface for human–AI collaboration, reshaping interaction design processes and the practice of design thinking. This study situates itself within an interaction design course, integrating the five-stage model of design thinking (empathize, define, ideate, prototype, test) with project-based learning to systematically explore the structural characteristics and cognitive pathways of prompt language. By analyzing 362 prompts created by 64 students, the study identifies five types of prompt structures—directive, descriptive, narrative, comparative, and hybrid—and reveals their significant impact on the accuracy, stylistic consistency, and creativity of the AI-generated content. Furthermore, the study proposes a “Prompt Interaction Design Model,” highlighting that prompt language in AI-assisted design functions not only as a task-oriented tool but also as a medium for expressing design thinking and as a vehicle for learning and reflection. This model provides a practical and operable language training framework for design education, enabling students to develop skills in prompt crafting, critical thinking, and creative experimentation. Ultimately, this research contributes to the pedagogical integration of AI tools in design education, offering insights for educators aiming to enhance AI literacy and foster innovative design practices among students.
Abstract: With the rapid development of generative artificial intelligence (AI), prompt language has emerged as a crucial interface for human–AI collaboration, reshaping interaction design processes and the practice of design thinking. This study situates itself within an interaction design course, integrating the five-stage model of design thinking (empathi...
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Research Article
Assessing Stress Levels Amongst Teachers: Factors, Impacts, Coping Strategies and Teacher Well Being
Yolande Jane Van Der Merwe,
Kezell Klinck*
Issue:
Volume 14, Issue 3, June 2025
Pages:
134-145
Received:
15 April 2025
Accepted:
27 April 2025
Published:
16 June 2025
DOI:
10.11648/j.edu.20251403.16
Downloads:
Views:
Abstract: Introduction: Teachers' health, day-to-day functioning, and career development are all greatly impacted by the elevated stress levels they are experiencing in the quickly changing educational landscape of today. Mounting data indicates that high stress degrades important parts of teaching, such as managing the classroom, emotional engagement, and general motivation, eventually reducing the quality of education and student results. Heavy workloads, difficulties integrating technology, regulatory changes, student behavior, a lack of administrative assistance, schedule issues, and rising societal demands are some of the interconnected pressures that are contributing to this developing concern. Many teacher preparation programs do not provide pre-service teachers with adequate stress management skills, which leads to early-career exhaustion and attrition despite the growing need for resilient and flexible teachers. Aim: The study aims to look into the main reasons why teachers experience stress, how it affects their health and performance on the job, and what coping strategies they use to stay productive. Method: A desk method methodology was used to identify common stressors and coping mechanisms, drawing on existing, reliable literature. Through data cross-referencing and triangulation across several sources, this approach guaranteed correctness and dependability. Findings: The study found that the main stressors were time management problems, workload, learner misconduct, and a lack of institutional support. Additionally, it uncovered trends in a range of educational settings, highlighting the necessity of coordinated stakeholder participation and focused stress-reduction interventions. Conclusions: Developing successful interventions that promote resilience, increase work satisfaction, and improve teaching quality and student achievement requires addressing the underlying causes of teacher stress. Contribution: This study aids in the creation of comprehensive support networks that foster teachers' well-being and a happier, more effective learning environment by addressing the causes and consequences of teacher stress and emphasising useful coping strategies.
Abstract: Introduction: Teachers' health, day-to-day functioning, and career development are all greatly impacted by the elevated stress levels they are experiencing in the quickly changing educational landscape of today. Mounting data indicates that high stress degrades important parts of teaching, such as managing the classroom, emotional engagement, and g...
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Research Article
The Developmental Trajectory of Adolescents' AI Ethical Cognition and Educational Intervention Pathways from the Perspective of Philosophy of Technology
Guoqing Yu*
Issue:
Volume 14, Issue 3, June 2025
Pages:
146-153
Received:
14 May 2025
Accepted:
27 May 2025
Published:
20 June 2025
DOI:
10.11648/j.edu.20251403.17
Downloads:
Views:
Abstract: With the rapid advancement of artificial intelligence technology, adolescents, especially those aged 12 - 18, are increasingly exposed to AI applications in daily life and educational contexts. This exposure presents new challenges to their ethical discernment capabilities. Grounded in the philosophy of technology framework, the study examines the developmental trajectory of adolescents' AI ethics cognition and explores corresponding pedagogical intervention approaches. The study employs a combination of documentary analysis, questionnaire surveys, and controlled experiments to systematically interpret the cognitive patterns and developmental mechanisms adolescents demonstrate when confronting AI ethical dilemmas. The findings reveal that 60% of adolescents aged 12 - 14 show a basic understanding of AI ethics, while 40% of those aged 15 - 18 demonstrate a more advanced level. Targeted educational interventions, such as scenario-based instruction and immersive simulations, can significantly enhance their ethical decision-making competencies by 30%. These outcomes provide practical guidelines for developing AI ethics education programs and serve as evidence-based references for policy formulation aimed at optimizing educational practices in the context of AI integration. While the study provides valuable insights into adolescent AI ethics cognition, further research is needed to address potential limitations, such as the sample size of only 300 participants and the scope of the interventions tested being limited to urban areas.
Abstract: With the rapid advancement of artificial intelligence technology, adolescents, especially those aged 12 - 18, are increasingly exposed to AI applications in daily life and educational contexts. This exposure presents new challenges to their ethical discernment capabilities. Grounded in the philosophy of technology framework, the study examines the ...
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