The Impact of Generative AI on Chinese Poetry Instruction

The Teaching Method Reformation for the Artificial Intelligence Course

In mainland China, the mental health of vocational high school students has been increasingly recognized as a critical issue by both the government and scholars. Positive education, a branch of positive psychology, has been proven to significantly enhance adolescents’ well-being and academic performance. Exploring how to effectively integrate positive education theories or models with traditional teaching methods in vocational classrooms is a promising research direction. To address this, the present study uses the Mechanical Drawing course as a case study, combining the PERMA model with the traditional PBL teaching model to propose an innovative and practical teaching method: the PERMA-based PBL teaching model. The study involved 207 first-year vocational high school students from four parallel classes. Based on their pre-test scores, the students were divided into two parallel groups (A and B) for a crossover experimental design. Quantitative data were collected using the Inventory of Positive Mental Characters among Chinese Middle School Students and a course survey questionnaire. Each group underwent pre-test, mid-test, and post-test assessments, with quantitative analysis conducted via t-tests to evaluate the advantages of the new teaching model compared to traditional teaching methods. The results indicated that the new teaching model significantly outperformed the traditional teaching model in enhancing all dimensions of vocational high school students’ positive psychological qualities (p < 0.001). Additionally, the new teaching model was superior in improving students’ Learning Interest (p < 0.001), Learning Motivation (p < 0.001), and Learning Attitude (p < 0.05). Furthermore, vocational students expressed a stronger preference for the PERMA-based PBL teaching model compared to the traditional teaching model (p < 0.001). This study explores a practical pathway for integrating positive psychology theories into classroom settings and provides a reference for future research in this field.

This article presents a research on innovative approaches in English language teaching through the application of Artificial Intelligence (AI). The aim is to address the issues found in traditional English language teaching methods by utilizing AI technology. The article begins by identifying the problems in traditional English language teaching and exploring the current applications of AI in education. Then, it specifically discusses the application of AI technology in English language teaching, such as interactive listening training, intelligent error correction and personalized post-class guidance, and cloud-based intelligent English translation teaching. Subsequently, a proposal is put forward to construct a new English language teaching system based on AI technology, including modules for engaging explanations, interactive English assignments, and creating scenarios for cross-cultural communication oral training. Lastly, an evaluation method for assessing the innovation of English language teaching models based on AI is introduced, which includes feedback and perceptions from both teachers and students, as well as an assessment of teaching outcomes. The research findings of this article can provide a more intelligent, personalized, and effective English language teaching approach, thus positively impacting the quality of English language teaching and enhancing students’ interest in learning.

This article presents a research on innovative approaches in English language teaching through the application of Artificial Intelligence (AI). The aim is to address the issues found in traditional English language teaching methods by utilizing AI technology. The article begins by identifying the problems in traditional English language teaching and exploring the current applications of AI in education. Then, it specifically discusses the application of AI technology in English language teaching, such as interactive listening training, intelligent error correction and personalized post-class guidance, and cloud-based intelligent English translation teaching. Subsequently, a proposal is put forward to construct a new English language teaching system based on AI technology, including modules for engaging explanations, interactive English assignments, and creating scenarios for cross-cultural communication oral training. Lastly, an evaluation method for assessing the innovation of English language teaching models based on AI is introduced, which includes feedback and perceptions from both teachers and students, as well as an assessment of teaching outcomes. The research findings of this article can provide a more intelligent, personalized, and effective English language teaching approach, thus positively impacting the quality of English language teaching and enhancing students’ interest in learning.

With the rapid development of artificial intelligence (AI) technology, its application in the field of education is becoming more and more extensive, especially in the teaching mode of language laboratory, AI technology shows great potential and innovation space. The purpose of this paper is to explore the practical teaching mode of language lab based on artificial intelligence, and to reveal its advantages and challenges in language learning by analysing the current status of the application of AI technology in teaching. This study aims to explore the in-depth analysis of the research on the practical teaching mode of language labs based on artificial intelligence. Firstly, it introduces the problems of language labs and analyses the limitations and problems of traditional labs. Secondly, the language laboratory solution measures are elaborated in detail to construct the practical teaching mode of language laboratory based on artificial intelligence. Then, the practical teaching mode of language laboratory based on artificial intelligence is explored. Finally, the application value of the language laboratory of artificial intelligence in the aspects of linguistic research and teaching practicability is discussed. As an innovative application of educational technology, the language laboratory of artificial intelligence has a positive role in promoting the transformation of the modern language teaching mode, and provides new perspectives and methods for foreign language teaching. This paper focuses on the design and construction of the practical language teaching mode of artificial intelligence. With the rapid development of artificial intelligence technology, its application in the field of education has become increasingly widespread. In language teaching, the construction of an AI-based practical teaching model can help to improve teaching efficiency and quality and stimulate students’ interest in learning. This paper elaborates the design principles, construction elements, implementation process and effect evaluation of this teaching mode from various aspects.

The purpose of this study is to research how students' interest in learning about the digital age is influenced by digital media based on artificial intelligence (AI) at the Yogyakarta Administrative Management Academy (AMAYO) in Yogyakarta. Quantitative approaches are used in this research methodology. Purposive sampling strategies were utilized to get data from 75 pupils. The study tool was a questionnaire, and the data was evaluated using the validity test, reliability test, linear regression, T-test, F-test, and coefficient of determination (R²) in SPSS 26. This study suggests that digital media based on artificial intelligence (AI) has a favorable effect on students' interest in learning, with a regression coefficient of 0.920. Because the t-test yields a calculated t value of 57.031, which is greater than the t-table value of 1.666, H₀ is rejected and Ha is accepted. This suggests that students' interest in studying in the digital age at AMAYO Yogyakarta is significantly impacted by the use of digital media based on artificial intelligence (AI). The computed F value of 3252.522, which is higher than the F table of 3.97, indicates that the F-test also reveals results that need serious consideration. Additionally, the 97.8% coefficient of determination (R2) suggests that digital media based on artificial intelligence (AI) can affect students' motivation in learning, whereas 2.2% is influenced by other elements that are not within the purview of this study. According to the study's findings, AMAYO Yogyakarta students can boost their interest in learning in the digital age by utilizing digital media powered by artificial intelligence (AI).

The article highlights the issue of integrating artificial intelligence technologies into the educational process, in particular in the context of higher education. The challenges and prospects of implementing artificial intelligence, as well as its advantages and disadvantages, are assessed. It is noted that the use of artificial intelligence in education is not only an innovative step, but also a strategic decision for preparing young people for the professions of the future. The article discusses the key aspects of using artificial intelligence to personalize learning, adapt to different learning styles, ensure accessibility of education for all students, and optimize learning processes through big data analysis. It is emphasized that various forms of artificial intelligence are designed to facilitate the work of scientists and contribute to the optimization of preparation for classes in teaching activities. The importance of using virtual and augmented reality as modern approaches to stimulate students’ interest in learning, as well as to optimize the process of integrating theoretical knowledge and practical skills, is determined. It is noted that artificial intelligence, thanks to personalized algorithms, adapts educational materials to the individual needs of students, assessing their strengths and weaknesses. The features of the use of artificial intelligence for automating the assessment and analysis of academic results of higher education students are analyzed. A classification of artificial intelligence types by content form is proposed for a better understanding of the possibilities of artificial intelligence technologies in education. Particular attention is paid to the analysis of competence in the sphere of artificial intelligence and the determination of the levels of this competence among educators. The importance of ensuring the ethical use of artificial intelligence is emphasized, in particular to minimize bias and protect student privacy. The strategies and approaches for training educators to use of artificial intelligence are presented. The importance of continuous professional development of educators for the effective integration of artificial intelligence into the educational process is stated.

This study investigated the integration of artificial intelligence (AI) tools into secondary school chemistry education in Zimbabwe, assessing their impact on student engagement and academic performance. Grounded in Vygotsky’s Sociocultural Theory and Cognitive Load Theory, the research employed a mixed-methods approach within a pragmatic framework. Quantitative data were collected through pre-test and post-test assessments and structured surveys, comparing an experimental group using AI tools with a control group employing traditional methods. Qualitative data from student and teacher interviews and classroom observations were analysed thematically. ANCOVA analysis revealed a statistically significant difference in post-test scores between the experimental and control groups, F (1, 117) = 188.86, p &lt; .005, η² = 0.617, demonstrating a large effect size of AI integration on academic performance. Students in the experimental group exhibited a mean improvement of 20%, controlling for pre-test differences. Additionally, interaction effects between AI use and gender (F (1,115) = 0.17, p = .684) as well as prior chemistry knowledge (F (1,115) = 0.05, p = .829) were not statistically significant. Furthermore, 85% of the experimental group reported higher engagement levels, confirming AI’s role in fostering motivation and conceptual understanding. AI tools facilitated personalized learning paths, interactive simulations, and real-time feedback, optimizing cognitive efficiency and deep learning. Despite these advantages, significant challenges emerged, including limited internet access, insufficient technological resources, lack of teacher training, and curriculum integration difficulties. These barriers highlight the need for strategic investments in digital infrastructure, professional development for educators, and curriculum revisions to fully integrate AI into chemistry education. The findings underscore AI’s transformative potential in STEM education within developing nations. Addressing infrastructural and pedagogical challenges is critical to maximizing AI's impact, ensuring equitable access, and fostering long-term sustainability in educational innovation.

This paper studies the use of artificial intelligence technology in the field of education and the way of empowering vocational education and constructs a wisdom teaching model of vocational education based on artificial intelligence. It also applies entropy weight and a fuzzy comprehensive evaluation model to determine evaluation indexes and weights, constructs a fuzzy relationship matrix, and synthesizes a fuzzy comprehensive evaluation model. Based on the model, the teaching effect of vocational education with artificial intelligence is studied, and the advantages of wisdom teaching in the creation of a learning environment and the triggering of students’ interest in learning, creative thinking and problem-solving ability are analyzed by comparing with traditional teaching methods. The results show that there is a significant difference between the effect of AI teaching and traditional teaching, p&lt;0.05. For problem-solving ability, the average score of AI teaching students (M=4.049) is higher than the average score of traditional teaching (M=3.153), where t=14.745, p=0&lt;0.05. The study is crucial for the utilization of artificial intelligence in education and the modernization and reform of teaching.

This study aims to explore aquaculture professionals’ perspectives on, attitudes towards and understanding of Mediterranean farm fish health management, regarding Artificial Intelligence (A.I.), and to shed light on the factors that affect its adoption. A survey was distributed during a major fish health management conference, representing more than 70% of Greek domestic production. A total of 73 questionnaires were collected, for which descriptive statistics and statistical analysis followed. Gender and age were shown to affect interest in A.I. and in viewing A.I. as a partner rather than a competitor. Age was additionally shown to affect trust in A.I. estimates and anticipation that A.I. will contribute to professional development. Education level shows no significant effect. Knowledge of A.I. is positively correlated with A.I. usage (r = 0.43, p &lt; 0.05), as is interest in learning about A.I. (r = 0.64). A.I. usage is in turn positively correlated with eagerness to see its contribution (r = 0.72). Despite the fact that 64.4% characterized their knowledge as little or non-existent, 67.1% expressed interest in learning more, while 43.8% believe that A.I. will revolutionize aquaculture and 74% do not fear they will be replaced by A.I. in the future. The findings highlight the importance of targeted educational initiatives to bridge the knowledge gap and encourage trust in A.I. technologies.

The advancement of artificial intelligence (AI) technology creates new educational opportunities. The purpose of this community service project is to use AI to boost secondary school students' interest in learning. AI-based tools are integrated into the learning process and a series of workshops are used to carry out the program. Among the techniques employed are AI tutoring systems, interactive learning materials, and teacher training. The quality of assignments, length of learning focus, and class participation all significantly rose as a result of the results, indicating a considerable improvement in students' enthusiasm for learning. According to post-program surveys, 90% of teachers believe AI is effective at increasing student engagement, and 85% of students feel that they are more interested in their classes. The infrastructure of technology and the initial adjustment to the new system present the biggest obstacles. To sum up, incorporating AI into education offers a lot of promise to boost student interest in studying, but doing so calls for a planned strategy and continuous assistance.

With the rapid development of information technology and intelligent tools in education, university music education faces the dual demands of personalized instruction and innovative classroom models. However, traditional music teaching methods have limitations in resource utilization, learning feedback, and creative guidance, such as difficulty in personalized content delivery, limited classroom interaction, and subjective evaluation of student works. To address this issue, this paper introduces network technology, micro-courses, and artificial intelligence-assisted teaching. Through the integration of multimedia resources, real-time learning data analysis, and the application of AI composition and intelligent evaluation systems, it achieves refined management and personalized guidance for student music learning. In the experiment, students' learning interest, creative ability, classroom participation, and musical knowledge mastery are significantly improved. The average interest score of students in experimental group A (micro-courses + online resources) is 4.5 points, an increase of approximately 1 point compared to the control group. This indicates that micro-courses combined with rich online resources can effectively stimulate students' learning interest, make them more actively engaged in class, and significantly enhance their exploratory learning of musical knowledge and skills. The results indicate that the integration of information technology and artificial intelligence can effectively optimize university music education models and provide practical reference for personalized, interactive, and refined teaching.

This research is motivated by the importance of the role of technology in education, especially the use of artificial intelligence (AI) and interactive learning tools such as Quizizz to increase students' interest in learning. The purpose of this study is to analyze the impact of the use of artificial intelligence and Quizizz on students' interest in the Digital Educational Technology course. The research method used is a quantitative approach using a survey method by distributing questionnaires to students of the Jakarta State University Office Administration Training Program in 2022 as the population in this study, with a sample of 50 respondents combined between class A and class B, and analyzed with the help of IBM SPSS Statistic 25 to obtain test results. The results of the study show that the use of AI provides a more personal and effective learning experience, while the Quizizz media creates an interesting learning environment through gamification elements. The combination of these two factors has been shown to have a significant positive impact on increasing students' interest in learning, as evidenced by the high level of student engagement and motivation in the learning process. The findings of this study provide insight for educators to develop innovative technology-based teaching strategies and also encourage educational institutions to use modern technology to improve the quality of education in the digital era.

Developments in the field of information and communication technology have produced various products. One of the results of this development is Android-based smartphones. The development of smartphones themselves has been used in the field of education, smartphones are used as learning media. This learning media is usually available in the form of an application that can be downloaded on the Play Store or Google Play. However, can this application produce learning media that is fun, effective and not boring or can this application overcome learning difficulties? This research, which aims to determine the effect of Android application-based learning media on students' interest in learning, will use quantitative research methods with analytical methods using simple linear regression analysis. Based on the results of data analysis and discussions carried out by researchers, it can be concluded that there is a large influence of Android application-based learning media on the interest in independent learning of Islamic Religious Education students at the Islamic University of Indonesia. This is proven by the results of a simple linear regression analysis test carried out, the test results show that the price or value of Android application-based media has a big influence on students' interest in independent learning. The influence of learning media proves that media is one of the factors that influences interest in learning. This research aims to find out the benefits of smartphones as a learning medium for Islamic education management and what applications can be used in learning media. This research is a type of qualitative descriptive research conducted by interviews. Data analysis used is in the form of data collection and data presentation.

This study investigates the effectiveness of Artificial Intelligence (AI) and Deep Learning (DL) tools in enhancing academic journal writing skills among students in the Arabic Language Education program at UIN Maulana Malik Ibrahim Malang. Utilizing a mixed-methods approach within a quasi-experimental design, the research involved 90 final-year students divided into experimental and control groups. The intervention group employed AI-based tools such as ChatGPT, Grammarly, and Quilbolt throughout the writing process, while the control group relied on conventional methods. Data were collected through pre-test and post-test assessments, reflective journals, and structured questionnaires. Quantitative results showed a statistically significant improvement in writing performance among students who used AI tools, with large effect sizes (Cohen’s d &gt; 1.0). Qualitative findings revealed that students engaged critically with AI outputs, valued teacher feedback, and developed ethical awareness regarding authorship and originality. The integration of AI tools also increased student confidence, enhanced writing fluency, and promoted autonomous learning. However, limitations in semantic precision and rhetorical fit especially in theology-specific content necessitated human revision. These findings affirm the role of AI as a cognitive scaffold in academic writing and highlight the need for culturally responsive, ethically guided AI integration in language teacher education.Keywords: Artificial Intelligence, Academic Writing, Deep Learning, Arabic Education, Cognitive Scaffold