Volume 113

In recent years, feminist film theory has continued to reflect on the structures of the patriarchal gaze in mainstream cinema. This paper is based on Laura Mulvey’s theory of the "male gaze" and combines it with bell hooks’ concept of the "oppositional gaze". It examines the visual subjectivity and counter-gaze strategies of the female protagonist Song Seo-rae in Park Chan-wook’s Decision to Leave. Using close reading to analyze camera language, character dynamics and narrative architecture, we reveal how Song Seo-rae negotiates her subjectivity through the act of seeing under the condition of being seen. The research is centered around the following questions: whether women can truly look, and whether Song Seo-rae's gaze constitutes a challenge to the gaze system of patriarchal hierarchy. The findings indicate that her "counter-gaze" operates as performative empowerment. Her scopic sovereignty is consistently obedient to patriarchal narratives. Her scopic sovereignty is consistently obedient to patriarchal narratives. While it satisfies a male’s desires of her, it leads to her self-destructive endings. Decision to Leave thus articulates a complex, paradoxical feminist gaze praxis: one that simultaneously reinscribes patriarchal norms and lightens a female’s awakening and negotiation of gaze sovereignty.

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In recent years, the rapid advancement of Artificial Intelligence (AI) has led to its increasingly pervasive integration within the domain of higher education. Although the implications of AI--both its opportunities and challenges--have been widely acknowledged, scholarly inquiry into effective strategies and methodological frameworks for leveraging its potential while mitigating associated risks remains relatively underdeveloped. This study investigates the transformative potential of AI in driving innovation and progress within the higher education sector, as well as the challenges that universities and colleges are likely to encounter. It concludes that, in terms of opportunities and potential, AI can support university professors in delivering feedback and assessment, enhance students' learning, and improve administrative and management processes. However, higher education is grappling with a range of pressing challenges, notably those related to academic honesty and the standard of academic work, inaccuracies generated by AI, and the exacerbation of educational inequality. In response, this article advances several recommendations, including the promotion of diversified assessment approaches to facilitate the development of AI-resistant evaluation methods, alongside the creation of effective policy measures and strategic approaches that promote the accountable use of AI technologies.

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The role of Artificial Intelligence (AI) in education has received widespread attention. However, the latest research focusing on cost-benefit analysis is relatively scarce. This essay analyzes the opportunities and challenges of AI in the development of education. This essay analyzes that the potential of AI in the field of education mainly focuses on improving the efficiency of teacher teaching and evaluation, promoting personalized learning, and advancing the concept of inclusive education. The main challenges faced are AI bias, teacher marginalization, and the phenomenon of students overly relying on AI. Based on this, this essay proposes suggestions to reduce the risks of AI use in education through the interaction of supervisory intervention and personal norms. Among them, in terms of supervision and intervention, it is recommended that supervisory agencies and teachers intervene in a dual track manner; Personal norms require teachers and students to constantly strive for self-discipline. Find a balance point to maximize the role of AI in educational development.

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With the rapid development of generative artificial intelligence (AI) technology, its impact on the professional competency of higher education teachers is receiving increasing attention. However, the current research mostly focuses on the application of technical tools and seldom systematically explores the multiple challenges and deep opportunities faced by teachers in remodeling and ability transformation. This article focuses on the ability reconstruction of college teachers in the dimensions of digital literacy, reflective practice, and lifelong learning in the context of the AI era. Combining literature and typical cases, this research reveals the challenges that AI brings to teachers, and also brings opportunities such as improved teaching efficiency and personalized development paths. Based on the above analysis, this paper puts forward three suggestions: improving the teacher AI training system and enhancing its technical adaptability; Promote the deep integration of AI and teaching, and realizing a new paradigm of human-machine collaborative education; Reconstruct the teacher evaluation mechanism and strengthening the process and collaborative evaluation.

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This paper will provide an overview of the various challenges that university students are likely to face when seeking employment in the era of artificial intelligence. As more students progressively rely on AI tools to complete their university assignments, the practical skills they possess become increasingly rare and insufficient when entering the competitive job market or having a few chances to get a higher salary. This concern is extremely serious. Under these circumstances, analysing the key problems students may encounter during this transition, as well as the underlying causes, will offer strong support for the central theme of the paper. These problems are categorized into three main areas: psychological challenges, structural job displacement, and institutional policies. The psychological part has a few factors: envy when browsing social media, uncertainty about future career pathways as well as reality reasons. In terms of structural job displacement, the AI is faster than the change of education policy is the key reason for the employment problems. For institutional policy, the staff in the university mainly focuses on short term-skill rather than preferring long term. Finally, the paper proposes strategies to address these issues, providing useful recommendations for students to improve their situations, for example, by developing the practical skills they currently lack.

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With the development of modern technology, like AI and the internet, online courses are gradually replacing traditional courses, which are widely used in many schools. However, online course also has many latent disadvantages that are not recognized by the public. This article discusses the advantages and disadvantages of online and traditional courses, respectively. The benefits of an online course are its flexibility and efficiency of knowledge transmission, while a traditional course provides a structured environment for study and gives more chances for communication between students and teachers. From these findings, this article suggests that these two teaching methods should be partially combined to reach the maximum learning efficiency and student satisfaction. There are two suggestions given, one of which is that online tools and platforms should be used in a traditional course to increase learning efficiency. The other is that structured environments need to be opened for an online course to reduce the effects of distractors.

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The rapid development of artificial intelligence (AI) is profoundly transforming the field of education, presenting unprecedented opportunities and challenges for mathematics education. Currently, the role of AI in promoting educational development has attracted widespread attention. However, existing literature mostly focuses on the macro-level discussions of AI in education, with relatively insufficient in-depth exploration of specific disciplines. This paper focuses on mathematics as a specific discipline, exploring how AI technology can empower mathematics education, systematically analyzing its potential possibilities and possible challenges, and exploring feasible implementation paths. The research finds that the core value of AI in mathematics education is significantly reflected in the precise customization of personalized learning paths and the deep innovation of teaching models. However, its wide application also faces key challenges such as the maturity of technology, the insufficient AI literacy of teachers, and data privacy and ethical risks. Based on in-depth analysis, this study proposes that the core path for the deep integration of AI and mathematics education requires technological iteration, the upgrading of teachers' educational concepts, and the construction of a teacher-student-AI collaborative classroom.

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The issue of how traditional culture can promote early childhood enlightenment education has received widespread attention. However, there are still shortcomings in better integrating traditional culture into the daily curriculum of kindergartens. Dramatic play, as one of the common teaching methods in kindergartens, aligns well with the enlightenment education of traditional culture for young children and offers innovative potential. However, the design of an excellent curriculum is dependent on the interconnectedness of three dimensions: the professional requirements for teachers, content grasp, and resource support. In response to the existing shortcomings, teachers need to enhance their deep understanding of traditional culture, grasp elements that align with children's cognitive characteristics and cultural connotations, and reasonably design these into dramatic play courses. Additionally, they must create a cultural environment for the curriculum and ensure resource support, providing a solid foundation for building dramatic play that is both beloved by children and effectively promotes their development.

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Under the collision of traditional teaching modes and new teaching modes, the teaching mode has undergone tremendous changes. The question of what changes have occurred in students' psychological construction based on this change has received widespread attention. Different teaching models, however, focus more on the transformation of educational teaching methods, neglecting students' mental health. This article analyzes the specific changes in students' psychological construction under different teaching modes in the transition between old and new teaching modes. Further analyzes the reasons and influencing factors based on students' psychological changes, and how to effectively improve and enhance different teaching modes. Based on it, this article proposes the following suggestions: to inherit and develop the factors that are advantageous to students in traditional education. Do not blindly follow the trend in implementing new teaching models, but consider whether they meet the needs of students and put students at the center of everything.

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With the rapid development of science and technology, people's demand for talents with the ability of inquiry, logical reasoning, and innovation is increasing, and the pre-school training of children's scientific inquiry and logical thinking has also been widely concerned and valued by parents and teachers. In kindergartens, scientific education, as one of the five major areas of teaching activities, plays a crucial role in the cultivation of children's ability in this area, and can potentially affect children's attitude towards new things and exploration methods in future science. In kindergartens, there are still problems such as children's low interest and participation in scientific activities, the lack of interest and rationality in scientific activity design, and the lack of kindergarten attention. Combined with the game, the main and preferred learning way of preschool children. Based on this, this paper puts forward suggestions on the interaction between teachers and children, such as providing children's thinking time and appropriate feedback, and methods and focuses of game teaching.

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