Teaching Programming in the Age of AI: Pedagogical Strategies for Computational Sociology

Student-facing conversational AI in primary classrooms: Should it be allowed?

This paper examines the opportunities and risks associated with student-facing conversational artificial intelligence (AI) in primary education. It aims to evaluate how large language models (LLMs) can support personalised learning while identifying developmental, pedagogical and ethical challenges. Rather than treating benefits and risks as discrete factors, the study conceptualises AI as a socio-technical intervention that reshapes relationships between learners, teachers and knowledge. The paper adopts a conceptual and theory-driven approach, synthesising current literature on AI in education, pedagogical theories and emerging practices in primary classrooms. The analysis is structured through a tension-oriented synthesis, identifying points of alignment and misalignment between AI affordances and core learning processes in primary classrooms. Based on this synthesis, the study develops a set of guiding principles grounded in developmental and educational considerations. Conversational AI offers significant benefits, including personalised learning support, immediate feedback and reduced teacher workload. However, risks include cognitive offloading, overreliance on AI, misalignment with curriculum goals and ethical concerns such as bias and privacy. The analysis suggests that these are not independent challenges but reflect underlying tensions between technological capabilities and pedagogical requirements. The study is conceptual and lacks empirical validation. Future research should focus on longitudinal and classroom-based studies to assess the actual impact of AI on primary learners' cognitive and social development. The paper highlights the need for interdisciplinary research bridging education, AI and developmental psychology. The study proposes a set of guiding principles derived from the identified tensions, emphasising teacher-mediated interaction, developmental calibration of AI use, transparency, curriculum alignment, privacy protection and equity considerations. These principles provide a structured basis for integrating AI in ways that support learning processes while mitigating potential risks. The adoption of AI in primary education raises concerns about equity, access and digital divides. Without careful implementation, AI may reinforce existing inequalities. Promoting critical AI literacy and ethical awareness among young learners is essential to prepare them for responsible participation in an AI-driven society. This paper contributes a developmentally informed, tension-based conceptual framework for understanding student-facing AI in primary education. By reframing commonly identified opportunities and risks as interrelated tensions, it offers a more analytically grounded basis for guiding AI integration beyond descriptive or normative approaches.

Artificial Intelligence in Classroom Learning: Opportunities and Challenges for Developing Students’ Growth Mindset

The rapid development of Artificial Intelligence (AI) has transformed education, particularly in classroom learning. AI technologies, including intelligent tutoring systems, generative AI, and adaptive learning platforms, provide new opportunities to enhance learning experiences. However, their integration also raises important pedagogical questions regarding students’ critical thinking, autonomy, and growth mindset. This article examines how AI can function as both an opportunity and a challenge in fostering students’ growth mindset. The study employs a qualitative literature review by analyzing recent research on AI in education, critical thinking, and growth mindset. The findings indicate that AI improves access to information, supports personalized learning, and encourages reflective thinking. However, excessive dependence on AI may reduce deep cognitive engagement without appropriate pedagogical guidance. The discussion focuses on three key dimensions: AI as a learning support tool, a catalyst for critical thinking, and a factor influencing students’ confidence and autonomy. The findings emphasize the essential role of teachers in guiding students to use AI responsibly and reflectively. When effectively integrated into classroom activities, AI can promote inquiry, evaluation, and independent learning rather than replace human thinking. Therefore, AI should not be viewed simply as beneficial or harmful but as a pedagogical challenge requiring thoughtful instructional integration. This study concludes that, when supported by appropriate teaching strategies, AI can contribute positively to the development of growth mindset, critical thinking, and reflective learning, while reinforcing the importance of balancing technological innovation with sound educational practice.

AI technologies in language education: Practical aspects and challenges of student usage

Doing the Work? Student Perspectives on AI Tools in Computing Education

The rapid expansion of artificial intelligence (AI) tools, including generative AI, is reshaping task completion and interaction, leading educational researchers to examine learning opportunities as well as emerging concerns in the present technological landscape. Despite ongoing discussions, it is less clear how students may envision such tools being integrated into computing education. We applied the Technology Acceptance Model and conducted a survey across three tertiary academic institutions in the United States, gathering quantitative and qualitative insights on n = 340 computing students' perspectives. Closed-ended items were examined with descriptive statistics, and an open-ended prompt around AI tool use in computing education was explored through reflexive thematic analysis. We found that 64.1% of students somewhat or strongly agreed that using AI tools (e.g., ChatGPT or GitHub Copilot) made them feel as though they were not truly doing the work themselves. Additionally, 48.8% of students somewhat or strongly agreed that they felt conflicted about using AI tools because competent computing/tech students should be able to figure things out without help. The qualitative themes spoke to instances where students may find adoption beneficial, like ''Expediting and enhancing learning, task completion, and organization,'' or problematic, such as ''Moral concerns and regard for social and environmental impact.'' Based on our results, we discuss strategies for teaching alongside AI tools and future considerations for computing educators and developers to support students' agency, ethical reasoning, and decision-making.

The Role of Generative AI (ChatGPT) in Computer Science Education

Generative Artificial Intelligence (AI) has rapidly transformed the educational landscape by providing intelligent, interactive, and personalized learning support. Among the various AI-powered tools, ChatGPT has emerged as one of the most widely adopted applications in higher education, particularly in computer science education. This paper explores the role of ChatGPT in improving programming skills, conceptual understanding, problem-solving abilities, and academic productivity among computer science students. The study also examines the benefits and challenges associated with integrating ChatGPT into teaching and learning environments. While ChatGPT enhances personalized learning, instant feedback, and coding assistance, concerns regarding academic integrity, overdependence, misinformation, and reduced critical thinking remain significant. The paper concludes that ChatGPT should serve as a complementary educational tool rather than a replacement for educators. Proper institutional policies, AI literacy, and ethical guidelines are essential to maximize its educational benefits while minimizing associated risks.

Education isn't fun anymore, is this why students use AI?

In contemporary academic environments, students are increasingly employing artificial intelligence (AI) for purposes that extend beyond traditional support functions such as shaping ideas and correcting grammar or spelling. While much of the existing discourse focuses on concerns around increased efficiency, reduced student engagement, and the erosion of authentic learning, this research reframes the issue from a broader perspective: the enjoyment of the educational experience. Rather than positioning AI solely as a threat to engagement, this study explores what students themselves find meaningful and engaging in their learning. Insights are drawn from end-of-year student feedback alongside discussions with academics participating in the “Universities Pull the Plug” Signal group. These data suggest that students respond positively to learning environments that are interactive, socially engaging, and intrinsically motivating. Within this context, the research investigates the role of game-based learning as a mechanism for enhancing engagement and enjoyment. Specifically, it examines the application of the PlanIT Sustainable Development Game as a pedagogical tool that integrates entertainment with the practical application of knowledge and skills acquired during teaching. Student feedback following gameplay is used to evaluate how such approaches influence engagement, understanding, and perceived relevance of course content. The overarching aim of this study is to develop a narrative and strategic framework for student engagement that emphasises enjoyment, active participation, and personal development. By fostering environments where students experience intrinsic motivation and recognise the value of their own skills development, the research seeks to encourage deeper engagement with learning processes—independent of reliance on AI tools.