Homework in the AI era: cheating, challenge, or change?

Abstract

Homework has always been one of the classic basic elements of teaching and learning (). It is usually seen as a tool to consolidate learning and discipline and to foster independence of young minds. Historically, homework has served as a critical link between formal learning in the classroom and independent learning (Epstein & Van Voorhis, 2001). It has been incorporated into both behavioral theory and constructivist pedagogy (Cooper, 1989), (Piaget and Inhelder, 1969), (Vygotsky, 1978) and has played a key facilitating role. However, the recent explosion of generative AI tools such as ChatGPT has upset this balance. These new systems are now able to provide high-quality answers to difficult scientific problems in seconds, whether it is solving multi-step mathematical problems or compiling entire essays. This transformation raises a fundamental dilemma: will students continue to use homework as a tool for learning at home, or will they outsource the cognitive effort to machines? As the distinction between aid and substitution becomes ambiguous, instructors must evaluate the suitability of present homework assignments for effective learning. This study contends that homework must transition from a model centered on repetition to one emphasizing logic, feedback, and reflection. Rather than simply banning AI tools, teachers should design intelligent, creative assignments that truly use and integrate AI effectively, and avoid simple, quick-solve tasks that AI can easily solve. It is crucial to design tasks for activities that both promote learning and use technology.Homework provides students with opportunities to consolidate classroom knowledge and foster independence. In mathematics in particular, repeated exposure and varied application are essential for mastering procedures and concepts.At their best, homework builds autonomy and mental flexibility. It provides space for experimentation, errors, and reflection, especially when the tasks are well designed.However, these benefits depend on meaningful design and context. Overburdening students with repetitive or overly difficult tasks can demotivate them (Deci & Ryan, 2008)), exacerbate inequalities (especially where support at home is lacking), and drive them toward mechanical or AI-based simplification. If homework is not discussed in class, if it does not consider changing abilities, or if it is viewed as unnecessary work, then its benefits cannot be realized.Technologies such as ChatGPT and Photomath present attractive expedients, particularly when tasks are easily automatable (Tulak, 2024). Students are likely to give their homework to AI if they see it as irrelevant or extremely difficult. On the other hand, AI, when appropriately included into assignments, can assist students by providing tips, comments, or simulations. Homework should be perceived as a dual-purpose educational instrument: it has the potential to enhance learning or devolve into meaningless work. The right balance in the era of AI relies on intentional design, explicit declaration of its worth, and ongoing feedback. Only through this approach can homework transform itself into an inclusive, reflective, and adaptable learning environment.The Core Dilemma: Learning vs Outsourcing Teachers now must consider not only the content and amount of homework but also its susceptibility to the simplification provided by technology with the development of artificial intelligence tools. This advancement begs a basic pedagogical and ethical conundrum: are students still learning while they finish assignments using artificial intelligence tools? Alternatively, are they outsourcing the fundamental cognitive tasks required for meaningful learning?Examining what homework is expected to achieve will help us to address this question. It should ideally provide a low-stakes environment for students to make mistakes, consider their knowledge, and apply it in novel settings. It is the fight with the problem, the so-called "desirab