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Productive_Struggle__AI_s_Help_(and_Hurt).mp4Definition
Productive struggle refers to the process of engaging with challenging tasks or problems that require effort, critical thinking and persistence to solve. This process involves encountering obstacles, making mistakes and experiencing a level of discomfort while working towards solving a problem (Young et al., 2023). In AI-enhanced education, learning is supported by reducing some of these barriers like decoding and organisation through the use of mastery, timely feedback (Campbell, 2025) - therefore supporting knowledge building and resilience - leading to deeper learning.
Potential Benefits
Enhance accessibility, personalisation and instructional quality for students
Adapts educational environments to meet individual learning needs through the use of intelligent tutoring systems to improve understanding
Creates a learning environment that fosters cognitive and social skills through the use of virtual agents enabling simulated social contexts
AI platforms can adapt content to individual student needs, meeting them where they are at and building on their learning, without overwhelming them
AI systems provide immediate, constructive feedback, helping students reflect and adjust their strategies while learning
AI tools enable instruction to be tailored, remove communication barriers and proviide autonomy in learning (Melo-Lopez et al., 2025)
Limitations and Risks
Without appropriate professional development of teachers, the potential of AI to improve and support students may be limited
AI tools may be biased towards a particular mastery or provision of feedback, thus not providing adequate support for students. This may also result in disengagement if the adjustments are too challenging or not challenging enough
Students in under-resourced areas may lack access to the relevant resources, limiting their ability to benefit from AI tools
Over-reliance may reduce social interaction and opportunities for social learning.
Real-World Examples - Pedagogy
A Year 6 student using an AI writing assistant begins struggling with sentence structure. Instead of providing the answer, the tool suggests a scaffolded prompt and encourages the student to revise just one sentence. The student eventually improves, realising through effort that they can solve the problem. This experience builds confidence and reinforces their belief in their ability to grow.
An AI maths tutor identifies that a student is consistently getting fraction problems wrong and begins offering multiple hints. However, the hints are overly helpful, effectively leading the student to the answer with minimal thought. Over time, the student becomes reliant on hints and stops attempting problems independently — leading to shallow understanding and a drop in self-efficacy. This illustrates how AI must be carefully designed to support — not replace — productive struggle.
Real-World Examples - Inclusion
A Year 8 student with dyslexia is reading a science article and struggling to decode the vocabulary. Through the use of AI tools, the student is able to have the sentence read out loud and summarised for them. This reduces the students cognitive load of learning the concept and builds reading stamina and comprehension.
Consider a student with English as an Additional Language (EAL) completing structured essay writing skills. The use of AI could be used to provide worked examples, with relevant scaffolded support, revising the theme of the task on a weekly basis to practice writing about different items and facts. As their writing improves, and they become more independent with their writing, the scaffolds reduce. This form of use can AI enhancement can foster student's cognitive development, but also their emotional and social development as their skills and confidence improve.
Further Reading
Campbell, Z. (2025, June 25). Productive Struggle: How Artificial Intelligence Is Changing Learning, Effort, and Youth Development in Education | Bellwether. Bellwether. https://bellwether.org/publications/productive-struggle
Department of Education and Training. (2020). High Impact Teaching Strategies. Victoria State Government. https://www.education.vic.gov.au/Documents/school/teachers/support/high-impact-teaching-strategies.pdf
Jamaal Rashad Young, Bevan, D., & Sanders, M. (2023). How Productive is the Productive Struggle? Lessons Learned from a Scoping Review. International Journal of Education in Mathematics, Science and Technology, 12(2), 470–495. https://doi.org/10.46328/ijemst.3364
Mcgee, N., Kozleski, E., Lemons, C., & Hau, I. (n.d.). AI + LEARNING DIFFERENCES Designing a Future with No Boundaries. Retrieved July 24, 2025, from https://acceleratelearning.stanford.edu/app/uploads/2025/07/AI-Learning-Differences-Designing-a-Future-with-No-Boundaries_Final.pdf
Melo-López, V. A., Basantes-Andrade, A., Gudiño-Mejía, C. B., & Hernández-Martínez, E. (2025). The Impact of Artificial Intelligence on Inclusive Education: A Systematic Review. Education Sciences, 15(5), Article 539. https://doi.org/10.3390/educsci15050539
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