Areas of Impact

During COVID-19 where rapid and wide-spread adoption of digital technologies for learning took place due to school closures, there was concurrently a decline in student achievement, greater inequities and disengagement from schooling that has had a lasting impact on attendance rates in New Zealand. Though the context of the COVID-19 disruption was complex with numerous factors impacting learning and education, it emphasised the importance of in-person schooling and teaching, the holistic role of education in socio-emotional and personal development, and that technology is not the singular solution.

The experience with COVID also highlighted the unpreparedness of education systems to adapt to online instruction. Countries with insufficient IT infrastructure and a lack of resourced digital learning systems suffered the most educational disruptions and learning loss. Though compared to other OECD countries, New Zealand was better prepared and saw less loss in reading and science performance than the OECD average but a greater loss in maths performance. However, a key issue was and still is the inequity in digital access across the country.  Digital adoption across the population is necessary for educational access, expanding opportunities and building pathways for life-long learning. New technological opportunities also underscore “the importance of rethinking what is taught, how it is taught and how learning is assessed”.

Although these technologies offer great potential to improve education, their implementation requires care to ensure these benefits are realised. Technological use should not only focus on availability, costs, or achievement outcomes, but also on the experiences of learners and educators. Teaching practices around creating supportive learning environment, encouraging reflective thought and action, facilitating shared learning, making connections to prior learning and experiences and providing sufficient opportunities to learn – will not be replaced by technology but can be enhanced.

This lists below highlights some key aspects of assessment, learning, teaching, and leadership and management where the use of AI could have a potential impact.

AI for Assessment

  • AI Generated Questions: AI can be used to generate assessment activities and items. LLMs are particularly good at generating multichoice questions related to a specific topic or text.
  • Marking: Some marking can be automated saving teachers’ time and reducing workload.
  • Formative Feedback: Generative AI can provide feedback to students on improving the quality of their writing and help analyse writing from different perspectives.

AI Impact on Assessment

  • Authentic Assessment: Assessment can focus on the application of skills and knowledge rather than content and memorisation. Technology can be helpful in evaluating what learning took place and make assessment more accessible or personalised.
  • Formative Assessment: Teachers will be able to focus on working with students and providing more engaging assessment activities, as the role of summative assessment changes based on AI replacing many low-level tasks. This is similar to the move in Mathematics towards understanding from mere number crunching.
  • Accessibility: Technology can increase access to educational resources for students; AI can also enable knowledge to be more accessible through tailoring the level of language.
  • Collaboration and Connection: Learners can more easily combine knowledge from different areas and engage with different communities and cultures.
  • Engagement: Digital mediums can be designed to capture attention, elements of gamification can be embedded, and generative AI can support creativity.
  • Personalisation: AI systems can give immediate, personalised feedback appropriate to the current level of a student and support the real-time identification of needs for learning.
  • Content Generation: Texts and resources can be generated for specific contexts or levels and questions or activity ideas can be easily co-constructed.
  • Curriculum and Pedagogy: Curriculum and pedagogy may need to be adapted or redesigned to incorporate the changing teaching and learning practices, due to changing technological contexts.
  • Differentiation: Identification of the different needs of students can be supported through data collection and algorithms to help teachers make learning recommendations.
  • Inquiry: Teachers will need to continue to ask what tools and practices might be effective for students and their educational outcomes.
    Translation: Content can be translated into different levels, languages, and for different cultural perspectives.
  • Admin: AI or algorithms can aid in resourcing, scheduling, and tracking attendance or engagement. Efficiency can be increased through implementing digital systems to reduce manual and repetitive tasks.
  • Data for Decision Making: Digital systems are useful in collating and storing data. This can be processed using algorithms and AI for forecasting and planning, informing decision making or aiding policy implementations.
  • Student Support: Collecting data on students and using AI systems could aid in the identification of at-risk students or students with special needs for timely interventions and support to be provided.

Last updated: December 21st, 2023