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The same for less or more for the same?

Updated: Jun 27


AI presents organisations with an interesting choice – provide the same level of service at a cheaper price by replacing workers with AI … the same for less … or increase the service that they provide at minimal or no extra cost by using AI to enhance staff productivity… more for the same. Each firm faces its own unique circumstances and decides accordingly.

 

What about governments and education? The current political zeitgeist is austerity; reduce spending and decrease governments’ footprints, i.e. the same for less. As AI grows more sophisticated and AI education solutions start to reach schools over the next 2-4 years, the temptation will be for governments to do likewise.  To reduce the cost of providing the current level of services; the same for less.  That would be a mistake and missed opportunity.

 

AI is a chance to do more for our students and therefore society, at a low or possibly zero marginal cost. This requires solutions that focus on raising teachers’ professional autonomy, teachers adapting to more sophisticated tools and solutions in their classrooms, and an awareness of the wider teaching ecosystems that support good teaching.

 

Raising Professional Autonomy

AI solutions for education must focus on teachers.  They must be easy and intuitive for busy teachers to use, and provide clear, quick data to teachers that informs their practice.

 

Adaptive Teachers

Effective AI solutions will enable great teachers to be more adaptive in the classroom.  Take writing literacy, a current focus in education.  Teaching writing is challenging as marking is complex and time-consuming.  It’s a mechanical process that provides important data which informs high-value decision-making and teaching by teachers.

 

If we automate the mechanics of marking and quickly provide teachers with quality information, they can use the data to adapt their classroom teaching to students’ needs. This requires a step-change for teachers as we disconnect the mechanics of marking from acquiring data and acting on it.  Teachers who can understand and use data will raise their productivity and value.

 

Teaching Ecosystems

As the use of AI evolves, we need to recognise the less obvious, but very real benefits of historic systems such as exam marking.  Through physically marking national assessments, a group of teachers build their curriculum and professional knowledge.  It’s great professional learning and development. AI solutions will increasingly be able to do the marking at a lower cost, i.e. the same for less.

 

Except that it’s not the same, because we potentially lose the professional development of teachers.  Instead the government must take a ‘more for the same’ approach.  Use AI for marking, and transfer the existing spend to sharing this data more quickly with schools to inform their decision making and employ teachers to train others in curriculum and data use.

 

Students, whānau and society don’t win if governments use AI to do the ‘same for less’ in education.  They do if we choose to get ‘more for the same’. 

 

Historic declines in teachers’ relative pay, e.g. compared to MP’s, reflect successive ‘same for less’ approaches to education and consequent declines in teachers’ perceived value. AI should be an opportunity to reverse that.

 

That’s our focus at Teachplus.  We’re designing tools and solutions that enhance teachers’ professional autonomy and support them to be more adaptive to the needs of students and their whānau (families). 

 

Our first cab of the rank is LISA – a self-marking diagnostic tool that we’re developing with schools to help them easily gather data about students’ writing and to use this to inform teachers’ work across all learning areas.  It’s an exciting time for teaching.

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