by Every few years, an emerging technology arrives on the doorstep of schools and universities promising to transform education. The latest one? Technologies and apps that include or are powered by generative artificial intelligence, also known as GenAI.
These technologies are sold on their educational potential. For example, the founder of Khan Academy opened his 2023 Ted Talk arguing that “we are on the verge of using AI for probably the biggest positive transformation education has ever seen.”
As optimistic as these visions of the future may be, the realities of educational technology over the past few decades have not lived up to their promises. Rigorous investigations of technology after technology – from mechanical machines to computers, from mobile devices to massive open online courses, or MOOCs – have identified the continuing failures of technology to transform education.
However, educational technology evangelists forget, remain ignorant or simply don’t care. Or maybe they are too optimistic that the next new technology will be different than before.
As vendors and startups pitch their AI-powered products to schools and universities, educators, administrators, parents, taxpayers and others should ask questions guided by lessons from the past before making purchasing decisions.
As a longtime researcher examining new technology in education, here are five questions I believe should be answered before school officials purchase any technology, app or platform that relies on AI.
1. What educational problem does the product solve?
One of the most important questions educators should ask is whether technology makes a real difference in the lives of learners and teachers. Is technology a solution to a particular problem or a solution in search of a problem?
To make this concrete, consider the following: Imagine you get a product that uses GenAI to answer questions related to the course. Is this product solving a known need, or is it being introduced into the environment simply because it can now provide this function? To answer such questions, schools and universities should conduct needs analyses, which will help them identify their most pressing concerns.
2. Is there evidence that a product works?
Strong evidence of the effect of GenAI products on educational outcomes is still lacking. This encourages some researchers and educational policy makers to stop buying products until such evidence emerges. Others recommend relying on whether the product design is based on basic research.
Unfortunately, there is no central source for product information and evaluation, meaning that the onus is on the consumer to evaluate products. My suggestion is to consider a pre-GenAI proposal: Require vendors to provide independent and third-party studies on their products, but use multiple methods to assess a product’s effectiveness. This includes peer reports and primary evidence.
Don’t settle for reports describing the potential benefits of GenAI – what you’re in for is what happens when teachers and students on the ground use the particular app or tool. Watch out for unfounded claims.
3. Did educators and students help develop the product?
Often, there is “a gap between what entrepreneurs take and what educators need”. This results in products that are disconnected from the realities of teaching and learning.
For example, one shortcoming of the One Laptop Per Child program – an ambitious program that sought to put small, cheap but sturdy laptops in the hands of children from low-income families – was that the laptops were designed for younger versions of their ideals. the developers. themselves, not so much the children who were actually being used.
Several researchers have recognized this divide and have developed initiatives where entrepreneurs and educators work together to improve educational technology products.
Questions to ask vendors include: In what ways have educators and learners been included? How did their input affect the final product? What were their biggest concerns and how were those concerns addressed? Were they representative of the different groups of students who might use these tools, including in terms of age, gender, race, ethnicity and socio-economic background?
4. What educational beliefs shape this product?
Educational technology is rarely neutral. Humans designed it, and humans have beliefs, experiences, ideologies and biases that shape the technologies they develop.
It is important that educational technology products support the types of learning environments that educators aspire to for their students. Questions to ask include: What pedagogical principles guide this product? What particular types of learning does it support or discourage? You don’t need to settle for generalities, such as the theory of learning or cognition.
5. Does the product level the playing field?
Finally, people should ask how a product addresses educational inequality. Will this technology help reduce learning gaps between different groups of learners? Or is it one that helps some learners – often those who are already successful or privileged – but not others? Is it adopting an asset or deficit based approach to tackling imbalances?
Education technology vendors and startups may not have answers to all of these questions. But they should still be asked for and appreciated. The answers could lead to improved products.
This article is republished from The Conversation, a non-profit, independent news organization that brings you reliable facts and analysis to help you make sense of our complex world. It was written by George Veletsianos, University of Minnesota
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George Veletsianos receives funding from the Bonnie Westby Huebner fund and the SSHRC.
