There are many claims being made that AI will “transform” education, both at the level of compulsory schooling and in higher education. Headlines like “AI will Revolutionize Education” or “Schools Must Change in Response to AI” have appeared worldwide.
When we unpack what EdTech companies are suggesting AI will do, we can identify nine specific features which they see as harbouring the beginnings of the AI education transformation journey. These nine features of AI which will have an impact on education are:
- Personalization of learning. This has been the desired goal of almost all EdTech developments since the first teaching machines were introduced in the 1920s. Defined as behaviourally shaped adaptive learning systems that use assessment to determine what the learner knows now and needs to know to deliver the next learning activity, personalization does not mean pursuing ideas and learning opportunities in creative and imaginative ways, although some AI systems are emerging that would enable this. The implicit learning models are behaviourist rather than constructivist[i].
- Highly interactive learning environments. Using multimedia, simulations and serious games, AI can enable powerful, engaged learning. AR/VR systems, coupled with instructionally designed algorithms, can create realistic situations that test students’ ability to apply their learning. Such systems are used extensively in pilot and air-crew training, engineering, health education and IT as well as in some trades education[ii].
- 24x7 teaching assistants (chatbot tutoring). Using large language learning models, chatbots can be created to tutor and support learning across a range of courses or for a very specific course. These can support students by answering questions, suggesting appropriate learning activities, assessing progress or drawing attention to learning deficits based on the results of assessment. The creation of a chatbot is now much easier and faster than it once was, and many instructors are deploying them to be available whenever a student needs help[iii]. For an example, Contact North | Contact Nord has released a free-to-use chatbot for students of any subject.
- Adaptive assessment on demand. Adaptive assessments leverage AI algorithms to analyze student responses in real time and adjust the difficulty level and content of questions based on individual performance. This allows for a precise evaluation of each student's knowledge and skills. As students answer questions, the AI system identifies their strengths, weaknesses and knowledge gaps. It then selects the optimal next questions to maximize information about the student's abilities. By continuously adapting the assessment based on the student's responses, the system can pinpoint the level of understanding across different concepts. Most learning management systems have adaptive assessment engines. There are also dedicated adaptive assessment systems, such as Adaptemy and AssessAI that enable adaptive learning from feedback.
- Curriculum design, development and deployment. Smart, creative AI engines can generate course content, including designs for student activities, assessments and projects, in a few minutes rather than several hours. Initially, the content of such material was poor, but course generation engines such as Learnery and CourseGen are gradually improving. Contact North | Contact Nord has recently released a free-to-use AI support system for course syllabus writing.
- Increased access to learning anytime, anywhere. The key value proposition for higher education within ChatGPT5 is that students at any level (K-PhD) will find appropriate content, self-assessments, peer support and chatbot tutors for any subject at any time. Although this may not lead to recognized certification, it may lead to faster completion of programs through the more extensive use of competency assessment and prior learning assessment and recognition.
- Data analytics to aid retention and completion. Using multiple data points and AI algorithms, student support services can be directed to those most in need. Significant improvements in retention and completion rates have been reported using analytics[iv].
- Support for project-based learning and research. New AI tools for finding and gathering research materials, analyzing data and automating research processes are a major focus for certain kinds of AI developers. Products such as Research Rabbit, Layer, Research Buddy and Scholarcy are attracting a great deal of attention. The new version of ChatGPT4 released at the end of October 2023 also provides powerful new tools for this work.
- Support for multi-language learning through instant translation: As communities become more complex, language and translation become increasingly important. New generative AI tools enable instant translation, text-to-speech and speech-to-text in more than 140 languages. AI is being used to create powerful resources that enable video, audio or text written in one language to be instantly translated into many others. New work is also being done by researchers to capture dying Indigenous languages using AI tools.
About 30 new apps are released every working day, so it pays to keep an eye on developments via sites like There’s An AI for That or through newsletters like Bens Bites or The Rundown AI. No doubt new categories of applications will develop, and some will have an impact on the work instructors, students and researchers do.
[i] For a critical assessment, see Murgatroyd, S. (2023) Rethinking Teaching in the Age of Artificial Intelligence. Revista Paraguaya de Education a Distancia, FACEN-UNA, Volume 4(2), pages 4-10.
[ii] For examples, see
Zoellener, B.P. & Alexander, P.A. (2019) Learning Simulations in Education. New York: Routledge.
[iii] See Tsivitanidou, O. & Ioannou, A. (2021) Envisioned Pedagogical Uses of Chatbots in Higher Education and Perceived Benefits and Challenges. Chapter in Zapharis, P. & Ioannou, A. [editors] Learning and Collaboration Technologies – Games and Virtual Environments for Learning. Switzerland: Springer.