Adopting Emerging Technologies within the School Sector
Just as important as managing technology is keeping pace with it. The launch in late 2022 of Chat Generative Pre-Trained Transformer, aka ChatGPT, thrust artificial intelligence squarely into the spotlight and it has remained there ever since.
Equal parts threat and opportunity for businesses and organisations of all stripes. Schools included. Determining how this potent, user-friendly technology is best incorporated into teaching and learning environments – keeping it out has already been deemed an impossibility – is something educators will continue to grapple with in 2024.
As AI-driven personalised learning platforms are being touted to improve engagement and outcomes by adapting to individual learning styles and paces, deciding whether and when to incorporate them into the teaching process is crucial.
In this article, Atturra’s Senior Consultant Ian Quartermaine provides his perspective on where schools should be focusing their attention when it comes to emerging technologies.
Types of Emerging Technologies
Artificial Intelligence (AI) isn’t the only emerging technology on the mind of school leadership, however it certainly is the most pervasive one at the moment. While schools grapple with AI, other technologies also warrant a mention.
Data analytics has advanced to provide both descriptive and prescriptive analysis through Platform-as-a-Service (PAAS) offerings and machine learning modelling, which is a branch of Artificial Intelligence (AI). In terms of cybersecurity, ICT managers are now opting for Security Operations Centre (SOC) platforms and fully integrated toolsets such as Security Information and Event Management (SIEM), Extended Detection and Response (XDR), which help prevent, detect and respond to threats across their environments. While there is mention of IoT, robotics, and other fields, we will focus on Generative AI.
Generative AI Most Applicable to Schools
AI itself is a huge realm. Branches include Machine Learning, Expert systems, and Speech & Image Generation Systems. Most relevant to schools are the generative text systems using Natural Language Processing (NLP) called Large Language Models (LLMs). Most schools now realise they must embrace this technology to both assist the teaching process and workload and enhance student learning. How schools can manage this while AI progresses at such a breakneck pace, is not an easy answer.
Developing AI Policies Within Schools
First drafts of schools’ AI policies are a good place to begin. A position on AI-enhanced student assessment submission must be clearly outlined, as students will inevitably use AI-generated content whether they are instructed to or not. Reliance on improved plagiarism tools should be treated with caution. It is recommended that use is encouraged, but ask that content is declared and cited correctly. Here is a useful resource for those looking to develop these policies.
In the longer term, teachers will need to review the very nature of old-style assessment tasks where reflection and analysis of AI-generated content is required rather than production of the possibly plagiarised content itself. The academic integrity issues will continue to be a challenge while the indisputable benefit to education becomes more obvious.
Work Intensification
AI has the potential to reduce the workload of teachers by generating teaching materials such as worksheets, rubrics, outlines, and formative feedback through simple but effective prompts. Additionally, AI can enhance students’ learning by providing study guides, summaries, formative tests, contextual versions of content, and the ability to interrogate whole PDFs. Therefore, all students should be encouraged to experiment with these tools and be guided by their teachers.
Short-Term Trends
One of the current trends in artificial intelligence is the development of customised or extended language models (LLMs). These models are being programmed to excel at specific content through the use of programmable mini versions known as “GPTs” (short for Generative Pre-trained Transformer). For instance, Microsoft’s standard 365 Copilot can be extended to access the internet, all 365 applications, and Microsoft Graph – which is the data stored in the M365 tenant. Through plugins and graph connectors, this can be further extended to other internal data sources.
Longer-Term Trends
AI development is expected to lead to the creation of personal learning agents. These AI-assisted agents will be exclusively dedicated and trained for an individual’s learning needs. By analysing the student’s performance and learning style, these agents can create personalised learning plans, offer real-time feedback, provide personal tutoring, and automate the assessment process.
About the author
Ian Quartermaine is a Senior Consultant within the Business Applications team for Atturra. Ian has over 30 years’ experience as an IT leader and manager, including as an adviser to IT managers and school leaders within the Independent Schools sector. He brings experience in school- based applications (school management and learning systems), has managed a national network for Independent Schools in partnership with AISNSW, and negotiated group purchase arrangements. Over these years, he has experienced and given advice on a huge range of school-based business and education applications and processes.
