In 2014, I wrote a blog piece on how digital content will be delivered to university students. While drawn from my experiences as a university academic, a description of the evolution of content delivery was applicable to students more generally. It described the evolution by decades. On recently re-reading the blog, I decided it might be good to update the content with the decade since the blog was written, especially with the current fascination with artificial intelligence.
First, the historical piece.
It is hard to keep track of all the relevant trends for developing digital content for higher education. Universities worldwide are experimenting with MOOCs (Massive Open Online Courses). Enterprise software such as Blackboard is being challenged by Platform-as-a-Service solutions. Smart phones and tablets are on the rise as everyone desires mobility. At the Consumer Electronics Show in Las Vegas in January this year (2014), wearable technology was proclaimed as the next big thing. All these may impact on how we deliver content into the future.
To know where we are going with digital content in the ubiquitously connected digital world, it helps to know where we came from. So lets explore developments over the last forty years, with snapshots every ten years. Relevant are the hardware used, software available and processes demanded of academics and content developers. Then lets speculate on the future.
Forty years ago, I was studying science at university. Lecturers stood at the front of the class speaking and/or writing on blackboards. Students were expected to take notes. Resources were found in the library. Photocopiers were only just invented and students spent many hours putting coins in slots to copy the knowledge found in books to peruse at one’s leisure. Primitive hardware, no software, and individual processes.
Thirty years ago, I was a postdoc giving occasional lectures and tutorials. Overhead projectors were commonplace. Lecture content was expected to be pre-prepared. Occasionally slides were distributed as handouts. Computers were on our desks to help create content. Ten years later, I was a senior teaching and research academic. Personal computers had become commonplace and were beginning to be hooked up to data projectors. Powerpoint had become the presentation medium of choice, and the Web was about to take off. Hardware was common, software was standardising, and more process was being requested.
Ten years ago, the web had become commonplace. It meant resources were viewable from computers in homes and libraries. Content development and distribution companies had thrived (or survived) the dotcom boom. Enterprise class learning management systems were starting to be deployed seriously in universities. Standards and process for teaching were now mandatory.
Today learning management systems are almost mandatory, but the delivery platforms are in flux. Smartphones and tablets are part of the picture, and consideration needs to be given for new hardware choices. The cloud is replacing standard software for email and is challenging in other areas. Universities are beginning to contemplate outsourcing. It is questionable why organisations such as universities should own hardware and software when teaching and research are their core business.
Let us consider future developments. Re hardware, we will see the continuing demise of traditional PCs in favour of mobile platforms such as tablets. There will be new cross overs between innovations in wearable technology and tablets. I personally do not imagine that people will want course material delivered on Google Glass, but some advocates think otherwise. Different parts of the body may come into play. Will people want electronic notes on their hands? Innovative products such as the Rufus cuff, integrated with smart phones, might be an interesting alternative.
Re software, we need to think beyond enterprise software. Organisations evolve quickly. It is not easily possible to adapt enterprise class software. An alternative is viewing software as a collection of services. Emerging offerings of PaaS, Platform as a Service, allow more rapid development of custom services in practice.
Re process, personalization will be paramount, for both students and content developers. There are already products promising adaptive learning for students. Content will need to be developed accordingly. Commercial models for content developers also need to develop. Not all academics will prepare their own content, but how much will higher education providers pay for their content. And what will consumers want? Quality, celebrity and economy are at odds with each other and there is an argument for each. Free content, freemium, subscription or other pricing mechanisms. Exciting times, and we are in for change.
Now, the update
My predictions were not especially insightful. Wearable technology for delivering content has not developed further. Enterprise class content management systems still abound, with Canvas successfully challenging Blackboard. There have been advocates for virtual reality with little impact. The attempt to launch the Metaverse has had limited success.
A dominant trend which I did not address was the influence of social media. There is much material on YouTube and TikTok, all with likes and comments. The need for textbooks has lessened with much content being available on the Web. Indeed for computing students the ability to find solutions to problems by searching the web, and learning from the abundance of content is an essential skill. The economics of social media is beyond the scope of this article, but it will fundamentally affect what is available. The ease of self-publishing content certainly makes it possible for many to contribute content.
While it was good to raise the issue of personalization, I did not envisage how it would link up with generative AI. Establishing the potential for AI will be a major focus for the foreseeable future. Only very recently, the Australian Government Australian schools officially permitted the use of artificial-intelligence tools such as ChatGPT in the classroom, following unanimous support from education ministers. A Government task force is being established.
People can already use ChatGPT instead of Google in many instances to both find and structure information. Note that there is an issue with the correctness of information generated by ChatGPT and other large languages models (LLMs). Training students how to use LLMs effectively is a challenge for the next decade.
The engagement with generative AI is much more interactive than finding information in a library or on the Web. Students need to pose a question appropriately. They also need patience to shape their answers over several iterations. It is a significant change from previous decades.
About The Author
Professor In Software Engineering Computing and Information Systems at The University of Melbourne
Professor Leon Sterling is a career academic with a distinguished academic record. After completing a PhD at the Australian National University, he worked for 15 years at universities in the UK, Israel and the United States.
He is an academic based in Melbourne, Australia with a 40+ year career working across the fields of artificial intelligence, ICT and design.
His current research focuses on incorporating emotions in technology development, where motivational models are an essential element.