How many of us can identify with these questions?
What is this piece of information and what does it mean to me?
I need to find information about…
Do I need to know this?
How can I find the right material for my needs?
What do I know now, and how can I improve my knowledge?
These are question that we all will have asked ourselves at some point, or heard our students ask of us. Questions such as these require us to make meaning from information and to use that information in meaningful ways. As we spend greater amounts of time online, or with increasing frequency look to the online world for information, the challenge facing us is to make meaning from the deluge of digital content. Semantic technologies can provide part of the answer, providing that we are clear what the question actually is.
There is an assertion in the introduction to JISC CETIS conference session on Semantic Structures for Teaching and Learning that for many teaching practitioners semantic technologies have remained peripheral at best, and perhaps even completely unknown to most. From a technical standpoint this is almost certainly true. But we should not be surprised, for why would a teacher need to know, let alone what to know, about the software engines that drive much of educational technology infrastructure any more than they would want to understand the mechanical engine that drives their car, providing of course that the journey is successful and the desired destination is reached.
Yet some of the benefits that semantic technologies can bring are of interest to many, perhaps even most teachers, even if they don’t even know what these semantic technologies are.
Using current, often simple software technologies we can create maps of the curriculum that allow teachers and learners to navigate the learning landscape. These maps can use straightforward approaches to using metadata to make associations between content. Frameworks of competency for knowledge, skills and attitudes can allow the learner to better understand their own learning. Semantic technologies can link content in meaningful ways and can link learning intent to content.
These approaches work and utilise some of the core concepts of semantic technologies. But we could do much more. Our information requirements are often highly personalised. Your information needs may be different from mine, despite us sharing a common outcome for learning. Adaptive learning systems can know us and know our needs and present learning opportunities and content to suit, presenting you with different content to me. Learning environments are yet to offer the kinds of personalised experience promised in recent decades. Yet with semantic technologies personalisation can become a reality.
We can already specify our information needs to repositories of content and have new or updated content automatically delivered to us using RSS, originally part of the Resource Description Framework (RDF), now appropriated en masse by bloggers and providers of syndicated news. Personal aggregators of content provide unique and personalised combinations of information, mixing our formal learning with informal learning or entertainment. Today, relatively few repositories or content collections syndicate their content in this way, but in the future much of the web could be available in this rip-and-mix format.
The themes that will become increasingly important to teaching and learning include a greater use of metadata, but metadata that facilitates the discovery and use of content rather than what sometimes seems a millstone around the neck of cataloguers.
A better understanding of the needs of teaching and learning will result in better semantic technologies, more attuned to the needs of non-technical users and those that would rather pay no attention to the man behind the curtain. While educational technology in general and semantic technologies in particular remain exclusively in the hands of technologists, then they will continue to have little impact in the world of the online learner.