Week 3: Semantic Web, Linked Data, & Intelligent Curriculum

Juanma:
Another issue is that we need to formalize the concepts and linkage relationships, i.e. the knowledge about educational concepts, so that they can be computer processed. We have to agree on the 'model' underlying that knowledge. But some people can be reluctant to an uniform, machine-understandable way of formalizing and expliciting the knowledge on education and educational research.

Formalization requires agreement about definitions. Not only about education, but epistemology as a whole. What can we know? What is expertise? How should we define and structure knowledge? There is a bottom-up approach to this which becomes more feasible if the definitions and the structures are making sense and are already adopted by the community using them. An imposed ontology is less likely to become accepted than an emerged ontology. That leads to the question: how can we influence the emergence of ontologies? We have seen that folksonomies tend to expand and therefore more difficult to manage. If three different words in a folksonomy have the same meaning, how can we make people want to use only one?

My assumption is that reputation is an instrument that can be used for this matter: Suppose that people's reputation in a community is expressed using the keywords/definitions of the community ontology. Then these keywords all have a relative value that decreases with the number of keywords that mean the same. It is therefore wise for people who find their reputation important to agree upon a set of keywords that express their knowledge, and not use too many keywords for that.

PS. I am doing research in this direction, and wrote an algorithm that supports this reputation mechanism.

I think its a wonderful project, but perhaps a little too ambitious, and I'll tell you why. Humans love to re-purpose things in unexpected ways, and I cant see a set of tags which would be broad enough to encompass all possible uses, yet retain enough specificity to be useful. As an example:
Once upon a time there was an astronomer who was looking at galaxies, and after two years of looking at galaxies everyday they asked for help:
http://en.wikipedia.org/wiki/Galaxy_Zoo
and currently
http://www.zooniverse.org/projects
Whats interesting in all of this is that:
1) These are collections of big data which still need many thousands of people to generate knowledge, and
2) A specific tool for a specific task, (deciding whether galaxies were spirals or not) is now looking for space junk on the moon, examining solar storms, and reading old ships logs to find out about global warming.
This is a very human thing to do, other examples, a website set up for selling Pez dispensers turned into Ebay, and a piece of software set up to help an academic keep track of references, turned into Google.
This is human.
At our best we look above and beyond.
The second problem is the one alluded to in the old joke about the British and the Americans being two nations divided by a common language.
As a chemist I once studied a set of small molecules each containing 4 atoms.
I was talking to another computational chemist and they recommended a particular piece of software as being good for small molecules.
I tried it, and it failed.
When I met them again, I asked about it. It turned out that they were doing computational biochemistry, and small for them was around 10,000 or so atoms big.
Even in very closely related fields terms can have very different meanings.
My 2c.
Laurence Cuffe

It is indeed true that not everybody finds relevant information in the same way. Indeed there are many students that still miss the skill to come up with relevant tags, screen options that pop-up. The difficulty might be related to understanding what makes meaning or what will deliver personal, relevant results.

Maybe the way students use tags to describe learning objects, and to search through them, can give an idea on how the first steps the semantic web are taken? At first tags and things do not really match sensitive differences in meaning, but as time goes by and linguistic semantics are fine-tuned, the tags linked to object become more precise.

I would think that this precise tagging and finding the most relevant key words related to a certain subject, is linked to the novice or expert state that a person is in. The more expertise, the easier it is to provide specific and accurate key words or phrases, the more one is a novice, the more those choices might be colored by popular nouns or hyped words.

@Laurence: I also really like your idea that human beings have the tendency to go above and beyond. If this urge to move beyond could be put into an algorithm, learning analytics would provide us with cognitive or other laws that we would not even have imagined (or proven).

Gillian, I enjoyed your blog post about designing learning for adults, also my background. I liked the idea of learners collecting their own data based on their learning patterns supplied through learning analytic means. This way they can understand how they work with content, etc, and become cognitive of their learning patterns, thus making decisions for themselves on what and how to engage.

I was struck by a notion given by Marissa Mayer of Google in a video provided in Week 3 of this course. Instead of being influenced by the content that is found through a general search online, our context (lives, desires, ideas, etc) would become the influence of that search and drive it. I can see this extending to learning. When we post an idea, etc. it would be unique to have our context come forward to shape and influence that post, such as images, sound, colour, data, etc. Who I am would come with me when I engage with content and others.

This collective self would change and morph over time presenting who I am at that time. To create a specified ontology ahead of time (as discussed in this thread) would negate that personal development and the emergence of new ideas to share with others. I believe we need to make way for evolution.

And, I don't fear that the unfettered development of ideas would become eccentric and chaotic creating misunderstood content. We are humans after all, and we do have limited processing powers that rests on previous knowledge and experiences. In essence, I don't think we would lose control but instead allow room for the expansion of thoughts and expressions.