Some time ago I wrote about Didaskon, a framework for composing curriculum for a specific user, basing on his profile and using formal and informal knowledge. I belong to team of the developers.
At the moment, I am developing the one of its component – IKHarvester (Informal Knowledge Harvester). It aims at collecting (harvesting) data from Social Semantic Information Sources (SSIS) and providing it to Didaskon as informal Learning Objects (LOs). By SSIS, I mean community sites (blogs, wikis, social semantic digital libraries, bookmark sharing, video sharing etc.) with semantic annotations added. The prototype will use only wikis based on MediaWiki engine, blogs that support SIOC, and JeromeDL. For the general idea look at earlier presented poster.
In this post, I will focus only on blog posts.
Continue reading ‘IKHarvester’
On 16th of April, there will be Faculty of Engineering Research Day at NUI Galway. Researchers will be given possibility to present themselves and what they are making research on. Those who apply shall prepare an abstact and a poster.
I will present my research ideas, regarding my Master’s Thesis and what I working on at DERI: the idea of employing Social Semantic Information Spaces (semantic blogs, semantic wikis, social semantic digital libraries etc.) for e-Learning. The following picture gives an idea of how I’m trying to do that.
At the bottom, there are SSIS – online communities enriched with semantic annotations. Due the semantics, the content is also machine readable. Consequently, application can use them and reason from them. I’m developing IKHarvester, which aims at harvesting knowledge from SSIS and provide it due Web Services in a form of informal Learning Objects (LOs). These LOs are delivered to Didaskon, a Learning Management System, in a common way – described according to LOM standard. Didaskon, using the user’s preconditions, creates a curriculum by combining formal and informal Learning Objects.
There is also an Abstract available. If you want to learn more about my ideas, feel free to contact me.
A few months ago, myself along with friends, wrote an article to the ICWSM ’06 conference which should have take place in Boukder, USA. The titke of the article was: “E-Learning on the Social Semantic Information Sources”. We wrote quite a few pages but the paper was rejected The reviewers stated it was quite good, but needed to be improved.
Now, after six months we have descided to do it; we aim at 2nd EC-TEL (Second European Conference on Technology Enhanced Learning). I care about the paper since it covers the topic of my Master Thesis (which, actually, has the same title). We want to redo the document. The goal is to focus on the way of integrating sources of informal knowledge (wikis, blogs, digital libraries, boomarks and multimedia sharing systems) so that they can be more efficiently used for learning purposes. We want to point out the importance of semantic annotations in such online communities; we ‘ll also present our solutions to the problem of storage and management information gathered from online communities.
The deadline for applying is the April 1st. Get back to work, then
Here is some information taken from my Master’s Thesis (still developed)..
Didaskon is a project developed in Digital Enterprise Research Institute (DERI), Ireland by a few students, including myself. It is a research project in the elearning field. Its main goal is to deliver a framework for assemblying an ondemand curriculum from existing Learning Objects (LOs) provided by e-Learning services.
Didaskon is an innovative solution since it derives from both formal and informal sources of knowledge. It has an access to a repository of LOs described with semantic annotations – LOM ontology. LOs are composed into a learning path for a specific student. Along with formal Learning Objects, Didaskon also uses the potentaial of Social Semantic Information Sources. It is capable fulfill informal learning postulates and create LOs from data harvested from SSIS. Consequently, a user is gets a course path prepared from information collected in both formal and informal way.
Furthermore, Didaskon composition algorithm takes into account some pre-conditions regarding a user. Each user is described with FOAF ontology. Basing on delivered user’s profile (knowledge level in different domains and goals/expectations from the course) it is capable of returning learning material customized for his/her needs. Moreover, the system allows more scalable helper features for students supervision.
At the moment, we still develop the system. One of my basic task is to adopt SSIS for its purposes. Therefore, I must create a common object model; the model should be able to map information collected from SSIS and “push” it further, to Didaskon learninig path composition mechanisms.
Now, returning to research…