Forum .LRN Q&A: Re: Request for Comment: Implementing Profiles in .LRN

Posted by Rafael Calvo on
I would like dotLRN to eventually be an Adaptive Learning Environment (or what I prefer to call a Intelligent LMS). An ILMS would change the way it presents its courses based on the information it has about the student. The student profile is then a key issue here.

Maybe the scope Al is looking at at this stage is smaller, but I think this issue should be looked at, it could give dotLRN a huge competitive difference with every other LMS. I think that the architecture of this user-profile package will have a huge impact on how we (at least in my group) can progress on this.

The base - extended - local architecture is a first step. I think that "courses" will also want to extend the user model. For example, if I have a course on OpenACS, I could first ask (or formally assess) if the student knows about PLSQL, TCL and other requirements. If he does, Those "modules" (or learning objects) could be skipped.

Another example (or use case), if a student finds it easier to learn by listening to video (and it is available) how do we highlight it over the text, so he uses it. If he prefers text (e.g. he is not native speaker and finds hard to understand spoken English), how do we use that to improve his learning experience?

Another example, if a profesor wants to motivate students to participate in the bboards, and he finds that some topics are more interesting to some groups than others, how can we customize the course to highlight those subtopics?

A lot of the student model can be "learned", by gathering information about what he reads and does in the ILMS. This is where the automatic document classification system -that I posted about a few days ago- comes in.

An introduction to adaptive learning environments is in:

Posted by Malte Sussdorff on
Hello Rafael,

I'd not use user profiles as requested in this case to ask for the students knowledge. Have him give the sources of his knowledge and make a judgement based on this. Within an university this is easy, as you could see which classes he has already visited and what grade he got there (so here we are touching the sequencing that SCORM 1.3 is so big about, especially if we look how good a student succeeded in an objective (e.g. learn PL/SQL)).

If you ask for  the bboards, you could have a linking structure within dotLRN like Sharenet does. Say we have a special portlet "interesting things" for a class and the professor has admin priviliges. Now her surfs the website and as he has priviliges in at least one of these portlets, he'd see a link at the button saying "add to favourites portlet". If he has more than one, then he gets to a second page allowing him to select where to add this one to. Using quicklinks with the object_id you could link to any content you want.

But wouldn't it be a good idea to have a more general approach maybe using Workflow and AI methods. My idea here would be that the workflow module supports knowledge flows. Say, if the student has read about TCL and read about PL/SQL, suggest him to read up on OpenACS. As it might be tedious to generate all this links manually, using artificial intelligence methods you could train your AI system by feeding it the learning flow of students (plainly: what objects did a student look at and for how long) along with the ideas of the professor how it should work. Taking in account the results of how the students scored you could create "best learning flows" for certain student types. How could you agregate these student types? If you have enough data on the students themself already you could probably use statistical methods. But if students come fresh to the learning organization the LO probably does not have enough information for grouping the students together in learning types. So an introductionary psychological test might be in order. But I'm heading of the topic here 😊.