I have to admit that I was only slightly active in the first 2 weeks, and totally 'tied up' with my other things during the rest. Haven't had time to catch up with any of the lost weeks also, but the daily #LAK11 paper.li kinda helped me a bit (when I have time to browse through the headlines, though).
Even though it was only for 2 weeks, I learnt a lot especially on the tools. It got me all excited, until we started to have long public holidays here in Malaysia and I had to hit the books again for my PhD study etc. (hahaha!)
Anyway, the structure of the course is good, quite organised despite the abundant resources supplied, but then again, if you're used to it, you know that you don't have to really go through all, so it's kinda less stressful for an experienced MOOC learner.
Honestly, for me to use this method in my teaching, I have to 'train' my students or let them experience a simpler or smaller scale MOOC before really implementing something like this. At least, I can estimate some expectations from them.
All I can say is thank you very much to George and everyone, for allowing me to learn from each other and this network. Hope I can still visit and refer to the content of this course whenever I have the time (can, right?).
All the best to everyone.
- Shazz, Kuala Lumpur
Shahrinaz Ismail
Posts made by Shahrinaz Ismail
Allow me to copy these links for my future use... (no time to explore now) ;D
Thanks, George!
- Shazz
Thanks, George!
- Shazz
This is marvellous, Bert! I think I should try this too!
I was just thinking of the keywords/tags, and never knew they have it in other applications. Kewl! B-)
Let me share my thoughts from yesterday here:
1. Testing the SNAPP and NetDraw:
http://shazz-lak.blogspot.com/2011/01/falling-for-snapp.html
2. Discussion on SNAPP:
http://shazz-lak.blogspot.com/2011/01/discussion-on-snapp.html
I was just thinking of the keywords/tags, and never knew they have it in other applications. Kewl! B-)
Let me share my thoughts from yesterday here:
1. Testing the SNAPP and NetDraw:
http://shazz-lak.blogspot.com/2011/01/falling-for-snapp.html
2. Discussion on SNAPP:
http://shazz-lak.blogspot.com/2011/01/discussion-on-snapp.html
I just remembered something...
Is there anything like an auto-suggest of books to read if the analytics find that a student is left behind in catching up on certain topics?
Or maybe some 'alert' function that can predict on certain 'inactivity' of some learners after more than a week or so?
I know data mining and prediction analytics can somehow do that.
Just wondering.
- Shazz, Kuala Lumpur
Is there anything like an auto-suggest of books to read if the analytics find that a student is left behind in catching up on certain topics?
Or maybe some 'alert' function that can predict on certain 'inactivity' of some learners after more than a week or so?
I know data mining and prediction analytics can somehow do that.
Just wondering.
- Shazz, Kuala Lumpur
Basically, I think everyone has some ideas here and there about this topic. Let me share what I believe and what I've been teaching all this while in my IS subjects.
1. Profile of the CIO/CTO/CKO of course should be with leadership skills, skills in people management, expectation management, risk management, change management, and able to influence the top management in deciding on the analytics purposes and implementation for teaching and learning the university.
2. Back to basic - the usage of analytics should align with the business strategy and mission of the organisation in terms of teaching and learning. There's no point having vast data without knowing what you want from the data. Only from knowing what we want from the data (or Task), we can identify the methods of using the vast data to analyse the patterns further.
3. 'Project stakeholders' should include everyone (a member or 2 of each) from faculties, support departments, etc. so that each aspect of data usage will be covered and looked into, especially data that integrate/interlink across dept/faculties. For example: Students who tend to fail in catching up, may be having some issues with financial, registration records or language fluency, which other departments may have records of. Stakeholders (in steering committee of this organisational Learning Analytics 'project') should be able to provide the requirements on what are needed from the analytics, from beginning of the project.
4. At the end of the day, the knowledge we learn from the vast data and learning analytics should reflect the learning objectives of the programmes we offer. Success of each cohort can be monitored and if the problem is deemed to be from the syllabus itself, then reviews of programme and changes can be made, and so on...
5. Like it or not, we can't run away from evaluation and assessment of the analytics tool itself. Knowledge audit on what's learnt should be looked into.
These are randomly poured from this tired mind. Timecheck it's midnite here in Kuala Lumpur.
- Shazz, Kuala Lumpur
1. Profile of the CIO/CTO/CKO of course should be with leadership skills, skills in people management, expectation management, risk management, change management, and able to influence the top management in deciding on the analytics purposes and implementation for teaching and learning the university.
2. Back to basic - the usage of analytics should align with the business strategy and mission of the organisation in terms of teaching and learning. There's no point having vast data without knowing what you want from the data. Only from knowing what we want from the data (or Task), we can identify the methods of using the vast data to analyse the patterns further.
3. 'Project stakeholders' should include everyone (a member or 2 of each) from faculties, support departments, etc. so that each aspect of data usage will be covered and looked into, especially data that integrate/interlink across dept/faculties. For example: Students who tend to fail in catching up, may be having some issues with financial, registration records or language fluency, which other departments may have records of. Stakeholders (in steering committee of this organisational Learning Analytics 'project') should be able to provide the requirements on what are needed from the analytics, from beginning of the project.
4. At the end of the day, the knowledge we learn from the vast data and learning analytics should reflect the learning objectives of the programmes we offer. Success of each cohort can be monitored and if the problem is deemed to be from the syllabus itself, then reviews of programme and changes can be made, and so on...
5. Like it or not, we can't run away from evaluation and assessment of the analytics tool itself. Knowledge audit on what's learnt should be looked into.
These are randomly poured from this tired mind. Timecheck it's midnite here in Kuala Lumpur.
- Shazz, Kuala Lumpur