Friday, February 26, 2016

AAOU 2016 Annual Conference in Manila, Philippines

The 30th Annual Conference of the Asian Association of Open Universities

Theme: Open Education in Asia: Changing Perspectives
Dates: 26–29 October 2016
Venue: Crowne Plaza Manila Galleria, the Philippines
Host: University of the Philippines Open University

For more details of the conference, please visit the conference website.

Thursday, October 31, 2013


The 2nd International Conference on Open and Distance e-Learning will be held on 18-20 June 2014, at Crowne Plaza Manila Galleria, Metro Manila, Philippines. See for details

Wednesday, December 14, 2011

First International Conference on Open and Distance e-Learning

On February 22-24, 2012 in Manila, Philippines.


Friday, April 8, 2011

Suzanne Darrow's Connectivism Learning Theory: Instructional Tools for College Courses

A related thesis that I have failed to cite in my project is Suzanne Darrow's Connectivism Learning Theory: Instructional Tools for College Courses (2009). I came across her work only after I have submitted my project report.

It's abstract follows:

This qualitative thesis explores the work of George Siemens and connectivist learning theory, 'A Learning Theory for the Digital Age'. Findings are based on a literature review which investigated the foundations, strengths and weaknesses of connectivism and synthesized conclusions into a knowledge base of practical applications for the college level, Instructional Technology classroom. The half-life of knowledge is shrinking, especially in the field of Instructional Technology; connectivism helps to ensure students remain current by facilitating the building of active connections, utilizing intelligent social networking and encouraging student-generated curricula. Connectivism allows the future of education to be viewed in an optimistic, almost utopian perspective, as individuals co-create knowledge in a global, networked environment (Darrow, 2009, p.ii).

Darrow tries to associate the term "digital natives" with connectivism. I wish she had taken into consideration Siemen's criticism of this concept at (2007). A list of works criticizing the term can be found in Doug Holton's blog- (2010).

Nevertheless, it's a good introduction to connectivism for teachers. It is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 United States License.

Hopefully more theses on connectivism will be shared online this year.

Project Report: Exploratory Approaches to the Design and Development of a Game for a Distance Education Course in Philippine History

Roel Cantada

I would like to share my project report for my master's degree in distance education at the University of the Philippines Open University (UPOU).


Report (4.57 mb)

WIP OARs of the game (15.22 mb) (5 mb) (10.44 mb)


The project explores the design and development of a prototype video game for a distance education course in Philippine history. The project seeks to answer these questions:

  1. What are the affordable learning actions and constraints of educational games in general and games for learning history in particular? 
  2. What production pipeline of design and development of educational games is appropriate for distance education teachers of Philippine history with meagre resources?
The rationale for the project is the following:

  1. There is little study on courses as games in distance education. 
  2. In the context of connectivist learning theory there is no study of games as hubs for a personal learning environment (PLE). 
  3. There is no available off the shelf game for teaching Philippine history. 
Open Simulator, a Multi-user Virtual Environment (MUVE) was used to create a prototype game. Formative research methods were adopted in the design and development of the game.

It has been found that the game affords the adoption of a wide range of learning theories and methods. As a PLE hub it has weak and strong affordances. In learning history it affords the following:

  1. It affords the linking and finding of historical sources.
  2. It affords role playing of historical characters.
  3. It affords reconstruction of history in multimedia.
  4. It affords the linking of game play with history.
It has also been found that teachers may impose a minimal amount of constraint on the learning path through quests and virtual objects that serve as obstacles. Items may be hidden from view (to delay use) or pointed out by Non-Player Characters. These constraints may help learners recognize affordable learning actions in the game. It may also scaffold the experience of novice players who are unfamiliar with the 3D environment.

In conclusion, series of steps and guidelines are suggested for developing educational games. It is recommended that teachers exploit the tools of the game for collaborative design and development as well as the production of reusable virtual world archives.

Thursday, February 3, 2011

Appending SNAPP graphml files in Gephi

  1. Browse a Moodle forum, 
  2. Click the bookmark link to the SNAPP
  3. Copy the export tab-graphml data
  4. Paste in a text document with the extension .graphml
  5. Open in Gephi and append other files.

Unfortunately tie strengts are not preserved. It may be a problem with SNAPP or Gephi, but I don't really know why.

Warning: There is an error in the graphml file export of the Moodle SNA tool. Use SNAPP instead.  The error is in the following tag:

<edge source="A" target="B"/>1</edge>

The extra forward slash / in the <edge> tag causes the problem. Gephi will not be able to open the graphml file from the Moodle SNA tool.

Perhaps a better solution is to create a VNA importer for Gephi and use the scripts here to extract and anonymize the data. Unfortunately I'm still working on my Graduate project and I can only look into this after my project is finished.

Workflow of the merger and anonymization of the CCK09 forum datasets

This is my workflow for anonymyzing and merging the VNA datasets of the CCK09 Moodle forum. I coded some python scripts to automate some of the steps. But it would still require some manual work with a spreadsheet.

Python Scripts

Download the python scripts: (3.11 kb)


Ubuntu Lucid amd64
Python 2.6.5
Moodle SNA Tool

I do not know if the extraction script will work with SNAPP.

Notes common for all scripts

1. This is needed for the scripts to work
add the following lines to to /etc/python2.6/

#change default python system  encoding
import sys

My is included in the downloadable archive above. Backup your original file to and place this in /etc/python2.6 .

2. Setting the permissions of the scripts

Right click the python script and  select Properties
In Properties - Permissions tab - enable Execute: Allow executing file as program.

Open a terminal and you can issue a command like this

if you cannot change permissions then you have to issue the following command in a terminal


3. Some possible errors
If you get errors like this:

Traceback (most recent call last):
  File "", line 29, in <module>
    inputfile = open(vnafilename, 'rb')
IOError: [Errno 2] No such file or directory:

That means you forgot to set the nfile or input file number to the correct number of files to process.

Extracting VNA files from saved html page output of Moodle SNA Tool

1. Browse a Moodle forum,
2. click the bookmark link to the Moodle SNA Tool
3. Save the page with the export VNA data as 1.html, 2.html, 3.html in a folder. I number my folders as forum1, forum2 etc. Naming the files as number 1 to n is important.
4. Download and extract in a folder where the vna files will be saved. Let's say folder vna1.
5. Open in a text editor and change the following values.

idirectory = 'file:///home/juan/Documents/CCK09/VNA/forum1/' #input file local url directory. Do not use /home/juan... it will result in python error. Always put a trailing slash / . There should be 3 and only 3 leading slash after file: e.g. ///

fextension = '.html' #file extensions. make it empty if there are no extensions e.g. ''. note NO space in between the quotes.

nfile = 1 #number of input files

6. open a terminal and issue the command



7. The terminal should scroll with the vna data being processed. If an error occurs leave me a comment about it. Make sure you have the same Python version. If it is successful it will say "finished extracting text".

8. You will have 1-n files without the vna extension in your folder.

Anonymyzing the dataset

When I anonymized the CCK08 dataset I waited until the union is complete before creating the code sheet.  In CCK09 I used a cumulative anonymization method. That is, I just add new names whenever I encounter them. This also allowed me to tag new CCK09 students in the dataset.

With an existing codesheet

If you already have a codesheet then go to step 1. If not manually create a codesheet from the union of the first set of vna files first.

1. Download and extract in the same folder where you have the extracted vna files. The example above is vna1.

2. Open in a text editor e.g. gedit then change the following values.

idirectory = 'home/juan/Documents/CCK09/VNA/vna1/' #input file directory
csfilename = '/home/juan/Documents/CCK09/VNA/codesheet08.csv' #codesheet
odirectory = '/home/juan/Documents/CCK09/VNA/vna1/' #output directory
nfile = 35 #number of input files

3. open a terminal and issue the command



4. If it is successful it will say "finished anonymyzing vna files". You will have 1.csv, 2.csv, 3.csv ... in your folder.

5. Apply to other forum sets and just add names and aliases to the codesheet.

Anonymyzing a Union of datasets

1. Download and extract in the extracted vna folder.
2. Open in a text editor and change the following values
idirectory = '/home/juan/Documents/CCK09/VNA/1/1union.csv' #input file directory
csfilename = '/home/juan/Documents/CCK09/VNA/codesheet1.csv' #codesheet
odirectory = '/home/juan/Documents/CCK09/VNA/1/' #output directory
fname = 'outputfile' #filename of output file

3. open a terminal and issue the command



4. If it is successful it will say "finished anonymyzing vna files". You will have a file named outputfileunion.csv
5. Apply to other forum union dataset and just add names and aliases to the codesheet.

Merging the datasets into a union dataset using spreadsheet.

This part will be very tedious if you have a lot of data.

1. Open each anonymized csv
Select Character set: Unicode (UTF-8)
Enable separated by space and text delimiter ".
2. Create a new spreadsheet with separate worksheets for node data and tie data. Copy every node data and tie data to this spreadsheet for merging.
3. Select the data columns minus the headers i.e. *Node data, ID posts; and *Tie data, from to talk strength.
4. Then sort the data with menu-Data-Sort.
5. When the names are sorted you will see the duplicate entries. Sum the numbers and erase the duplicate entries.
6. In another worksheet copy your node data and tie data then save as csv.
7. Select field delimiter space and text delimiter ". Disable save cell content as shown.
8. Open the saved csv file and remove the quotes from the headers. *Node data, ID posts; and *Tie data, from to talk strength. Otherwise you will not be able to open the file in Netdraw.
9. Rename the file extension to vna and open in Netdraw.
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