Posts

Gist of LAK 22 paper

After a long inactive period of about two years, I’m finally bringing my blog back to life. Yayy!!! I will be blogging on topics related to learning analytics, text and writing analytics, learning technologies, educational research and probably more general research topics that are useful for fellow PhD students. Note: I’ve tried to import my previous blog ...

It’s been a great experience working with the Data, Analytics and Learning MOOC (DALMOOC) from EdX at https://www.edx.org/course/data-analytics-learning-utarlingtonx-link5-10x#.VJO6xF4AA. I’m so glad  my boss found it and encouraged me to take it (Although I started only in Week 5 of the 9-Week course). It was not easy, nevertheless, it was a very rewarding experience. I would think ...

Competency 9.2: Integrate various course concepts through creation of a graphical representation (concept map) of the relationships between prominent course topics. We’ve had a fruitful time learning about different topics in Learning Analytics. The next task in hand was to create a concept map by finding connections among them. With an assurance from the instructors that ...

Competency 4.2: Describe and interpret the results of social network analysis for the study of learning. I’m going to use the analysis I did by extracting twitter data with hashtag #DALMOOC (explained in my post for competency 3.2) to interpret the results of modularity in the network. The density was 0.05 which means that the network ...

Competency 4.1: Describe and critically reflect on approaches to the use of social network analysis for the study of learning. I’ve seen some great insights on how to use social network analysis to improve learning. The impact of social network analysis on educational constructs like learning design, sense of community, creative potential, social presence, academic performance ...

Competency 3.2: Perform social network analysis and visualize analysis results in Gephi. I did assignment 79 in which we are asked to extract data from twitter and analyse the twitter network in Gephi. I extracted twitter data using NodeXL, a freely available add-on to excel. I searched for all tweets with the tag DALMOOC and used ...

I’m going back to Weeks 3 and 4 to learn about Social Network Analysis since the course is nearing completion. I will go back to the final wrap up Week 9 after I finish these two weeks’ lessons. Competency 3.1: Define social network analysis and its main analysis methods. Social Network Analysis (SNA) provides insights into how different social ...

Competency 8.5: Examine texts from different categories and notice characteristics they might want to include in feature space for models and then use this reasoning to start to make tentative decisions about what kinds of features to include in their models. I tried the Bazaar activity in Prosolo (but my myself since I ...

Competency 8.3: Compare the performance of different models. I compared two models, one from a unigram only feature set and the other from a unigram, bigram and trigram feature set using my test data set. I was at first using the Newsgroup data set as suggested in the Prosolo assignment, but some options were not working ...

Competency 8.2: Build and evaluate models using alternative feature spaces. I used the different feature spaces that I saved in the previous exercise for building models. My data set was very small and I intended to use it just for testing. I found significant improvement in metrics while comparing the models of POS features Vs Unigrams ...