- Questioning Learning Analytics – Cultivating critical engagement (LAK’22)
Gist of LAK 22 paper
- Notes: Discipline-independent argumentative zoning
Reference:
Teufel, S., Siddharthan, A., & Batchelor, C. (2009, August). Towards discipline-independent argumentative zoning: evidence from chemistry and computational linguistics. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3-Volume 3 (pp. 1493-1502). Association for Computational Linguistics.
Background:
Argumentative Zoning (AZ) classifies each sentence into one of the categories below (inspired by knowledge claim KC) ...
- Notes: Mover – a Machine Learning tool to analyze technical research papers
Reference: Anthony, L., & Lashkia, G. V. (2003). Mover: A machine learning tool to assist in the reading and writing of technical papers. IEEE transactions on professional communication, 46(3), 185-193.
Background:
Identifying the structure of text helps in reading and writing research articles.
The structure of research article introductions in terms of moves is explained in the CARS model (Ref: ...
- Notes: NLP Techniques for peer feedback
Reference: Xiong, W., Litman, D. J., & Schunn, C. D. (2012). Natural language processing techniques for researching and improving peer feedback. Journal of Writing Research, 4(2), 155-176.
Background:
Feedback on writing is seen to improve students’ writing, but the process is resource intensive.
Possible options to reduce the workload in giving feedback:
Direct feedback using technology assisted approaches (from ...
- Notes: The calibration of student judgement through self-assessment
Reference: Boud, D., Lawson, R., & Thompson, D. G. (2015). The calibration of student judgement through self-assessment: disruptive effects of assessment patterns. Higher Education Research & Development, 34(1), 45-59.
Background:
Effective judgement of own work is an important attribute for HDR students
Focused on Self-Assessment (also represented as Self-regulation and Metacognition in few works)
Problem:
Self assessment is not facilitated ...
- Critical analysis for researchers
A critical approach is often needed for researchers when it comes to reading, writing and analysis of research articles. Being critical is not to find faults, but rather to ask questions and evaluate the reliability of what is stated. Here’s some useful information from a UTS session on ‘Critical Analysis – What is it and Why is it important for ...
- Reading research articles
Reading research articles can be a daunting task for new students. Even after reading many articles over the last few years, I still take time to read, understand and critically evaluate research articles (Takes double the time for theoretical ones, since I’m from a technical background). I’m no expert on this topic (or any topic for ...
- Hello again!
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 ...
- My reflections on DALMOOC
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 ...
- Concept Map
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
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 ...