November 10th, 2015, 3pm: Dr. Noureddine Elouazizi

An NLP-informed learning analytics approach for extracting and measuring aspects of argumentation

Venue: Buchanan C105C


This paper/presentation reports on a work-in-progress and shares preliminary results for an attempt to use NLP-informed learning analytics methods to extract and measure aspects of students’ argumentation while they learn how to think and argue like scientists. The approach explored in this paper caters to aspects of deep learning and detects the flow of the argumentation directly from the structure and the composition of the language that the students use in their writings. The model integrates insights from natural language processing techniques and argumentation theory in such a way that derives the metalinguistic features of argumentation directly from the linguistic units produced in students’ written language.


Lava Hackathon Data drop

Hackathon participants, please share your files with us! :
– Manipulated data
– Presentation
– Results (including failed results)
– …

Please include a readme.txt file with the following information:
– Names of group members
– Names and descriptions of the included files
– A short description of the process – what was your approach and what have you found (or did not find)? (do not spend much time on this)

Please create a zip file with the readme.txt file and the original files, and upload it at

password: lava (all lower case).

Learning analytics: Ethical issues and dilemmas

On October 6th, Leah gave a short presentation on key themes and ethical issues identified by the authors of this paper..

Slade, S., & Prinsloo, P. (2013). Learning analytics: Ethical issues and dilemmas. American Behavioral Scientist57(10), 1510-1529. doi:10.1177/000276421347936

…and we had a healthy discussion about data ethics for a learning analytics era.

It’s a complex and multidimensional area, but some universities have already made good headway in developing policy and ethical guidelines:

See for example:
Ethical use of Student Data for Learning Analytics Policy (UK Open University)
Code of practice for learning analytics

Why is learning hard to study?

This week we watched this video from Educause which had various professionals discussing why measuring learning is difficult.

Some key ideas from the video that had us talking were descriptions of the process of learning as a “black box” or “magic”. We tried to bring the discussion of measuring and studying learning into the context of learning analytics.


Tableau’s “Talk Data to Me” Webinar Series – on demand

Check it out

A set of current 30-minute videos:

Talk Data to Me Webinar Series: How to Excel Using Tableau
Talk Data to Me Webinar Series: Rapid Fire Tips & Tricks
Talk Data to Me Webinar Series: Hot Dirty Sets
Talk Data to Me Webinar Series: How to Excel Using Tableau, Part 2
Talk Data to Me Webinar Series: Become a Mix Master with Data Blending
Talk Data to Me – Data in the Wild: Transforming Excel, text, and other stuff into data you can use.
Talk Data to Me Webinar Series: Table Calculations: A First Foray
Talk Data to Me: Data Visualization Best Practices
Talk Data to Me Webinar Series: Salesforce Canvas

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