The following post contains the content from a poster designed for the 2017 USQ Toowoomba L&T celebration event. It provides some rationale for a technology demonstrator at USQ based on the Moodle Activity Viewer. What is the problem? Learner engagement is a key to learner success. Most definitions of learner engagement include “actively participating, interacting,
A few of us recently submitted a paper to ALASI’2017 that examined a “case study” of a teacher (me) engaging in a bit of DIY learning analytics. The case was used to drawing a few tentative conclusions and questions around the institutional implementation of learning analytics. The main conclusion is that teacher DIY learning analytics
In which I play with some analytics and use some literature in an attempt to understand why the institutional implementation of learning analytics as a starvation problem (like most institutional attempts to leverage digital technologies). In this context, I’m using the definition of starvation from computer science. Multiple time scales of human behaviour and appropriate
“failure” (CC BY 2.0) by tinou bao When it comes to research I’ve been a bit of failure, especially when measured against some of the more recent strategic and managerial expectations. Where are those quartile 1 journal articles? Isn’t your h-index showing a downward trajectory? The concern generated by these quantitative indicators not only motivated
Last year I started using with Perl to play with analytics around Moodle Book usage. This year, @beerc and I have been starting to play with Jupyter Notebooks and Python to play with analytics for meso-level practitioners (Hannon, 2013). Plotly provides a fairly useful platform for generating graphs of various types and sharing the data.
My current institution is – like most other universities – attempting to make some use of learning analytics. The following uses a model of system conditions for sustainable uptake of learning analytics from Colvin et al (2016) to think about how/if those attempts might be enhanced. This is done by summarising the model; explaining how
So the indicators notebooks/platform is on github. The one and only bit of analysis is almost completely useless and still requires a fair bit of set up code. The aims in this post are Add in a custom library for connecting to the data source. Add an indicator/notebook that does something kind of useful. Hopefully,
Following on from the last post the following documents how to share the “indicators platform” for analytics via github. It’s largely intended to help @beerc. I doubt there’s nothing (at the moment) that makes this inherently interesting for anyone else. End result The (almost completely useless) end result of this work is this github repository.
The last post documented early explorations of Jupyter notebooks ending with a simple query of a Moodle database. This post takes the first baby steps toward some sort of indicators platform using Jupyter notebooks, Python and github. The focus here is to find some form of ORM or other form of database independent layer. Problem:
This is the third in a series of posts documenting “thinking” and progress around the next step of some bricolage with learning analytics and attempts to make some progress with the Indicators project. The last post in this series revisited some work I did last year. The aim of this post is to consider and