Week 9 already! Wow!
This week’s Lifestream activity has been dominated by the group ‘Tweetorial’ in which we investigated some topics and issues highlighted in the recommended viewings and readings. In summarising my Tweetorial activity, I would note that I contributed to discussion threads surrounding the following key themes concerning Big Data and Learning Analytics (LA):
- Ethical considerations
- Social media influence on algorithmic culture
- Big data influence over students
- Algorithmic pattern identification
- Dependence on analytics
I felt it essential to explore the vastness of Big Data and to consider the implications of identifying patterns when it is analysed. I felt that this week’s recommended material focused on either how data was gathered/analysed or the resulting consequences for students. Therefore, I became increasingly interested in the gap between big data and hypotheses and what new knowledge we can discover from the space in between. My ‘Analyzing and modeling complex and big data’ post attempted to address this issue.
Following on from the ‘Tweetorial’ I was motivated to explore some of the issues raised to put them into a relevant context. My ‘Learning Analytics – A code of practice’ post summarised my investigation into a JISC funded LA project in which the project team addressed many (if not all) of my concerns around ethics and student intervention. In hindsight, I had only really considered LA from the perspective of the institution and the learner – not of the individual as a person.
It was another enjoyable week and I’d like to thank my tutors and peers for a very engaging Tweetorial.
