I decided the best way to summarize how algorithms have influenced my livestream would be to have a closer look into my fellow students’ conclusions on algorithms and comparing them with my own experiences.
They played with You Tube, Netflix, Google, etc., algorithms and meddled with their recommendation feeds (video, audio, friends, ads, courses). The most interesting fact was that MSCEDC students had very similar experiences and many recurring conclusions on algorithms I similarly noticed.
When developing and implementing my livestream, I witnessed most of these conclusions myself. I used You tube, twitter and google search frequently for research and their algorithms influenced my selection, my reality and therefore the outcome of my liveblog. “You Loops” or “Echoing” was frequently observable, inefficient results and predomination of certain information sources detectable. Troubleshooting of malfunctioning ITTT algorithms was difficult to solve due to multilayered connections. This reality shaping power algorithms have were well described by Kitchen (2007, page 15).
Although we tend to struggle with the accuracy or the missing information about hidden agendas, the use of algorithm has – and will have – a potential to influence learning and teaching.
In order to work with algorithm-based technology educationalists must maintain a critical perspective. The algorithm is currently shaping the culture to a great extend and education is not excluded. Therefore, teachers should accept the new status quo and openly engage with the technology.
Developing a liveblog is a good start!
Kitchin, R. (2017): Thinking critically about and researching algorithms, Information, Communication & Society, 20:1, 14-29
Knox, J. (2015): Algorithmic Cultures. Excerpt from Critical Education and Digital Cultures. in Encyclopedia of Educational Philosophy and Theory. M.A. Peters (ed.)
Knox, J. (2015): Community Cultures. Excerpt from Critical Education and Digital Cultures. In Encyclopedia of Educational Philosophy and Theory. M. A. Peters (ed.). DOI 10.1007/978-981-287-532-7_124-1
Knox, J., Williamson, B. & Bayne, S. (2020): Machine behaviourism: future visions of ‘learnification’ and ‘datafication’ across humans and digital technologies, Learning,Media and Technology, 45:1, 31-45, DOI: 10.1080/17439884.2019.1623251
Schmidt, E. and Rosenberg, J. (2018): How Google Works – Eric Schmidt and Jonathan Rosenberg, Retrieved from: https://www.alexjhughes.com/books/2018/3/11/how-google-works-eric-schmidt-and-jonathan-rosenberg, 29.03.2020
Williamson, B. (2017): Introduction: Learning machines, digital data and the future of education (chapter 1). In Big Data and Education: the digital future of learning, policy, and practice.
Algorithmic play of all MSCEDC 2020 students. Thank you very much!
That was really cool. I especially liked your observation of the thumbnails on Netflix. It had never occurred to me that those change with a purpose, using different thumbnails to make the same movie appeal to different viewers. It’s an interesting idea that being in Mexico might influence your algorithm.
I really liked your presentation style by the way, very slick.
I also didn’t know some of those movies were on Netflix and now I’m going to go watch them…