The filter bubble is of significant importance for online learners, as it touches on several key issues. Firstly, it questions how trustworthy the instruments are that help learners find information and peers online. Also, it forces learners to reassess the relationship between their agency and critical thinking (what is their own choice of resources) and their reception of information and opinion (Bakshy et al. 2015). Finally, it also draws into question the values underlying the algorithms that make up the tools that learners use (Rajagopal et al. 2016).
In this workshop, aimed at practitioners and researchers in education technology, we will deal with the topic of breaking your filter bubble. Starting from the concept of the Personal Learning Network (PLN) (a personal network designed by a learner to continuously support their learning), we will create two outputs: 1) a Code of Conduct for online learners, with guidelines to prevent their PLN from becoming a bubble, and 2) a list of desired social media values and functionalities that can prevent filter bubbles.
We will use a conversational knowledge-building format (with brainstorming, concept mapping and discussion) in which participants will be asked to reflect in groups on the following questions:
– What is diversity in a PLN?
– How do we actively maintain diversity in our PLNs?
– What is the role of social media in this?
– To what extent are social media a cause of filter bubbles?
– How can social media be changed to help us in preventing filter bubbles?
The outcomes of this workshop align with the conference theme “Empowerment in Learning Technology” by offering learners a useable Code of Conduct, and researchers a list of potential innovations to explore.
Bakshy, E., Messing, S. and Adamic, L.A., 2015. Exposure to ideologically diverse news and opinion on Facebook. Science, 348(6239), pp.1130-1132.
Hess, A. 2017. How To Escape Your Political Bubble For A Clearer View. Nytimes.com. 2017. Web. 27 Mar. 2017
Pariser, E., 2011. Beware online” filter bubbles”(TED Video). https://www.ted.com/talks/eli_pariser_beware_online_filter_bubbles Retrieved May 30 2017.
Rajagopal, K., Bruggen, J.M. and Sloep, P.B., 2016. Recommending peers for learning: Matching on dissimilarity in interpretations to provoke breakdown. British Journal of Educational Technology.
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