I’ll be teaching Julia this semester to introduce computational thinking for undergrad students of Library and Information Science (LIS) in the Department of Information Science of Javeriana University and this post is documenting the context, approach, rationale and some materials in a similar way to what has been done in the past for other courses using Julia.
For many of my undergrad students this will be their first introduction to computational thinking and as I said in my introductory message to this forum, I would like to bring a particular balance that bridge the contents of more traditional STEM (Science Technology Engineering and Mathematics) with the critical approaches of STS (Science and Technology Studies) from the trans/inter disciplinary point of view of information science.
I think this resonates with the two cultures talk given about Julia, but it’s trying to build a bigger bridge, not between two STEM cultures, but between the original Humanities (including Arts and Social Sciences) and the positive-analytical sciences and disciplines where Julia is already used.
We depart from treating technoscience as this neutral pursuit of truth and instead we share the STS acknowledgement of the mutual relationship and influence between technoscience and wider society, which means also to acknowledge that technoscience participates of power dynamics, geopolictics, funding resources and agendas, among other things.
This is reflected in many places, like the map of Julia Local Groups and its locations in the so called Global North, while the Global Majority is mostly absent:
In fact, I showed that map to my LIS undergrad students on last Thursday class and I told them that the work we are starting this semester will contribute to put a spot from Latin America on that map. Of course, as many maps, this one answers a particular question and other cartographies could showcase the wider nature of the Global Julia community (for example, the one of places, formal and informal, where Julia is practiced, that was the way we add to the map our local practices with Pharo not only in University, but in our local hackerspace, where they started).
Inspired by the STS perspective and our local experience, we depart too from the let’s start printing “hello world!” approach (which always disliked me as a first example, despite of being so naturalized by a niche tradition) and we start by contextual meaningful problems trying to avoid what George Wilson called in his talk the “tyranny of syntax”
Our critical approach to Computational Archival Sciences (another CAS, but not like in Computer Algebra Systems), resonates with other practices for teaching CAS in LIS, but has a different genealogy, based on our local hacktivist practices and their bridge with university researches and courses. We also try to start from real world problems, but not global ones, as climate change (despite being grateful that this problem is being addressed and taught with Julia), and instead we approach local ones (which are typically unseen and unattended in broader global narratives), as we did in “Amanecer la palabra”, our research work for linguistic revitalizing of indigenous languages for 4 communities in Colombian Amazonas, where we deployed, intervened and understood digital infrastructures for memory to attend (part of) the needs of grassroots communities. In this particular case, we co-created this wiki, with people in the local communities:
and its data narrative made in our flexible tool Grafoscopio, running/build over Pharo/GToolkit
I would like undergrad LIS students to develop the computational skills to be able also to do something similar for other communities and organizations and to tackle important contextual problems locally or elsewhere via computational thinking. So, following the strategy we developed with our hacktivist/academic practices, we are going to deploy and intervene agile/light digital infrastructures for memory (HedgeDoc, Hypothesis, TiddlyWiki, Fossil SCM) and to connect and enhance them using Julia/Pluto this time instead of Grafoscopio/Pharo.
We use the same critical perspective to approach AI (or Apparent Intelligence, as I like to call it), presenting a counter narrative to the “revolutionary tech (bro)” discourse, showcasing how it is based on extractivist expropriation and exploitation of human labor and natural resources, particularly from the Global Majority (including rare earths) to enrich few ones, particularly from the Global North.
And we show how critical voices from academics and activist have been systematically ignored in this new attempt of a self fulfilling prophesy of “AI first everything”.
BTW, this is way I asked how to disable AI in Pluto and why this is a worrying default for an educational tool when academics have expressed concerns about the uncritical adoption of AI in academia. It’s also a good example of the inbrincation of technoscience and society in a particular community, showcasing how, where and when decisions are taken for others via enabled defaults (I don’t remember the source, but its estimated that 90% of people don’t change their software defaults) and surely we are going to point to this forum and the respective GitHub Issue thread to examine this with our students, if time permits. With the time, we plan to deconstruct other Julia/Pluto defaults, like its integration with GitHub for hosting packages and hopefully adding Fossil to the mix.
This is the panoramic view of how we plan to introduce Julia from a STS perspective, starting this semester, mostly with my undergrad students (and some doctoral ones). And this is the context from where some more particular technical and more detailed questions/requirements will arrive, from changing AI defaults, to Fossil instead of Git, Markdown parsing or Lua integrations.
I’m hopeful in using Julia and so far the first impressions from my undergrad and post-grad students and my colleges has been positive and with warming expectations. Thanks for making this start possible and again for Julia and its communities.
