Raiding the inarticulate since 2010

accelerated academy acceleration agency AI Algorithmic Authoritarianism and Digital Repression archer Archive Archiving artificial intelligence automation Becoming Who We Are Between Post-Capitalism and Techno-Fascism big data blogging capitalism ChatGPT claude Cognitive Triage: Practice, Culture and Strategies Communicative Escalation and Cultural Abundance: How Do We Cope? Corporate Culture, Elites and Their Self-Understandings craft creativity critical realism data science Defensive Elites Digital Capitalism and Digital Social Science Digital Distraction, Personal Agency and The Reflexive Imperative Digital Elections, Party Politics and Diplomacy digital elites Digital Inequalities Digital Social Science Digital Sociology digital sociology Digital Universities elites Fragile Movements and Their Politics Cultures generative AI higher education Interested labour Lacan Listening LLMs margaret archer Organising personal morphogenesis Philosophy of Technology platform capitalism platforms populism Post-Democracy, Depoliticisation and Technocracy post-truth psychoanalysis public engagement public sociology publishing Reading realism reflexivity scholarship sexuality Shadow Mobilization, Astroturfing and Manipulation Social Media Social Media for Academics social media for academics social ontology social theory sociology technology The Content Ecosystem The Intensification of Work The Political Economy of Digital Capitalism The Technological History of Digital Capitalism Thinking trump twitter Uncategorized work writing zizek

Some thoughts on machine translation in higher education

I really enjoyed this discussion with Klaus Mundt and Michael Groves for the TELSIG Podcast. There’s a reading list attached in the YouTube comments. Here are some notes from the discussion which are my attempts to characterise the insights shared in the podcast, rather than offer my own analysis:

  • It’s now possible to primarily work in your first language inside and outside the class, thanks to the affordances of machine translation. This has been developing for a long time but it’s rapidly accelerated in recent years.
  • We’ve assumed that someone graduating from an English speaking university will develop conversational proficiency through immersion. This is no longer the case and we need to address this. However the assumption that you get better at English just by being on the campus is a flawed one, which applied to some students. It may actually facilitate immersion if students have communication support which makes it easier for them to interact with speakers of other languages.
  • This expectation has implications for the university brand, in so far as that certifying learning implies graduate outcomes perceived by employers. It’s important to distinguish these concerns, even if they’re valid, from questions of academic conduct where this isn’t explicitly stated in the learning outcomes.
  • The assumption this is an academic integrity issue urgently needs to be examined and unpacked, because it’s not a tenable assumption once you examine it.
  • Do we teach English so that students can thrive at university? Or do we teach them to thrive intellectually using the best tools available? This was a great question from the podcast.
  • Just saying to students you must not use this isn’t a tenable strategy for ealing with, particularly in a sector which is aggressively recruiting international students.
  • There are signs of staff adjusting how they mark student’s work, reducing the emphasis on grammar and vocabulary in the marking criteria. If the technology can do it, should we be giving credit for it? Virtues like ‘readability’ can be a way of preserving composition and communication skills as things which are assessed, even if we move away from grammar and vocabulary.