Blogging an Unpublished Paper: South African & Egyptian Academic Developers’ Perceptions of AI in Education Part 4: Findings: Participants & General Attitudes Towards AI

Estimated reading time: 5 minutes, 9 seconds

In case you missed my first post on this process, I am blogging an unpublished paper as a series in parts over several days. You can read that post to understand the story and the reason behind this. Comments on each post welcome. This is this fourth post, I start sharing my findings, showcasing the participants and their general attitudes towards AI. Upcoming posts will showcase their attitudes towards specific forms of AI used in education. Previous posts covered abstract/references, intro/literature review and research methodology/positionality

Findings

Participants

I was able to interview 10 academic developers. 5 from AUC, 5 from SAU, with varying degrees of experience in the field of education and as academic developers. At AUC, all but one were female, all but one were Egyptian. At SAU, all were female, two were not South African but had grown up and worked in European countries beforehand. Coincidentally, most of the AUC participants used to be language or writing teachers, and two SAU participants had taught writing before, and this influenced their perspectives on several AI applications that have direct uses for language education, but I did not intentionally select these participants. Most participants had some background in education at some stage of their studies, from masters in international comparative education, to teaching English to speakers of other languages, to primary education, to degrees in instructional design and online education. Some had additional background in linguistics,  journalism, photography, literature, history, social work, and feminist studies. No participants have a STEM background, which I thought might have influenced how well they understand AI or may have influenced their attitude towards AI. All of those at AUC had taught before, most of those from SAU had taught at some point. All were currently academic developers, where the bulk of their work was supporting teaching/teachers at their institution. Those at SAU were a generally more experienced cohort, several of them with PhDs, and only one was new to the department, whereas those at AUC all had Masters degrees, most of them early to mid-career, and only one of them had substantially more experience than the others, and one was very new to the department.

When quoting participants below, I will refer to participants by number, AUC1-AUC5 and SAU1-SAU5. For SAU participants, I use “she” since all are female. For AUC participants I use “they” so as not to identify the one male participant too strongly, to help maintain anonymity.

General Knowledge and Attitudes Towards AI

When asked what comes to their mind when they hear about AI, several participants mentioned “robots” and movies, often laughing at themselves for thinking of that. Some mentioned the word “automation” and a few mentioned particular applications like Turnitin and Siri. Two participants thought of ways in which machines could move beyond human intelligence (SAU2) and become independent of humans altogether (AUC3).

Participants had varying degrees of familiarity with AI that they use in daily life. Some mentioned the recommendations from Google search, to social media sites, shopping, Netflix, Siri as an example of voice/speech recognition software and DuoLingo language learning app that also uses speech recognition. SAU3 said early on that she “struggled… between what AI is imagined to be versus [its] reality. It’s not really intelligence, it’s still based on data crunching.” 

All but one participant were aware of Turnitin.com as one use of AI in education, and although AUC participants had all used it extensively as teachers or as academic developers supporting people using it, the SAU participants seemed to know it, but have less extensive experience with it (more about this in the next section). A couple of participants (SAU3, SAU4, SAU5) mentioned the uses of AI in administration and recruitment and learning analytics rather than teaching and learning per se. 

When participants did not mention many uses of AI around them, I talked to them about Google search, YouTube recommendations and such, as some were not aware that there was AI underlying these.

When asked about their knowledge of and attitudes towards AI in education in general, participants had varying responses.

AUC1 and AUC2, two of the younger participants in the study, had a generally positive attitude towards embracing uses of AI in education, particularly as it would be something undergraduate students are already used to in their everyday lives. SAU5 expressed her view that it was “rather inevitable” and she said that discussing it now is like discussing the internet in the early 90s – it may seem far away, but we probably won’t have a choice anyway. Her main concern related to the African context “where there is a huge gap between universities and [within the] student population” and she wonders whether AI might change that. She has “more questions and more worries but think it is something that will appear more and more” because there are too many business interests invested, and education is a natural market for them.

A couple of participants had balanced views. SAU3 felt “ambivalent” and thought AI had potential to bring efficiencies to things like admissions systems, but that it also brought along risks, particularly with regards to the ethical dilemma of data collected and owned by institutions without people understanding what they are consenting to. AUC3 and SAU4 said it would depend on the platform and evidence of its effectiveness.

SAU1 mentioned that her first reaction was “suspicion”, not with the “intrinsic technology” but how it is used – especially that technology was often being used without informed consent, or when consent was given, it was given without true clarity for the users. She called this an “obfuscatory environment designed to create a fog” that made it difficult to engage. She also questioned what AI in education was “appropriated for” and felt that people as users were less critical of them because they “appear to be free” and help maintain their “filter bubbles”. AUC4 also had a generally skeptical stance towards AI in education, which will appear in future sections in more detail.

That’s it for today – let me know what you think so far!

Photo by Possessed Photography on Unsplash (cropped by me)

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