What is the ideal methodological response for the learning and teaching of critical thinking and evaluative judgement in the age of generative artificial intelligence?
DOI:
https://doi.org/10.26473/ATLAANZ.2024/006Keywords:
Generative artificial intelligence, GenAI, critical thinking, evaluative judgment, motivation, methodologyAbstract
The two-lane approach as a response to assessment in the new world of generative artificial intelligence (GenAI) (Liu & Bridgeman, 2023), has fast gained traction with tertiary education providers. The flexible, adaptive and experimental nature of this approach arguably complements much of what the literature on second language (L2) motivation research advocates. A key component of that literature is that the more students can see a rationale for their learning and its relevance, the more they will become and remain motivated. While L2 motivation research greatly expands on these broad concepts, two key theoretical constructs underpin much of it. The first is the Process Model of Motivation (Dörnyei & Ottó, 1998) and the second is Dörnyei’s (2009) L2 Motivational Self System, which expanded on the former. This article will background the two-lane approach and then discuss the perceived merits of it by way of example. It will posit that this approach may work to the advantage of students in a world in which they will be increasingly expected to incorporate GenAI into their course work. Finally, this article will speak to the reservations in the literature about GenAI’s role and ability to promote critical thinking and the use of evaluative judgment, which are both core elements that learning advisors teach and support students with.
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