Abstract:

This research adopts a sociotechnical lens to understand how and where artificial intelligence (AI) technologies add value in curriculum design processes. Early research studies suggest that AI in education (AIEd) – that is the use of artificial intelligence technologies in educational settings to facilitate learning, teaching or decision-making - was grounded in technological determinism, that is the belief that learners adjust their behaviours to fit learner pathways as predetermined by the technologies; for example, higher education (HE) learning management systems that may use predictive analytics to analyse student performance data and possibly specify remedial (or advanced) pathways to support student progression. More recent applications of artificial intelligence in HE are framed using social constructivism where, for example, tools such as ChatGPT are used by students to scaffold their learning experiences. These applications of artificial intelligence technologies however suggests a more passive role of students in the design of learning experiences within existing HE outcomes-based frameworks. The literature therefore debates the exact impact of artificial intelligence technologies on student attainment, retention and autonomy; and the extent of the utility of the technologies in creating more personalised learning experiences that support learner autonomy. This is particularly relevant as students are traditionally not perceived as active participants in curriculum design processes, including in the development of learning outcomes.

Therefore the risk implied in the adoption of artificial intelligence technologies in HE is that the technologies serve to mask more deep-rooted problems that contribute to curricula misalignment; that is a lack of cohesiveness between curricula learning outcomes (LOs), pedagogical approaches and assessment strategies that may in turn impact stakeholder expectations, including student misinterpretation and misunderstanding of learning outcomes. We therefore view future AIEd applications as cohesive sociotechnical systems that optimise interdependent relationships between social (culture, processes and people), and technical aspects such that learners have greater autonomy in shaping their own learning pathways. In this study we explore the literature to further understand the framework in which such a sociotechnical system would effectively operate in HE, with consideration of the social and technological factors as well as implications of the environment (e.g. policy and regulatory frameworks) in which the solution is placed.

Keywords:

Artificial intelligence, higher education, curriculum design, curriculum misalignment.