Abstract
This paper examines how adult learners in open and distance education (ODE) mobilise artificial intelligence (AI) as a metacognitive scaffold—a support that helps them plan, monitor, and refine their learning without substituting their judgement. Drawing on twelve semi-structured interviews analysed through inductive thematic analysis, we identify four interlocking practices through which metacognition is enacted in digitally mediated study: (1) targeted information seeking using keywords, academic filters, and rapid source appraisal; (2) micro-scheduling and personal deadlines that externalize monitoring and sustain study pace; (3) feedback uptake for redesign, converting instructor/peer comments into explicit revision plans; and (4) selective, critical AI use (translation, summarisation, ideation) tempered by concerns about authenticity, reliability, and data protection. We theorise these practices via a synthesis of metacognition (awareness–regulation), Vygotsky’s sociocultural perspective (scaffolding within the Zone of Proximal Development), and connectivism (learning as maintaining networks of people, tools, and informational nodes). The result is a functional model of digital metacognition with AI—Goals → Strategies → AI-mediated feedback → Reflection → Transfer—that positions AI as a co-regulator rather than an answer engine. Implications for instructional design include making criteria and success metrics explicit, embedding brief reflective checkpoints, cultivating feedback literacy for human- and AI-generated responses, and introducing time scaffolds that mitigate procrastination while preserving autonomy. The study offers empirically grounded guidance on integrating AI in ODE in ways that strengthen—rather than dilute—the metacognitive core of adult learning.
Presenters
Georgia KaragianniPhD Candidate, Humanitarian Studies, Hellenic Open University, Achaïa, Greece
Details
Presentation Type
Paper Presentation in a Themed Session
Theme
Considering Digital Pedagogies
KEYWORDS
Digital Metacognition, AI, ODE
