A goal of educational technology since the 1930s has been to adapt teaching to the personal needs of each student. Significant developments have included programmed instruction, branched instruction, intelligent tutoring systems, and adaptive courseware. Personalized learning is coming back into prominence with the development of new techniques for linking learning analytics to adaptive teaching. Research challenges include how to enable personalization of informal and inquiry-led learning, and how to link personalization with learning through conversation and social networking.
Personalized open learning must offer opportunities for students from widely differing backgrounds to learn in ways that match their needs and abilities. This requires new designs for flexibility of timing, pace, facilitation and assessment. For informal learning, personalization must align with changes in context, learning materials co-created by students, and self-directed study. In social networked learning, students need support to merge their individual pathways through the curriculum into shared goals, positive interdependence and productive conversation.
I shall discuss recent work at The Open University on predictive analytics and flexible pathways for learners, as part of a strategic university initiative in personalized open learning. Our iSpot and nQuire-it platforms combine informal science learning with personalization through reputation management and student authoring. Adaptive crowdsourcing may offer mechanisms for personalized social networked learning.
Event URL: http://www.icce2017.canterbury.ac.nz/