A Framework for Guiding Personalised Learning Design in African ODL Institutions | Webtoolkit

PL Framework

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This framework has been integrated with an AI agent + to facilitate searching and summarization, providing a personalized understanding of its elements, components, and processes. Responses and results are limited to the private materials and data used to develop the framework.

Personalised Feedback and Assessment
Data Mining and Visualisation Continuous feedback with personalised adjustments Integration of activity-tool based personalisation Problem solving Personalised reinforcement Self evaluation Personalised feedback based on incorrect attempt Personalised feedback based on user responses/scores
Personalised Content Adaptation
Content adaptation authoring tools Content adaptation based on difficulty levels Content adaptation based LMS plugins Data mining personalisation Games based personalisation Learning objects/units categorisation Machine learning / AI personalisation Metadata - based classification Networking concepts or hypermedia pages Personalisation based on agent Systems Personalisation based on learning analytics Content recommendation techniques Semantic web technologies Web 2.0 driven personalisation
Technology integration
Intelligent and Adaptive Systems Data driven and Analytical Approaches Semantic, AI, and Web based technologies
Learner Characteristics
Ability Behaviour Cognitive Competence Computer Literacy Characteristic of devices Digital Access and Literacy Disability Social and Cultural Context Information needs Interests Language Learning Goals Learning Styles Background Context Learning Reflection Motivation Objectives Preferences Prior experiences Prior Information Prior Knowledge Reasons to study Skills Social profile Social Scraping Time of Study Use of Technology