Schagaev, Igor, Kirk, Brian and Bacon, Liz (2014) Essential knowledge aggregation, delivery and assessment. eLearn Magazine, 14 (5):1. ISSN 1535-394X (Online)

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Abstract

It is clear that the use of ICT for education has not yet achieved its potential. In this paper we present our vision on the further development and widening of learning through the enhanced use of ICT. In this context, learning is considered as having a framework with several essential and connected processes. Web semantic methods now enable the monitoring of knowledge and curriculum updates. Substantial research is required as well as an understanding of how the human brain manages various channels of information delivery. We consider knowledge delivery in combination with textual, visual and audio information. Its efficiency can be improved when we discover and apply methods used for successful performances and plays. A paradigm shift from in-class assessment toward self-assessment assisted by individually tailored ICT increases the efficiency of learning. As a first step, an individual assessment tool (App) for iOS is briefly described.

What does education need from ICT? It is clear that we need to address how we extract knowledge from Web, how we aggregate new with existing knowledge, how we deliver more current and essential knowledge and how we can ease and improve assessment. All of these steps include ICT, web and human involvement. This is called Essential Knowledge Extraction, Aggregation, Delivery and Assessment. It is a practical pathway for considerable research in knowledge aggregation (using information processing support), extraction, and delivery. To succeed in delivering this aggregated knowledge we must understand how the learner’s brain absorbs knowledge. In addition self-assessment supported and implemented by individually tailored (adaptive) assessment technology and tools can also improve knowledge delivery.

Item Type:	Article
Subjects:	L Education > L Education (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group:	Faculty of Liberal Arts & Sciences > eCentre Greenwich Research into Innovative Pedagogies (GRIP) Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS) Faculty of Engineering & Science
Last Modified:	04 Mar 2022 13:08
URI:	http://gala.gre.ac.uk/id/eprint/17255

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