A Framework for Higher Education.

Abstract

It is well documented that the traditional protocol for higher education doesn’t suit each learner, the rhetorical method of lecturing while presupposing certain domain knowledge and experience is a very inefficient method of imparting knowledge. An ideal solution is to have a one-to-one system, where an instructor generates mathemagenic content for each learner. Obviously this is not an ideal situation considering the high increase of learners into higher education. One solution is for higher education to partially traverse into an online learning environment with an element of suitable adaptive content. Adaptive learning systems attempt to adapt learning content to suit the needs of the learners using the system. Most adaptive techniques however are constrained by the pedagogical preference of the author of the system and are always constrained to the system they were developed for and the domain content. This paper describes a personal profile that can be used to automatically generate instructional content to suit the pedagogical preference and cognitive ability of a learner in a tractable amount of time. The paper discusses the manifestation of measurable cognitive traits in an online learning environment and identifies cognitive resources that can be used to stimulate these manifestations. Additionally this paper describes a Content Analyser that is used to automatically generate Metadata to encapsulate cognitive resources within instructional content. The content is repackaged as independent Sharable Content Objects (SCOs) as described by the Sharable Content Object Reference Model. Finally the paper concludes with an example learning component that utilizes the CA for building course content to an expected predetermined minimum learning experience suited to each learner’s cognitive ability and pedagogical preference delivered through Moodle.