Some aspects of eLearning experience can be enhanced in a very natural way by using the basic tools offered by fuzzy logic. As a matter of example, consider the uncontrolled growth of information produced in a collaborative-oriented context, in which each participant (e.g. students, teachers) is able to insert and share new contents (e.g. comments, texts) concerning a university course. All the incrementally added pieces of information can be evaluated in several ways: by the intervention of a “dictator” (e.g. the teacher), using a rating form, or even according to the frequency of access. As contents rapidly become unusable for the effects of information overload, basic tools of fuzzy logic such as membership functions and measures of fuzziness can help to distinguish between relevant and trivial content, without thereby canceling any contribution. This very same idea can of course also be applied to different contexts.
A fuzzy methodology to alleviate information overload in eLearning
D(')Asaro, F. A.
;
2013-01-01
Abstract
Some aspects of eLearning experience can be enhanced in a very natural way by using the basic tools offered by fuzzy logic. As a matter of example, consider the uncontrolled growth of information produced in a collaborative-oriented context, in which each participant (e.g. students, teachers) is able to insert and share new contents (e.g. comments, texts) concerning a university course. All the incrementally added pieces of information can be evaluated in several ways: by the intervention of a “dictator” (e.g. the teacher), using a rating form, or even according to the frequency of access. As contents rapidly become unusable for the effects of information overload, basic tools of fuzzy logic such as membership functions and measures of fuzziness can help to distinguish between relevant and trivial content, without thereby canceling any contribution. This very same idea can of course also be applied to different contexts.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.