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Open AccessJournal ArticleDOI

Enhancing student learning through hypermedia courseware and incorporation of student learning styles

TLDR
An adaptive hypermedia interface was developed that provided dynamic tailoring of the presentation of course material based on the individual student's learning style, and the authors believe students learned more efficiently and more effectively.
Abstract
This paper outlines attempts to enhance student learning by addressing different learning styles through course hypermedia. Students learn by a variety of different learning styles. Previously, instructors were unable to effectively address these different learning styles outside the classroom. Two approaches were developed to address this problem. The first approach was the development of hypermedia courseware. This provided a wide variety of tools which students could use to prepare for lessons. In this way students retained complete control over how they prepared for a lesson and could choose those hypermedia tools that were most conducive to their learning. An assessment of the multimedia and hypertext documents in the course revealed that the value of a particular multimedia tool to a student varied widely. Each student was traversing the course material according to his/her unique learning style. Unfortunately, the plethora of tools confused some students because they were uncomfortable making active choices of what course material would be most conducive to their learning. As a result, a second approach was adopted. An adaptive hypermedia interface was developed that provided dynamic tailoring of the presentation of course material based on the individual student's learning style. By tailoring the presentation of material to the student's learning style, the authors believe students learned more efficiently and more effectively.

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Citations
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Journal ArticleDOI

A genetic algorithm approach to recognise students' learning styles

TL;DR: In this article, a genetic algorithm approach is used to automatically identify the individual learning styles of students based on their actions while attending an academic course, which can be used to adapt a course according to the individual characteristics of the students.
Journal ArticleDOI

E-learning: a model and process proposal

TL;DR: The following theoretical reflection on the learning processes are proposed: studying classical didactics that have been revised from the point-of-view of distance learning, individuating the new actors interacting in theDidactics, and deducing a possible learning model.
Journal ArticleDOI

Integration into mathematics classrooms of an adaptive and intelligent individualized e-learning environment: Implementation and evaluation of UZWEBMAT

TL;DR: An adaptive and intelligent individualized e-learning environment based on learning style and expert system named UZWEBMAT is designed and evaluated to evaluate its effects on students' learning of the unit of probability.

Discovering Student Preferences in E-Learning

TL;DR: This paper uses all the background knowledge available about a particular student to build an initial decision model based on learning styles, which can be fine-tuned with the data generated by the student's interactions with the system in order to reflect more accurately his/her current preferences.
Journal ArticleDOI

Learning style detection in E-learning systems using machine learning techniques

TL;DR: The authors have identified new attributes and scaled-down the attributes identified earlier, which would help identify the learner's learning style, and implemented classification algorithms and compared the accuracy of the different algorithms on the dataset.
References
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Journal ArticleDOI

A Sign That Education is Maturing: Taxonomy of Educational Objectives, the Classification of Educational Goals, Handbook I: Cognitive Domain

TL;DR: Using Bloom's Taxonomy to Write Effective Learning Objectives: The Abcds of Writing Learning ObjectIVES: A Basic Guide.

Learning and Teaching Styles in Engineering Education.

TL;DR: A self-scoring web-based instrument called the Index of Learning Styles that assesses preferences on four scales of the learning style model developed in the paper currently gets about 100,000 hits a year and has been translated into half a dozen languages.
Journal Article

Reaching the Second Tier--Learning and Teaching Styles in College Science Education.

TL;DR: This paper defined two tiers of entering college students, the first consisting of those who go on to earn science degrees and the second those who have the initial intention and the ability to do so but instead switch to nonscientific fields.