DIGITAL LIBRARY
PRINCIPAL COMPONENT ANALYSIS AND BLOOM TAXONOMY TO PERSONALISE LEARNING
Vilnius Gediminas Technical University (LITHUANIA)
About this paper:
Appears in: EDULEARN19 Proceedings
Publication year: 2019
Pages: 2910-2920
ISBN: 978-84-09-12031-4
ISSN: 2340-1117
doi: 10.21125/edulearn.2019.0780
Conference name: 11th International Conference on Education and New Learning Technologies
Dates: 1-3 July, 2019
Location: Palma, Spain
Abstract:
The purpose of spreading, deploying and using information and communication technologies (ICTs) in virtual learning environments and providing digital tools for classrooms is to make learning process easier, more comfortable for students and more personalised, thus helping learners to reach his or her learning objectives.

As taxonomies of learning provide incredibly useful tools for defining the types of work that learners should do for reaching their learning purpose, learning environments are designed or constructed on the basis of these taxonomies. The taxonomies function as powerful heuristics, helping to analyse learning objectives and to design assignments. Applying taxonomies, the point is to suggest the learner assignments aligned with assessments and current learning objectives, also providing personalised learning environment using advanced ICTs. Here taxonomies application problem as the basis for development and/or construction of learning environment arises, bringing up a question how to choose the right and optimal set of taxonomy elements helping the particular group of learners to reach their learning goals and eliminating “noisy”, i.e. non-significant elements.

Novel methodology using principal component analysis alongside the techniques for extraction of the most important ICT features and elimination the other features is proposed in the paper.

In the paper, first of all, systematic research review on analysed topics is performed. Second, research methodology on using principal component analysis alongside the techniques for extraction of the most important ICT features elimination the other features is provided. Third, experiment using digital Bloom’s taxonomy activities was conducted to develop the proposed methodology – experimental results are described in the paper.
Keywords:
Virtual learning environment, learning taxonomy, principal component analysis, personalisation, digital Bloom’s taxonomy.