The study of learners' preference for visual complexity on small screens of mobile computers using neural networks

Lan Ting Wang, Kun-Chou Lee

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

The vision plays an important role in educational technologies because it can produce and communicate quite important functions in teaching and learning. In this paper, learners' preference for the visual complexity on small screens of mobile computers is studied by neural networks. The visual complexity in this study is divided into five levels, including "very high" complexity, "slightly high" complexity, "medium" complexity, "slightly low" complexity and "very low" complexity. This study focuses on the age effects for vision problems in educational technologies. The age of the tested subjects distributes from 10 to 64, and is uniformly divided into 11 groups with each group composed of 30 tested subjects. For simplicity, the effects of gender, words, colors, and other visual factors are ignored. This study found that only learners of the younger and older age groups have special preference on the picture of very high complexity. Most learners prefer pictures of medium and slightly high complexity. These results are consistent with many existing studies. With the use of neural networks, only about half of the investigation data are required to predict the overall investigation results. Discussions and interpretations on the results are also given in this study. This study will be helpful in vision problems of educational technologies.

Original languageEnglish
Pages (from-to)168-180
Number of pages13
JournalTurkish Online Journal of Educational Technology
Volume13
Issue number2
Publication statusPublished - 2014 Jan 1

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neural network
educational technology
age group
Group
interpretation
gender
Teaching
learning

All Science Journal Classification (ASJC) codes

  • Education

Cite this

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