Mining formative evaluation rules using web-based learning portfolios for web-based learning systems

Chih Ming Chen, Chin-Ming Hong, Syuan-Yi Chen, Chao Yu Liu

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Learning performance assessment aims to evaluate what knowledge learners have acquired from teaching activities. Objective technical measures of learning performance are difficult to develop, but are extremely important for both teachers and learners. Learning performance assessment using learning portfolios or web server log data is becoming an essential research issue in web-based learning, owing to the rapid growth of e-learning systems and real application in teaching scenes. The traditional summative evaluation by performing examinations or feedback forms is usually employed to evaluate the learning performance for both the traditional classroom learning and the web-based learning. However, summative evaluation only considers final learning outcomes without considering learning processes of learners. This study presents a learning performance assessment scheme by combining four computational intelligence theories, i.e., the proposed refined K-means algorithm, the neuro-fuzzy classifier, the proposed feature reduction scheme, and fuzzy inference, to identify the learning performance assessment rules using the web-based learning portfolios of an individual learner. Experimental results indicate that the evaluation results of the proposed scheme are very close to those of summative assessment results of grade levels. In other words, this scheme can help teachers to assess individual learners precisely utilizing only the learning portfolios in a web-based learning environment. Additionally, teachers can devote themselves to teaching and designing courseware since they save a lot of time in evaluating learning. This idea can be beneficially applied to immediately examine the learning progress of learners, and to perform interactively control learning for e-learning systems. More significantly, teachers could understand the factors influencing learning performance in a web-based learning environment according to the obtained interprtable learning performance assessment rules.

Original languageEnglish
Pages (from-to)69-87
Number of pages19
JournalEducational Technology and Society
Volume9
Issue number3
Publication statusPublished - 2006 Aug 14

Fingerprint

learning performance
Learning systems
Teaching
performance assessment
evaluation
learning
Fuzzy inference
Artificial intelligence
Classifiers
Servers
teacher
Feedback
electronic learning
learning environment
learning success
learning process
intelligence
school grade
classroom
examination

Keywords

  • Data Mining
  • Learning Performance Assessment
  • Web-based Learning
  • Web-based Learning Portfolio

ASJC Scopus subject areas

  • Education
  • Sociology and Political Science
  • Engineering(all)

Cite this

Mining formative evaluation rules using web-based learning portfolios for web-based learning systems. / Chen, Chih Ming; Hong, Chin-Ming; Chen, Syuan-Yi; Liu, Chao Yu.

In: Educational Technology and Society, Vol. 9, No. 3, 14.08.2006, p. 69-87.

Research output: Contribution to journalArticle

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