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Preliminary Explorations on the Statistical Profiles of Highly-Rated Learning Objects

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Metadata and Semantic Research (MTSR 2009)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 46))

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Abstract

As learning object repositories grow and accumulate resources and metadata, the concern for quality has increased, leading to several approaches for quality assessment. The availability of on-line evaluations in some repositories has opened the opportunity to examine the characteristics of learning objects that are evaluated positively, in search of features that can be used as a priori predictors of quality. This paper reports a preliminary exploration of some learning object attributes that can be automatically analyzed and might serve as quality metrics, using a sample from the MERLOT repository. The bookmarking of learning objects in personal collections was found to be a potential predictor of quality. Among the initial metrics considered, the number of images has been found to be also a predictor in most of the disciplines and the only candidate for the Art discipline. More attributes have to be studied across disciplines to come up with automated analysis tools that have a degree of reliability.

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References

  • Cafolla, R.: Project MERLOT: Bringing peer review to web-based educational resources. Journal of Technology and Teacher Education 14(2), 313–323 (2006)

    Google Scholar 

  • Guntram, G.: Open Educational Practices and Resources: The OLCOS Roadmap 2012. Revista de Universidad y Sociedad del Conocimiento 4(1) (2007), http://www.uoc.edu/rusc/4/1/dt/eng/geser.pdf [Date of consultation: April/10/2009]

  • Han, K., Kumar, V., Nesbit, J.C.: Rating learning object quality with bayesian belief networks. In: E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, & Higher Education, Phoenix, AZ (2003)

    Google Scholar 

  • Ivory, M.Y., Hearst, M.A.: The state of the art in automating usability evaluation of user interfaces. ACM Computing Surveys 33, 470–516 (2001)

    Article  Google Scholar 

  • Ivory, M.Y., Hearst, M.A.: Statistical profiles of highly-rated web sites. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems: Changing Our World, Changing Ourselves CHI 2002, Minneapolis, Minnesota, USA, April 20 - 25, pp. 367–374. ACM, New York (2002)

    Chapter  Google Scholar 

  • Kelty, C.M., Burrus, C.S., Baraniuk, R.G.: Peer Review Anew: Three Principles and a Case Study in Postpublication Quality Assurance. Proceedings of the IEEE 96(6), 1000–1011 (2008)

    Article  Google Scholar 

  • Lundgren-Cayrol, K., Marino, O., Paquette, G., Léonard, M., de la Teja, I.: Implementation and Deployment Process of IMS Learning Design: Findings from the Canadian IDLD Research Project. In: Proc. of the IEEE International Conference on Advanced Learning Technologies 2006 (ICALT 2006), pp. 581–585 (2006)

    Google Scholar 

  • McGreal, R.: A Typology of learning object repositories. In: Adelsberger, H.H., Kinshuk, Pawlowski, J.M., Sampson, D.G. (eds.) International Handbooks on Information Systems. Springer, Heidelberg (2008)

    Google Scholar 

  • Nash, S.S.: Learning objects, learning object repositories, and learning theory: Preliminary best practices for online courses. Interdisciplinary Journal of Knowledge and Learning Objects 1, 217–228 (2005), http://ijklo.org/Volume1/v1p217-228Nash.pdf

    MathSciNet  Google Scholar 

  • Ochoa, X., Duval, E.: Relevance Ranking Metrics for Learning Objects. IEEE Trans. Learn. Technol. 1(1), 34–48 (2008)

    Article  Google Scholar 

  • Ochoa, X., Duval, E.: Quantitative Analysis of Learning Object Repositories. In: Proceedings of World Conference on Educational Multimedia, Hypermedia and Telecommunications 2008, pp. 6031–6048. AACE, Chesapeake (2008)

    Google Scholar 

  • Sicilia, M.A., García-Barriocanal, E.: On the Concepts of Usability and Reusability of Learning Objects. International Review of Research in Open and Distance Learning 4(2) (2003)

    Google Scholar 

  • Sicilia, M.A., García-Barriocanal, E., Pagés, C., Martínez, J.J., Gutiérrez, J.M.: Complete metadata records in learning object repositories: some evidence and requirements. International Journal of Learning Technology 1(4), 411–424 (2005)

    Article  Google Scholar 

  • Vargo, J., Nesbit, J.C., Belfer, K., Archambault, A.: Learning object evaluation: Computer mediated collaboration and inter-rater reliability. International Journal of Computers and Applications 25(3), 198–205 (2003)

    Google Scholar 

  • Vuorikari, R., Manouselis, N., Duval, E.: Using Metadata for Storing, Sharing and Reusing Evaluations for Social Recommendations: the Case of Learning Resources. In: Social Information Retrieval Systems: Emerging Technologies and Applications for Searching the Web Effectively, pp. 87–107. Idea Group Inc., New York (2008)

    Chapter  Google Scholar 

  • Wiley, D., Wayers, S., Dawson, D., Lambert, B., Barclay, M., Wade, D.: Overcoming the limitations of learning objects. Journal of Educational Multimedia and Hypermedia 13(4), 507–521 (2004)

    Google Scholar 

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García-Barriocanal, E., Sicilia, M.Á. (2009). Preliminary Explorations on the Statistical Profiles of Highly-Rated Learning Objects. In: Sartori, F., Sicilia, M.Á., Manouselis, N. (eds) Metadata and Semantic Research. MTSR 2009. Communications in Computer and Information Science, vol 46. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04590-5_10

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  • DOI: https://doi.org/10.1007/978-3-642-04590-5_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04589-9

  • Online ISBN: 978-3-642-04590-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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