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Development of a visual e-learning system for supporting the semantic organization and utilization of open learning content

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Abstract

In an open e-learning content management environment, relation metadata is of benefit to improve semantic organization and reusability of learning content. Although the suggested relations defined in the SCORM and the extended relations proposed in the past studies can describe semantic relationships, there are some new requirements of semantic organization and utilization of open learning content. Based on existing models, this paper presents an extended relation metadata model for open knowledge communities. In order to help users to author and utilize the semantic relation, the visual authoring system named web-based visual authoring system for relation metadata (WVAS-RM) in the Learning Cell Knowledge Community is designed and implemented to assist the construction and utilization of semantic relations of Learning Cells. The paper presents an empirical evaluation of the teachers’ and learners’ acceptance and satisfaction of the proposed system using the adapted Technology Acceptance Model and System Usability Scale. The semi-structured interviews are also carried out with participants including teachers and students. It is concluded that students and teachers feel confident and satisfied with the system.

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Notes

  1. vis.js - A dynamic, browser based visualization library. http://visjs.org/.

References

  1. Brooke J (1996) Sus-a quick and dirty usability scale. Usability Evaluation in Industry 189:4–7

    Google Scholar 

  2. Burkhard RA (2004) Learning from architects: the difference between knowledge visualization and information visualization. In: IV ‘04: Proceedings of the Information Visualisation, Eighth International Conference, IEEE Comput. Soc, pp 519–524

  3. Curlango-Rosas C, Ponce GA, Lopez-Morteo GA (2011) A specialized search assistant for learning objects. ACM Trans Web 5(4):1–29

    Article  Google Scholar 

  4. Davis FD (1989) Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Q 13(3):319–340

    Article  Google Scholar 

  5. Downes S (2001) Learning objects: resources for distance education worldwide. International Review of Research in Open & Distance Learning 2:1

    Google Scholar 

  6. Duval E, Hodgins W (2003) A LOM research agenda. In: Hencsey G, White B, Chen Y, Kovacs L, Lawrence S (eds.) Proceedings of the 12th international conference on World Wide Web. Budapest, Hungary, pp. 659–667

  7. Fischer S (2001) Course and exercise sequencing using metadata in adaptive hypermedia learning systems. ACM Journal of Education Resource in Computing 1(1):1–21

    Google Scholar 

  8. Harrati N, Bouchrika I, Tari A, Ladjailia A (2016) Exploring user satisfaction for e-learning systems via usage-based metrics and system usability scale analysis. Comput Hum Behav 61:463–471

    Article  Google Scholar 

  9. Huang TC, Chen CC (2013) Animating civic education: developing a knowledge navigation system using blogging and topic map technology. Educ Technol Soc 16(1):79–92

    Google Scholar 

  10. Karger P, Ullrich C, Melis E (2006) Integrating learning object repositories using a mediator architecture. Paper presented at the First European Conference on Technology Enhanced Learning, Crete

  11. Liu IF, Chen MC, Sun YS, Wible D, Kuo C (2010) Extending the TAM model to explore the factors that affect intention to use an online learning community. Comput Educ 54(2):600–610

    Article  Google Scholar 

  12. Lu JL, Hsieh CJ (2009) A relation metadata extension for scorm content aggregation model. Computer Standards & Interfaces 31(5):1028–1035

    Article  Google Scholar 

  13. Lu JL, Horng G, Yu CS, Chou LY (2010) Extended relation metadata for scorm-based learning content management systems. Educ Technol Soc 13(1):220–235

    Google Scholar 

  14. Mann WC, Thompson SA (1988) Rhetorical structure theory: toward a functional theory of text organization. Text 8(3):243–281

    Article  Google Scholar 

  15. Müller D, Yi MY (2014) Annotating korean text documents with linked data resources. Multimed Tools Appl 68(2):413–427

    Article  Google Scholar 

  16. Ngai E, Poon J, Chan Y (2007) Empirical examination of the adoption of WebCT using TAM. Comput Educ 48:250–267

    Article  Google Scholar 

  17. Persico D, Manca S, Pozzi F (2014) Adapting the technology acceptance model to evaluate the innovative potential of elearning systems. Comput Hum Behav 30:614–622

    Article  Google Scholar 

  18. Reigeluth C (1999) Instructional-design theories and models, volume II: a new paradigm of instructional theory. Lawrence Erlbaum, Mahwah

    Google Scholar 

  19. Robles-Gómez A, Ros S, Hernández R, Tobarra L, Caminero AC, Agudo JM (2015) User acceptance of a proposed self-evaluation and continuous assessment system. Educ Technol Soc 18(2):97–109

    Google Scholar 

  20. Sddik AE, Fischer S, Steinmetz R (2001) Reusable multimedia content in web-based learning systems. IEEE Multimedia 8(3):30–38

    Article  Google Scholar 

  21. Shee D, Wang Y (2008) Multi-criteria evaluation of the web-based e-learning system: a methodology based on learner satisfaction and its applications. Comput Educ 50:894–905

    Article  Google Scholar 

  22. Steinacker A, Faatz A, Seeberg C, Rimac L, Hormann S, Saddik AE, Steinmetz R (2001) Medibook: combining semantic networks metadata for learning resources to build a web based learning system. Paper presented at the Ed-Media Conference, Tampere

  23. Tergan SO, Keller T, Burkhard RA (2006) Integrating knowledge and information: digital concept maps as bridging technology. Inf Vis 5(3):167–174

    Article  Google Scholar 

  24. Tiropanis T, Davis H, Millard D, Weal M (2009) Semantic technologies for learning and teaching in the web 2.0 era. IEEE Intell Syst 24(6):49–53

    Article  Google Scholar 

  25. Ullrich C (2004) Description of an instructional ontology and its application in web services for education. Paper presented at the Workshop on Application of Semantic Web Technologies for E-learning, Hiroshima

  26. Verbert K, Duval E (2008) Alocom: a generic content model for learning objects. Int J Digit Libr 9(1):41–63

    Article  Google Scholar 

  27. Wang M, Peng J, Cheng B, Zhou H, Liu J (2011) Knowledge visualization for self-regulated learning. Educ Technol Soc 14(3):28–42

    Google Scholar 

  28. Wu P, Yu S (2015) Design of a Novel Intelligent Framework for finding experts and learning peers in open knowledge communities. EAI Endorsed Transactions on Future Intelligent Educational Environments 15(2):e4

    Article  Google Scholar 

  29. Yang X, Qiu Q, Yu S, Tahir H (2014) Designing a trust evaluation model for open-knowledge communities. Br J Educ Technol 45(5):880–901

    Article  Google Scholar 

  30. Yu S, Yang X, Cheng G, Wang M (2015) From learning object to learning cell: a resource organization model for ubiquitous learning. Educ Technol Soc 18(2):206–224

    Google Scholar 

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Acknowledgements

This research was funded by the project “the Research on Internet plus Educational System” (Project No.16JZD043).

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Authors and Affiliations

  1. School of Educational Technology, Faculty of Education, Beijing Normal University, No.19 Xinjiekouwai St. Haidian district, Beijing, 100875, People’s Republic of China

    Pengfei Wu, Shengquan Yu, Qi Wang & Dan Wang

  2. Advanced Innovation Center for Future Education, Beijing Normal University, Beijing, 100875, China

    Pengfei Wu, Shengquan Yu, Na Ren, Qi Wang & Dan Wang

  3. School of Education, Shijiazhuang University, Shijiazhuang, 050035, China

    Pengfei Wu

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  1. Pengfei Wu
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Correspondence to Shengquan Yu.

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Wu, P., Yu, S., Ren, N. et al. Development of a visual e-learning system for supporting the semantic organization and utilization of open learning content. Multimed Tools Appl 77, 17437–17456 (2018). https://doi.org/10.1007/s11042-017-5312-7

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