Skip to main content
Top

2017 | OriginalPaper | Chapter

Towards a Characterization of Educational Material: An Analysis of Coursera Resources

Authors : Carlo De Medio, Fabio Gasparetti, Carla Limongelli, Matteo Lombardi, Alessandro Marani, Filippo Sciarrone, Marco Temperini

Published in: Emerging Technologies for Education

Publisher: Springer International Publishing

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

When teachers are surfing the Web to search suitable learning material for their courses it would be very important that web resources were characterized to restrict the scope of the search. Hence, it arises the need of finding characterizing properties for learning materials. This paper proposes an initial reflection on this issue. We exploit the huge potential of the MOOC, in particular Coursera, to discover new educational information that might characterize material of MOOCs. This goal is achieved by means of data mining techniques. Two types of features about resources have been discovered: teaching context and resource attributes. The resulting knowledge can be very helpful for a more accurate recommendation of resources to the particular teaching context of an instructor, as well as improving the creation and arrangement of learning activities.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Footnotes
4
DAJEE can be accessed publicly for research purposes only, following the authors’ approval. Apply for it by filling in the form at http://​144.​6.​235.​142/​dajee.
 
Literature
1.
go back to reference Adomavicius, G., Tuzhilin, A.: Context-aware recommender systems. In: Ricci, F., Rokach, L., Shapira, B., Kantor, P.B. (eds.) Recommender Systems Handbook, pp. 217–253. Springer, New York (2011) Adomavicius, G., Tuzhilin, A.: Context-aware recommender systems. In: Ricci, F., Rokach, L., Shapira, B., Kantor, P.B. (eds.) Recommender Systems Handbook, pp. 217–253. Springer, New York (2011)
3.
go back to reference Drachsler, H., Verbert, K., Santos, O., Manouselis, N.: Panorama of recommender systems to support learning. In: Ricci, F., Rokach, L., Shapira, B. (eds.) 2nd Handbook on Recommender Systems, pp. 421–451. Springer, New York (2015) Drachsler, H., Verbert, K., Santos, O., Manouselis, N.: Panorama of recommender systems to support learning. In: Ricci, F., Rokach, L., Shapira, B. (eds.) 2nd Handbook on Recommender Systems, pp. 421–451. Springer, New York (2015)
4.
go back to reference Estivill-Castro, V., Limongelli, C., Lombardi, M., Marani, A.: Dajee: a dataset of joint educational entities for information retrieval in technology enhanced learning. In: Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 681–684. ACM (2016) Estivill-Castro, V., Limongelli, C., Lombardi, M., Marani, A.: Dajee: a dataset of joint educational entities for information retrieval in technology enhanced learning. In: Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 681–684. ACM (2016)
5.
go back to reference Granitto, P.M., Furlanello, C., Biasioli, F., Gasperi, F.: Recursive feature elimination with random forest for ptr-ms analysis of agroindustrial products. Chemometr. Intell. Lab. Syst. 83(2), 83–90 (2006)CrossRef Granitto, P.M., Furlanello, C., Biasioli, F., Gasperi, F.: Recursive feature elimination with random forest for ptr-ms analysis of agroindustrial products. Chemometr. Intell. Lab. Syst. 83(2), 83–90 (2006)CrossRef
6.
go back to reference Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The weka data mining software: an update. SIGKDD Explor. Newsl. 11(1), 10–18 (2009)CrossRef Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The weka data mining software: an update. SIGKDD Explor. Newsl. 11(1), 10–18 (2009)CrossRef
7.
go back to reference Kay, J., Reimann, P., Diebold, E., Kummerfeld, B.: Moocs: so many learners, so much potential. Technology 52(1), 49–67 (2013) Kay, J., Reimann, P., Diebold, E., Kummerfeld, B.: Moocs: so many learners, so much potential. Technology 52(1), 49–67 (2013)
8.
go back to reference Kohonen, T.: Learning vector quantization. In: Self-Organizing Maps, pp. 175–189. Springer, Heidelberg (1995) Kohonen, T.: Learning vector quantization. In: Self-Organizing Maps, pp. 175–189. Springer, Heidelberg (1995)
9.
go back to reference Limongelli, C., Lombardi, M., Marani, A.: Towards the recommendation of resources in coursera. In: Micarelli, A., et al. (eds.) ITS 2016. LNCS, vol. 9684, p. 461. Springer, Heidelberg (2016) Limongelli, C., Lombardi, M., Marani, A.: Towards the recommendation of resources in coursera. In: Micarelli, A., et al. (eds.) ITS 2016. LNCS, vol. 9684, p. 461. Springer, Heidelberg (2016)
10.
go back to reference Limongelli, C., Lombardi, M., Marani, A., Sciarrone, F.: A teaching-style based social network for didactic building and sharing. In: Lane, H.,Chad, Yacef, K., Mostow, J., Pavlik, P. (eds.) AIED 2013. LNCS, vol. 7926, pp. 774–777. Springer, Heidelberg (2013). doi:10.1007/978-3-642-39112-5_110 CrossRef Limongelli, C., Lombardi, M., Marani, A., Sciarrone, F.: A teaching-style based social network for didactic building and sharing. In: Lane, H.,Chad, Yacef, K., Mostow, J., Pavlik, P. (eds.) AIED 2013. LNCS, vol. 7926, pp. 774–777. Springer, Heidelberg (2013). doi:10.​1007/​978-3-642-39112-5_​110 CrossRef
11.
go back to reference Limongelli, C., Lombardi, M., Marani, A., Sciarrone, F., Temperini, M.: A recommendation module to help teachers build courses through the moodle learning management system. In: New Review of Hypermedia and Multimedia, pp. 1–25 (2015) Limongelli, C., Lombardi, M., Marani, A., Sciarrone, F., Temperini, M.: A recommendation module to help teachers build courses through the moodle learning management system. In: New Review of Hypermedia and Multimedia, pp. 1–25 (2015)
12.
go back to reference Lombardi, M., Marani, A.: A comparative framework to evaluate recommender systems in technology enhanced learning: a case study. In: Lagunas, O.P., Alcántara, O.H., Figueroa, G.A. (eds.) MICAI 2015. LNCS, vol. 9414, pp. 155–170. Springer, Heidelberg (2015). doi:10.1007/978-3-319-27101-9_11 CrossRef Lombardi, M., Marani, A.: A comparative framework to evaluate recommender systems in technology enhanced learning: a case study. In: Lagunas, O.P., Alcántara, O.H., Figueroa, G.A. (eds.) MICAI 2015. LNCS, vol. 9414, pp. 155–170. Springer, Heidelberg (2015). doi:10.​1007/​978-3-319-27101-9_​11 CrossRef
13.
go back to reference Maulik, U., Bandyopadhyay, S.: Performance evaluation of some clustering algorithms and validity indices. IEEE Trans. Pattern Anal. Mach. Intell. 24(12), 1650–1654 (2002)CrossRef Maulik, U., Bandyopadhyay, S.: Performance evaluation of some clustering algorithms and validity indices. IEEE Trans. Pattern Anal. Mach. Intell. 24(12), 1650–1654 (2002)CrossRef
14.
go back to reference Porter, M.F.: An algorithm for suffix stripping. Program 14(3), 130–137 (1980)CrossRef Porter, M.F.: An algorithm for suffix stripping. Program 14(3), 130–137 (1980)CrossRef
15.
go back to reference Xu, R., Wunsch, D., et al.: Survey of clustering algorithms. IEEE Trans. Neural Netw. 16(3), 645–678 (2005)CrossRef Xu, R., Wunsch, D., et al.: Survey of clustering algorithms. IEEE Trans. Neural Netw. 16(3), 645–678 (2005)CrossRef
Metadata
Title
Towards a Characterization of Educational Material: An Analysis of Coursera Resources
Authors
Carlo De Medio
Fabio Gasparetti
Carla Limongelli
Matteo Lombardi
Alessandro Marani
Filippo Sciarrone
Marco Temperini
Copyright Year
2017
DOI
https://doi.org/10.1007/978-3-319-52836-6_58

Premium Partner