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T-MAESTRO and its authoring tool: using adaptation to integrate entertainment into personalized t-learning

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Abstract

Interactive Digital TV opens new learning possibilities where new forms of education are needed. On the one hand, the combination of education and entertainment is essential to boost the participation of viewers in TV learning (t-learning), overcoming their typical passiveness. On the other hand, researchers broadly agree that in order to prevent the learner from abandoning the learning experience, it is necessary to take into account his/her particular needs and preferences by means of a personalized experience. Bearing this in mind, this paper introduces a new approach to the conception of personalized t-learning: edutainment and entercation experiences. These experiences combine TV programs and learning contents in a personalized way, with the aim of using the playful nature of TV to make learning more attractive and to engage TV viewers in learning. This paper brings together our work in constructing edutainment/entercation experiences by relating TV and learning contents. Taking personalization one step further, we propose the adaptation of learning contents by defining A-SCORM (Adaptive-SCORM), an extension of the ADL SCORM standard. Over and above the adaptive add-ons, this paper focuses on two fundamental entities for the proposal: (1) an Intelligent Tutoring System, called T-MAESTRO, which constructs the t-learning experiences by applying semantic knowledge about the t-learners; and (2) the authoring tool which allow teachers to create adaptive courses with a minimal technical background.

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Notes

  1. http://www.internetworldstats.com.

  2. Inside the term edutainment coined by Heyman, we distinguish two different forms of integrating education and entertainment: edutainment and entercation.

  3. In e-learning, the term LMS refers to the system designed to deliver, track, report on and manage learning content, learner progress and learner interactions.

  4. An Intelligent Tutoring System (ITS) is a computer system that provides direct customized instruction to students, without the intervention of human beings.

  5. Our use of the term stereotype obviously lacks the negative connotation present in general usage.

  6. A SCORM-conformant LMS is the one that adheres to the requirements exposed in [4]. There are three categories of conformance for LMSs, corresponding to the SCORM three main topics: RTE, CAM and SN. A SCORM-conformant LMS should be able to import Content Aggregation Packages using PIF format, launch a learning resource (SCO or Asset), implement SCORM RTE API and data model, implement SCORM navigation data model, adhere to the Content Aggregation Model and implement SCORM sequencing behaviors. If an LMS is derived from the standard but has not been given a conformance test, it is said to be compliant.

  7. Following the SCORM Content Aggregation Model (CAM) recommendations, t-maestro_idtv_det_uvigo_es is used as the namespace, like we have done for the creation of new adaptation parameters.

  8. The reader can watch some video demos about the authoring tools presented in this article and adaptive courses behavior in an IDTV receiver at http://idtv.det.uvigo.es/proyectos/t-learning/en/index.html, section Demos.

  9. Complete ontology available at http://tvdi.det.uvigo.es/proyectos/t-learning/SCORM_ontology/index.html.

  10. Content-based methods and collaborative filtering are the recommending strategies that have achieve outstanding popularity. The former recommends to users contents similar to those they have watched in the past, whereas the latter suggests the users contens appealing to viewers with similar preferences.

  11. Passepartout website: http://www.citi.tudor.lu/passepartout.

  12. In http://tvdi.det.uvigo.es/proyectos/t-learning/en/demos.html there are some videos showing the current state of the system.

  13. http://www.vanderwal.net/random/entrysel.php?blog=1750.

References

  1. Aarreniemi-Jokipelto P (2004) Experiences with an interactive learning environment in digital TV. In: Proceedings of the 4th IEEE international conference on advanced learning technologies (ICALT’04)

  2. Abdullah NA, Davis H (2003) Is simple sequencing simple adaptive hypermedia? In: Proceedings of the fourteenth ACM conference on hypertext and hypermedia. ACM Press, Nottingham, UK, pp 172–173

    Chapter  Google Scholar 

  3. Advanced Distributed Learning (ADL) (2006) Sharable Content Object Reference Model (SCORM®) 2004, 3rd edn

  4. Advanced Distributed Learning (ADL) (2006) Sharable Content Object Reference Model (SCORM®) 2004, 3rd edn, Conformance Requirements Version 1.0

  5. Advanced Distributed Learning (ADL) (2006) Sharable Content Object Reference Model (SCORM®) 2004, 3rd edn, Content Aggregation Model Version 1.0

  6. Advanced Distributed Learning (ADL) (2006) Sharable Content Object Reference Model (SCORM®) 2004, 3rd edn, Run-Time Environment Version 1.0

  7. Advanced Distributed Learning (ADL) (2006) Sharable Content Object Reference Model (SCORM®) 2004, 3rd edn, Sequencing and Navigation Version 1.0

  8. Blackmon W, Brooks J, Roberts E, Rehak D (2004) The Overlap and Barriers between SCORM, IMS Simple Sequencing, and Adaptive Sequencing. In: Adaptive hypermedia conference (AH’04), Eindhoven (The Netherlands)

  9. Blanco Fernández Y, Pazos Arias JJ, Gil Solla A, Ramos Cabrer M, López Nores M, García Duque J, Fernández Vilas A, Díaz Redondo RP, Bermejo Muñoz J (2007) AVATAR: enhancing the personalized television by semantic inference. Int J Pattern Recogn Artif Intell, Special issue on Personalization Techniques for Recommender Systems and Intelligent User Interfaces 21(2):397–422

    Google Scholar 

  10. Blanco Fernández Y, Pazos Arias JJ, Gil Solla A, Ramos Cabrer M, López Nores M, García Duque J, Fernández Vilas A, Díaz Redondo RP, Bermejo Muñoz J (2008) An MHP framework to provide intelligent personalized recommendations about digital TV contents. Softw Pract Exp (in press)

  11. Blanco Fernández Y, Pazos Arias JJ, López Nores M, Gil Solla A, Ramos Cabrer M (2006) AVATAR: an improved solution for personalized TV based on semantic inference. IEEE Trans Consum Electron 52(1):223–231, Feb

    Article  Google Scholar 

  12. Brusilovsky P (1996) Methods and techniques of adaptive hypermedia. User Model User Adapt Interact (Special issue on adaptive hypertext and hypermedia) 6(2–3):87–129

    Google Scholar 

  13. Buckingham D, Scanlon M (2002) Education, entertainment and learning in the home. Open University Press

  14. Consortium D (2004) DVB Framing structure, channel coding and modulation for digital terrestrial television. In: European Standard ETSI EN 300 744 V1.5.1

  15. Dagger D, Wade V, Conlan O (2003) Towards “anytime, anywhere” learning: the role and realization of dynamic terminal personalization in adaptive eLearning. In: World conference on educational multimedia, hypermedia and telecommunications (Ed-Media 2003), Hawaii (USA)

  16. Damásio MJ, Quico C (2004) T-Learning and interactive television edutainment: the Portuguese case study. In: Proc of ED-MEDIA 2004

  17. DVB Consortium (2003) Multimedia home platform specification 1.2.1. In: European Standard ETSI TS 102 812 V1.2.1

  18. Fallahkhair S, Pemberton L, Masthoff J ( 2004) A dual device scenario for informal language learning: interactive television meets the mobile phone. In: Proc of the 4th IEEE international conference on advanced learning technologies (ICALT’04), August 2004, pp 16–20

  19. Golder SA, Huberman BA (2006) The structure of collaborative tagging systems. J Inf Sci 32(2):198–208

    Article  Google Scholar 

  20. Goren-Bar D, Glinansky O (2002) Family stereotyping—a model to filter TV programs for multiple viewers. In: The 2nd workshop on personalization in future TV (TV’02). Malaga (Spain)

  21. IEEE Learning Technology Standards Committee (LTSC) (2002) Learning object metadata. IEEE Standard 1484.12.1

  22. International Standard ISO/IEC 15938-5 (2003) Moving Pictures Experts Group. Information Technology Multimedia Content Description Interface. Part 5: Multimedia Description Schemes

  23. Kraan W (2003) The dynamic appearance model and implementing scorm 1.3. http://zope.cetis.ac.uk/content/20030713202337

  24. Lackner TM (2000) Enhancing children’s educational television with design rationales and justifications. PhD thesis, Massachusetts Institute of Technology. Los Angeles

  25. López Nores M, Fernández Vilas A, Díaz Redondo RP, Gil Solla A, Pazos Arias JJ, Ramos Cabrer M, García Duque J (2003) A Mixed XML-JavaBeans approach to developing T-learning applications for the multimedia home platform. In: Springer-Verlag (ed), Interactive Multimedia on Next Generative Networks: Proc of Multimedia Interactiva Protocols and Systems (MIPS), LNCS, pp 376–387

  26. Luckin R, Du Boulay B (2001) Imbedding AIED in ie-TV through broadband user modelling (BbUM). In: 10th international conference on artificial intelligence in education (AIEd2001). San Antonio, Texas (USA)

  27. Luckin R, Du Boulay B (2003) Lines of desire: the challenges of interactive educational TV. In: 11th international conference on artificial intelligence in education (AIEd2003). Sydney, Australia

  28. Lytras M, Lougos C, Chozos P, Pouloudi A (2002) Interactive television and e-learning convergence: examining the potential of t-learning. In: Proceedings of the European conference on e-learning. Uxbridge, UK

  29. Masthoff J (2002) Modeling a groupof television viewers. In: Workshop future TV: adaptive instriction in your living room. San Sebastián (Spain), pp 34–41

  30. Masthoff J, Pemberton L (2005) Adaptive hypermedia for personalized TV. In: Adaptable and adaptive hypermedia systems, IDEA group publishing, pp 246–263

  31. McTearl MF (1993) User modelling for adaptive computer systems: a survey of recent developments. J Artif Intel Rev 7(3-4):157–184

    Article  Google Scholar 

  32. Middleton SE (2003) Capturing knowledge of user preferences with recommender systems. PhD thesis, University of Southampton

  33. Mödritscher F, García Barros V (2004) Enhancement of SCORM to support adaptive e-learning within the scope of the research project AdeLE. In: Proceedings of the ELEARN 2004 conference. Washington, USA

  34. Mudge R (1999) Interactive television. In: Gerbarg D (ed) The economics, technology and content of digital TV. Kluwer Academic Publishers, pp 125–144

  35. Niles I, Pease A (2001) Towards a standard upper ontology. In: Welty C, Smith B (eds) Proc of FOIS-2001, USA

  36. Niwa S, Doi T, Honiden S (2006) Web page recommender system based on Folksonomy mining for ITNG’06 submissions. In: Society IC (ed) Third international conference on information technology: new generations (ITNG’06). Washington, DC (USA), pp 388–393

  37. Paramythis A, Loidl-Reisinger S (2004) Adaptive learning environments and e-Learinng standards. Electronic Journal of e-Learning 2(1):181–194

    Google Scholar 

  38. Pazos Arias JJ, López Nores M, García Duque J, Gil Solla A, Ramos Cabrer M, Blanco Fernández Y, Díaz Redondo RP, Fernández Vilas A (2006) ATLAS: a framework to provide multiuser and distributed t-learning services over MHP. Softw Pract Exp 36(8):845–869, July

    Article  Google Scholar 

  39. Pemberton L (2002) The potential of Interactive TElevision for Delivering Individualised Language Learning. In: Workshop future TV: adaptive instruction in your living room. San Sebastián (Spain), pp 10–14

  40. pjb Associates (2003) A study into TV-based interactive learning to the home. http://www.pjb.co.uk/t-learning

  41. Prata A, Guimarães N, Kommers P (2004) iTV enhanced system for generating multi-device personalized online learning environments. In: 4th AH2004 workshop on personalization in Future TV. Eindhoven (The Netherlands)

  42. Project R (2006) Reusable eLearning object authoring & delivery. http://www.reload.ac.uk/

  43. Qin J (2001) The educationl resource ontology (EduOnto). http://web.syr.edu/~jqin/eduonto/eduonto.html

  44. Qin J, Hernández N (2004) Ontological representation of learning objects: building interoperable vocabulary and structures. In ACM Press (ed) Proceedings of world wide web (WWW2004). New York, pp 348–349

  45. Rey-López M, Díaz-Redondo RP, Fernández-Vilas A, Pazos-Arias JJ (2006) Entercation experiences: engaging viewers in education through tv programs. In: 4th European conference on interactive television (EuroITV 2006). Athens, Greece, May 2006

  46. Rey-López M, Fernández-Vilas A, Díaz-Redondo RP, Pazos-Arias JJ, Bermejo-Muñoz J (2006) Extending scorm to create adaptive courses. In: Verlag S (ed) First European conference on technology enhanced learning (EC-TEL 2006). Lecture Notes in Computer Science, Crete, Greece, October 2006

  47. Sampson D, Karagiannidis C (2002) Re-using Adaptive Educational e-Content: the KOD VLP. In: Proc of the international conference on computers in education (ICCE’02). Auckland, New Zealand

  48. Santos JM, Anido L, Llamas M (2003) Aplicabilidad de los estándares de e-learning en los sistemas de aprendizaje adaptativos. In:III Congreso Iberoamericano de Telemática (CITA’2003). Montevideo, Uruguay

  49. Szomszor M, Cattuto C, Alani H, O’Hara K, Baldassarri A, Loreto V, Servedio VD (2007) Folksonomies, the Semantic Web, and Movie Recommendation. In: 4th European semantic web conference, bridging the gap between semantic web and web 2.0. Innsbruck (Austria)

  50. The TV-Anytime Forum (2004) Broadcast and on-line services: search, select and rightful use of content on personal storage systems. European Standard ETSI TS 102 822

  51. Wallace M, Stefanou M, Karpouzis K, Kollias S (2003) Towards supporting the teaching of history using an intelligent information system that relies on the electronic road metaphor. In: 3rd IEEE international conference on advanced learning technologies (ICALT 2003). Athens (Greece)

  52. Weber G, Kuhl H-C, Weibelzahl S (2001) Developing adaptive internet based courses with the authoring system netcoach. In: Third workshop on adaptive hypertext and hypermedia. Sonthofen (Germany), pp 35–48

  53. World Wide Web Consortium (W3C) (2004) Web Ontology Language (OWL). http://www.w3.org/2004/OWL/

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Authors and Affiliations

  1. Department of Telematic Engineering, University of Vigo, Vigo, Spain

    Marta Rey-López, Rebeca P. Díaz-Redondo, Ana Fernández-Vilas, José J. Pazos-Arias, Martín López-Nores, Jorge García-Duque, Alberto Gil-Solla & Manuel Ramos-Cabrer

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  1. Marta Rey-López
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  2. Rebeca P. Díaz-Redondo
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  3. Ana Fernández-Vilas
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Correspondence to Marta Rey-López.

Additional information

This work has been funded by the Ministerio de Educación y Ciencia (Gobierno de España) research project TSI2007-61599, by the Consellería de Educación e Ordenación Universitaria (Xunta de Galicia) incentives file 2007/000016-0, and by the Programa de Promoción Xeral da Investigación de Consellería de Innovación, Industria e Comercio (Xunta de Galicia) research project PGIDIT05PXIC32204PN.

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Rey-López, M., Díaz-Redondo, R.P., Fernández-Vilas, A. et al. T-MAESTRO and its authoring tool: using adaptation to integrate entertainment into personalized t-learning. Multimed Tools Appl 40, 409–451 (2008). https://doi.org/10.1007/s11042-008-0213-4

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