Smart e-Learning Systems with Big Data

• Autorzy: Caviglione L. , Coccoli M.

Identyfikatory

DOI

10.24425/123544

• Języki publikacji: EN

Abstrakty

EN

Nowadays, the Internet connects people, multimedia and physical objects leading to a new-wave of services. This includes learning applications, which require to manage huge and mixed volumes of information coming from Web and social media, smart-cities and Internet of Things nodes. Unfortunately, designing smart e-learning systems able to take advantage of such a complex technological space raises different challenges. In this perspective, this paper introduces a reference architecture for the development of future and big-data-capable e-learning platforms. Also, it showcases how data can be used to enrich the learning process.

Słowa kluczowe

EN

e-learning; Internet of things; smart city; big data

• Wydawca: Polish Academy of Sciences, Committee of Electronics and Telecommunication
• Czasopismo: International Journal of Electronics and Telecommunications
• Rocznik: 2018
• Tom: Vol. 64, No. 4
• Strony: 445--450
• Opis fizyczny: Bibliogr. 34 poz., rys.

Twórcy

autor

Caviglione L.

• National Research Council of Italy, Genoa, Italy

autor

Coccoli M.

• Department of Informatics, Bioengineering, Robotics and Systems Engineering (DIBRIS), University of Genoa, Genoa, Italy

Bibliografia

• [1] N. Contractor, “The Emergence of Multidimensional Networks”, Journal of Computer-Mediated Communication, Vol. 14, pp. 743 - 747, April 2009.
• [2] S. Manca, L. Caviglione, J. E. Raffaghelli, “Big data for Social Media Learning Analytics: Potentials and Challenges”, Journal of e-Learning and Knowledge Society, Vol. 12, No. 2, pp. 27 - 39, May 2016.
• [3] B, Kedzierska, J. Wnek-Gozdek, “Modern Didactics in Contemporary Education”, International Journal of Electronics and Telecommunications, Vol. 61, No.3, pp. 251-260, 2015.
• [4] The New Media Consortium, “Horizon Report - 2017 Higher Education Edition”, on-line: http://cdn.nmc.org/media/2017-nmc-horizonreport-he-EN.pdf [Last Accessed: Oct. 2017].
• [5] L. Cen, D. Ruta, J. Ng, “Big Education: Opportunities for Big Data Analytics”, IEEE International Conference on Digital Signal Processing, Singapore, pp. 502-506, July 2015.
• [6] S. B. Shum, R. Ferguson, “Social Learning Analytics”, Journal of Educational Technology & Society, Vol. 15, No. 3, pp. 3 - 26, July 2012.
• [7] A. Singh, “Mining of Social Media Data of University Students”, Education and Information Technologies, Vol. 22, No. 4, pp. 1515-1526, July 2017.
• [8] M. Coccoli, P. Maresca, L. Stanganelli, “The Role of Big Data and Cognitive Computing in the Learning Process”, Journal of Visual Languages & Computing, Vol. 38, pp. 97-103, Feb. 2017.
• [9] L. Caviglione, F. Davoli, “Peer-to-Peer Middleware for Bandwidth Allocation in Sensor Networks”, IEEE Communications Letters, Vol. 9, No. 3, pp. 285-287, March 2005.
• [10] M. Anshari, Y. Alas, L. S. Guan, “Developing Online Learning Resources: Big Data, Social Networks, and Cloud Computing to Support Pervasive Knowledge”, Education and Information Technologies, Vol. 6, No. 21, pp.1663-1677, 2016.
• [11] M. Coccoli, I. Torre, “Interacting with Annotated Objects in a Semantic Web of Things Application”, Journal of Visual Languages & Computing, Vol. 25, No, 6, pp. 1012-1020, Dec. 2014.
• [12] V. Mayer-Sch¨onberger, K. Cukier, “Learning with Big Data: the Future of Eeducation”, Houghton Mifflin Harcourt, 2014.
• [13] B. Logica, R. Magdalena, “Using Big Data in the Academic Environment”, Procedia Economics and Finance, Vol. 33, pp. 277-286, 2015.
• [14] B. Dietz-Uhler, J. E. Hurn, “Using Learning Analytics to Predict (and Improve) Student Success: a Faculty Perspective”, Journal of Interactive Online Learning, Vol. 12, No. 1, pp. 17-26, Spring 2013.
• [15] T. Yu, I. H. Jo, “Educational Technology Approach Toward Learning Analytics: Relationship Between Student Online Behaviour and Learning Performance in Higher Education”, in Proceedings of the Fourth International Conference on Learning Analytics and Knowledge, Indianapolis, IN, USA, March 2014 pp. 269-270.
• [16] M. El Mabrouk, S. Gaou, M. K. Rtili, “Towards an Intelligent Hybrid Recommendation System for e-learning Platforms Using Data Mining”, International Journal of Emerging Technologies in Learning, Vol. 12, No. 6, pp. 52-76, 2017.
• [17] S. V. Kolekar, R. M. Pai, M. M. M. Pai, “Prediction of Learner’s Profile Based on Learning Styles in Adaptive e-learning System”, International Journal of Emerging Technologies in Learning, Vol. 12, No. 06, pp. 31-51, 2017.
• [18] B. Habegger, O. Hasan, L. Brunie, N. Bennani, H. Kosch, E. Damiani, “Personalization vs. Privacy in Big Data Analysis”, International Journal of Big Data, pp. 25-35, 2014.
• [19] D. Dagger, A. O’Connor, S. Lawless, E. Walsh, V. P. Wade, “Serviceoriented e-Learning Platforms: from Monolithic Systems to Flexible Services”, IEEE Internet Computing, Vol. 11, No. 3, pp. 28-35, 2007.
• [20] Z. Zheng, J. Zhu, M. R. Lyu, “Service-generated Big Data and Big Data-as-a-Service: an Overview”, in Proceedings of the 2013 IEEE International Conference on Big Data, Santa Clara, CA, USA, Oct. 2013, pp. 403-410.
• [21] L. Berruti, L. Caviglione, F. Davoli, M. Polizzi, S. Vignola, S. Zappatore, “On the Integration of Telecommunication Measurement Devices within the Framework of an Instrumentation Grid”, in F. Davoli, N. Meyer, R. Pugliese, S. Zappatore (Ed.s), Grid Enabled Remote Instrumentation, Springer, pp. 283 - 300, 2009.
• [22] S. C. Kong, Y. Song, “An Experience of Personalized Learning hub Initiative Embedding BYOD for Reflective Engagement in Higher Education”, Computers & Education, Vol. 88, pp. 227-240, Oct. 2015.
• [23] D.-H. Shin, Y.-J. Shin, H. Choo, K. Beom, “Smartphones as Smart Pedagogical Tools: Implications for Smartphones as u-Learning Devices”, Computers in Human Behavior, Vol. 27, No. 6, pp. 2207-2214.
• [24] P. Ducange, R. Pecori, L. Sarti, M. Vecchio, “Educational Big Data Mining: how to Enhance Virtual Learning Environments”, in M. Grana, J. Lopez-Guede, O. Etxaniz, A. Herrero, H. Quintian, E. Corchado. (Eds.), Advances in Intelligent Systems and Computing, Vol. 527, pp. 681 - 690, Oct. 2016.
• [25] J. Miguel, S.Caball´e, F. Xhafa, J. Prieto, “A Massive data Processing Approach for Effective Trustworthiness in Online Learning Groups”, Concurrency and Computation: Practice and Experience, Vol. 27, No. 8, pp. 1988 - 2003, 2015.
• [26] C. Romero, S. Ventura, “Educational data Mining: a Review of the State of the art”, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), Vol. 40, No. 6, pp. 601-618, Nov. 2010.
• [27] L. Caviglione, “Introducing Emergent Technologies in Tactical and Disaster Recovery Networks”, International Journal of Communication Systems, Vol. 19, No.9, pp. 1045-1062, April 2006.
• [28] P. Chen, C.-Y. Zhang, “Data-intensive Applications, Challenges, Techniques and Technologies: a Survey on Big Data”, Information Sciences, Vol. 275, pp. 314-347, Aug. 2014.
• [29] M. Sharples, D. Spikol, “Mobile Learning”, in E. Duval, M. Sharples, R. Sutherland (Eds.), Technology Enhanced Learning, pp. 89-96, 2017.
• [30] L. Caviglione, M. Coccoli, A. Grosso, “A Framework for the Delivery of Contents in RFID-driven Smart Environments”, in Proc. of the IEEE International Conference on RFID-Technologies and Applications, Sitges, Spain, pp. 45-49, Sept. 2011.
• [31] A. del Blanco, A. Serrano, M. Freire, I. Martinez-Ortiz, B. Fernandez-Manjon, “E-Learning Standards and Learning Analytics: can data Collection be Improved by Using Standard Data Models?”, IEEE Global Engineering Education Conference, Berlin, Germany, pp. 1255-1261, March 2013.
• [32] G. Cardenas, R. E. Sanchez,“Security Challenges of Distributed elearning Systems”, in F. F. Ramos, V. Larios Rosillo, H. Unger, (Eds.), Advanced Distributed Systems, Lecture Notes in Computer Science Vol. 3563, pp. 538-544, Springer, 2005.
• [33] L. Caviglione, M. Coccoli, A. Merlo, “A Taxonomy-based Model of Security and Privacy in Online Social Networks”, International Journal of Computational Science and Engineering, Vol. 9, No. 4, pp. 325-338, 2014.
• [34] W. Mazurczyk, L. Caviglione, “Information Hiding as a Challenge for Malware Detection”, IEEE Security & Privacy, Vol. 13, No. 2, pp. 89-93, Mar.-Apr. 2015.

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).