Articles - Special Issue

Learning Analytics: opportunities for schools


Abstract


Evaluating learning experiences that take place in contexts where interactions are mediated by technology is a formidable challenge and one that must be addressed with suitable approaches. In the field of Learning Analytics, techniques have recently been developed that provide the means to maximize learning experiences. These allow teachers to intervene in a timely manner, managing the whole process or individual students in a personalized way, towards more effective learning process. Although Learning Analytics techniques have been developed primarily for online higher education, this article highlights the potential they offer for school contexts. Here, technologies are increasingly being employed to support formal and informal learning experiences based on the use of mobile devices, serious games and social networks. Consequently, more and more learning data are being produced, opening the way for analysis based on Learning Analytics techniques that can provide important insights for improving the learning experience.

Keywords

Educational Technology; IT; Learning Analytics; Social Learning Analytics; Learning assessment; Personalized learning; Technology Enhanced Learning (TEL)

Full Text:

PDF (Italiano)


DOI: http://dx.doi.org/10.17471/2499-4324/185

References


Arnab, S. (2014, August 25). GALA report on Learning Analytics for Serious Games [Web log post].Retrieved from http://seriousgamessociety. org/index.php/2014-07-11-14-15-51/explore/ 134-media/794-gala-report-on-learninganalytics- for-serious-games

Bakharia, A., & Dawson, S. (2011). SNAPP: A Bird’s-Eye View of Temporal Participant Interaction. Proceedings of the Learning Analytics and Knowledge, Canada, (pp. 168-173). doi: 10.1145/2090116.2090144

Clow, D. (2013). MOOCs and the funnel of participation. In D., Suthers, K., Verbert, E., Duval, & X., Ochoa. Proceedings of the Third International Conference on Learning Analytics and Knowledge, (LAK 2013), 8-12 April 2013, Leuven, BE (pp. 185-189). New York, NY, USA: ACM.

Coffrin, C., Corrin, L., de Barba, P., & Kennedy, G. (2014). Visualizing patterns of student engagement and performance in MOOCs. Proceedings of the Fourth International Conference on Learning Analytics and Knowledge, USA (pp. 83-92). doi: 10.1145/2567574.2567586

Downes, S. (2010). New technology supporting informal learning. Journal of Emerging Technologies in Web Intelligence, 2(1), 27-33.

Duval, E. (2011). Attention please! learning analytics for visualization and recommendation. Proceedings of the 1st International Conference on Learning Analytics and Knowledge, Canada, (pp. 9-17). doi: 10.1145/2090116.2090118

Fulantelli, G., Taibi D., & Arrigo M. (in press). A framework to support educational decision making in mobile learning. Computers in Human Behavior. doi: http://dx.doi.org/10.1016/j.chb.2014.05.045

Johnson, L., Adams Becker, S., Estrada, V., & Freeman, A. (2014). Horizon Report: 2014 Higher Education. Austin, TX, USA: The New Media Consortium. Johnson, L., Adams Becker, S., Estrada, V., & Freeman, A. (2014b). NMC Horizon Report: 2014 K- 12 Edition. Austin, TX, USA: The New Media Consortium.

Johnson, L., Adams Becker, S., Estrada, V., & Martín, S. (2013). Technology Outlook for STEM+ Education 2013 - 2018: An NMC Horizon Project Sector Analysis. Austin, TX, USA: The New Media Consortium.

Johnson, L., Adams Becker, S., & Estrada, V. (2012). Technology Outlook for STEM+ Education 2012 - 2017: An NMC Horizon Project Sector Analysis. Austin, TX, USA: The New Media Consortium.

Kobsa, A. (1990). User Modeling in Dialog Systems: Potentials and Hazards. AI & Society. 4(3), 214-240.

Kobsa, A. (2007). Privacy-Enhanced Personalization. Communications of the ACM, 50(8), 24-33.

Littlejohn, A. (2013). Understanding massive open online courses. Retrieved from: http:// cemca.org.in/ckfinder/userfiles/files/EdTech%2 0Notes%202_Littlejohn_final_1June2013.pdf

Pea, R. (2014). The Learning Analytics Workgroup: A Report on Building the Field of Learning Analytics for Personalized Learning at Scale. Retrieved from: http://lytics.stanford.edu/law-report/

Sefton-Green, J. (2004). Literature review in informal learning with technology outside school. Bristol, UK: Futurelab.

Selwyn, N. (2012). I Social Media nell'educazione formale e informale tra potenzialità e realtà. TD Tecnologie Didattiche, 20(1), 4-10.

Serrano-Laguna, Á., & Fernández-Manjón, B. (2014). Applying learning analytics to simplify serious games deployment in the classroom. In Global Engineering Education Conference (EDUCON), 2014 IEEE (pp. 872-877). IEEE. doi: 10.1109/EDUCON.2014.6826199

Serrano-Laguna Á., Torrente J., Moreno-Ger P., & Fernández-Manjón B. (2014). Application of Learning Analytics in educational videogames. Entertainment Computing. 5(4), 313-322. doi: http://dx.doi.org/10.1016/j.entcom. 2014.02.003

Siemens, G., & Long, P. (2011). Penetrating the fog: Analytics in learning and education. Educause Review, 46(5), 30-32.

Solomon, G., & Schrum, L. (2007). Web 2.0: New tools, new schools. Washington, D.C., USA: ISTE.

Taibi, D. and Dietze, S. (2013), Fostering Analytics on Learning Analytics Research: the LAK Dataset. In: CEUR WS Proceedings Vol. 974, Proceedings of the LAK Data Challenge, held at LAK2013 - 3rd International Conference on Learning Analytics and Knowledge (Leuven, BE, April 2013).


Article Metrics

Metrics Loading ...

Metrics powered by PLOS ALM

Refbacks

  • There are currently no refbacks.




Copyright (c) 2015 TD Tecnologie Didattiche

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Italian Journal of Educational Technology (IJET) | ISSN (print) 2532-4632 | ISSN (online) 2532-7720