From Big Data to Learning Analytics for a personalized learning experience

Agnihotri, L., & Ott, A. (2014, July). Building a Student At-Risk Model: An End-to-End Perspective From User to Data Scientist. In Proceedings of the 7th International Conference on Educational Data Mining (pp. 209-212).Search in Google Scholar

Aljohani, N. R., & Davis, H. C. (2013). Learning analytics and formative assessment to provide immediate detailed feedback using a student centered mobile dashboard.10.1109/NGMAST.2013.54Search in Google Scholar

Arnold, K. E., & Pistilli, M. D. (2012). Course signals at Purdue: Using learning analytics to increase student success. In Proceedings of the 2nd international conference on learning analytics and knowledge (pp. 267-270). ACM.10.1145/2330601.2330666Search in Google Scholar

Arnold, K. E., Tanes, Z., & King, A. S. (2010). Administrative perceptions of data-mining software Signals: Promoting student success and retention. The Journal of Academic Administration in Higher Education, 6(2), 29-39. Assessment, King’s College, London.Search in Google Scholar

Baker, B. (2007). A conceptual framework for making knowledge actionable through capital formation. (Doctoral dissertation). University of Maryland University College, Maryland. Retrieved from ABI/INFORM Global. (Publication No. AAT 3254328).Search in Google Scholar

Black P., Wiliam D. (1998), Inside the black box: Raising standards through classroom assessment. NferNelson: London.Search in Google Scholar

Campbell, J. P., DeBlois, P. B., & Oblinger, D. G. (2007). Academic Analytics: A New Tool for a New Era. Educause Review, 42(4), 40-57.Search in Google Scholar

Cauley, K. M., & McMillan, J. H. (2010). Formative assessment techniques to support student motivation and achievement. The Clearing House: A Journal of Educational Strategies, Issues and Ideas, 83(1), 1-6.10.1080/00098650903267784Search in Google Scholar

Caulfield, M. (2013). Purdue Course Signals data issue explainer. Retrieved from https://mfeldstein.com/purdue-course-signals-data-issue-explainer/Search in Google Scholar

Cordova, D. I., & Lepper, M. R. (1996). Intrinsic motivation and the process of learning: Beneficial effects of contextualization, personalization, and choice. Journal of educational psychology, 88(4), 715.10.1037/0022-0663.88.4.715Search in Google Scholar

de Waal, P. (2017). Learning Analytics: i sistemi dinamici di supporto alla decisione per il miglioramento continuo dei processi di insegnamento e apprendimento. Formazione & Insegnamento. Rivista internazionale di Scienze dell’educazione e della formazione, 15(2), 43-52.Search in Google Scholar

Ferguson, R. (2014). Learning Analytics: fattori trainanti, sviluppi e sfide. TD tecnologie didattiche, 22(3), 138-147.Search in Google Scholar

Fulantelli, G., & Taibi, D. (2015). Editoriale. TD Tecnologie Didattiche, 22 (3), 130-131.Search in Google Scholar

Goos, M., Galbraith, P., & Renshaw, P. (2002). Socially mediated metacognition: Creating collaborative zones of proximal development in small group problem solving. Educational studies in Mathematics, 49(2), 193-223.10.1023/A:1016209010120Search in Google Scholar

Gorunescu, F. (2011). Data Mining: Concepts, models and techniques (Vol. 12). Springer Science & Business Media.Search in Google Scholar

Ifenthaler, D., & Widanapathirana, C. (2014). Development and validation of a learning analytics framework: Two case studies using support vector machines. Technology, Knowledge and Learning, 19(1-2), 221-240.10.1007/s10758-014-9226-4Search in Google Scholar

Ifenthaler, D. (2015). Learning Analytics: Benefits and challenges for higher education. In Food for thought, the academic eye. The Council on Business & Society. https://councilcommunity.com/2015/05/23/learning-analytics-benefits-and-challenges-for-higher-education/Search in Google Scholar

Johnson, L., Smith, R., Willis, H., Levine, A., and Haywood, K. (2011). The 2011 Horizon Report.Search in Google Scholar

LAK11: 1st International Conference on Learning Analytics and Knowledge, Retrieved from https://tekri.athabascau.ca/analytics/ (accessed August 2018)Search in Google Scholar

Limone, P. (2012a). Ambienti di apprendimento e progettazione didattica. Proposte per un sistema educativo transmediale (pp. 1-176). Roma: Carocci.Search in Google Scholar

Limone, P. (2012b). Valutare l’apprendimento on-line. Esperienze di formazione continua dopo la laurea (pp. 1-102). Bari: Progedit.Search in Google Scholar

Long, P. D., & Siemens, G. (2014). Penetrare la nebbia: tecniche di analisi per l’apprendimento. TD Tecnologie Didattiche, 22(3), 132-137.Search in Google Scholar

Lonn, S., Aguilar, S. J., & Teasley, S. D. (2015). Investigating student motivation in the context of a learning analytics intervention during a summer bridge program. Computers in Human Behavior, 47, 90-97.10.1016/j.chb.2014.07.013Search in Google Scholar

Loperfido, F. F., Dipace, A., & Scarinci, A. (2018. Qualitative learning analytics to detect students’ emotional topography on EduOpen. Research on Education and Media, 10 (1), 49-60.10.1515/rem-2018-0007Search in Google Scholar

Lotti, A. (2018). Problem-Based Learning: Apprendere per problemi a scuola: guida al PBL per l’insegnante. Milano: Franco Angeli.Search in Google Scholar

Kingston, N., & Nash, B. (2011). Formative assessment: A meta analysis and a call for research. Educational measurement: Issues and practice, 30(4), 28-37.10.1111/j.1745-3992.2011.00220.xSearch in Google Scholar

Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Hung Byers, A. (2011). Big Data: The Next Frontier for Innovation, Competition and Productivity. Washington: McKinsey Global Institute.Search in Google Scholar

New Media Consortium. (2012) NMC Horizon report. Higher Education Edition. Austin, Texas. http://www.nmc.org/publications/horizon-report-2012-higher-ed-editionSearch in Google Scholar

Papamitsiou, Z., & Economides, A. (2014). Learning Analytics and Educational Data Mining in Practice: A Systematic Literature Review of Empirical Evidence. Educational Technology & Society, 17(4), 49–4. Perspectives on Curriculum Evaluation, Rand McNally, Chicago.Search in Google Scholar

Park, Y., & Jo, I. H. (2015). Development of the Learning Analytics Dashboard to Support Students’ Learning Performance. J. UCS, 21(1), 110-133.Search in Google Scholar

Quagini, M. (2015). SMARTechnology. Crm & Digital Innovation per creare valore in azienda: Crm & Digital Innovation per creare valore in azienda. Franco Angeli.Search in Google Scholar

Sclater, N. (2017). Learning analytics explained. New York: Routledge.10.4324/9781315679563Search in Google Scholar

Scriven M. (1967), The methodology of evaluation. Lafayette, Ind: Purdue University.Search in Google Scholar

Shute, V. J. (2008). Focus on formative feedback. Review of educational research, 78(1), 153-189.10.3102/0034654307313795Search in Google Scholar

Siemens, G. (2010). What Are Learning Analytics?. [web log post] Elearnspace.org. Retrieved from http://www.elearnspace.org/Search in Google Scholar

Siemens, G., & d Baker, R. S. (2012, April). Learning analytics and educational data mining: towards communication and collaboration. In Proceedings of the 2nd international conference on learning analytics and knowledge (pp. 252-254). ACM.10.1145/2330601.2330661Search in Google Scholar

Siemens, G., & Long, P. (2011). Penetrating the fog: Analytics in learning and education. Educause review, 46(5), 30.Search in Google Scholar

Straumsheim, C. (2013). Mixed signals. In Inside higher ed. Retrieved from https://www.insidehighered.com/news/2013/11/06/researchers-cast-doubt-about-early-warning-systems-effect-retentionSearch in Google Scholar

Tanes, Z., Arnold, K. E., King, A. S., & Remnet, M. A. (2011). Using Signals for appropriate feedback: Perceptions and practices. Computers & Education, 57(4), 2414-2422.10.1016/j.compedu.2011.05.016Search in Google Scholar

Vygotsky, L. (1987). Zone of proximal development. Mind in society: The development of higher psychological processes, 5291, 157.Search in Google Scholar