Unlocking the potential of technology in education

• Authors: Czopek Agata , Pietrzak Piotr
• Languages of publication: EN

Abstracts

EN

Over the last years various attempts to legitimate technology in education have been observed. Beginning from the examples of simple digitization of schools books through „iPad school” initiative in the Netherlands till dedicated closed tablet solutions in the USA. At the end of 2014 first adaptive learning solutions were introduced. The Knewton's system using knowledge graph started giving recommendations for learners on what questions should they work next, provided learning analytics and instructions predicting future results. In 2015 cognitive computing and artificial intelligence systems that use natural language processing and machine learning entered the market. IBM started working on a comprehensive solution for personalized learning. The practical implementations of those system can not only improve students' outcomes but also help to close skills gaps and rise employability. This article presents solutions that are being unlocked right now showing examples of newly created value of technology in education.

Keywords

EN

technology in education; digitization; learning

• Publisher: Szkoła Główna Handlowa w Warszawie
• Journal: e-mentor
• Year: 2016
• Issue: 3 (65)
• Pages: 78-82

Contributors

author

Czopek Agata

• PhD, PMP is a consultant and researcher with more than 10 years of professional experience. Currently holds a position of Strategy & Development Associate at Young Digital Planet (company that delivers educational solutions to over 45 countries). She divides her time between research initiatives in the field of technology implementation in education, consultancy for country wide projects (Saudi Arabia; UAE; South Africa) and managing strategic partnerships with tech giants (Microsoft, IBM, Intel). Agata is helping organizations to enhance efficiency through professional project management, program management and corporate governance. Also a speaker (Project Management Days Romania, OPPI New York City, AgilebyExample Light Warsaw, IGEP Paris, Wolves Summit Gdynia, Frankfurt Book Fair).

author

Pietrzak Piotr

• Chief Technology Officer, IBM Poland and the Baltics has 17 years of experience in the IT industry. Piotr specializes in enterprise digital transformation projects, business model optimisation, incubation of innovative projects and their commercialization. He is responsible for collaboration with VC/PE investment firms, incubators and accelerators. On daily basis engaged in IBM R&D works. In his current role as a CTO in IBM responsible for development of the cloud and cognitive computing market in Poland. Author of many industry specific and business publications. Member of the Academy of Technology and CAS Advisory Board at Technical University of Gdansk.

References

• Bloom B.S., The 2 Sigma Problem. The Search for Methods of Group Instruction as Effective as One-to-One Tutoring, „Educational Researcher” 1984, Vol. 13, No. 6, pp. 4-16.
• Doignon J.P., Falmagne J.C., Knowledge Spaces, Springer 1999.
• Evens M.W., Michaels J., One-on-one Tutoring by Humans and Computers, Lawrence Erlbaum, 2006.
• Ferrucci D., et al., Building Watson: An Overview of the DeepQA Project, „AI Magazine” 2010, Fall, http://www.aaai.org/Magazine/Watson/watson.php.
• Frase K., IBM Education Solutions on the Cloud, Creating success for students, institutions and economies, 2014.
• Gertner A.S., A Coached Problem Solving Environment for Physics, [in:] Gauthier G., Frasson C., VanLehn K. (eds.), Intelligent Tutoring Systems, Springer-Verlag, 2000, pp. 133-142, >http://dx.doi.org/10.1007/3-540-45108-0_17.
• Graesser A.C, Wiemer-Hastings K., Wiemer-Hastings P., Kreuz R., AutoTutor: A Simulation of a Human Tutor, „Cognitive Systems Research” 1999, Vol. 1, No. 1, pp. 35-51, http://dx.doi.org/10.1016/S1389-0417(99)00005-4.
• Graesser A.C., Conley M.W., Olney A., Intelligent Tutoring Systems, [in:] K. Harris, et al. (eds.), APA educational psychology handbook, Vol. 3: Application to learning and teaching, American Psychological Association, Washington DC 2012, pp. 451-473, http://dx.doi.org/10.1037/13275-018.
• Self J.A., Bypassing the Intractable Problem of Student Modelling. Intelligent Tutoring Systems: At the Crossroads of Artificial Intelligence and Education, Lancaster University, Lancaster 1990.
• Sherwood S.G., Educational Uses of the PLATO Computer Systems, „Science” 1976, Vol. 192, No. 4237, pp. 344-352, http://dx.doi.org/10.1126/science.769165.
• Silvi J., How can we tackle youth unemployment in the Middle East?, World Economic Forum Global Agenda, 2015, https://agenda.weforum.org/2015/11/how-can-we-tackle-youth-unemployment-in-the-middle-east.
• The Talent Shortage Continues: How the Ever Changing Role of HR Can Bridge the Gap, 2014, https://www.manpower.de/fileadmin/manpower.de/Download/2014_Talent_Shortage_WP_US2.pdf.
• This is Watson, „IBM Journal of Research and Development” 2012, No. 3.4, http://ieeexplore.ieee.org/xpl/tocresult.jsp?reload=true&isnumber=6177717&punumber=5288520.
• VanLehn K., The Relative Effectiveness of Human Tutoring, Intelligent Tutoring Systems, and Other Tutoring Systems, „Educational Psychologist” 2011, Vol. 46, No. 4, pp. 197-221, http://dx.doi.org/10.1080/00461520.2011.611369.
• Wilson K., Nichols Zack, The Knewton Platform. A General-Purpose Adaptive Learning Infrastructure, Knewton, 2015.