Challenge and Ethical Aspects of technological use in Rwanda Basic Education
DOI:
https://doi.org/10.53819/81018102t5143Abstract
The implication of artificial intelligence in education brought significant improvement to traditional models of teaching and learning processes. This paper was aiming at bringing to the right prospects, challenges and ethical aspects of technological use in Rwandan basic education. Purposive non probability sampling technique was used to select study participants. Descriptive statistics and thematic approach were used to analyze collected quantitative and qualitative data. Effective creation and implementation of technological with various adaptive learning platforms (Liushuo in China, NLP in USA, PAM in Germany, Education Technology company Greekie in Brazil and M-shule in Kenya), Advanced data analytic platforms, the introduction of technological use as major course in universities, and Investment for technological use research were established as prospects of technological use at the level of 26.80%, 24.10%, 26%, and 23.10% respectively. Besides, other potential prospects like multi-source of data analysis and audio-Visio teaching and learning materials were revealed as key prospects of technological use. Fragile technological infrastructure, inadequate government expenditure in education, achievement gap in education, resistance to implement technological use and unprepared teacher for technological use implementation were found as challenges of technological use at 85%, 75%, 65%, 60%, 40% respectively. In addition, curriculum transition, culture and religion of some countries, resistance to change mindset were suggested as other challenges of technological use. Cultural integration; accountability; fairness, equity and affordability; security, and privacy were found out as the main ethical aspects of technological use at 33.3%, 28.6%, 14.3%, 14.3% 9.5% respectively. Increasingly Humanity, singularity, authentication and profitability, personal interests’ investment, humanitarianism, and solitary were suggested as ethical aspects of technological use. The paper recommends that technological use theorists carefully mitigate the impacts of technological use on humans.
Keywords: Technological use, ethical aspect and technological challenges
References
Andama, S. (2014). Promoting digital literacy in African education: ICT innovation in a Ugandan Primary teacher college. The University of British Columbia: Vancouver.
Campus France (2018). Intelligence artificielle: un plan national à 1,5 milliard d‟euros‟. Available at: https://www.campusfrance.org/fr/intelligence-artificielleplan-macron-Aifor-humanity.
China Daily (2018). „China Launches First University Program to Train International AI Talents‟. Available at: http://www.chinadaily.com.
Conroy, M. & Rothstein, R. (2013, January 15). International test show achievement gaps in all countries, with big gains for U.S. disadvantaged students. Retrieved from http://www.epi.org.
Dashtestani, R. (2014). Exploring English as a foreign language (EFL) teacher trainer’ perspective on challenges to promoting computer literacy of EFL teachers. The JALT CALL Journal, 10(2), 139-151. Government of the People. https://doi.org/10.29140/jaltcall.v10n2.172
Republic of China (2017). Next Generation Artificial Intelligence Plan. Government of the Republic of Korea (2016). Mid- to Long-Term Master Plan in Preparation for the Intelligent Information Society: Managing the Fourth Industrial Revolution.
Hadfield-Menell, D., McKane, A., & Hadfield, G.K. (2019, January) Legible normativity for AI alignment: The value of silly rules. In Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 417–422. Honolulu, Hawaii. https://doi.org/10.1145/3306618.3314258
Hawking, S. (2014). Artificial intelligence could end mankind. BBC News. Available at: http://www.bbc.com/news/technology-30290540 (video & text).
Köse, U. (2018). Are we safe enough in the future of artificial intelligence? A discussion on machine ethics and artificial intelligence safety. BRAIN: Broad Research in Artificial Intelligence & Neuroscience, 9(4), 184–197.
Leading Countries of the World (2018). Lessons from Using Advanced Learning Analysis in the Education Sector, p. 10. Available at: https://www.leadingcountries.com/wpcontent/uploads/2018/08/19498_MSEdu_Learnin gAnalytics12ppBrochure_V2.pdf.
Leslie, D. (2019). Understanding artificial intelligence ethics and safety: A guide for the responsible design and implementation of AI systems in the public sector. The Alan Turing Institute. https://doi.org/10.5281/zenodo.3240529.
Luckin, R., Holmes, W., Griffiths, M. & Forcier, L. B. (2016). Intelligence Unleashed. An argument for AI in Education. London: Pearson.
Malle, B.F., Bello, P., & Scheutz, M. (2019). Requirements for an artificial agent with norm competence. In Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 21–27. ACM, New York, NY, USA. doi: https://doi.org/10.1145/3306618.3314252.
Marr, B. (2020). 28 Best Quotes about Artificial Intelligence. Available at: https://www.bernardmarr.com/default.asp?contentID=1158.
Mayer-Schönberger, V. & Cukier, K. (2014), Big Data: A revolution that will transform how we live, work, and think. Eamon Dolan/Mariner Books, USA.
Nye, B.D. (2015). Intelligent Tutoring Systems by and for the Developing World: a review of trends and approaches for Educational Technology in a Global Context. International Journal of Artificial Intelligence in Education, 25 (2), 177-203.
Paton, G. (2014, October 16). Four-in-10 children not ready for school at the age of five. The Telegraph. Retrieved from http://www.telegraph.co.uk/.
Perera, M. & Aboal, D. (2018). The impact of a Mathematics Computer-Assisted Learning Platform on Students Mathematics Test Scores. Fundación CEIBAL. Available at: https://digital.fundacionceibal.edu.uy/jspui/Mhandle/123456789/225.
Rigby, C. (2016). How Software that Learns as It Teaches is Upgrading Brazilian Education. The Guardian. Available at: https://www.theguardian.com/technology/2016/jan/10/geekie-educational-softwarebrazil-machinelearning.
Rundle, M. (2015). How Geekie’s Adaptive Education Shattered Centuries of Pain in Brazil, Wired. Available at: https://www.wired.co.uk/arti cle/claudio-sassaki-wired-2015.
Samarrai, S. A., Cerdan-Infantes, P. & Lebe, J. (2019). Policy research working paper 8773: mobilizing resources for education and improving spending effectiveness, establishing realistic benchmarks based on past trends. World Bank Group, education global practice. Available at: https://files.eric.ed.gov/fulltext/ED594458.pdf.
Santry, C. (2018). Artificial intelligence risks school apartheid. Tes. Retrieved from https://www.tes.com/news/artificial-intelligence-risks-school-apartheid
Sharma, Y. (2018). Boost to university-industry AI research collaboration. University World News. Available at: http://www.universityworldnews.com/article.php?story=20181012084845359.
Son, J.-B., Robb, T., & Charismiadji, I. (2011). Computer literacy and competency: A survey of Indonesian teachers of English as a foreign language. CALL-EJ, 12(1), 26-42.
UNCTAD (2016). Data Protection Regulations and International Data Flows: Implications for Trade and Development.
UNESCO (2019). Artificial Intelligence in Education: Challenges and Opportunities for Sustainable Development. Paris, France: UNESCO.
UNESCO. (2000). The Dakar Framework for Action: Education for All: Meeting our Collective Commitments adopted by the World Education Forum Dakar, Senegal 26-28 April 2000. Including six regional frameworks for action.
UNESCO: Paris, France. UNESCO. (2015). Sustainable development goal for education cannot advance without more teachers. UIS Fact Sheet No.33. Retrieved from http://www.uis.unesco.org/Education/Documents/fs33-2015-teachers.pdf.
UNESCO. (2018). Raising Learning Outcomes: the opportunities and challenges of ICT for learning. UNESCO: Paris, France. Retrieved from www.unesco.org accesses on 18th July 2020.
Villani, C. (2018). Donner un sens à l’intelligence artificielle: pour une stratégie nationale et européenne. Available at: https://www.aiforhumanity.fr/pdfs/9782111457089_Rapport_Villani_accessible.
Vinge, V. (1993). Vernor Vinge on the singularity. Presented at the VISION-21 Symposium sponsored by NASA Lewis Research Center and the Ohio Aerospace Institute. WISE (2011). Geekie: Personalized Learning for All. WISE Initiative. Available at: https://www.wise-qatar.org/geekie-personalized-learningall-brazil.
World Bank. (2001). World Development Indicators 2001.World Bank: Washington, DC. https://doi.org/10.1596/0-8213-4898-1
World Bank. (2017). World Development Indicators 2017.World Bank: Washington, DC. https://doi.org/10.1596/26447
World web foundation. (2017). Algorithmic accountability: Applying the concept to different country contexts. World web foundation: USA.