The Prospects, Challenges and Ethical Aspects of Artificial Intelligence in Education
Abstract
Implication of Artificial intelligence in education brought significant improvement on traditional models of teaching and learning process. This paper was aiming at bringing to the right prospects, challenges and ethical aspects of Artificial Intelligence in Education (AIED). Purposive non probability sampling technique was used to select study participants. Descriptive statistics and thematic approach were used to analyse collected quantitative and qualitative data Effective creation and implementation of AIED various adaptive learning platforms (Liushuo in China, NLP in USA, PAM in Germany, EdTech company Greekie in Brazil and M-shule in Kenya), Advanced data analytic platforms, the introduction of AI as major course in universities, and Investment for AI research were established as prospects of AI at the level of 26.80%, 24.10%, 26%, and 23.10% respectively. Other potential prospects like Multi-source of data analysis and audio-Visio teaching and learning materials were revealed as key prospects of AIED. Fragile technological infrastructure, inadequate government expenditure in education, achievement gap in education, resistance to implement AIED, and unprepared teacher for AIED implementation were found as challenges of AIED 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 AIED. Cultural integration; accountability; fairness, equity and affordability; security, and privacy were found out as the main ethical aspects of AIED at 33.3%, 28.6%, 14.3%, 14.3% 9.5% respectively. Increasingly Humanity, singularity, authentication and profitability, personal interest’s investment, humanitarianism, and solitary were suggested as ethical aspects of AIED. The paper recommends AIED theorists to mitigate carefully the impacts of AI on human kinds.
Keywords: Artificial Intelligence in Education (AIED), Prospects, challenges, ethical aspects, Adaptive learning platform, Algorithm, 21st century skills.
