Artificial intelligence (AI) is rapidly finding practical applications across an abundance of business areas, with educational assessment and tutoring, grading, and student performance estimation is no exception. Over the last decade, a number of intelligent tutoring systems have emerged based on the idea that AI must not only automate assessment but also provide feedback, repetition opportunities, and well-optimized individual curricula.

Personalized Learning: AI-based educational platforms provide tailored learning experiences by assessing student progress and making necessary material modifications. It means that each student can learn at their own pace and receive feedback that is specifically customized to them.

Luckin et al. states that adaptive learning systems analyze student interactions with the material and adjust the presentation to suit the learner’s needs. (Luckin et al, 2016)

AI makes fast assignment grading. It concerns such subjects as science and math where answers are more objective. Thanks to advancements in natural language processing, artificial intelligence can already score written assignments. This offers the possibility of scaling examinations in areas that need subjective grading (Baker & Smith, 2019).

Thanks to AI traits such as text-to-speech and speech-to-text technologies, students with disabilities may now access education more readily. Besides, by translating educational resources into various languages, Holmes et al. (2019) declared that AI enhances inclusivity by breaking language barriers and providing equal learning possibilities. Large-scale student performance data may be analyzed by AI-powered predictive analytics to determine which pupils may have issues or require further help. This predictive capacity, according to Zawacki-Richter et al. (2019), allows teachers to interfere early, improving student storage and success rates. Despite these achievements, concerns over data privacy and the need for teacher’s preparation remain regarding AI in education. Selwyn pointed out “the role of the teacher remains central, with AI being a tool to increase rather than replace traditional teaching methods” (Selwyn, 2019).

In summary, AI has the power to change education by pushing its effectiveness, accessibility, and customization. AI use has to be moderated with human’s supervision to ensure that it increases and supports education rather than decreases it.

References:

1. Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson. https://www.researchgate.net/publication/299561597_Intelligence_Unleashed_An_argument_for_AI_in_Education
2. Baker, T., & Smith, L. (2019). Educ-AI-tion rebooted? Exploring the future of artificial intelligence in schools and colleges. Nesta. 56
3. Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: promises and implications for teaching and learning. center for curriculum redesign. 39 https://curriculumredesign.org/wp-content/uploads/AIED-Book-Excerpt-CCR.pdf
4. Zawacki-Richter, O., Marín, V., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education. International journal of educational technology in higher education: https://educationaltechnologyjournal.springeropen.com/articles/10.1186/s41239-019-0171-0
5. Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. Polity.: https://research.monash.edu/en/publications/should-robots-replace-teachers-ai-and-the-future-of-education