1. Data-driven Insight
Arguably the defining feature of Artificial Intelligence (AI) across sectors is the deep insight it offers through real-world data. In education, the consequences of this are far-reaching; through real-time updates, student performance can be monitored closely, undergo thorough processing, and be presented to all relevant stakeholders (teachers, parents, students’ themselves) in creative ways that visually display performance and growth. Not only does this insight play a key role in personalization, which will be discussed further on, but it also empowers educators with the information they need to tweak their teaching/training strategies, develop alternative content, or focus on particular areas. It also highlights critical observations on student performance in particular, by highlighting specific trouble areas requiring further work.
In a world where we are continually learning that fairness means equity (giving people what they need to succeed based on where they start out) and not just equality (treating everyone the same regardless of individual differences), personalized tutoring can set us on track for transformational impact.
Building on the rich insight AI, and machine learning in particular, offers, content can be customized to meet the learning needs and challenges of individual students. This means that based on their own strengths and weaknesses, students can be offered different levels of academic support.
3. Grading and Feedback
Teachers can breathe a sigh of relief while looking on to the AI future. Computers can accurately mark assignments within microseconds (from objective to subjective type questions) based on machine learning algorithms. This saves valuable times for teachers to focus on broadening their skills through professional development and/or self-study, as well as to prepare course materials, set their vision and goals, realign teaching strategies, etc.
Furthermore, deep learning offers vast feedback for detailed, intelligent feedback, given that it allows unsupervised learning—that is, the ability to learn from unstructured (or unlabeled) texts, videos, images, etc. This is of huge consequence to both student and teacher, meaning that quality feedback is always just a submission away, with almost no waiting time.
4. Virtual Support
Through machine learning and its branch of deep learning, in particular, computers designed to imitate human neural networks can simulate not only an intelligent person but an expert in their field. AI robots, hence, can act as tutors in online classrooms, and/or play the role of a virtual “study buddy” or “teacher’s assistant”, much like Apple’s Siri, the Google AI assistant, and Amazon’s Alexa. This is game-changing for the classroom for its immense scope in assisting remedial learning, as well as supporting self-paced education.