Digitalization has had a major impact on each and every aspect of our lives. We manage our personal finances via net banking, interact with our friends and kin on social media websites and look for prospective partners on dating apps. But, digitization has not just impacted our private lives, but has also proliferate the vocational world. University Professor, Davidson, on her new book, “The New Education” forecasts that more than 6/10ths of jobs that will be available to students that graduate in one-and-a-half decades do not exist, however. A majority of these new jobs are poised to evolve in the quarternary sector, which is made up of knowledge-driven, and increasingly demanding service occupations like those in legal, business, and IT functions. 

To keep up with these swift advancements, we need a robust educational system which preps students the right amount for a career in unpredictable environments. Thus far, the steps taken by academic institutions and schools to achieve compliance with these high expectations often disappoint. For the longest time, organizations indicate an increasing rift between graduate’s skill set and employer’s requirements, while students make the complaint that the expenditure of higher education is escalating quickly. As an outcome of these problems, the education technologies (EdTech) field has experienced evolution to a considerable degree with a market share expected to be approximately 165$ billion in 2016. One of the forerunning personalities within the EdTech field is the previous head of Google’s autonomous car unit and Stanford professor Sebastian Thrun. A decade ago, he initiated the online course “Intro into AI” for which 160,000 students made enrolments in the first batch. On the basis of their performance in the online course, Trhun went to discover the massive open online course (MOOC) platform Udacity, 9 years ago, in 2012. His primary intention and motivation was to take high-quality and practically-oriented education available to individuals all over the globe, regardless of their social standing. 

“I felt that if we could just build a new kind of university that could democratize education and really reach everybody, we could have a bigger impact on the world than just building a self-driving vehicle.” 

If MOOCs are the future for the education sectors, are teachers expendable?
 

This is not probable to happen. The hue and cry with regards to MOOCs has plateaued and regardless of massive investments of late, MOOCs do not appear to become the learning format of preference for learners and students, which is also denoted by the present dropout rates which are pretty high. Often >95%. Hybrid learning strategies, in which classroom training coalesces with online sessions external to the classroom setting, are much more apt to create disruption in conventional education. This theory provides the best of both perspectives, the advantages of education technologies like the permanent accessibility of content and the benefits of face-to-face interaction. For instance, the creation of a community and the developing of social skills. As educational institutions have persisted to be reliant on conventional lectures/classroom scenarios of late, they witnessed limitless possibilities from AI solutions to supplement conventional learning by enhancing present typical practices and reducing the load of teachers and instructors. 

The following are three of the hottest subjects that the EdTech scene is presently working on leveraging artificial intelligence technologies: 

Customized/personalized learning 

Due to simple practicality, our present educational system is on the basis of categorizing learners just by age, ignoring the differences in student’s learning pace, spheres of interests, and inherent talents. As a consequence, in each classroom there are some students who experience boredom as they have comprehended a topic very quickly and others who are discouraged as they cannot adhere or comprehend the instructor’s explanations. To put it in other words, education has experienced a paradigm shift towards a one-size-fits-all solution. 

Rochelle, lead of product management at Google, forecasts that AI applications will soon customize the experiences of learners by indicating individual learning aims, choosing instructional strategies and visualizing exercises that on the basis of their interests and the appropriate skill level of each learner. Much like Netflix displays to us the movie that we would probably like, Spotify develops a personal playlist on the basis of our prior music choices. AI could indicate to learners their most apt educational setting. Providing and individual, and unique learning journey would enable students not just to learn at their own speed, but also obtain the joy and thrill that outstanding education provides. 

Automated Grading 

A lot of teachers often make the assertion that the most awful part of the teaching profession is grading the learners. It is a monotonous activity that takes up a lot of assets and resources which could be leveraged as a valuable classroom session for the interaction amongst students and faculty. As a matter of fact, Kraus, president of the German Teacher’s Union opines that teachers in Germany spend approximately 1,000 hours annually on grading dependent on the classes and subjects they are providing instruction for. Aside from teacher’s discontent with the status quo, additionally, students critique that they grades they get are partially inconsistent, subjective, and opaque. 

AI scientists are undertaking work on solutions to go about automating the monotonous grading procedure and one winning instance is the AI-driven grading solution Gradescope, a framework which is already leveraged in several universities  which includes Stanford and Berkeley. Gradescope queries instructors to scan the learner’s handwritten test answers and automatically goes about applying pre-defined grading criteria to all evaluations, therefore minimizing times taken in grading considerably, and furnishing a transparent grading key to all learners. 

While Gradescape already works solidly for standardized test forms like multiple choice question tests, a subsequent hurdle has its basis in how to grade larger texts, a discipline also called as automated essay scoring (AES). One strategy to AES is identifying objective measures like the length of words, the number of spelling errors, and the ratio of lower case letters to upper case letters. But, these overt and quantifiable measures do not provide the critical insight for assessing critical aspects of an essay like the strength of a student’s argument, or how conclusive their argumentation is. To observe how well machines would grade several essays and emulate instructor’s gradings, the Flora and William Hewlett Foundation begin a contest in 2012. Almost shockingly, the output of the team that won was in 81% concurrence with the instructor’s gradings, an amazing result that indicated a turning point in instructor’s perceptions with regards to educational technologies. Presently, AES engines are leveraged to assist human raters in evaluating academic essays like TOEFL and the GRE.  

24×7 personalized student and instructor support 

Have you ever observed your teaching assistant, who gives you specific course data and solutions to all your questions with regards to the course syllabus on campus? If you haven’t, the person in all likelihood does not exist and is merely an AI bot. This is what occurred to 400 students at the Georgia Institute of Technology, when Prof. Goel put forth the new teacher’s assistant Jill Watson in front of the class. Ms. Watson provided insightful replies to questions, transmitted reminders with regards to due dates, and queried learners mid-week to stimulate discussions. Students detailed that her answers were dependable and that her tone was easily understandable. The only difference with a conventional teaching assistant was that Ms. Watson was not an actual individual but an artificial intelligence robot produced to minimize the workload of the professors learners. Ms. Watson handled activities in which she possessed at least 97% confidence in that she was aware of the correct answer. An AI-driven robot like this is beneficial for both teachers as it minimizes their cumulative workloads as they can obtain assistance on typical issues instantaneously and whenever the desire, 24×7. 

Conclusion 

Educational organizations have to find new strategies to prep students adequately for their careers. To accomplish that, teachers and digital frameworks such as artificial intelligence engines will have to go about learning to collaborate in an effective and efficient fashion to surpass the pending hurdles on the path towards improved education. Hence, it is vital that AI frameworks are customized to act side-by-side with instructors, the monotonous and tedious activities outsourced to them and leaving the more dynamic tasks to the human agent. This will facilitate academic institutions to enhance productivity, save up on expenditure, and develop new opportunities. The latest advancements in educational technologies and specifically in artificial intelligence provide confidence that we will see positive results in furnishing the learners of the future a high-standard education and facilitate instructors to do more of what they’re passionate about – teaching.