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6 W A Y S A R T I F I C I A L I N T E L L I G E N C E A N D C H A T B O T S A R E C H A N G I N G E D U C A T I O N Q S S
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Chatbots are about to change the world in more ways than we can imagine. Already, bots around the globe can complete a diverse set of varying tasks. chatbots are about to become a normal element in everyday life. As the scope of chatbots becomes broader every day, there are new applications popping up constantly. Education has traditionally been known as a sector where innovation moves slowly. During the most recent years, there has been a large hype over innovative tools to enhance teaching and learning through educational technology.
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“The time has come for chatbots and artificial intelligence to meet the educational sector. Already, there’s a lot happening but there is no question technology will have an even deeper reach in the near future.” We’ve come across six applications of both chatbots and artificial intelligence within the educational area that could have an astounding impact on the whole industry.
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1. Automatic Essay Scoring Giving feedback on individual written essays is an enormously time demanding task that many teachers struggle with, and in massive open online courses, the problem is even larger. Because there are often over 1000 students in one class, there’s simply no realistic way to give individual feedback to written essays. To combat this problem, innovators have been flirting with the artificial intelligence (AI) industry, and a solution is relatively close at hand.
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By feeding a machine-learning algorithm thousands and thousands of essays, many people believe there’s a good chance of replacing human feedback on essays with AI systems. The project has made rapid improvement since 2012 when The Hewlett Foundation sponsored a competition between essay grading systems. The winner presented a 0.81 correlation, on average, with human graders. Since then, researchers and scholars have continued accelerating and improving systems in full force. One report claims to have achieved a 0.945 correlation on the same data as in the Hewlett competition. Astonishing!
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However, there’s also strong opposition towards relying on only technology when setting grades. Skeptic Les Perelman has set out to expose the true nature of grading algorithms and has successfully managed to point out weak points amongst autograding vendors. How will auto-grading turn out? The future is not yet clear, but realistically there should be a chance of replacing at least one or two of the necessary graders with AI in a few years time.
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2. Spaced Interval Learning Polish inventor Piotr Wozniak has come up with a learning app built around the spacing effect. This app keeps track of what you learn and when you learn it. By incorporating artificial intelligence, the app is able to learn when you are most likely to forget information and remind you to repeat it. It only takes a couple of repetitions to make sure the information sticks for years to come. Instead of students studying intensely before finals only to forget everything a few weeks later, schools and universities should aim for more lasting knowledge retention using this method.
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Sadly, findings like the spacing effect have had a small impact on the educational system, which lives up to its reputation of being a sector of slow adoption of technology and innovation. 3. Conversational Course Assessments & Student Ratings Student evaluations of teaching-surveys have been around for almost 100 years. Despite moving from paper to online surveys, there has been minimal progress to make the feedback process better in any way. Using a chatbot to collect feedback is the ultimate compromise between a qualitative and a quantitative research method. As teachers are normally way too busy to collect qualitative feedback from each student, an end-course survey is often used.
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A chatbot can collect opinions through a conversational interface with the same advantages as a ‘real’ interview but with a fraction of the required work. The conversation can be tailored according to the responses and personality of the student, ask follow-up questions, and find out the reason behind opinions. It’s also possible to filter out personal insults and foul language, which are sometimes present in teacher ratings. Other than being a compelling option to surveys and with more qualitative data, a chatbot brings many other advantages for teachers who seek to improve efficiency in teaching. By involving more data sources such as self-assessment, grades, peer feedback, and the latest scientific findings on how to teach effectively, it’s possible to form a more nuanced picture of teaching performance.
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Comparing the data to that of other teachers around the world should make it possible for the system to suggest new and powerful ways to improve teaching and share findings throughout the teacher’s community. 4. Watson, the Teacher Assistant At the Georgia Institute of Technology, students were charmed by the new teachers assistant, Jill Watson, who managed to respond to student inquiries in a fast and accurate way.
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5. The Chatbot Campus Genie At the Deakin University in Victoria, Australia, development is in full swing to complete the first ever chatbot campus genie. Just like in the case of the AI teacher assistant, the intelligence behind it comes from IBM’s supercomputer system, Watson. Once operational, the Deakin genie will be able to answer questions related to everything a student needs to know about life on campus. How to find the next lecture hall, how to apply for next semester’s class, how to submit assignments, where to find parking or where a counselor can be reached are all questions that can be handled by the genie.
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When new students swarm the campus, they have similar questions every year which makes for a perfect application of a chatbot. William Confalonieri is the driving force behind the genie-project and the CIO at Deakins University. Confalonieri hopes to be able to expand the capabilities of the system rapidly in the coming years and have it handle significantly more complex tasks in the future.
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6. Student-Centered Feedback The current educational system can, a bit maliciously, be described as a factory-line where the end-goal is to produce competent students to fill employee needs. The factory expects the same raw material (students), the same response to treatment (lessons) and the same result in the same time frame. As human beings are complex beyond the reach of even the most advanced science, the factory approach is not ideal when it comes to transferring knowledge to a diversified new generation.
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The content adapts to individual learning pace and can present gradually harder problems to accelerate learning as the student comprehend more and more. This way, both fast and slow learners can keep going at their own pace without being discouraged by other students. It’s also possible for an AI-driven curriculum to foresee future trouble areas and present more problems related to it in order to prevent future struggles.
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