Interaction with learners

Artificial intelligence to assist, mentor, teach and evaluate in higher education

Higher education is already using artificial intelligence in several effective ways: planning courses and facilities, developing student recruitment campaigns, investing and supporting endowments, and many other operational activities are driven by AI. in large institutions. Programs that run AI (algorithms) can use big data to project or predict outcomes based on machine learning, in which the computer “learns” to adapt to a myriad of elements, conditions and conditions. changing trends.

Adaptive learning is one of the first applications of AI to the teaching and learning process. In this case, AI is used to orchestrate the interaction between the learner and the educational material. This allows the program to more effectively guide the learner to achieve desired outcomes based on the learner’s unique needs and preferences. Using a series of assessments, the algorithm presents a personalized selection of teaching aids tailored to what the learner has demonstrated mastery and what he has yet to learn. This method effectively eliminates unnecessary repetition of already learned material while progressing through the content at the learner’s pace, ensuring that learning outcomes are achieved.

There is a big room for progression of AI in higher education, as Susan Fourtané writes in Fierce upbringing:

The potential and impact of AI on education has prompted some colleges and universities to take a closer look, accelerating its adoption on campuses. As a perspective, the global AI market is expected to reach nearly $ 170 billion by 2025. By 2028, the size of the AI ​​market is expected to grow to more than 360 Billion dollars, growing at 33.6% between 2021 and 2028, according to a report by research firm Fortune Business Insights. The market is primarily segmented into Machine Learning, Natural Language Processing (NLP), Image Processing, and Speech Recognition.

One of the pioneers in applying AI to support college-level learning, Ashok Goel of Georgia Tech, developed the famous “Jill Watson,” an AI program to serve as a graduate virtual assistant. Since the first semester of “Jill” in 2016, Goel has repeatedly and gradually improved the program, expanding the potential for creating additional AI assistants. The program is becoming more and more affordable and reproducible:

Jill Watson’s first iteration took between 1,000 and 1,500 person-hours. While this is understandable for a groundbreaking research project, it is not an achievable investment of time for a college teacher. So Goel and his team set out to reduce the time it takes to create a personalized version of Jill Watson. “Now we can build a Jill Watson in under ten hours,” Goel says. This reduction in build time is due to Agent Smith, a new creation of Goel and his team. All the Agent Smith system needs to create a personalized Jill Watson is a one-on-one lesson plan and question-and-answer session with the teacher … which you want in the long run, because if humans keep making AI, it’s going to take a long time.

More and more students are used to interacting with AI-driven chatbots. Serving a wide range of abilities in colleges, chat bots typically converse in computer-generated text or speech using natural language processing. These algorithms can even create a virtual relationship with the students. This is the case of a chatbot named “Oli” tested by Common App. For 12 months, this chat bot communicated with half a million students in the High School Class of 2021 twice a week to guide them through the college application process. In addition to the pro forma steps of the application process, Oli would offer students friendly reminders to take care of themselves in these COVID times, including suggestions to remind them to stay in touch with their friends, listen to their favorite music or take a deep breath. When the process was complete, Oli texted.

“Hey buddy,” Oli said a week before officially signing, “I wanted to let you know that I have to say goodbye to you soon. Remember, even without me you are never alone. to reach out to your counselor or loved ones if you need help or someone to talk to. College isn’t easy, but it’s exciting and you are so ready! The relationship could have ended There. But some of Oli’s human correspondents had more to say. Hundreds of them responded by text message, praising them for the support the chatbot had offered as they continued their education. social robots show that children see them as “kind of alive” and make “an attempt to establish a mutual relationship,” writes MIT professor Sherry Turkle. It’s a type of bond, a “degree of friendship.” , which excites some researchers and worries others.

Last month, Google announced a new AI tutor platform to give students personalized feedback, homework and advice. Brandon Paykamian writes in GovTech,

[Google Head of Education] Steven Butschi described the product as an extension of Student Success Services, Google’s software suite released last year that includes virtual assistants, analytics, enrollment algorithms, and other applications for higher education. He said the new AI tutors platform collects educator-created ‘skill competency charts’ and then uses AI to generate learning activities, such as short answer questions. or multiple choice, which students can access on an app. The platform also includes apps that can chat with students, provide coaching for reading and writing comprehension, and advise them on academic lesson plans based on their prior knowledge, career goals and of their interests.

With all of these AI applications in development and early launch, questions have arisen as to how best to ensure that bias is avoided in AI algorithms used in education. At the same time, concerns have been raised that we are ensuring that learners recognize that these are computer programs rather than direct communication with live instructors, that learner privacy is maintained and that related concerns regarding the use of AI have been raised. The Federal Office of Technology and Science Policy collects information with the aim of creating an AI bill of rights. Typically, the AI ​​Bill of Rights aims to “clarify the rights and freedoms” of people using or subject to data-driven biometric technologies.

How is your school preparing to integrate reliable, cost-effective, and effective AI tools for teaching, assessment, counseling, and deeper engagement with learners? Are stakeholders, including faculty, staff, students and the wider community included in the process to facilitate the broadest contribution and ensure the benefits and expected results from using the IA?