In 1966, Professor Patrick Suppes of Stanford University posed a bold prediction: with advances in computer technology, many school-aged children would have their tutors at their disposal. He foresaw that these tutors would be free to all and determinedly provide infinite information and assistance.
He stated that the conditions would emulate the times when the young prince Alexander the Great was mentored by Aristotle – a unique, intense tuition relationship.
ChatGPT, an AI-powered chatbot with enhanced conversational skills, may become a viable tutor tool with the potential to help students learn. Possessing advanced dialogue capabilities gives this chatbot the potential other tutors lack, making it a promising solution.
ChatGPT boasts a lot of pertinent information on different topics, succeeding even in passing rigorous graduate school exams. As a researcher in computer-assisted learning applications, I believeChatGPT is more than capable of aiding students in academic pursuits.
While ChatGPT can perform effectively, it shows difficulty remaining focused on one task, particularly in providing effective tutoring.
Scholars of philosophy, engineering, and artificial intelligence had already dreamt of utilizing the computer as an “intelligent tutor” even before the reality of a far-flung internet was let loose in the economics cape in the 1990s.
Students and educators can best use ChatGPT’s tutoring systems when considering insights from early development stages. By understanding these lessons, they can maximize their potential benefits.
The Potential Of Computers As Tutors For Education
Albert Suppes, a pioneering Stanford philosophy professor, revolutionized the field of computer-assisted instruction. By creating some of the first educational software, he laid the foundations for future students and educators to benefit from these advances.
I worked for Suppes from 2004 to 2012, providing software and other online programs. During this time, the company was able to develop a program that enabled individual instruction via computer and, ultimately, led its students to score higher on exams than those who did not use it.
Artificial intelligence, computer hardware, and social network developments spring from experiments that aim to construct ‘intelligent tutors’ to aid students. This trend began with the earliest conception of digital learning systems.
ChatGPT, with its prolific capabilities such as essay writing, tackling philosophical problems, and programming, is anticipated to revolutionize computerized tutoring. This is something that Peter Suppes had been envisaging for a long.
Innovative Personalized Learning Solutions For Early Learners
A system known as PLATO (Programmed Logic for Automated Teaching Operations) was developed in 1972. It can be regarded as one of the first personalized learning systems made available to the public. PLATO allowed people to learn the material at their own pace without requiring external instruction.
PLATO, created by Professor Don Bitzer of the University of Illinois’s Electrical Engineering department, allowed up to 1000 users simultaneous access to the mainframe.
Each student can explore various online courses in various topics, from a foreign language to math and music, all with the convenience of computerized feedback on their work.
Most students were fond of PLATO-based instruction due to the level of achievement it enabled them to reach, equaling in-person classes over a saving of time. Nonetheless, for many higher learning institutions, the system was uneconomically costly.
Each computer terminal was priced at over $8,000 (approximately $58,000 today), plus fees were applied each time a student interacted with the system.
PLATO was a revolutionary educational tool used with students in the ’70s; Its success led to the emergence of companies such as the College Curriculum Corporation, co-founded by Suppes—this type of software-enabled similar tutoring methods.
Home computers, like Apple and Commodore, were often marketed based on how educational software could benefit families who invested in them.
Artificial intelligence and cognitive psychology had both seen advances by 1985, allowing Carnegie Mellon University researchers to create software mimicking human tutors’ effects. The systems being designed could interact with students and assess their learning needs.
Even though there were approximately 10,000 types of educational software on the market in those days, most of these offerings lacked effectiveness and did not offer effective tutoring services.