engleski

LOW-CODE AND NO-CODE APPROACH TO TEACHING ARTIFICIAL INTELLIGENCE

The importance of artificial intelligence (AI) education is rising as the digital world is eating the physical one. In addition, AI has infiltrated our daily routine through personal and driving assistants, intelligent house appliances, cities, and different robots. UNESCO is investigating the current practices of developing and implementing AI curricula in primary and secondary education from a global perspective, as AI technology represents a new subject area for K–12 schools worldwide. Educators cannot ignore AI education at all levels, notably higher education. At the same time, we should understand that we need to teach AI basic concepts and critical approaches to using AI to students who do not need to become AI experts. Since AI is part of computer science (CS), teachers often relate programming and coding to AI. End users should develop and adapt AI systems at the complexity level adequate to respective domain expertise, practices and skills. CS teachers should differ between teaching programming and teaching coding to students. Regardless of the never-ending debate on programming and coding definitions, we can agree that programming is the general process of creating a program to perform a specific task following standards. On the other hand, coding is a part of programming that deals strictly with converting human language into machine commands, usually using a high-level programming language. As stated, teaching AI includes introducing complex concepts and approaches to non- programmers. For example, James Martin presented the idea of introducing users to the production of complex programming tasks using a low-code or no- code strategy in 1982. in his book "Application Development Without Programmers". Are we reinventing the wheel, or are we just ignorant? At the Faculty of Science, University of Split, Croatia, we are educating future teachers of mathematics, physics, biology, chemistry, informatics and technics, as well as engineers in respective fields and data science engineers. This paper presents our findings on using low-code and no-code approaches compared to traditional code- based AI teaching to different student groups.

Artificial intelligence, no-coding, low-coding, teaching programming.

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