Wyniki wyszukiwania - BazTech

Ograniczanie wyników

1 Annals of Computer Science and Information Systems

1 2024

Znaleziono wyników: 1

Liczba wyników na stronie

Wyniki wyszukiwania

Sortuj według:

Ogranicz wyniki do:

Goliath, a Programming Exercises Generator Supported by AI

Freitas Tiago Carvalho, João Varanda Pereira Maria, Neto Alvaro Costa, Rangel Henriques Pedro

Annals of Computer Science and Information Systems

2024

Vol. 39

331–-342

The teaching-learning process is complex in nature, requiring many tasks and skills to achieve success in the construction of knowledge. As per any particular kind of cognitive development, teaching and learning Computer Programming is no different in this regard: tasks must be executed, sometimes repeatedly, and skills must be developed. Despite different approaches and methodologies, exercising what has been studied is proven to be effective in pretty much any teaching-learning process. Many tools have been developed throughout time to aid in the execution of this important task, sometimes approaching the problem from the students' perspective, sometimes from the teachers'. This paper presents Goliath, a semi-automatic generator of Computer Programming exercises, whose functionality is based on Artificial Intelligence (AI) models, a Domain-Specific Language (DSL), and an online application that binds them together. Goliath's goals are directed towards teachers (and indirectly, students) by aiming to lower the burden of repeatedly constructing exercises. This is achieved through the use of templates that allow for automatic variations of an exercise to be created instantly, while relying on a common foundation. Goliath is meant to be a facilitator, raising availability of exercise lists, while avoiding repetition and the common mistakes that accompany their construction.