Advisor(s)
Abstract(s)
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.
Description
Keywords
Computer Programming Programming Education Artificial Intelligence Domain Specific Languages Programming Exercises
Citation
Publisher
IEEE