How linguistic descriptions of data can help to the teaching-learning process in higher education, case of study: artificial intelligence

TL;DR

This paper explores how linguistic data descriptions can enhance feedback and assessment in AI education, using a web platform to improve teaching and learning of heuristic algorithms in a project-based course.

Contribution

It introduces a novel approach using linguistic data descriptions for personalized feedback and proposes a new Turing test for game bots based on linguistic modeling.

Findings

Improved student understanding of algorithms

Enhanced feedback through linguistic descriptions

Successful implementation of a web-based assessment platform

Abstract

Artificial Intelligence is a central topic in the computer science curriculum. From the year 2011 a project-based learning methodology based on computer games has been designed and implemented into the intelligence artificial course at the University of the Bio-Bio. The project aims to develop software-controlled agents (bots) which are programmed by using heuristic algorithms seen during the course. This methodology allows us to obtain good learning results, however several challenges have been founded during its implementation. In this paper we show how linguistic descriptions of data can help to provide students and teachers with technical and personalized feedback about the learned algorithms. Algorithm behavior profile and a new Turing test for computer games bots based on linguistic modelling of complex phenomena are also proposed in order to deal with such challenges. In order to show and explore the possibilities of this new technology, a web platform has been designed and implemented by one of authors and its incorporation in the process of assessment allows us to improve the teaching learning process.