Litcius/Paper detail

Artificial Intelligence Models for Assessing the Evaluation Process of Complex Student Projects

Jose Divasón, Francisco Javier Martínez-de-Pisón, Ana Romero, Eduardo Sáenz‐de‐Cabezón

2023IEEE Transactions on Learning Technologies13 citationsDOI

Abstract

The evaluation of student projects is a difficult task, especially when they involve both a technical and a creative component. We propose an artificial intelligence (AI)-based methodology to help in the evaluation of complex projects in engineering and computer science courses. This methodology is intended to evaluate the assessment process itself allowing to analyze the influence of each variable in the final grade, to discover possible biases, inconsistencies and discrepancies, and to generate appropriate rubrics that help to avoid them. As an example of its application, we consider the evaluation of the projects submitted in an undergraduate introductory course on computer science. Using data collected from the evaluation during five academic years, we follow the proposed methodology to create AI models and analyze the main variables which are involved in the assessment of the projects. The proposed methodology can be applied to other courses and degrees, where both technical and creative components are considered to evaluate the projects.

Topics & Concepts

RubricComputer scienceProcess (computing)Task (project management)Component (thermodynamics)Variable (mathematics)Artificial intelligenceData scienceManagement scienceSoftware engineeringMathematics educationSystems engineeringEngineeringPhysicsThermodynamicsMathematical analysisMathematicsOperating systemExperimental Learning in EngineeringBiomedical and Engineering EducationOnline Learning and Analytics