Evidence-Based Assessment of Student Performance in Virtual Worlds

Manuel Palomo-Duarte, Anke Berns, Antonio Balderas, Juan Manuel Dodero and David Camacho
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Manuel Palomo-Duarte: Departmento de Ingeniería Informática, Universidad de Cádiz, 11519 Puerto Real, Spain
Anke Berns: Departamento de Filología Francesa e Inglesa, Universidad de Cádiz, 11003 Cádiz, Spain
Antonio Balderas: Departmento de Ingeniería Informática, Universidad de Cádiz, 11519 Puerto Real, Spain
Juan Manuel Dodero: Departmento de Ingeniería Informática, Universidad de Cádiz, 11519 Puerto Real, Spain
David Camacho: Departamento de Sistemas Informáticos, Universidad Politécnica de Madrid, 28031 Madrid, Spain

Sustainability, 2020, vol. 13, issue 1, 1-17

Abstract: Virtual Worlds (VWs) are popular tools for teaching/learning in the twenty-first century classroom. The challenge remains however, to provide the means by which teachers could sustainably analyse and assess the performance of large groups of students in such environments. Unfortunately, external game features such as game scores and play duration have turned out to be unfair in some assessments. In this context, a case study was carried out in a foreign language course, illustrating how teachers could easily retrieve a number of performance indicators from VW-interaction logs and harness them to conduct a fine-grained analysis of students’ performance, while facilitating at the same time valuable tools for their assessment. Objective performance indicators in a server database were made accessible using an end-user development programming language. This way, a range of data visualisation methods could be employed to contrast different assumptions regarding learner performance when playing a VW-based game, which was designed to help CEFR A1 level students to learn German. This way, factors such as randomisation of game tasks, which could negatively affect learner performance, were alleviated.

Keywords: virtual worlds; VW-based games; end-user development; programming language; interaction logs; assessment; language learning (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
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