PLAY Minecraft! Assessing secondary engineering education using game challenges within a participatory learning environment

Abstract

This paper describes an initial step towards understanding how computational tools such as natural language processing and machine learning might be used to assess K-12 student learning in engineering education. The study used an online participatory learning environment, PLAY! (Participatory Learning and YOU!), as a platform for student work. Minecraft, an online construction game popular with young teens, was chosen as the learning topic to be assessed. Within PLAY, students created and shared Minecraft 'challenges' during a focus session consisting of five boys, ages 9 to 16. Machine learning techniques were used to create a classification scheme for engineering standards based on the Science and Engineering Practices in the Next Generation Science Standards. Natural language processing and data mining techniques were applied to student challenges to assess and report on students' engineering domain and topic learning. Results show that student application of engineering standards and student discussion of domain topics varied consistently by age. Responses to a corresponding questionnaire showed that the session was a highly positive experience for the children. The potential for use in engineering education is discussed. © American Society for Engineering Education, 2013.