Using educational data mining to assess students’ skills at designing and conducting experiments within a complex systems microworld

• We assessed the skill of designing and conducting experiments in the context of complex systems.
• Students engaged in experimentation with an ecosystems microworld.
• Using educational data mining, we developed an assessment of students’ experimentation processes.
• This technique was successful at scoring students at designing and conducting experiments.
• Our results demonstrate the potential of educational data mining for assessing ill-defined skills.

Many national policy documents underscore the importance of 21st century skills, including critical thinking. In parallel, recent American frameworks for K-12 science education call for the development of critical thinking skills in science, also referred to as science inquiry skills/practices. Assessment of these skills is necessary, as indicated in policy documents; however, this has posed a great challenge for assessment researchers. Recently, some science learning environments seek to assess these science skills. These systems log all students’ interactions within the given system, and if fully leveraged, these logs provide rich assessments of inquiry skills. Here, we describe our environment Inq-ITS (inquiry intelligent tutoring system), that uses educational data mining to assess science inquiry skills, as described as 21st century skills. Additionally, here, we describe how we measure students’ skills at designing controlled experiments, a lynchpin skill of inquiry, in the context of complex systems. In doing so, our work addresses 21st century skill assessment in two ways, namely of inquiry (designing and conducting experiments), and in the context of complex systems, a key topic area of 21st century skills. We use educational data mining to develop our assessment of this skill for complex systems.