Systems thinking of pre- and in-service science and engineering teachers

ABSTRACT

Systems thinking is an important skill in science and engineering education. Our study objectives were (1) to create the basis for a systems thinking language common to both science education and engineering education, and (2) to apply this language to assess science and engineering teachers’ systems thinking. We administered two assignments to teacher teams: first, modelling the same adapted scientific text, and second, modelling a synthesis of peer-reviewed articles in science and engineering education, with teams selecting a topic from a list and summarising them. We assessed those models using a rubric for systems thinking we had developed based on our literature review of this topic. We found high interrater reliability and validated the rubric’s theoretical construct for the system aspects of function, structure and behaviour. We found differences in scores between the assignments in favour of the second assignment, for two attributes of systems thinking: ‘expected outcome/intended purpose’ and ‘main object and its sub-objects’. We explain the first attribute difference as stemming from the modellers’ domain expertise as science or engineering teachers, rather than as scientists or engineers, and the second attribute difference – from the larger amount of information available for modelling the articles synthesis assignment. The theoretical contribution of this study lies in the definition of the systems thinking construct as a first step in establishing a common language for the science education and engineering education communities. The study's methodological contribution lies in the rubric we developed and validated, which can be used for assessing the systems thinking of teachers and potentially also of undergraduate students.

KEYWORDS:

• systems thinking
• assessment
• in-service teachers
• pre-service teachers

ORCID

Rea Lavi http://orcid.org/0000-0002-0788-7236

Yehudit Judy Dori http://orcid.org/0000-0001-7775-5872

Additional information

Funding

This work was supported by the Bernard B. Gordon Center for Systems Engineering at the Technion [grant number 2023427].