Characterising immersive argument-based inquiry learning environments in school-based education: a systematic literature review

ABSTRACT

Educational initiatives in multiple disciplinary areas call for student engagement in the practice of argumentation (CCSSI, 2010a, 2010b; Mullis & Martin, 2017; NGSS Lead States, 2013; OECD, 2018). In science education, immersive argument-based inquiry (ABI) is one category of approaches which integrates argumentation in all classroom activity in order to support conceptual understanding in science. Previous research has reported details of specific immersive ABI approaches but has failed to summarise the characteristics common to all approaches categorised this way and the critical components underlying the learning environments supporting these approaches. This study identified common elements of immersive ABI learning environments through a systematic literature review of 16 existing approaches. Open and axial coding led to the identification of three categories of common elements, including student actions, teacher actions, and generative opportunities. Implications and potential steps to build further understanding of the common elements are discussed.

KEYWORDS:

• Generative Learning
• Argument-Based Approaches
• Immersion

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Kathleen A. Weiss

Kathleen A. Weiss is an Instructional Design and Educational Support Specialist in the Center for Educational Enhancement at Des Moines University. Her current work is focused on development of faculty and student supports in medical and health science education. Her research focuses on generative learning environments.

Mark A. McDermott

Mark A. McDermott is a clinical professor of Science Education at the University of Iowa.  His research focuses on STEM education and methods for improving pre-service teacher learning.

Brian Hand

Brian Hand is a professor of Science Education at the University of Iowa. His research interests are centred on improving learning through understanding the complexity of generative learning environments.