Feed

Scientific modelling plays a crucial role in students’ science learning. Modelling proficiency and literacy development reinforce each other. This study investigates the relationship between teacher support of student literacy development and their modelling proficiency in the context of elementary project-based learning science environments. To explore the relationship, we sampled 557 students from 24 classrooms in 12 different schools. Data were analysed by multilevel mixed linear regression model analysis.

Having a negative attitude toward science plays a major factor in elementary teachers avoiding teaching science in elementary school. This mixed methods study examined changes in pre-service elementary teachers’ (PSETs) attitudes toward teaching science. PSETs (n=59) engaged in a semester-long university course in the Southeastern United States. The course focused on demonstrating and applying knowledge of scientific concepts and inquiry-based teaching. PSETs took a Dimension of Attitudes toward Science (DAS) questionnaire before and after the course.

Argumentation is fundamental to science education, both as a prominent feature of scientific reasoning and as an effective mode of learning—a perspective reflected in contemporary frameworks and standards. The successful implementation of argumentation in school science, however, requires a paradigm shift in science assessment from the measurement of knowledge and understanding to the measurement of performance and knowledge in use.

The complex and interdisciplinary nature of scientific concepts presents formidable challenges for students in developing their knowledge-in-use skills. The utilization of computerized analysis for evaluating students’ contextualized constructed responses offers a potential avenue for educators to develop personalized and scalable interventions, thus supporting the teaching and learning of science consistent with contemporary calls.

There is growing support and interest in postsecondary interdisciplinary environmental education, which integrates concepts and disciplines in addition to providing varied perspectives. There is a need to assess student learning in these programs as well as rigorous evaluation of educational practices, especially of complex synthesis concepts.

An ability to engage in system thinking is necessary to understand complex problems. While many pre-college students use system modeling tools, there is limited evidence of student reasoning about causal relationships that interact in diverging and converging chains, and how these affect system behavior. A chemistry unit on gas phenomena was implemented in two successive years with 73 high school students. Although the phenomena could be explained with simple linear causal reasoning, many student models included surprising and problematic causal chains and non-linear patterns.

Attention to improving science education has grown nationally and globally, as science and policy communities fnd themselves challenged by complex real-world problems that have neither straight-forward nor ultimate solutions (Anderson & Li, 2020). Science, technology, engineering, and math-ematics (STEM) permeate nearly every facet of modern life; indeed, STEM holds the key to meeting many of the problems facing humans today and in the future (OECD, 2019). Moreover, understand-ing science can fundamentally improve people’s lives (National Research Council, 2012b; OECD, 2019).

This paper discusses the potential of two computational modeling approaches in moving students from simple linear causal reasoning to applying more complex aspects of systems thinking (ST) in explanations of scientific phenomena. While linear causal reasoning can help students understand some natural phenomena, it may not be sufficient for understanding more complex issues such as global warming and pandemics, which involve feedback, cyclic patterns, and equilibrium. In contrast, ST has shown promise as an approach for making sense of complex problems.

As technology advances, opportunities and challenges of its uses arise. The educational field is no different, and along with the need for educators to adapt to technological changes that occur spontaneously (widespread use of smartphones, for example), the opportunity of utilizing various digital platforms for educational purposes that were not possible or at least not cost-effective until now exist. The authors in this section illustrate these opportunities and challenges.

Understanding the world around us is a growing necessity for the whole public, as citizens are required to make informed decisions in their everyday lives about complex issues. Systems thinking (ST) is a promising approach for developing solutions to various problems that society faces and has been acknowledged as a crosscutting concept that should be integrated across educational science disciplines. However, studies show that engaging students in ST is challenging, especially concerning aspects like change over time and feedback.