Toward a Scientific Practice of Science Education

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Since then, design thinking has been used to create thick-handled toothbrushes for children — it is easier for their small hands to grip a big handle than a small one — and to launch disruptive companies such as Airbnb. Located in a small office just a minute walk from the Massachusetts Institute of Technology in Cambridge, the Woodrow Wilson Academy of Teaching and Learning is home to a handful of staff and incoming students.

They are busily identifying some of the problems with current STEM teacher training and are working on ways to overcome them. One challenge is to give teachers more practice managing classrooms, working with colleagues and even dealing with parents. The staff and students came up with several ideas to address this problem.

The students do not have to be there, so teachers need to connect with them and keep them engaged if they want the students to stick around. He recalls a middle-school student who came to the clubhouse and loved video editing and animation. The student was eager to expand his skills and wanted to share what he was learning, but he was struggling at school. It would be better, he adds, to connect a lesson to existing student interests and then guide them within the constraints of the curriculum. Imagine a student with an interest in video production taking a class on environmental science.

Another idea being tried at the academy is to have students practise real-world situations through a computer simulator. For example, teachers often have to deal with upset parents but rarely get to practise that encounter before it happens in real life. Science teachers benefit from practising experiments before performing them with students.

Gaining such experience as student teachers is critical because a lack of classroom experience is inversely related to teacher effectiveness — and directly related to teacher turnover.

Position in Brief

Their first day of teaching is their first day with kids. We found this was especially true for new science teachers. A lack of practice as a student teacher translates to a lot of science teachers leaving the profession. This figure is similar to the national average, according to a study 4 by the US Department of Education. Because STEM often relies on technology and experiments, it is important to practise its use in the classroom.

One day he went to his classroom of 42 students prepared to teach a lesson on circuits. Although Wild was well-versed in the subject matter, his failure to consider space challenges and to prepare for technical problems undermined the lesson.

Another important point in teacher training, McLaren says, is to teach the teachers using the methods you want them to use in the classroom. McLaren agrees and describes an example from a professional-development workshop.

Better teachers are needed to improve science education

So to convey one of the Next Generation Science Standards such as understanding causation, teachers would be presented with classroom situations and asked to identify causes and patterns. As a result, the teachers are using evidence based on their investigation to arrive at an explanation. Osborne also encourages a shift in the way STEM teachers engage with their students. He advocates teaching argumentation in science as a way for students to understand scientific concepts.

McLaren says it takes time for teachers to learn these skills, and he was no exception. In , he won the Milken Educator Award, which is given each year to exemplary early- to mid-career teachers in each state. What would he write? This article is part of Nature Outlook: Science and technology education , an editorially independent supplement produced with the financial support of third parties. About this content. Ingersoll, R. Kappan Mag. Gray, L.

Better teachers are needed to improve science education

Download references. An essential round-up of science news, opinion and analysis, delivered to your inbox every weekday. Advanced search. Search for this author in: Pub Med Nature. PDF version. There is much overlap between scientific disciplines on the practice of using models. However, there are differences between the disciplines in employing models as the curricular focus. Hestenes , describes models as being one of the integral parts of scientific knowledge.

This is one of the major differences between biology and physics models. We reject these strict definitions of scientific and physics models and expand these definitions of models, particularly scientific models, to better function for biology. While this definition of a scientific model is more in line with modeling in biological systems, it is insufficient to shape how models can be used in a classroom.

With this in mind, we define a scientific conceptual model as a coordinated set of representations e. In addition, we contend that students should first model specific situations by constructing specific models and then abstract out to basic models Nersessian, , Basic models are models that cover all fundamental conceptions, but that are not tied to specific phenomena or systems.

In the example of L. This was later generalized to a more basic model of pathogenic bacteria. Basic models are both descriptive and explanatory, while being general enough to apply to multiple similar phenomena Halloun, The procedural knowledge that Hestenes refers to as the scientific method can be incorporated into the biology classroom through the process of developing specific models that are then abstracted out to more basic models Hestenes, UMI is a curricular framework that establishes modeling as the science classroom norm.

UMI is composed of three aspects: modeling theory of science Hestenes, ; Wells et al. UMI represents the juncture of the modeling theory of science, the modeling theory of instruction, and modeling discourse management, as seen in Figure 1. We will now describe each of these three components in further detail. Figure 1.


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UMI is considered the nexus of modeling theory of science, modeling theory of instruction, and modeling discourse management. The modeling theory of science is the basic premise that scientific paradigms, such as biology, progress through an ongoing process of model construction, validation, deployment, and revision Halloun, This basic premise also states that disciplinary knowledge is generated through this same ongoing process.

Thus, UMI rests on the epistemological foundation established by the modeling theory of science. This perspective places models in the middle of a hierarchical structure, below laws and theories but above concepts, and argues that models are the way in which scientists understand and conceptualize science Hestenes, This middle level between theories and concepts allows models to serve a critical function within science; they act as the bricks and mortar of a theory and are the basis for how scientists argue.

Therefore, they serve as the ideal level for the development of student of understanding of both concept and theory. The modeling theory of instruction serves as a framework for the application of the modeling theory of science to the classroom. The modeling theory of instruction asserts that building, validating, deploying, and revising models is the central activity of scientists, and students therefore should be engaged in a similar pursuit. Models should be the focus of the content and modeling should be the primary activity in which students are engaged throughout a science course.

The modeling theory of instruction suggests a pedagogy that is student-centered, and it intentionally creates a community of learning through student-to-student communications. This pedagogy also explicitly asks students to create, validate, deploy, and revise these scientific models. While both the modeling theory of science and the modeling theory of instruction may together establish a classroom that engages students in authentic scientific practice, we believe that it is also important to structure the discourse to support the development of models and the process of modeling.

Modeling discourse management shapes in-class discourse by providing instructors with a set of discourse management tools to guide students so that authentic science discourse occurs.

Making a connection

Seeding is the introduction of a new concept, idea, or question into an intentionally chosen small group that allows them to create their own interpretation of the concept, idea, or question Durden et al. The small group then presents the created interpretation to the whole class. Classroom discussion is generated, because students, rather than the instructor, present the idea, and this leads to a resolution. These research results are one of the motivating factors in adapting UMI to biology.

They also investigated the performance differences between students in traditional lecture courses versus those enrolled in UMI-Physics. In addition, UMI-Physics students had higher 6. However, these positive results become mixed when broken down to examine gender and ethnicity. UMI-Physics did not widen the ethnicity gap in FCI scores, the ethnicity gap in odds of success, or the gender gap for odds of success, but it did widen the gender gap for FCI score Brewe et al.