Memo #3

Jackson, Dukerich, and Hestenes: Modeling Instruction: An Effective Model for Science Education

          The authors describe modeling as hands-on experience by building and applying models of concepts that students learn in class. Previous research has shown that modeling instruction can help students speak more eloquently, confidently, and in-depth about the scientific concepts that they learn about. This learning style also prevents students from falling victim to inactivity, indifference, and non-participation in their science education by allowing students to predict, visualize, and work collaboratively on understanding their models. The authors go on to describe a “before-and-after” process for using the modeling in the classroom: model development, where the students create their own model and analyze data, and model deployment, where students apply their models to practice problems and examinations.

•  ·             Reconstructing knowledge: modeling can be used as a technique to help students lose their false preconceptions about scientific concepts without simply explaining why their beliefs about scientific phenomena are incorrect.
• ·             Inquiry-based learning: experiments are set up in a way that allows the students to truly delve into the material. Teachers must give the students freedom to fail at constructing models in order to allow students to grapple with scientific concepts on their own.

Lehrer and Schauble: What Kind of Explanation is a Model?

Lehrer and Schauble have a similar definition of modeling, which uses tangible, real-world analogies to represent scientific concepts. While they argue that modeling instruction is not a natural learning process for novice thinkers, the authors note that experimentation and graphical analysis of data foster inquiry-based learning in students. To expose novice thinkers to the benefits of modeling, teachers can help students “arrange conditions for seeing” and “invent measures,” or let the students determine what materials might be used and what qualities can be measured to model a certain concept.  

• ·             Experimentation vs. right answers: the authors emphasize the way in which students should be able to construct, revise, and discuss the effectiveness of various models instead of trying to determine what representation is considered “correct.”
• ·             Discussion and collaboration: students need to work cooperatively to evaluate each other’s ideas, ask quality questions about experimental modeling, and analyze evidence.

Lehrer, Schauble, and Petrosino: Reconsidering the Role of Experiment in Science Education

The authors here argue that teachers should not place too much emphasis on experiments in science education. Teachers must scaffold experiments with design, inquiry, and focus on specific testable qualities to help the students understand the purpose of the experiment. Furthermore, students can learn the effectiveness of various inscriptions to understand how well data and their related models represent the realities of scientific phenomena.

• ·             Experiments vs. models: the authors indicate that typical classroom experimentation either replicates experiments with known outcomes or limits students’ ability to think abstractly about the topics they are meant to explore. Models, however, allow the students more freedom to represent classroom concepts based on their own inquiry.
• ·             Continuous development of modeling skills: the authors demonstrate modeling at different ages, showing how, with age, students are able to gain new skills. (For example: third grade students were able to represent their experiments qualitatively and mathematically, whereas the majority of first grade observation was strictly qualitative).

Overall, these readings emphasized how to use modeling instruction in elementary education classrooms. While standardized experiments have their role, the authors argue that experimenting should serve as part of a larger model of inquiry and representation, not as the initial objective. This limit on experiments helps ensure that science education is more open-ended. Similarly, the readings helped outline a various facets of modeling instruction and how to apply it to teaching, including inquiry-based discussion, model representation, and scaffolding.

While I am generally a strong proponent of modeling instruction, I wonder how much information should be modeled in the classroom. Given time constraints, testing, etc., how can we balance modeling and teacher-based instruction? How far should this balance lean towards student modeling?