Now that we've made the technological advancements in our NSF Cyberlearning grant by publicly releasing Physics Toolbox AR Field Visualizer for Android (as well as embedding it into our Suite), we now turn toward how we hope to use the app as a tool to support learning. While our focus is on learners in secondary and tertiary education, we look to K-12 education to see what educational stakeholders and other STEM professionals view as "essential" to general science literacy, and then to extant research to understand learners' struggles with conceptualizing fields.
In the Framework for K-12 Science Education (National Research Council, 2013), the United States recognized the importance of including fields (electric, magnetic, and gravitational) as an underlying disciplinary core idea that should permeate a study of forces and energy. The authors of the Next Generation Science Standards pushed for the inclusion of fields starting as early as the 7th grade (NGSS Lead States, 2013).
Although the performance expectations ask students to look for evidence of fields based on the interaction of forces, they do not go so far as to visualize fields. Most of the references to magnetic fields fall within the Framework disciplinary core idea PS2.B: Types of Interactions. The relevant sub-ideas are listed below.
PS2.B: Types of Interactions
Electric and magnetic (electromagnetic) forces can be attractive or repulsive, and their sizes depend on the magnitudes of the charges, currents, or magnetic strengths involved and on the distances between the interacting objects.
Forces that act at a distance (electric, magnetic, and gravitational) can be explained by fields that extend through space and can be mapped by their effect on a test object (a charged object, a magnet, or a ball, respectively).
At least three relevant performance expectations emanate from this disciplinary core idea—two for middle school (MS-PS2-3 and MS-PS2-5) and one from high school (HS-PS2-5). Although the high school standard is linked to a science and engineering practice associated with providing evidence for and testing models, this is difficult, if not impossible, to accomplish robustly without visualization tools to see the cause of these interactions. In many cases, students use small compasses to explore magnetic fields around current-carrying wires, but we hope that we can improve upon this visualization with the help of AR.
MS-PS2-3. Ask questions about data to determine the factors that affect the strength of electric and magnetic forces. [Clarification Statement: Examples of devices that use electric and magnetic forces could include electromagnets, electric motors, or generators. Examples of data could include the effect of the number of turns of wire on the strength of an electromagnet, or the effect of increasing the number or strength of magnets on the speed of an electric motor.] [Assessment Boundary: Assessment about questions that require quantitative answers is limited to proportional reasoning and algebraic thinking.]
MS-PS2-5. Conduct an investigation and evaluate the experimental design to provide evidence that fields exist between objects exerting forces on each other even though the objects are not in contact. [Clarification Statement: Examples of this phenomenon could include the interactions of magnets, electrically-charged strips of tape, and electrically-charged pith balls. Examples of investigations could include first-hand experiences or simulations.] [Assessment Boundary: Assessment is limited to electric and magnetic fields, and limited to qualitative evidence for the existence of fields.]
HS-PS2-5. Plan and conduct an investigation to provide evidence that an electric current can produce a magnetic field and that a changing magnetic field can produce an electric current. [Assessment Boundary: Assessment is limited to designing and conducting investigations with provided materials and tools.]
With few tools to help students deeply understand invisible magnetic phenomena, we want to take a deep dive into creating a learning experience the addresses common pitfalls in conceptualizing fields.
Fortunately, students’ difficulties with magnetic fields are well-documented (Maloney, et al., 2001), with students demonstrating problems with understandings about magnetic force, magnetic field caused by a current, and magnetic field superposition. After giving an assessment based on the identified problem areas to undergraduate introductory physics students, Maloney reports that “overall pretest scores are very weak, being barely above random choice for the algebra [-based physics] students.” This suggests that students learned very little of value about magnetic fields in high school.
Interestingly, students were shown to do better on electricity assessments than on magnetism assessments—this is especially true for algebra-based physics students. Magnetism is likely to have a greater reliance on the field model, whereas students’ understandings about electricity are often supported by the concept of electrical flow. Other validated assessments of student conceptual understanding of magnetism have shown similar results (Ding et al., 2006). An analysis of gender differences on a similar Magnetism Conceptual Survey have shown that while gender has no bearing on pre-test performance, males significantly outperform women on post-tests (Li & Sing, 2011). This difference merits some attention in ensuring equitable experiences for students for learning about magnetic fields.
In the past few decades, researchers have developed a number of other diagnostic tools that attempt to break up the conceptual understanding of magnetism, including the Brief Electricity and Magnetism Assessment, Conceptual Survey of Electricity and Magnetism, and the Diagnostic Exam for Introductory Undergraduate Electricity and Magnetism. However, most of these assessments focus on electromagnetic relationships, rather than on field visualizations. On any assessment, very few questions focus on elementary or basic concepts that can also be hard to grasp, such as the three-dimensional nature of fields, irregularly-shaped fields, field intensity, or magnetic fields contextualized by Earth and space science.
Many educators' lack of insight into student learning about magnetic fields has led to a persistence of poor instruction. When looking beyond simple conceptual knowledge, an investigation by Greca and Moreira (1997) on university engineering students in introductory physics showed that students tended to build “propositional” understandings of magnetic fields that are heavily dependent upon algebraic relationships for solving analytical problems, likely because this is what is typically emphasized by instructors.
However, what is often needed for real-world workforce applications is a more robust set of mental models to solve more complex, often conceptual types of problems that relate to field interactions.
The use of AR to teach about magnetic fields is in its infancy, but AR has been gaining special attention for field-based topics because of its conceptual reliance upon spatial components. Some efforts to visualize both electric and magnetic fields have be implemented, but are reliant upon pre-calculated fields and the use of visual markers such as a printed image of a magnet or the Earth on which the magnetic field is displayed (Buchau et al., 2009; Billinghurst & Duenser, 2012; Ibanez, et al., 2014). Some attempts have been made to connect to sensor-based real-time changes of physical objects to visualizations in a computational environment. In a study by Scheucher et al. (2009), students at MIT used avatars to collaborate with classmates in a virtual world to modify a simulated induced magnetic field surrounding two coils. Changes made in the virtual world’s lab environment were transmitted to the actual coils, and returning data on how this impacted the current flowing through the device were used to visualize the simulated magnetic field in the virtual world. All of the aforementioned research experiences, although they illuminated the possibilities associated with 3-D visualization, were dependent either upon specialized hardware or lab equipment that is not accessible to wide audiences, and only presented students with idealized simulations. Beyond the ability of teachers to convey 3-D images, however, of great promise is the education research that suggests that AR has the added benefit that visuospatial capabilities can be improved through augmented reality (Martín-Gutiérrez et al., 2010).
There is some evidence that teaching about magnetic fields with AR improves both general learning outcomes and enhanced student-reported interest when compared to traditional instruction. Students who used the AR-supported visualizations allowing them to visualize and interact with fields, such as changing the polarity of a bar magnet target by rotating it, demonstrated significantly increased gains and long-term retention, as opposed to those who did not use the AR-supports (Billinghurst & Duenser, 2012). In one other study, high school students used a web-based tutorial or an AR-based electromagnetic field visualization tool using physically-manipulated targets (plastic paddles with visual cues printed on them that they could move around the space viewed by the camera) to learn the same concepts in electromagnetism, with an emphasis on visualizing the magnetic field produced around a current-carrying wire. The students using the AR-based visualization tool reported characteristics of higher “flow” in the learning process (including better concentration, greater sense of time distortion, better sense of control, clearer direct feedback, and more intrinsic satisfaction) than those who used the web tutorial. Moreover, the students using AR scored higher gains on pre/post testing of electromagnetic concepts, especially on those questions relating to visualization of fields. Although focused on whole classroom instructional, early research with MIT’s Technology-Enabled Active Learning (TEAL) project demonstrated that active introductory physics instruction that included hands-on activities supplemented by computer-based 3-D visualization of electromagnetic fields produced significantly greater student gains that those who received traditional lecture instruction (Dori, Y. J. & Belcher, J.; 2005).
Collectively, the research to date on magnetic fields and AR visualizations make a good case for the potential of tools like Physics Toolbox AR. In our next blog, we will explore the specific topics and assessments we are considering for use in our own research.
This work is funded by NSF Grant #1822728. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.