Engineering and Physics Students’ Perceptions About Learning Quantum Mechanics via Computer Simulations

Quantum mechanics (QM) is an important topic in engineering and physics, necessary for both the mathematical and physical prediction and explanation of a particle’s behavior at atomic and subatomic levels. Computer simulations provide an advantage for helping students make sense of abstract concepts and visualize complex phenomena in the process of developing a conceptual understanding of quantum knowledge. Students’ experiences and attitudes about learning via computer simulations can inform educational design and improve content delivery. In this paper, we studied students’ perspective about how simulations influenced their QM learning. Results of this study showed that most students agreed that simulations are helpful for their QM learning. The positive feedback from freshman and sophomore students focused mainly on basic interactive functions of simulations. Such functionality included: ease of operation, direct visualization, and animated demonstration. Senior level students were more critical of simulations in their descriptions, pointing out the limitations of the models behind the physical explanations and the authenticity of the computational representations. Based on these research findings, we provided recommendations to improve simulation-based instructional design. Background and Motivation Quantum mechanics (QM) constitutes the theoretical basis to explore unknown physical phenomena in the quantum world, which enables scientists and engineers to use the different features of atomic and molecular structures to develop innovative technologies. The concepts and objects in the quantum world are hard to visualize and difficult to describe because of their abstract nature. In learning QM, students are required to abandon models and intuitive analogies they have learned in classical physics. Invisibility and counterintuitive transitions are two major challenges for students when studying QM. Cognitive studies have demonstrated that students experience difficulty in learning physical concepts when those concepts are not directly observable. In QM study, most of the phenomena cannot be demonstrated using manipulative or concrete models that closely and precisely represent reality. Indeed, educators and researchers have debated about issues regarding teaching and learning of QM for several decades—e.g., when is it developmentally appropriate to introduce QM ideas? What are the most effective pedagogies for teaching QM? Research has shown that quantum concepts generally have been taught via traditional instructional methods, often resulting in disappointment and confusion for students as they make the transition from a deterministic to a probabilistic perspective. With this in mind, researchers have started to develop and test innovative teaching strategies and educational tools for the teaching and learning of QM among different age groups. For example, Olsen conducted a study to examine high school students’ conceptual understandings after traditional QM lecture. His essential finding was that students could only show a partial understanding on the wave-particle duality. Some students continued to demonstrate non-normative conceptions that were rooted in classical point of view, e.g., electrons’ momentum and kinetic energy. In a study examining meaningful learning process, Hilger et al. used mind and concept maps to facilitate the concept learning on quantization, uncertainty, state, and superposition of states to third-year high school students. Throughout the unit, students articulated their understandings with mind and concept maps, which indicated the some level of sophistication in definitions and connections between terms. As another example, Fanaro et al. adjusted the Conceptual Structure of Reference (CSR) based on the Feynman’s Path Integral Method and designed a Proposed Conceptual Structure for Teaching (PCST) to teach high school students some fundamental ideas of quantum mechanics without using mathematical formalism. During the intervention, students used simulation software that designed to visualize the double slit experiment without involving mathematical formalism. The researchers found that students were able to justify the given quantum phenomena, draw graphs based on the data and compare the results, and predict the results of simulation after setting the initial conditions. At university level, Johnston and colleagues examined how third-year-level students who completed traditional quantum mechanics course conceptualized wave-particle paradox, wave properties and probability. They conducted a survey consisting of open-ended, contentfocused questions. After analyzing students’ responses, researchers found that even though students’ models seemed to be advanced at the individual level, there were no connections between models that constituted the components of a consistent structure. The researchers concluded that learning occurred only on the surface level. Students were not able to internalize and logically construct knowledge. In a similar study, Müller and Wiesner investigated students’ learning of basic quantum phenomena such as photon, electron, atom models, and the Heisenberg uncertainty principle using virtual laboratories. They found that almost all students accurately conceptualized the quantum phenomena. Zollman and his colleagues argued that quantum mechanics learning is not as difficult as it is commonly perceived. They suggested that non-science high school and first year college students have the capacity to comprehend quantum mechanics without classical mechanics backgrounds. However, to accomplish this, instruction has to be carefully and internationally designed. Thus, they developed a new instructional design for quantum mechanics that included handson activities and a computer-based simulation. 175 teachers in 160 schools implemented the instructional unit in their classrooms. The results indicated that visual QM tools facilitated the learning of students who were considered “novice” in science and math. The materials also increase the understanding of QM concepts for science and engineering students. In these studies, computer-based simulation tools were extensively used in increasing students’ quantum learning, both conceptually and practically. On one hand, the visualization capabilities, especially dynamic behavior, provided idealized representations of complex underlying mathematical models of quantum phenomena that could not be described by words or observed by experiments. On the other hand, the interactive capabilities of simulations showed great advantages in helping students test as well as manipulate abstract concepts, and therefore improved their learning by facilitating students’ building of dynamic models. Further, an implication of these studies is that new computer simulation designs should consider research-based cognitive and pedagogical studies to effectively integrate them in classroom settings. One of examples is the Quantum Interactive Learning Tutorials (QuILTs) along with the peer instruction tools developed by the research group in University of Pittsburgh. The feature of QuILTs simulation modules is that the developers combine verbal tutorials to guide students to discover the non-normative conceptions and then scaffolds their development of normative conceptions. As supplemental materials, the tutorials play an important role in bridging “the gap between the abstract quantitative formalism of quantum mechanics and the qualitative understanding necessary to explain and predict diverse physical phenomena” (p.47). Another commendable simulation tool is the Physics Education Technology (PhET) simulation series from University of Colorado Boulder. The PhET simulations feature multiple scientific visualizations of basic concepts. With dynamic guidance and feedback when exploring scientific puzzles and phenomena, students can create intuitive models along with interactive connections between concepts under study. All of these inquiry features make PhET simulations educationally effective tools for engaging students in physical science learning. Simulation use has been extensively accepted as an innovative instructional approach for quantum mechanics education. As the foundation of modern engineering and nanotechnology, quantum mechanics has immense influence on multiple engineering disciplines as well as science disciplines. Hence, as part of a design-based process for creating simulations, it is important to consider different perspectives on how students perceive simulations as learning tools. With this in mind, the overarching research question for this study was: • What are engineering and physics students’ perceptions of the educational value of using simulation tools for quantum mechanics learning? Method and Research Design This work is part of Quantum Learning in Engineering And Physics (Quantum LEAP) project. The Quantum LEAP project aims to develop an integrated framework for the design and assessment of effective simulation-based learning environments for quantum education based on studies about engineering and physics students’ non-normative conceptions and metacognitive learning strategies. Research Design. The presented study is guided by interpretive research design. Interpretive research design enables the researcher to presume that knowledge and understanding are results of interpretation and based on individual’s subjective experiences. Interpretive researches consider that knowledge and understanding are socially constructed and that the researcher plays an important role in explaining the process of knowledge/understanding construction. Our goal with this research setting is to investigate human-technology interaction in a natural social setting. To achieve this goal, an interpretive researcher focuses on obtaining meaning from data sources such as interviews and observation. Therefore, with this study we focused on analyzing