Program - Computational Physics in a Nordic Perspective
14.00-14.15: Anders Malthe-Sørenssen: Welcome
14.15-14.45: Urban Ericsson (Lund University, Sweden): ”What does this picture have to do with learning physics?” On learning and communication from representations.
When entering a new discipline, one must learn the ways that the discipline communicates its knowledge. This involves learning how to ”read” and ”write” all the representations the discipline use for communication, such as text, mathematics, graphs, tables, simulations, programming, gestures, etc. It is like learning a new language!
In this talk I will address some learning challenges that novice students face when entering the science disciplines, in particular physics and astronomy, and bring to the fore some educational implications based on various representation and in particular computer simulations.
Bio: Assoc. Prof. Urban Eriksson (PhD, Docent) is scientific leader of Lund University Physics Education Research (LUPER) group and director of the National resource centre for physics education in Sweden. He has a background as a physics and mathematics teacher and has +25 years’ experience in science teacher education. His research focuses on learning and communication and in particular university students struggle to learn about universe, from the smallest particles to the largest structures, i.e., their struggle with traversing the powers of 10 in spatio-temporal scales.
14.45-14.55: Discussion
14.55-15.05: Pause
15.05-15.35: Kim Svensson (Lund University, Sweden): Programming to learn physics
Learning is a complicated process that involves discovery, exploration, realization, communication, and creation. Not all learning tasks afford all of these activities and creating such a task is difficult. However, one activity that comes close, is programming. By using programming as a tool to understand something, such as physics, programming can be analysed and its role in the meaning-making process can be understood.
Programming provide opportunity to unpack, filter, highlight, and iterate through different aspects, and each step allows for the discernment of something new. Through the act of coding, visualising, and interacting with simulations, the programmer can begin to explore, ask questions, gain insight, and, eventually, learn about different physical concepts and ideas.
Bio: Kim Svensson is a PhD student at the National resource centre for physics education at Lund University. He is part of the Lund University Physics Education Research (LUPER) group where he is focusing on understanding the role and dynamics of representations in the learning process. This is done in a physics context with a focus on the construction, interaction, communication, and interpretation of representations. Kim has used programming as tool to examine these ideas and has shown that programming is a potent meaning-making tool if its affordances are used.
15.35-15.45: Discussion
15.45-16: Pause
16-16.30: Sehoya Harris Cotner: Maximizing student learning with Open-Source, Course-Based Research Experiences (OSCREs)
Some recent collaborations merge two high-impact practices —authentic, course-based research experiences (CREs) and Open Science (OS). Open-Source Course-Based Research Experiences (OSCREs) provide a platform for educators to develop and implement meaningful activities that promote science practice, data literacy, and general skills (e.g., communication, collaboration) —all in the context of existing curricula.
In this seminar, I will present OSCREs, provide some recent examples, and discuss emerging related projects in Norwegian higher education.
16.30-16.45: Discussion
16.45-16.55: Pause
16.55-17.20: Geir Kjetil Ferkingstad Sandve: Can programming be used as an alternative basis for learning statistics?
Almost any statistician today rely on computers, and almost any student will use programming as part of a course in statistics. However, programming arguably serves more of an auxiliary role in typical statistics courses, being drawn in for exemplifications or student exercises, after a topic has already been introduced and explained based on other perspectives.
For students that have good prior programming skills, an intriguing alternative is to use programming-based exploration as a core technique for helping the students in forming their initial intuition about core topics in statistics. These students may find it easier to form their initial understanding of a statistics concept by relating to an incrementally developed computer program, and afterwards connect this with established terminology and mathematical properties, rather than vice versa.
I will show some very brief examples of what we envision that such a programming-driven learning process might looks like, ranging from absolute basics like what a random variable or a probability distribution is, to more advanced techniques like Bayesian marginalization.
17.20-17.50: Andreas Haraldsrud (University of Oslo, CCSE): How does computation and numerical methods shape how students think and make sense of chemistry?
In this talk, I will present research on how chemistry students think about mathematics in a chemical context, and how computations and numerical methods can shape this way of thinking. I will discuss how numerical methods can be used to understand conceptual mathematics and how computation can be a valuable tool in exploring dynamic systems and understanding models in physical chemistry.
17.50-18: Anders Malthe-Sørenssen: CCSE 2021: short yearly review