Sem Sælands vei 24
What do we mean by "learning programming", why do many find it challenging to learn, what are really the main challenges, which aspects do people in different settings need to learn and how do they best learn it? Geir Kjetil Sandve will give a brief introduction to a discussion where we look forward to hearing experiences and viewpoints inspired by the myriad settings where people in our environment have been involved in programming.
Tor Ole Odden:
"The field of educational research has a massive literature base, with many journals that have been publishing articles for almost a century (or longer). How do we sort through and make sense of literature at this scale? We have begun using an unsupervised machine learning technique from the field of natural language processing, known as latent Dirichlet allocation, to analyze articles from the fields of physics education research and science education research. This technique allows us to extract latent themes, or topics, from the literature and quantify the rise and fall of those topics over time.
In this talk, I will present the basics of the technique, describe some of its underlying theory and applications, and showcase some of the trends that it reveals in how science education theory and practice has evolved over the last 20-100 years."
Doctoral candidate John Mark Aiken at the Department of Physics, Faculty of Mathematics and Natural Sciences, is defending the thesis "Understanding University Student Pathways Towards Graduation with Machine Learning and Institutional Data" for the degree of Philosophiae Doctor.
Computer science was originally invented as a tool to support learning in other disciplines, including engineering and economics. Today, most of computer science education is aimed at preparing future software developers. How do we broaden the appeal of and access to computer science education, to something closer to what the inventors of the field had in mind?
Practical work like laboratory work and fieldwork is integrated parts of many science educational programmes. However what do students learn through practical work?, and is it the same in different types of practical work?
The ScienceAtHome group at Aarhus University has developed a number of games and tools for quantum-physics-based citizen science and education. One of these tools, Quantum Composer, allows students and researchers to explore quantum mechanics in one dimension.
We have developed a framework to describe the modeling process in physics laboratory activities.
This talk investigates what it means to learn computer science content, how we might better support computer science learning, and how we might better understand what learners know.
The presentation touches on learning goals, assessment, and teaching practices around computation and discusses research that has been carried out in the context of P-Cubed that has informed our thinking and resulted in iterations on our design.
A curriculum for the introductory calculus-based course taken by beginning university science and engineering students, takes a contemporary perspective on introductory-level physics.
Although quantitative approaches to data generation, collection and analysis are common in physics education research (PER), they are frequently misunderstood even among veteran scholars in the field.
New trends in physics education stress the importance of an inquiry based learning. Arduino and smartphones make it possible for every student to perform quantitative, precise and instructive experiments, even at home. Both tools can be exploited at universities as well as in high schools and are complementary to each other.
In this session, we describe how peer observation can be used to promote lasting adoption of evidence-based instructional practices.
Sociologists and historians of science/engineering have documented the salience of meritocracy and technocracy in engineering and engineering education (Cech, 2014; Slaton, 2015; Riley, 2008). Meritocracy, a problematic worldview, conveys that “worth” accrues with an individual based solely on their own accomplishment.
Counting problems have been shown to be challenging for students to solve correctly, and one reason is that they can be difficult to verify (e.g., Eizenberg & Zaslavsky, 2004).
In response to the growing emphasis on computational thinking in K-12 education standards and modern science professions, our research team designed a year-long professional development series for high school physics teachers to learn how to program and utilize computer simulations in their curricula.
The State of Equity in College Physics Student Learning in the United States: a Critical Quantitative Intersectionality Investigation
Meet Felek Baran: She has a PhD in chemistry education and will tell us about her work. She has a workplace at ILS but will work with both KURT and ILS on science education.
In this seminar, we share some of the work that is being done to prepare to teach programming as part Norwegian Math and Science Curriculum Redesign in 2020.