Brazilian, born in Marilia/São Paulo, 39, I live in Londrina, Brazil.
Currently, I am an Associate Professor at the Federal Institute of Mato Grosso do Sul. I have a doctorate degree in Computer Science Education from Aalto University under the supervision of Professor Lauri Malmi.
My research interests are the psychology of programming, cognitive complexity of computer programs, notional machines, plan-composition strategies, instruments to evaluate prior programming knowledge, instructional design differences in teaching programming to K-12 and undergraduate students, and K-12 students' CS projects in Science Fairs.
I have a bachelor's in Computer Science from Londrina State University (2002) and a Master's degree in Computer Graphics from the University of São Paulo (2005). Worked with home automation systems as a software developer and I am a senior lecturer at the Mato Grosso do Sul Federal Institute of Science and Technology since 2011.
COGNITIVE COMPLEXITY OF COMPUTER PROGRAMS
I am interested in defining and evaluating the cognitive complexity of computer programs. I have developed (with Juha Sorva and Sofia Leite) a model to extract meaningful metrics of cognitive complexity from computer programs (our work presented at ICER 2018, here). Currently, I am collecting data to support this model and provide more evidence to further improve it.
Program Comprehension and Plan-Composition Strategies
At ITiCSE 2017 WG5, we suggested that readability is one of the most important factor students, instructors and professional developers value regarding code quality. You can see the result of this work here.
I am interested in how students read and comprehend code and how merged vs sequenced plan-composition strategies impact code comprehension and what kind of patterns or strategies students use to read these types of programs.
Evaluating prior-programming knowledge
I developed (with my Aalto co-authors Jan-Mikael Rybicki, Sanna Suoranta, Arto Hellas, and Juha Sorva) a Self-Evaluation Instrument (SEI) to investigate in detail students' prior knowledge in concepts usually taught in CS1 courses.
We compared the SEI to previous background metrics (our work presented at ITiCSE 2019, here) and course grades and other tests, such as the SCS1 (our work presented at ICER 2019, here). We will continue to develop this instrument and validate it by applying the SEI in other contexts.
Psychology of programming and differences between K-12 and Undergrad contexts
My institution allows me to teach to undergraduate and vocational high school students. It is a peculiar context and very little explored:
- Very often I teach the same topic to HS and undergrads. In the same day.
- The programming classes are mandatory for all high-school students! And they learn not only basic programming concepts, but Data Bases, networks, web development, operational systems and software engineering as well.
- We have gender balance!
- Most of HS students don't want to go to a CS undergraduate course later!
I want to explore this context and investigate how the differences in these two contexts impact instructional design of programming classes, how the HS students learn programming and how it compares to the Undergrad students. Interested in this research setting? Want to explore it too? Contact me!
K-12 CS projects in Science Fairs
Well, a very interesting approach to allow students to express themselves through projects in our HS CS courses is to let them develop any kind of projects, from the most basic to the most complex ones. However, most of these projects are not research oriented and traditional venues such as conferences were not suited to this kind of work.
The science fairs proved to be a very engaging context for students. Not only they are able to show their projects to everyone, but also develop their communication, scientific writing and networking skills. We have being very successful and our students were awarded with regional, national and even being able to show their projects in the biggest stage, the Intel ISEF science fair.
I am interested in how the science fair impacts student engagement, what kind of CS projects students present at these science fairs, how impacts their choice regarding STEM careers and what kind of difficulties they face when developing these kind of complex projects.
Rodrigo Duran. 2017. Towards a Fine-grained Analysis of Complexity of Programming Tasks. In Proceedings of the 2017 ACM Conference on International Computing Education Research (ICER '17). ACM, New York, NY, USA, 271-272. DOI: https://doi.org/10.1145/3105726.3105731
Haaranen, Lassi, & Duran, Rodrigo. (2017). Link Between Gaming Communities in YouTube and Computer Science. In CSEDU (2) (pp. 17-24).
Haaranen, Lassi., & Duran, Rodrigo. (2017, April). Computer Science in Online Gaming Communities. In International Conference on Computer Supported Education (pp. 279-299). Springer, Cham.
Jürgen Börstler, Harald Störrle, Daniel Toll, Jelle van Assema, Rodrigo Duran, Sara Hooshangi, Johan Jeuring, Hieke Keuning, Carsten Kleiner, and Bonnie MacKellar. 2018. "I know it when I see it" Perceptions of Code Quality: ITiCSE '17 Working Group Report. In Proceedings of the 2017 ITiCSE Conference on Working Group Reports (ITiCSE-WGR '17). ACM, New York, NY, USA, 70-85. DOI: https://doi.org/10.1145/3174781.3174785
Rodrigo Duran. 2018. Towards an Instructional Design of Complex Learning in Introductory Programming Courses. In Proceedings of the 2018 ACM Conference on International Computing Education Research (ICER '18). ACM, New York, NY, USA, 262-263. DOI: https://doi.org/10.1145/3230977.3231007
Rodrigo Duran, Juha Sorva, and Sofia Leite. 2018. Towards an Analysis of Program Complexity From a Cognitive Perspective. In Proceedings of the 2018 ACM Conference on International Computing Education Research (ICER '18). ACM, New York, NY, USA, 21-30. DOI: https://doi.org/10.1145/3230977.3230986
Rodrigo Duran, Jan-Mikael Rybicki, Sanna Suoranta, and Arto Hellas. Towards a Common Instrument for Measuring Prior Programming Knowledge. In Proceedings of the 24th Annual ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE 2019). ACM, New York, NY, USA, 6. https://doi.org/10.1145/3304221.3319755
Rodrigo Duran, Jan-Mikael Rybicki, Juha Sorva, and Arto Hellas. Exploring the Value of Student Self-Evaluation in Introductory Programming. In Proceedings of the 2019 ACM Conference on International Computing Education Research (ICER '19). ACM, New York, NY, USA, 21-30. DOI: https://doi.org/10.1145/3291279.3339407
Pirttinen, Nea, Arto Hellas, Lassi Haaranen, and Rodrigo Duran. "Study Major, Gender, and Confidence Gap: Effects on Experience, Performance, and Self-Efficacy in Introductory Programming." In 2020 IEEE Frontiers in Education Conference (FIE), pp. 1-7. IEEE, 2020.
Zavgorodniaia, Albina, Rodrigo Duran, Arto Hellas, Otto Seppala, and Juha Sorva. "Measuring the cognitive load of learning to program: A replication study." In United Kingdom & Ireland Computing Education Research conference., pp. 3-9. 2020.
Bispo Jr, Esdras Lins, André Raabe, Ecivaldo Matos, Eleandro Maschio, Ellen Barbosa, Leandro Carvalho, Roberto Bittencourt, Rodrigo Duran, and Taciana Falcão. "Tecnologias na educaçao em computaçao: Primeiros referenciais." Revista Brasileira de Informática na Educação 28 (2020): 509-527.
Duran, Rodrigo, Lassi Haaranen, and Arto Hellas. "Gender Differences in Introductory Programming: Comparing MOOCs and Local Courses." In Proceedings of the 51st ACM Technical Symposium on Computer Science Education, pp. 692-698. 2020.