A journal paper detailing the data collected over the past three years of utilizing MediaLib is currently conditionally accepted and will be available soon.
Adam Wynn, Jingyun Wang and Andrea Valente
Proceedings of the 2024 Innovation and Technology in Computer Science Education V. 2 (ITiCSE 2024)
Abstract: Beginner programmers can develop an intuitive understanding of programming by leveraging the motivating field of multimedia to visually inspect outputs and experiment with different ways to solve problems. This paper presents MediaLib, a Python library designed to facilitate multimedia programming and lessen the cognitive load associated with programming for novice programmers. In addition, we designed an official MediaLib website which contains the library itself, two tutorials, and clear documentation. The tutorial clearly presents the learning objectives of each lesson and contains exercises related to MediaLib. We designed these exercises to help students gain knowledge incrementally, without requiring in-depth maths knowledge.
Min Lu, Jingyun Wang, Masatoshi Arikawa and Ryo Sato
85th National Convention of the Information Processing Society of Japan (2023)
Abstract: In recent years, programming education has become increasingly compulsory in secondary education. However, in higher education, the majority of undergraduate students in their early years are still novices at programming. Conventional programming learning materials for university students are primarily aimed at students specializing in information systems, and the exercises contain many abstract learning contents such as numerical processing and text processing, which fail to pique students' interest. MediaLib, which we have been focusing on, is a Python library based on PyGame that can achieve simple multimedia functions with simple code, and has the potential to pique students' interest. In this presentation, we will introduce the design and implementation of lessons using MediaLib, and report on the efforts and trial and error results of our efforts to deepen students' understanding of mechanisms such as control syntax.
Andrea Valente, Emanuela Marchetti and Jingyun Wang
2020 9th International Congress on Advanced Applied Informatics (IIAI-AAI 2020), 169-175
Abstract: Starting from our teaching experience and previous research on programming for non-technical university students in Japan and Denmark, we identify an unarticulated dependency of programming materials from other technical domains, which causes a knowledge domain mismatch in learners. We approach this mismatch on two fronts: by defining a novel way to structure beginners courses that moves away from the classic bottom-up approach based on math-related problems, and instead leverages on multimedia as a motivational and powerful general-purpose domain to ground programming and scaffold its understanding; and via the design and implementation of new Python library that simplifies multimedia programming. We are currently organizing tests of both multimedia library and the new course structure in Japan and Denmark.
doi: 10.1109/IIAI-AAI50415.2020.00041