Jingyun Wang, Adam Wynn, Andrea Valente, Daner Sun and Emanuela Marchetti
Smart Learning Environments (2026)
Abstract: Multimedia has been recognised as a powerful domain for contextualising programming concepts. However, the inherent complexity of multimedia applications, particularly their reliance on advanced data structures, often poses significant challenges for novice programmers. To address this issue, we implemented Medialib, a user-friendly Python multimedia library specifically designed for beginners at or above the high school level. Medialib was developed through an iterative process informed by empirical studies involving non-technical university students and their instructors, with the goal of making multimedia programming more accessible to learners without prior technical backgrounds. This paper introduces, for the first time, a simplified multimedia Python library and accompanying pedagogical materials tailored to the cognitive and instructional needs of novice programmers. Medialib enables a pedagogical shift in introductory Python courses from traditional mathematics-oriented exercises to multimedia-focused tasks. To evaluate its effectiveness and transferability, two empirical studies were conducted: a 14-week study in Japan (21 instructional hours, 36 students) and a 2-week study in the UK (12 instructional hours, 84 students). Analyses are done on the study data which includes teacher observational notes, questionnaires, and interviews. Specifically, a comparison of the weekly performance of learners in traditional maths-related exercises and Medialib-related exercises in the first study is discussed. Findings from both studies indicate that learners responded positively to the Medialib materials. Notably, in the Japanese study, students who initially struggled with maths-related programming tasks were able to successfully acquire foundational programming skills through Medialib activities. From week 7 onward, students consistently demonstrated strong performance in both types of exercises, suggesting that Medialib serves not only as an effective entry point for programming education but also as a transferable learning scaffold across contexts.
doi: 10.1186/s40561-026-00450-4
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
