There is an ongoing debate about the fact that educational models of the industrial age are no longer adequate. Future educational models need to provide students with the abilities to solve complex problems as well as to collaborate and interact to generate new meaning and knowledge. In order to do so, teamwork activities should be pedagogically strengthened and technologically augmented in science and engineering education. This paper presents a pilot study implementing a blended learning scenario in a bachelor course at École polytechnique fédérale de Lausanne (EPFL). In this framework, digital tools are proposed to support collaboration. The tools considered are a learning experience platform, an integrated Tasks Management Application, as well as a collaborative reporting editor. This article also presents our findings on the usability and adoption of those tools, as well as preliminary results on their impact on engagement and teamwork. We also mention the effect of collaborative writing on contributions. Finally, we draw insightful lessons on engagement, the use of learning analytics, and the peer evaluation of teamwork.This paper contributes to science and engineering education by providing new insights on teamwork activities supported by digital tools in blended learning scenarios.

The value proposition canvas introduced in 2015 by Pigneur et al. is broadly used by entrepreneurs and intrapreneurs to create new services and products. We decided to apply it for collaborative and blended design thinking activities in a specialization in human-Computer interaction for master students in computer and data sciences. While being very useful, the original value proposition canvas relies on a business-oriented vocabulary not familiar to science and engineering students. Moreover, its underlying profit-oriented objective makes it difficult to focus on impact and trust-oriented design activities. In this paper, we propose two alternative value proposition canvases, one dedicated to sustainability for development and one to explainability for artificial intelligence. The motivations why and the ways how these alternative canvases were elicited and used in higher education are also discussed.