Marc Lafuente Martinez | EPFL Graph Search

Scientist, researcher, policy advisor, teacher and educator in general. Also, street flâneur and amateur chess player. Marc focusses his research on educational innovation and learning improvement, digital technologies and system change.Marc holds a PhD. in Educational Psychology and a Bachelor's in Psychology from the University of Barcelona where he also taught. He's been an international policy analyst at the OECD where he led a project on pedagogical innovation addressed to a number of education ministries. He has been a lecturer at the Open University of Catalonia (Spain), and has performed research stays at McGill University (Canada) and Southern Cross University (Australia).Apart from his current research at EPFL on topics like computational thinking, project-based learning, and ethical competence, he collaborates with several think-tanks and governmental agencies across the EU.

Assessing Computational Thinking: Development and Validation of the Algorithmic Thinking Test for Adults

Cécile Hardebolle, Marc Lafuente Martinez, Olivier Lévêque

This study describes the development and validation process of a computational thinking (CT) test for adults. The team designed a set of items and explored a subset of those through two qualitative pilots. Then, in order to provide validity evidence based on the test content, a team of 11 subject-matter experts coded the initial pool of items using two different systems of categories based on CT components and contents. Next, the items were piloted on a sample of 289 participants, 137 experts in CT, and 152 novices. After a series of confirmatory factor analyses, a unidimensional model that represents algorithmic thinking was adopted. Further analyzing the psychometric quality of the 27 items, 20 of them with excellent reliability indices were selected for the test. Thus, this study provides a tool to evaluate adults’ CT: the Algorithmic Thinking Test for Adults (ATTA), which was developed according to psychometric standards. This article also reflects on the nature of CT as a construct.

2022

Promoting Computational Thinking Skills in Non-Computer Science Students Gamifying Computational Notebooks to Increase Student Engagement

Juan Carlos Farah, Pascal Felber, Denis Gillet, Adrian Christian Holzer, Marc Lafuente Martinez

Computational thinking (CT) skills are becoming increasingly relevant for future professionals across all domains, beyond computer science (CS). As such, an increasing number of bachelor and masters programs outside of the computer science discipline integrate CT courses within their study program. At the same time, tools such as notebooks and interactive apps designed to support the teaching of programming concepts are becoming ever more popular. However, in non-CS majors, CT might not be perceived as essential, and students might lack the motivation to engage with such tools in order to acquire solid CT skills. This paper presents a field study conducted with 115 students during a full semester on a novel computational notebook environment. It evaluates computational notebooks and CT skills in an introductory course on information technology for first-year undergraduates in business and economics. A multidimensional evaluation approach makes use of pre- and post-test surveys, lectures, and self-directed lab sessions tracking analytics. Our findings suggest that, in the process of learning CT for non-CS students, engagement in active learning activities can be a stronger determinant of learning outcomes than initial knowledge. Furthermore, gamifying computational notebooks can serve as a strong driver of active learning engagement, even more so than initial motivational factors.

2022

Students' learning strategies, motivation and project-management skills during interdisciplinary projects in Covid times

Julien Delisle, Siara Ruth Isaac, Helena Kovacs, Marc Lafuente Martinez

In this study, we investigated an interdisciplinary project-based learning program. Students were confronted with interdisciplinary challenges in the form of complex and authentic problems, like building a racing car or making a mobile laboratory for genetic analysis. These hands-on educational formats had a clear aim to develop skills required in students’ future careers, as well as bridge the gap between theory and practice. In this paper, we show preliminary results of an on-going mixed method study where the students’ learning strategies, motivation, and project management skills were measured through a survey using a pre and post-test approach. Quantitative results were contrasted with qualitative input from interviews with projects’ coaches and students’ focus groups. The results provided evidence of gains regarding professional skills (e.g. risk assessment in projects), but also shed light on difficulties and needs to implement meaningful experiential learning content within engineering education (e.g. collaboration). On top of this, the research took place during COVID-19 lockdown, hence both students’ and coaches’ reflections accounted for ways in which this situation did impact the projects.

Technische Universität Berlin2021