Christian Giang

Biographie

Christian Giang is a researcher at the École Polytechnique Fédérale de Lausanne (EPFL) and the Department of Education and Learning at the University of Applied Sciences and Arts of Southern Switzerland (SUPSI-DFA). His research focuses on the use of educational technologies in formal education. He received the Ph.D. in Educational Robotics from EPFL in 2020. Before that, he received the BSc and MSc degrees in Electrical Engineering and Information Technology from ETH Zürich. Moreover, he is currently completing the teaching certificate in Electrical Engineering (Didaktik-Zertifikat) at ETH Zürich.

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https://people.epfl.ch/christian.giang?lang=fr

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Evolutionary Clustering of Apprentices' Self- Regulated Learning Behavior in Learning Journals

Christian Giang, Mirko Marras, Paola Mejia Domenzain

Learning journals are increasingly used in vocational education to foster self-regulated learning and reflective learning practices. However, for many apprentices, documenting working experiences is a difficult task. In this paper, we profile apprentices' learning behavior in an online learning journal. Based on a pedagogical framework, we propose a novel multi-step clustering pipeline that integrates different learning dimensions into a combined profile. Specifically, the profiles are described in terms of effort, consistency, regularity, help-seeking behavior, and quality of the written entries. Our results on two populations of chef apprentices (183 apprentices) interacting with an online learning journal (over 121K entries) show that our pipeline captures changes in learning patterns over time and yields interpretable profiles that can be related to academic performance. The obtained profiles can be used as a basis for personalized interventions, with the ultimate goal of improving the apprentices' learning experience.

2022

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Computational thinking (CT) is considered an emerging competence domain linked to 21st-century competences, and educational robotics (ER) is increasingly recognised as a tool to develop CT competences. This is why researchers recommend developing intervention methods adapted to classroom practice and providing explicit guidelines to teachers on integrating ER activities. The present study thus addresses this challenge. Guidance and feedback were considered as critical intervention methods to foster CT competences in ER settings. A between-subjects experiment was conducted with 66 students aged 8 to 9 in the context of a remote collaborative robot programming mission, with four experimental conditions. A two-step strategy was employed to report students' CT competence (their performance and learning process). Firstly, the students' CT learning gains were measured through a pre-post-test design. Secondly, video analysis was used to identify the creative computational problem-solving patterns involved in the experimental condition that had the most favourable impact on the students’ CT scores. Results show that delayed feedback is an effective intervention method for CT development in ER activities. Subject to delayed feedback, students are better at formulating the robot behaviour to be programmed, and, thus, such a strategy reinforces the anticipation process underlying the CT.

2022

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Accessible Maker-based Approaches to Educational Robotics in Online Learning

Amaury Robert Dame, Christian Giang, Anthony Guinchard, Aditya Mehrotra, Francesco Mondada

Educational Robotics holds the potential to promote the development of important 21st century skills, such as creativity and problem-solving skills in addition to digital literacy. However, the emergence of the Covid-19 pandemic has posed particular obstacles that had to be overcome in order to allow Educational Robotics activities to be conducted in distance learning. In the first place, the obligation to work from home limited the access to required equipment for many students. Secondly, many teachers had to face the novel challenge of creating pedagogically meaningful activities in online learning formats. Aiming to address these challenges, this work explored maker-based approaches as a way to implement Educational Robotics activities in online learning. The devised tools and activities were evaluated in two case studies performed with (i) high school students participating in a mobile robotics summer school and (ii) in-service teachers attending a professional development course on Educational Robotics. The teachers’ and students’ perception of the proposed activities was analyzed using online surveys and video interviews. The findings showed that the combination of the devised tools and activities allowed teachers and students to explore the basics of mobile robotics while helping them develop a maker mindset. The use of ubiquitous construction materials and affordable electronic components promotes accessibility of the approach. The proposed tools and activities may therefore provide an exemplary framework for more general applications of Educational Robotics in online learning that go beyond the context of emergency remote teaching.

2021

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