I am deeply passionate about applying research and data analytics to enhance education. Specializing in educational dashboards, I provide insightful visualizations that shape effective strategies. Beyond my profession, I explore the realms of web development and startup culture, constantly seeking innovative ways to leverage technology for practical solutions. My goal is to use my diverse skills to make a meaningful impact on education. Let's connect to discuss the intersection of psychology, data science, and education.
As digital education curriculums continue to gain momentum globally, there's a growing necessity to enhance the digital skills of educators through tailored training programs. To ensure effective monitoring of these programs, the "EduNum" project, a digital education reform undertaken in the Canton of Vaud, has refined an existing model to oversee the entire process - from the training phase to the analysis of student learning outcomes. This model introduces crucial indicators for evaluation within digital education programs and fosters the utilization of an analytical methodology to augment the success of such ventures. The subsequent project aims to further validate the advantages of implementing a methodology derived from this model in the context of enhancing teachers' digital competencies and boosting students' learning outcomes. As a part of the 'EduNum' reform's initiatives, a critical evaluation was carried out to overcome the challenges that trainers encounter when they aim to appraise their training programs. This analysis gave rise to the conception of a web toolbox enhanced by AI language models named The Digital Training Companion, specifically designed to assist trainers in tracking their digital education training. For example, The Digital Training Companion provides an easy-to-use tool including key functionalities such as:
Building on current theoretical frameworks and existing empirical findings, my doctoral research developed our understanding of the form and functioning of collaborative problem-solving (CPS). This programme of research led to two significant contributions evidenced in theoretical development and observable outputs.
(1) My research integrated theoretical approaches and findings from different domains of research related to the identification (form) of individual and group elements of goal directed collaborative interactions, that spanned cognitive (i.e., to look at communications focused on problem-solving) (e.g., Decuyper et al., 2010), motivational (i.e., considering the persistence of behavior to solve a problem) (e.g., Järvelä et al., 2008) and relational (i.e., reflecting the development of group relationships) (e.g., Hale et al., 2005) dimensions. Based on this integration of theory and research, I developed a new collaborative problem-solving (CPS) model to capture how these three dimensions interact with each other (functioning). This model (in revision) represents a dynamic process that illustrates how individuals engaged in CPS build and update mental models (Dillenbourg et al., 2016), i.e., individual in-memory representations, combining general knowledge and strategies (Miele & Scholer, 2018; Veenman et al., 2004) and incoming information from both self (via individual processing) and other group members (through observable outputs) regarding cognitive, motivational, and relational aspects of the CPS task.
(2) The second contribution of my doctoral research was to highlight an additional role of emotion processes in the functioning of CPS. Previous research has found that emotion modulates the personal and interpersonal processes in CPS. My research extends existing conceptualisations of the role of emotions in CPS suggesting that it represents a distinctive and pervasive phenomenon that cannot be easily assimilated to the socio-relational dimension of collaboration. My research demonstrated how emotions are clues that group members use to make real-time inferences regarding themselves and their collaboration partners. For example, confusion can indicate a difficulty in understanding an aspect of the problem, boredom can indicate low commitment, contempt can indicate little liking for the collaboration partner, etc. Group members can therefore enrich their cognitive, motivational, and relational collaborative models through the understanding of their own and others’ emotions and use them to regulate collaboration.
My thesis presents several experimental studies that provide empirical evidence of the impact of different emotional processes (i.e., subjective feeling, sharing of emotions, emotion regulation dispositions on the three core dimensions of CPS. This work has significant implications for training CPS to students and employers and that focuses on emotional awareness – to teach individuals to effectively regulate their own emotion and read others’ emotions during a collaborative task. This important and highly novel work has been published in peer-reviewed journals and proceedings of international conferences (e.g., Avry et al., 2020a; Avry et al., 2020b).
The ﬁeld of collaborative problem-solving has been gaining interest over the last decades. However, we are still far from getting a complete picture of its functioning. One of the reasons is undoubtedly its underlying complexity. Indeed, a compre- hensive understanding of collaborative problem-solving requires paying attention to various phenomena that dynamically interact when people try to solve problems together. The present thesis aimed at deepening the understanding of collaborative problem- solving at four main levels. The ﬁrst contribution is an extensive review of the current state of research on various personal and interpersonal processes playing a role in collaborative problem-solving. To this end, we reviewed scientiﬁc contri- butions from different ﬁelds of research concerning the cognitive, motivational and relational aspects of collaboration. The second contribution is the construction of an integrative model that considers how these afore-mentioned dimensions inter- act during collaborative problem-solving at the personal and interpersonal levels. Moreover, the pervasive role of emotions as a source of information and regulation in each of these dimensions is also highlighted, challenging the classic dichotomy between socio-cognitive and socio-emotional spaces of collaboration classically pre- sented in the literature. All in all, this model is intended to provide a theoretical framework for further research in this domain. The third contribution concerns the study of some ways in which emotional processes inﬂuence collaborative problem- solving. Four studies explored the impact of self-experienced emotions, explicit sharing of emotions and emotion regulation dispositions on collaborative exchanges and the perception of different aspects of the collaboration. Finally, as a fourth con- tribution, we build on the ﬁndings uncovered in this thesis and the literature to propose new promising avenues for future research in this domain.
Course: Digital learning and Distance Education (Master) with Prof. ass. Gaëlle Molinari
Course: Software Engineering (Bachelor) with Prof. Philippe Dugerdil
Course: Data Structure (Bachelor) with Prof. Stéphane Marchand-Maillet
Course: Algorithms Programming (Bachelor) with Prof. Thierry Pun
Course: Methodology in Experimental Psychology (Bachelor) with Prof. ass. Gaëlle Molinari