Abstract:

In education, data-based decision-making typically refers to a process by which “teachers, principals, and administrators systematically collecting and analyzing data to guide a range of decisions to help improve the success of students and the school” (Ikemoto & Marsh, 2007, p. 108). Data accessed or generated in schools can come from either internal sources (e.g., student outcomes) or external sources (e.g., parents’ perceptions of school, information from the Internet) (Schildkamp, 2019; Schildkamp & Kuiper, 2010).

By definition, a professional learning community (PLC) refers to a collaborative modality of school operations among school stakeholders, in this case, teachers and principals, with the highest priority placed on the continuous improvement of student academic achievement (Hord & Sommers, 2008). From this perspective, the use of data represents a critical element in the educational decision-making process (DuFour et al., 2019; Marsh et al., 2015).

While we recognize the use of data as an indispensable part of regulating educational action (Mandinach & Jimerson, 2016), the fact remains that this use of data is a complex cognitive process for teachers and principals due to the multiplicity of data sources present in schools (e.g., from classroom contexts or various databases) (Breiter & Light, 2006).

To address this complexity, we designed and developed, in collaboration with a technological partner, a tool to support pedagogical decision-making within the framework of an action-research project conducted in a PLC. This tool provides stakeholders with the ability to continuously collect and analyze data that is accessible or produced in the school, either quantitative (e.g., student results) or qualitative (e.g., stakeholders’ comments), which we call local multi-source data. This pedagogical decision support tool aims to identify in real time the major issues regarding students’ learning, behaviours, and circumstances.

Theoretically and methodologically, the design of the tool is mainly based on Concept-Knowledge Theory (C-K) (Le Masson et al., 2018) and its development of artificial intelligence techniques such as principal component analysis or natural language processing, among others.
In short, this tool is undoubtedly a value-added to any pedagogical decision-making process in a professional learning community context. In our communication, we will present the most recent version of this pedagogical decision support tool which is still under development.

Keywords:

Artificial intelligence, Data-based decision-making, Pedagogical decision support tool, Professional learning community.