Abstract:

In Quebec (Canada), official documents stipulate that principals and teachers must base their pedagogical decisions on data from multiple sources. Moreover, the advent of big data forces these educational actors to adapt to new data analysis technologies. However, although available computer tools facilitate the use of data, the fact remains that data-driven decision-making is a complex cognitive process for individuals (Breiter & Light, 2006). Indeed, these tools only allow the description of past or present learning and behaviours or social situations, without satisfactorily identifying the factors explaining these situations, much less anticipating them or prescribing actions to improve them.

To Meet This Need:
A professional learning community (PLC) of a French-language high school in Quebec, in collaboration with an external technological partner, has begun an innovative design process for a pedagogical decision support tool. The process involved the use of advanced analytics and artificial intelligence techniques. The tool is operationalized in both a Web and mobile interface.

On the theoretical and methodological level, the PLC has mobilized the foundations of the C-K theory of design (Le Masson et al., 2018), the data competence maturity model of Cech (2018) as well as the pedagogical object development model of Van der Maren (2014). Thus, the prototype designed seeks to describe, diagnose and predict situations that students experience in terms of learning, behaviour and social order and to prescribe actions for educational actors to improve them. In concrete terms, the tool automates in real time the analysis of local data from multiple sources, i.e. data that is accessible or produced in the school. The data collected can be quantitative (e.g. numerical results) or qualitative (e.g. collected observations) and stored in databases, among others. When used, actors have the possibility to write texts, record voice comments or transfer files in PDF format (e.g.: summary of results, student work, scientific articles) and Mp4 format (e.g.: recorded discussions). Finally, the tool’s architecture allows for the analysis of big data.

Our prototype has been designed to be integrated into a collective decision-making process in the context of PLCs, which can be used either face-to-face or online.

Keywords:

Innovative design, pedagogical decision-support tool, data-based decision-making, professional learning community.