Using Learning Analytics at School: a Go-Lab Study

Denis Gillet, Maria Jesus Rodriguez Triana, Andrii Vozniuk
2016
Discussion par affiche

Résumé

Go-Lab is an European project devoted to promote STEM education by means of pedagogical guidelines based on blended Inquiry-Based Learning (IBL), authoring tools for rich open educational resources, and online labs. In such a framework, we have analysed the orchestration needs of expert teachers in inquiry learning and STEM, and provided a set of Learning Analytics (LA) apps to address them. This document reports on three LA apps -Online Users, Student Time Spent, and Submitted Reports- which, based on the context description, provide visualisations of the student activity to support teacher awareness and reflection.

Official source

https://infoscience.epfl.ch/record/220331?ln=fr

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Publications associées (4)

Contextual Learning Analytics Apps to Create Awareness in Blended Inquiry Learning

Denis Gillet, Sten Govaerts, Adrian Christian Holzer, Maria Jesus Rodriguez Triana, David Sandoz, Andrii Vozniuk

Blended inquiry learning, where students for example use online labs to perform experiments, is considered a promising approach to increase the skills and interest of students in science, technology, engineering, and mathematics domains. For teachers to provide adequate guidance to their students, it is critical that they are aware of the progress and difficulties encountered by each student. This can be accomplished through visual learning analytics, namely by tracking student interaction, data analysis and adequate visualisations. To address this awareness issue, we present in this paper a set of contextual learning analytics apps which provide the teacher with learning-specific information. This paper presents a requirement analysis from a summer school with 32 teachers, the design and implementation of three contextual learning analytics apps, the main outcomes from a case study as well as an outlook on future research avenues.

2015

Chargement

The European Go-Lab project aims to promote Inquiry-based Learning (IBL) with online laboratories. To support teachers and students in this endeavor, the project provides an IBL model (a sequence of inquiry phases) as well as the technological infrastructure to implement it: the Graasp platform and the Golabz repository. Using these technologies, teachers create Inquiry Learning Spaces (ILSs) where they adapt the proposed IBL model to their needs, and enrich each one of its phases with online resources, apps or labs to build a web-based learning environment and distribute it to the students. The aim of this paper is to reflect on the deviations from the model proposed within the project on the teacher model and the way students adapt it. For that purpose, we analyzed the 102 most frequently used ILSs with respect to the perspectives of teachers and students. The results show deviations of the authored spaces from the pedagogical model of inquiry learning as well as deviations in the actual learning process models from the teachers’ specifications. Additionally, the analysis points out best practices for the learning design, particularly the inclusion of resources and apps into the spaces.

Asia-Pacific Society for Computers in Education2015

Chargement

Using Educational Data From Teaching And Learning To Inform Teachers’ Reflective Educational Design In Inquiry-Based STEM Education

Denis Gillet, Maria Jesus Rodriguez Triana

Science, Technology, Engineering and Mathematics (STEM) education is recognized as a top priority for school education worldwide and Inquiry-based teaching and learning is identified as one of the most dominant approaches. To effectively engage individual students in Inquiry tasks, appropriate guidance needs to be provided, usually by combining different digital tools such online labs, data analysis tools and modelling tools. This is a cumbersome task for teachers to perform manually since it involves (a) assessing during the education design, the type and level of tool-supported guidance to be provided to students and (b) potentially refining this level and types to meet the guidance needs of individual students based on educational data from the delivery of the educational design. Thus, in our research we target to investigate how to support this process with educational data analytics methods and tools from both the design and the delivery of educational designs, that inform teachers’ decision making for systematic reflection. To this end, the contribution of this paper is the design and evaluation of a novel “Teaching and Learning” Analytics method and supporting research prototype tool, extending the scope of purely learning analytics methods, to (a) analyze inquiry-based educational designs in terms of the tool-supported guidance they offer and (b) relate these analyses to students' educational data that are already being collected by existing learning analytics systems, so as to increase teachers’ awareness and understanding and scaffold their reflection. A two-layer evaluation methodology was adopted to evaluate both the capacity of our method to analyze educational designs in terms of appropriate guidance as well as to investigate whether the insights generated by the method offer statistically significant indicators that impact students' activity during the delivery of these educational designs. The results obtained, based on real-life educational data, argue that the proposed method and tool can support teachers to accurately analyse Inquiry-based educational designs and receive meaningful insights to improve and tailor students' learning experiences. The insights of this work aim to contribute in the research field of cognitive data analytics for teaching and learning, by investigating new ways to combine analyses of the educational design and the students’ activity, so as to inform teachers’ reflective decision making from a holistic perspective

2019

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Using Educational Data From Teaching And Learning To Inform Teachers’ Reflective Educational Design In Inquiry-Based STEM Education

Denis Gillet, Maria Jesus Rodriguez Triana

2019