TY - JOUR
T1 - Using educational data from teaching and learning to inform teachers' reflective educational design in inquiry-based STEM education
AU - Sergis, Stylianos
AU - Sampson, Demetrios G.
AU - Rodríguez-Triana, María Jesús
AU - Gillet, Denis
AU - Pelliccione, Lina
AU - de Jong, Ton
N1 - Funding Information:
The work presented in this article has been partially co-funded by the European Commission in the context of the Go-Lab project (Grant Agreement no. 317601 ) under the Information and Communication Technologies (ICT) theme of the 7th Framework Programme for R&D (FP7). The first and second authors' contribution in this work has been also partially co-funded by the Greek General Secretariat for Research and Technology , under the Matching Funds 2014–2016 for the EU project “Inspiring Science: Large Scale Experimentation Scenarios to Mainstream eLearning in Science, Mathematics and Technology in Primary and Secondary Schools” (Project Number: 325123 ). The second author's contribution in this work has been also partially co-funded by the European Commission in the context of the "Learn2Analyze" project (Project Number: 588067-EPP-1-2017-1-EL-EPPKA2-KA ) under the Erasmus + Knowledge Alliance program. This article reflects the views only of the authors and it does not represent the opinion of neither the European Commission nor the Greek General Secretariat for Research and Technology, and the European Commission and the Greek General Secretariat for Research and Technology can not be held responsible for any use that might be made of its content.
Publisher Copyright:
© 2017 Elsevier Ltd
PY - 2019/3
Y1 - 2019/3
N2 - Science, Technology, Engineering and Mathematics (STEM) education is recognized as a top school education priority worldwide and Inquiry-based teaching and learning is identified as a promising approach. To effectively engage students in Inquiry tasks, appropriate guidance should be provided, usually by combining digital tools such online labs and modeling tools. This is a cumbersome task for teachers, since it involves manually assessing the type/level of tool-supported guidance to be provided and potentially refining these to meet guidance needs of individual students. In our research we target to investigate how to support this systematic reflection process with educational data analytics methods and tools from both the design and the delivery of Inquiry-based educational designs (IED). The contribution of this paper is to propose a novel "Teaching and Learning" Analytics method and research prototype tool, extending the scope of purely learning analytics methods, to analyze IED in terms of the tool-supported guidance they offer and relate these analyses to students' educational data that are already being collected by existing learning analytics systems, increasing teachers' awareness. A two-layer evaluation methodology positively assessed the capacity of our method to analyze IED and provided initial evidence that the insights generated offer statistically significant indicators that impact students' activity during the delivery of these IED. The insights of this work aim to contribute in the field of cognitive data analytics for teaching and learning, by investigating new ways to combine analyses of the educational design and students' activity, and inform teachers' reflection from a holistic perspective.
AB - Science, Technology, Engineering and Mathematics (STEM) education is recognized as a top school education priority worldwide and Inquiry-based teaching and learning is identified as a promising approach. To effectively engage students in Inquiry tasks, appropriate guidance should be provided, usually by combining digital tools such online labs and modeling tools. This is a cumbersome task for teachers, since it involves manually assessing the type/level of tool-supported guidance to be provided and potentially refining these to meet guidance needs of individual students. In our research we target to investigate how to support this systematic reflection process with educational data analytics methods and tools from both the design and the delivery of Inquiry-based educational designs (IED). The contribution of this paper is to propose a novel "Teaching and Learning" Analytics method and research prototype tool, extending the scope of purely learning analytics methods, to analyze IED in terms of the tool-supported guidance they offer and relate these analyses to students' educational data that are already being collected by existing learning analytics systems, increasing teachers' awareness. A two-layer evaluation methodology positively assessed the capacity of our method to analyze IED and provided initial evidence that the insights generated offer statistically significant indicators that impact students' activity during the delivery of these IED. The insights of this work aim to contribute in the field of cognitive data analytics for teaching and learning, by investigating new ways to combine analyses of the educational design and students' activity, and inform teachers' reflection from a holistic perspective.
KW - Educational data analytics
KW - Guidance
KW - Inquiry-based teaching
KW - Learning analytics
KW - STEM education
KW - Teaching analytics
KW - Teaching and learning analytics
KW - 2023 OA procedure
UR - http://www.scopus.com/inward/record.url?scp=85038812636&partnerID=8YFLogxK
U2 - 10.1016/j.chb.2017.12.014
DO - 10.1016/j.chb.2017.12.014
M3 - Article
AN - SCOPUS:85038812636
SN - 0747-5632
VL - 92
SP - 724
EP - 738
JO - Computers in human behavior
JF - Computers in human behavior
ER -