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Rodriguez-Triana, Maria Jesus; Prieto, Luis P.; Dimitriadis, Yannis; de Jong, Ton; Gillet, Denis – Journal of Learning Analytics, 2021
Orchestrating technology-enhanced learning is a difficult task, especially in demanding pedagogical approaches like inquiry-based learning (IBL). To foster effective teacher adoption, both the complexity of designing IBL activities and the uncertainty about the student learning path during enactment need to be addressed. Previous research suggests…
Descriptors: Learning Analytics, Design, Instructional Design, Inquiry
Saar, Merike; Rodríguez-Triana, María Jesús; Prieto, Luis P. – Journal of Learning Analytics, 2022
Data-informed decision-making in teachers' practice, now recommended by different teacher inquiry models and policy documents, implies deep practice change for many teachers. However, not much is known about how teachers perceive the different steps that analytics-informed teacher inquiry entails. This paper presents the results of a study into…
Descriptors: Learning Analytics, Evidence Based Practice, Data, Decision Making
Ruiz-Calleja, Adolfo; Prieto, Luis P.; Ley, Tobias; Rodriguez-Triana, Maria Jesus; Dennerlein, Sebastian – IEEE Transactions on Learning Technologies, 2021
Despite the ubiquity of learning in workplace and professional settings, the learning analytics (LA) community has paid significant attention to such settings only recently. This may be due to the focus on researching formal learning, as workplace learning is often informal, hard to grasp, and not unequivocally defined. This article summarizes the…
Descriptors: Learning Analytics, Professional Education, Workplace Learning, Educational Trends
Kasepalu, Reet; Chejara, Pankaj; Prieto, Luis P.; Ley, Tobias – Technology, Knowledge and Learning, 2022
Monitoring and guiding multiple groups of students in face-to-face collaborative work is a demanding task which could possibly be alleviated with the use of a technological assistant in the form of learning analytics. However, it is still unclear whether teachers would indeed trust, understand, and use such analytics in their classroom practice…
Descriptors: Teacher Attitudes, Secondary School Teachers, Technology Uses in Education, Online Systems
Saar, Merike; Prieto, Luis P.; Rodríguez Triana, María Jesús – Technology, Pedagogy and Education, 2022
Research indicates that data-informed practice helps teachers change their teaching and promotes teacher professional development (TPD). Although educational data are often collected from digital spaces, in-action evidence from physical spaces is seldom gathered, providing an incomplete view of the classroom reality. Also, most learning analytics…
Descriptors: Data Collection, Data Use, Teaching Methods, Faculty Development
Pishtari, Gerti; Prieto, Luis P.; Rodriguez-Triana, Maria Jesus; Martinez-Maldonado, Roberto – Journal of Learning Analytics, 2022
This research was triggered by the identified need in literature for large-scale studies about the kinds of designs that teachers create for mobile learning (m-learning). These studies require analyses of large datasets of learning designs. The common approach followed by researchers when analyzing designs has been to manually classify them…
Descriptors: Scaling, Classification, Context Effect, Telecommunications
Prieto, Luis P.; Rodríguez-Triana, María Jesús; Martínez-Maldonado, Roberto; Dimitriadis, Yannis; Gaševic, Dragan – Australasian Journal of Educational Technology, 2019
Despite the recent surge of interest in learning analytics (LA), their adoption in everyday classroom practice is still slow. Knowledge gaps and lack of inter-stakeholder communication (particularly with educational practitioners) have been posited as critical factors for previous LA adoption failures. Yet, what issues should researchers,…
Descriptors: Learning Analytics, Adoption (Ideas), Stakeholders, Technology Uses in Education