Learning analytics approach of EMMA project

The EMMA project provides a MOOC platform to aggregate and delivers massive open online courses (MOOC) in multiple languages from a variety of European universities. Learning analytics play an important role in MOOCs to support the individual needs of the learner.This work is funded by the EU, under the Competitiveness and Innovation Framework Program 2007-2017 (CIP) in the European Multiple MOOC Aggregator (EMMA) project. Grant Agreement no. 621030

Õpianalüütika võimalused õppimise ja õpetamise toetamisel õpetajahariduses

Info- ja kommunikatsioonitehnoloogia rakendamine ning õpihaldussüsteemide ja õpikeskkondade kasutamine õppeprotsessis on muutnud õpetajaks õppijate õpikogemusi ning õpetajahariduse õppejõudude õpetamisviise. Sellega kaasnevad erinevad digitaalsed andmed, mis annavad õppijale, õpetajale ning õppekava eestvedajale tagasisidet õppimise ja õpetamise tõhustamiseks. Haridusvaldkonnas aina enam rakendust leidev õpianalüütika võimaldab suurendada õppijate teadlikkust ja tõhusust õppeprotsessis, individualiseerida õppeprotsessi ning saada pidevat ja jooksvat tagasisidet õppimise edenemise kohta. Artikli eesmärk on analüüsida õpetajahariduse üliõpilaste ja õppejõudude ootusi õpianalüütika võimaluste suhtes, et toetada õpikeskkonnas õppimist ja õpetamist. Uurimuse teoreetilise raamistiku loob ennastjuhtiva õppija kontseptsioon. Uurimistulemused baseeruvad disainipõhisel uurimusel, kus osalusdisaini sessioonide käigus selgitati välja õpikeskkonna kasutajate (üliõpilaste, õppejõudude, õppekavade juhtide) ootused õpikeskkonna õpianalüütikarakenduste suhtes.  Summar

How can the EMMA approach to learning analytics improve employability?

In our current society there is a strong need for citizens to work on their employability and to develop key competences. Developing those competences should starts during formal education, but maintained throughout working life. MOOCs can accommodate several of the needs of the lifelong learners. EMMA facilitates learners in obtaining their personalised learning goals. And an integrated learning analytic solution will help to track the learning process and provide actionable feedback to improve, correct and ensure the achievement of students’ learning goalsThis work is funded by the EU, under the Competitiveness and Innovation Framework Program 2007-2017 (CIP) in the European Multiple MOOC Aggregator (EMMA) project. Grant Agreement no. 621030

Lastekirjanduse kasutamine õppe- ja kasvatustegevuses lastes lugemishuvi tekitamisel Harku valla lasteaedade näitel

https://www.ester.ee/record=b552002

School-University Partnership for Evidence-Driven School Improvement in Estonia

It has been acknowledged that evidence-driven practices may lead schools to improved instructional practices, student learning, or organizational improvement; still the evidence is underused by the teachers or school leaders. This study focuses on analyzing how to strengthen the evidence-driven school improvement in school-university partnership programs. Five schools learnt over a period of one school year in collaboration with the university coaches how to collect evidence in classroom and organizational level for improvement process. The results of our study illustrate profiles of the schools based on the usage of data-informed evidence, research-based evidence, or both to make decisions in the instructional and organizational level. Enablers and barriers of data use from the perspective of organizational, user, and data characteristics to implement evidence-driven practices are discussed

Contextualising Learning Analytics with Classroom Observations: a Case Study

Educational processes take place in physical and digital places. To analyse educational processes, Learning Analytics (LA) enable data collection from the digital learning context. At the same time, to gain more insights, the LA data can be complemented with the data coming from physical spaces enabling Multimodal Learning Analytics (MMLA). To interpret this data, theoretical grounding or contextual information is needed. Learning designs (LDs) can be used for contextualisation, however, in authentic scenarios the availability of machine-readable LD is scarce. We argue that Classroom Observations (COs), traditionally used to understand educational processes taking place in physical space, can provide the missing context and complement the data from the colocated classrooms. This paper reports on a co-design case study from an authentic scenario that used CO to make sense of the digital traces. In this paper we posit that the development of MMLA approaches can benefit from codesign methodologies; through the involvement of the end-users (project managers) in the loop, we illustrate how these data sources can be systematically integrated and analysed to better understand the use of digital resources. Results indicate that CO can drive sense-making of LA data where predefined LD is not available. Furthermore, CO can support layered contextualisation depending on research design, rigour and systematic documentation/data collection efforts. Also, co-designing the MMLA solution with the end-users proved to be a useful approach

Learning analytics: European perspectives

Since the emergence of learning analytics in North America, researchers and practitioners have worked to develop an international community. The organization of events such as SoLAR Flares and LASI Locals, as well as the move of LAK in 2013 from North America to Europe, has supported this aim. There are now thriving learning analytics groups in North American, Europe and Australia, with smaller pockets of activity emerging on other continents. Nevertheless, much of the work carried out outside these forums, or published in languages other than English, is still inaccessible to most people in the community. This panel, organized by Europe’s Learning Analytics Community Exchange (LACE) project, brings together researchers from five European countries to examine the field from European perspectives. In doing so, it will identify the benefits and challenges associate