FUTURE LEARNING: Orchestrating 21st Century Learning Ecosystems using Analytics

Læringsteknologi blir stadig mer populært, og forskjellige teknologier har allerede blitt brukt for å støtte undervisnings- og læringspraksis. Å designe teknologi for å styrke menneskelig læring er en kompleks utfordring, som krever innspill fra flerfaglige felt (f.eks. Menneske-datamaskin-interaksjon, programvareutvikling, psykologi, læringsvitenskap). Moderne læringssystemer mangler kunnskap om studentenes tilstander, og dataene som genereres av slike teknologier (dvs. Learning Analytics) blir ikke alltid brukt når det gjelder læringsdesign, orkestrering og forbedringer av brukergrensesnittet. Bruken av slike data har potensialet til å tilby nye prinsipper for å støtte undervisning og læring. Typiske eksempler på slike data er datamaskinloggfiler, klikkstrømmer, tastetrykk, undersøkelsesresponser og enda mer sofistikerte data som kommer fra multimodale kanaler som lyd, video, øyesporing, for å nevne noen. FUTURE LEARNING-prosjektet gjennomførte vi flere studier på tvers av forskjellige kontekster og innhold og samlet forskjellige typer læringsanalyser (f.eks. Klikkstrømmer, øyesporing, undersøkelsesresponser). Dette tillot oss å identifisere funksjonene i læringsanalyser som har kapasitet til å informere læringsdesign, orkestrering og forbedre læringsteknologier. Resultatene hjelper oss spesielt med å utforme læringsteknologier på nytt, samt å fremme læringsdesign (for eksempel med innovative læringstjenester). Våre studier i moderne læringsmiljøer og multimodal læringsanalyse (f.eks. Via wearables, EEG) åpner nye veier for forskning på hvordan man kan analysere bevis fra multimodale data og hvordan vi kan hente ut mening fra disse stadig mer flytende og komplekse data.

First of all, the project funded one Ph.D. student, who is about to complete her Ph.D. during 2020. In addition, the project resulted in several dozens of scientific papers, published on top-tier journals and conferences, including Computers in Human Behavior, BJET, CSCL, IDC, EC-TEL to mention few. Thoss papers provided scientific and empirical knowledge on how to leverage on Learning Analytics to support learning design and orchestration. The project also supported the organization of several national and international workshops and conferences that attracted several hundreds of participants. Utilizing the scientific knowledge, datasets, and articles published during the lifetime of FUTURE LEARNING, we applied for follow-up EU grants, with many of them successfully granted (H2020 COMnPLAY-Science, Erasmus+ Learn2Analyze). Last but not least, FUTURE LEARNING played a central role in the establishment of the Learner-Computer Interaction lab (https://lci.idi.ntnu.no/) at NTNU.

The systematic use of learning technologies has become widely employed in the past years, diverse technologies have been applied in a variety of teaching practices; for instance learning tools which allow you to flip the classroom or monitor and enhance other learning practices. However, the developed systems are only a subset of different kinds of learning materials and learning tools that an educator should take into consideration; and most importantly they do not offer an overview of the different learning experiences and dynamics. Information gathered from multiple technologies via learning analytics can allow us to orchestrate the respective technologies and practices, and support better learning. In the proposed project, we focus: a) on an analysis of the prior empirical and theoretical knowledge to address requirements for efficient learning orchestration and b) iteratively develop, use and evaluate a framework for efficient orchestration of 21st century learning ecosystems. In particular, the proposed research seeks to explore, with both qualitative and quantitative data sources, practical and technical knowledge for improving 21st century learning ecosystems and to situate Norway a leading country in the area. Information generated from this project will inform educators/practitioners, and policy makers at district, national, and international levels who are connected to learning policies and technologies. The intellectual merit of this proposal is the developed framework with practical and technical knowledge, addressing how instructors and policy makers can increase learning technologies benefits. The broader impact of FUTURE LEARNING on both the educational and scientific communities is the advancement of the understandings, potentials, and limitations of learning systems for knowledge acquisition to yield the best practice and effective use thereof.