FUTURE LEARNING: Orchestrating 21st Century Learning Ecosystems using Analytics

Learning technology is becoming increasingly popular and various technologies have already been used to support teaching and learning practices. Designing technology to enhance human learning is a complex challenge, requiring input from multidisciplinary fields (e.g., human-computer interaction, software development, psychology, learning sciences). Contemporary learning systems lack knowledge of students' states, and the data generated by such technologies (i.e., Learning Analytics) is not always utilized in terms of the learning design, orchestration and user interface improvements. The utilization of such data has the potential to offer new principles to support teaching and learning. Typical examples of such data are computer log files, clickstreams, keystrokes, survey responses, and even more sophisticated data coming from multimodal channels such contents video, eye tracking, to name a few. FUTURE LEARNING project we conducted several studies across different contexts and contents and collected different types of learning analytics (e.g., click-streams, eye tracking, survey responses). This allowed us to identify the features of learning analytics the have the capacity to inform the learning design, orchestration and improve learning technologies. In particular, the results help us to re-design learning technologies, as well as to promote learning design (for example, with innovative learning services). Our studies in modern learning environments and multimodal learning analytics (e.g., via wearables, EEG) open new avenues for research on how to analyze evidence from multimodal data and how we can extract meaning from these increasingly fluid and complex 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.