Introduction to Smart Learning Analytics: Foundations and Developments in Video-Based Learning

Smart learning has become a new term to describe technological and social developments (e.g., Big and Open Data, Internet of Things, RFID, and NFC) enable effective, efficient, engaging and personalized learning. Collecting and combining learning analytics coming from different channels can clearly provide valuable information in designing and developing smart learning. Although, the potential of learning analytics to enable smart learning is very promising area, it remains non-investigated and even ill-defined concept. The paper defines the subset of learning analytics that focuses on supporting the features and the processes of smart learning, under the term Smart Learning Analytics. This is followed by a brief discussion on the prospects and drawbacks of Smart Learning Analytics and their recent foundations and developments in the area of Video-Based Learning. Drawing from our experience with the recent international workshops in Smart Environments and Analytics in Video-Based Learning, we present the state-of-the-art developments as well as the four selected contributions. The paper further draws attention to the great potential and need for research in the area of Smart Learning Analytics

Enhancing video-based learning experience through smart environments and analytics

This paper describes the potential and promising value of smart environments and analytics on the emerging area of video-based learning. In particular, we describe the contributions presented at the International Workshop of Smart Environments and Analytics on Video-Based Learning (SE@VBL) and envision the future of this research area. SE@VBL presents the current state-of-the- art in the design, development and evaluation of video-based learning systems. SE@VBL 2016 emphasized the importance and benefits of smart environments and analytics for video-based learning to support learners and instructors with the appropriate resources for improving the use of video-based learning systems. The long term goal of SE@VBL is to develop a critical discussion about the next generation of environments and analytics employed in video learning tools, the form of these environments and analytics, and the way they can be utilized in order to help us to better understand and improve the value of video-based learning. In this volume, we have included the 4 contributions, 1 keynote presentation and 1 tutorial that were featured at the workshop

Clinical Application of Autologous Adipose Stem Cells in Patients with Multiple Sclerosis: Preliminary Results

The clinical outcome of autologous adipose stem cell (ASC) treatment of patients with multiple sclerosis (MS) was investigated following one year of observation. Methods. The clinical and MRI outcomes of 16 ASC-treated patients with RRMS and SPMS are reported after a one-year follow-up period. Results. At 18 months of follow-up, some patients showed “enticing” improvements on some exploratory efficacy measures, although a significant benefit was not observed for any measure across the entire group. Neither the progression of disability nor relapses were observed in any cases. In four patients, we found new gadolinium+ (Gd+) lesions on MRI. Our results indicate that ASC therapy is safe and does not produce any substantial side effects. Disease progression-free survival (PFS) of 18 months was seen in all patients with RRMS and SPMS. In these patients, EDSS scores did not progress above baseline scores. Gd-enhancing lesions were observed in two cases with RRMS, but these patients did not exhibit changes in EDSS score. Conclusion. Intrathecal treatment with ASCs is an attractive form of therapy for patients with MS but should be reserved for cases with aggressive disease progression, for cases that are still in the inflammatory phase, and for the malignant form

Clinical Application of Autologous Adipose Stem Cells in Patients with Multiple Sclerosis: Preliminary Results

The clinical outcome of autologous adipose stem cell (ASC) treatment of patients with multiple sclerosis (MS) was investigated following one year of observation. Methods. The clinical and MRI outcomes of 16 ASC-treated patients with RRMS and SPMS are reported after a one-year follow-up period. Results. At 18 months of follow-up, some patients showed "enticing" improvements on some exploratory efficacy measures, although a significant benefit was not observed for any measure across the entire group. Neither the progression of disability nor relapses were observed in any cases. In four patients, we found new gadolinium+ (Gd+) lesions on MRI. Our results indicate that ASC therapy is safe and does not produce any substantial side effects. Disease progression-free survival (PFS) of 18 months was seen in all patients with RRMS and SPMS. In these patients, EDSS scores did not progress above baseline scores. Gd-enhancing lesions were observed in two cases with RRMS, but these patients did not exhibit changes in EDSS score. Conclusion. Intrathecal treatment with ASCs is an attractive form of therapy for patients with MS but should be reserved for cases with aggressive disease progression, for cases that are still in the inflammatory phase, and for the malignant form