Dynamic Group Formation with Intelligent Tutor Collaborative Learning: A Novel Approach for Next Generation Collaboration

\ua9 2013 IEEE. Group Formation (GF) strongly influences the collaborative learning process in Computer-Supported Collaborative Learning (CSCL). Various factors affect GF that include personal characteristics, social, cultural, psychological, and cognitive diversity. Although different group formation methods aim to solve the group compatibility problem, an optimal solution for dynamic group formation is still not addressed. In addition, the research lacks to supplement collaborative group formation with a collaborative platform. In this study, the next level of collaboration in CSCL and Intelligent Tutoring System (ITS) platforms is achieved. First, initial groups are formed based on students learning styles, and knowledge level, i.e. for knowledge level, an activity-based dynamic group formation technique is proposed. In this activity, swapping of students takes place on each permutation based on their knowledge level. Second, the formed heterogeneous balanced groups are used to augment the collaborative learning system. For this purpose, a hybrid framework of Intelligent Tutor Collaborative Learning (ITSCL) is used that provides a unique and real-time collaborative learning platform. Third, an experiment is conducted to evaluate the significance of the proposed study. Inferential and descriptive statistics of Paired T-Tests are applied for comprehensive analysis of recorded observations. The statistical results show that the proposed ITSCL framework positively impacts student learning and results in higher learning gains

Features of mobile apps for people with autism in a post Covid-19 scenario: Current status and recommendations for apps using AI

\ua9 2021 by the authors. Licensee MDPI, Basel, Switzerland. The new ‘normal’ defined during the COVID-19 pandemic has forced us to re-assess how people with special needs thrive in these unprecedented conditions, such as those with Autism Spectrum Disorder (ASD). These changing/challenging conditions have instigated us to revisit the usage of telehealth services to improve the quality of life for people with ASD. This study aims to identify mobile applications that suit the needs of such individuals. This work focuses on identifying features of a number of highly-rated mobile applications (apps) that are designed to assist people with ASD, specifically those features that use Artificial Intelligence (AI) technologies. In this study, 250 mobile apps have been retrieved using keywords such as autism, autism AI, and autistic. Among 250 apps, 46 were identified after filtering out irrelevant apps based on defined elimination criteria such as ASD common users, medical staff, and non-medically trained people interacting with people with ASD. In order to review common functionalities and features, 25 apps were downloaded and analysed based on eye tracking, facial expression analysis, use of 3D cartoons, haptic feedback, engaging interface, text-to-speech, use of Applied Behaviour Analysis therapy, Augmentative and Alternative Communication techniques, among others were also deconstructed. As a result, software developers and healthcare professionals can consider the identified features in designing future support tools for autistic people. This study hypothesises that by studying these current features, further recommendations of how existing applications for ASD people could be enhanced using AI for (1) progress tracking, (2) personalised content delivery, (3) automated reasoning, (4) image recognition, and (5) Natural Language Processing (NLP). This paper follows the PRISMA methodology, which involves a set of recommendations for reporting systematic reviews and meta-analyses

Liver regeneration and inflammation:from fundamental science to clinical applications

Liver regeneration is a complex process involving the crosstalk of multiple cell types, including hepatocytes, hepatic stellate cells, endothelial cells and inflammatory cells. The healthy liver is mitotically quiescent, but following toxic damage or resection the cells can rapidly enter the cell cycle to restore liver mass and function. During this process of regeneration, epithelial and non-parenchymal cells respond in a tightly coordinated fashion. Recent studies have described the interaction between inflammatory cells and a number of other cell types in the liver. In particular, macrophages can support biliary regeneration, contribute to fibrosis remodelling by repressing hepatic stellate cell activation and improve liver regeneration by scavenging dead or dying cells in situ. In this Review, we describe the mechanisms of tissue repair following damage, highlighting the close relationship between inflammation and liver regeneration, and discuss how recent findings can help design novel therapeutic approaches