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The current SMAC (Social, Mobile, Analytic, Cloud) technology trend paves the way to a future in which intelligent machines, networked processes and big data are brought together. This virtual world has generated vast amount of data which is accelerating the adoption of machine learning solutions & practices. Machine Learning enables computers to imitate and adapt human-like behaviour. Using machine learning, each interaction, each action performed, becomes something the system can learn and use as experience for the next time. This work is an overview of this data analytics method which enables computers to learn and do what comes naturally to humans, i.e. learn from experience. It includes the preliminaries of machine learning, the definition, nomenclature and applications' describing it's what, how and why. The technology roadmap of machine learning is discussed to understand and verify its potential as a market & industry practice. The primary intent of this work is to give insight into why machine learning is the future.

Virtual and augmented reality (VR/AR), teleoperation, and telepresence technologies heavily depend on video streaming and playback to enable immersive user experiences. However, the substantial bandwidth requirements and file sizes associated with VR/AR and 360-degree video content present significant challenges for efficient transmission and storage. Modern video coding standards, including HEVC, AV1, VP9, VVC, and EVC, have been designed to address these issues by enhancing coding efficiency while maintaining video quality on par with the H.264 standard. Nonetheless, the adaptive block structures inherent to these video coding standards introduce increased computational complexity, necessitating additional intra-prediction modes. The integration of AI in video coding has the potential to substantially improve video compression efficiency, reduce file sizes, and enhance video quality, making it a crucial area of research and development within the video coding domain. As AI systems can execute a wide array of tasks and adapt to new challenges, their incorporation into video coding may result in even more advanced compression techniques and innovative solutions to meet the ever-evolving demands of the industry. In this study, we introduce a state-of-the-art adaptive instant learning-based model, named iHELP, developed to address the computational complexity arising from encoders’ adaptive block structures. The iHELP model achieves outstanding coding efficiency and quality while considerably improving encoding speed. iHELP model has been tested on HEVC, but it applies to other encoders with similar adaptive block structures. iHELP model employs entropy-based block similarity to predict the splitting decision of the LCU, determining whether to divide the block based on the correlation between the block content and previously adjacent encoded blocks in both spatial and temporal dimensions. Our methodology has been rigorously evaluated using the HEVC standard’s common test conditions, and the results indicate that iHELP serves as an effective solution for efficient video coding in bandwidth-constrained situations, making it suitable for real-time video applications. The proposed method achieves an 80% reduction in encoding time while maintaining comparable PSNR performance relative to the RDO approach. The exceptional potential of the iHELP model calls for further exploration, as no other existing methods have demonstrated such a high level of performance.

Background Technological advances have driven huge change in educational practices though concerns exist about a lack of evidence informing this change, in particular with social media-based medical education activities. The purpose of this study was to conduct a scoping review of WhatsApp use in medical education, narratively describing how it has been used and evaluated, and the theoretical considerations in relevant articles. Methods A modified 5-stage scoping review model was used. We performed 2 searches from February 2009 to February 2019 in EBSCO, SCOPUS, Web of Science, EMBASE, Medline PubMed and Google Scholar) using the term “WhatsApp” in all search fields. A 3-stage process for study selection was performed. Only original articles in English presenting original data about WhatsApp in medical education were included. The Kirkpatrick model of training evaluation was used to describe learning outcomes in included studies. Results Twenty-three articles were selected for review. Three strategies for WhatsApp use were apparent; primarily educational use with a pre-defined curriculum ( n  = 5), primarily educational use without a curriculum ( n  = 11), and primarily non-educational use ( n  = 7). Most of the educational studies used an online moderator and were in a local hospital or university department. Studies not primarily educational were national or international and seldom included an online moderator. All 5 studies with a pre-defined curriculum reported Kirkpatrick level 2 learner knowledge outcomes. A majority of the remaining studies only reported Kirkpatrick level 1 learner attitudes. Seven studies with 647 participants reported an improvement in learners’ knowledge following WhatsApp learning, though methodological weaknesses were apparent. Evidence for underlying learning theory considerations were scant throughout the studies. Conclusions WhatsApp is popular and convenient in medical education. Current published literature suggests it may also be effective as a medical learning tool. By combining the 3 strategies for WhatsApp use and the exploration-enactment-assessment integrated learning design framework, we propose an instant messenger design model for medical education. This may address the need for theory-driven instructional design in social media learning. Further research would clarify the role of WhatsApp and our design model in this area.

The purpose of this paper was to investigate the effects of mobile instant messaging on collaborative learning processes and outcomes. The collaborative processes were measured in terms of different types of interactions. We measured the outcomes of the collaborations through both the students' taskwork and their teamwork. The collaborative learning processes and outcomes in the Mobile Instant Messaging group (Mobile IM) were also compared with the Personal Computer-based Instant Messaging group (PC IM) and the Bulletin Board System group (BBS). A total of 48 students participated in this study, and the main results show that more cognitive and metacognitive interactions were found in the BBS group while social and affective interactions were the major types of interactions in the Mobile IM group and the PC IM group. As a result of the collaborative learning outcomes, the Mobile IM group shows better teamwork than the other two groups. However, better taskwork was found in the BBS group and the PC IM group rather than the Mobile IM group. Finally, the researchers discuss the implications of this study from the perspective of the educational potential of mobile learning.

Blended learning models have been extensively used in foreign language environments to extend in-class time as well as reinforce in-class explanations. Among these models, the increasing popularity of flipped learning has given rise to transformative pedagogies that address many of the problems experienced in traditional lecture-based classes. In this context, the use of stationary devices to develop flipped learning processes has been a common practice over the last years. However, the ubiquitous characteristics of mobile devices have rarely been investigated to carry out these types of learning methodologies. With this aim, the present investigation explores students’ perceptions and technological acceptance of the implementation of a flipped learning model in two English as a Foreign Language classes. A quantitative analysis was carried out in order to evaluate the information collected in the two groups. Findings yielded a positive perception of the flipped learning experience, particularly in terms of overall satisfaction. In addition, with regard to the use of mobile devices, participants reported ease of use and highlighted the importance of an appropriate design of the video contents for a successful flipped learning experience through mobile devices. Further research into this topic is sought as students also faced difficulties during the project.

Mobile instant messaging (MIM) has become the most popular means for young people to communicate. MIM apps typically come with a myriad of features that educators may leverage to increase student learning. However, it remains poorly understood to what extent and in what aspect MIM can facilitate student engagement. We address the gap by comparing the effects of using MIM and asynchronous online discussion (AOD) on student online engagement, using a quasi-experimental study involving a historical cohort control group. Understanding which communication mode can better promote student online engagement is particularly important during the current widespread use of online learning. Specifically, we examined engagement from the behavioral, emotional, and cognitive dimensions. The results showed that the MIM group was more behaviorally engaged in discussion activities, producing more messages, more words, and higher rates of participation, task completion, and interaction. Emotionally, no statistically significant difference was found in students’ affective evaluation of course interaction and satisfaction between the two groups. However, MIM appeared to help students with improved intimacy and interpersonal relationships. Cognitively, the MIM group was more engaged than the AOD group. In particular, MIM seemed to facilitate interactive idea exchange and thus contributing to more “creating” activities. We conclude by providing suggestions for future instructional practice and research directions.

Background Simulation via Instant Messaging- Birmingham Advance (SIMBA) delivers simulation-based learning (SBL) through WhatsApp® and Zoom® based on Kolb’s experiential learning theory. This study describes how Kolb’s theory was implemented in practice during SIMBA adrenal session. Methods SIMBA adrenal session was conducted for healthcare professionals and replicated Kolb’s 4-stage cycle: (a) concrete experience—online simulation of real-life clinical scenarios, (b) reflective observation—discussion and Q&A following simulation, (c) abstract conceptualisation—post-session MCQs, and (d) active experimentation—intentions to implement the acquired knowledge in future practice. Participants’ self-reported confidence levels for simulated and non-simulated cases pre- and post-SIMBA were analysed using Wilcoxon Signed-Rank test. Key takeaway and feedback were assessed quantitatively and qualitatively in a thematic analysis. Results Thirty-three participants were included in the analysis. A Wilcoxon signed-rank test showed that the SIMBA session elicited a statistically significant change in participants’ self-reported confidence in their approach to Cushing’s syndrome (Z = 3.873, p  = 0.0001) and adrenocortical carcinoma (Z = 3.970, p  < 0.0001). 93.9% ( n  = 31/33) and 84.8% ( n  = 28/33) strongly agreed/agreed the topics were applicable to their clinical practice and accommodated their personal learning style, respectively. 81.8% ( n  = 27/33) reported increase in knowledge on patient management, and 75.8% ( n  = 25/33) anticipated implementing learning points in their practice. Conclusions SIMBA effectively adopts Kolb’s theory to provide best possible experience to learners, highlighting the advantages of utilising social media platforms for SBL in medical education. The ability to conduct SIMBA sessions at modest cost internationally paves way to engage more healthcare professionals worldwide.

The present investigation analyses the potential of a pedagogical dynamic assessment (DA) approach to foster second language (L2) development through the use of a mobile instant messaging application. Students’ zone of actual and proximal development is observed through the use of a grammar and vocabulary level test and the use of the WhatsApp application respectively. Sixty students taking a B1 English course at the language centre of a Spanish university were studied. A mixed methods methodology was used to analyse the differences between two pre-existing groups (control and experimental), each consisting of 30 participants. Both groups received the same tuition and content, and students in the experimental group participated in a daily conversation in the application during a five-month period where negative feedback was provided by the teacher through the use of an inventory of prompts, from most implicit to most explicit. Throughout the research, pedagogical mobile-mediated DA became a central part of the students’ learning process, extending learning beyond the in-class time and becoming a constant source of L2 input and feedback. Moreover, results indicated that DA and dialogic mediation helped students reflect on their language performance, gradually requiring less explicit feedback and metalinguistic explanations.

PurposeWith the growth of digital education, students increasingly interact in a variety of ways. The potential effects of these interactions on their learning process are not fully understood and the outcomes may depend on the tool used. This study explores the communication patterns and learning effectiveness developed by students using two basic synchronous and asynchronous communication tools in e-learning environments, specifically business simulation games.Design/methodology/approachThe authors conduct a quasi-experiment research with 478 online business students, 267 of whom used online discussion forums and 211 interacted via an instant messaging app. The application of learning analytics and text mining on natural language processing allows us to explore the student communication patterns with each of tools and their effectiveness in terms of learning.FindingsThe results confirm the complementarity of the communication tools, asynchronous tools being especially the suitable for task-related communication and synchronous ones for speeding up and facilitating student social interactions.Originality/valueThe main value of this research lies in the use of data analytics and text mining to access and analyse the content of student interactions to assess the learning process in greater depth, comparing synchronous and asynchronous learning modes, considering that little is known about the impact of online synchronous interaction or instant messaging, and even less about the different features, content and performance that emerge when these two learner interaction modalities are compared.

The popularity of Mobile Instant Messaging (MIM) has prompted educators to integrate it in teaching and learning in higher education. WhatsApp® is a multi-platform instant messaging application widely used worldwide, however, there is still little applied research on its use as a platform for educational activities in management higher education. In this article, the authors present a quantitative and qualitative assessment of a concrete experience of WhatsApp® use that involved 140 undergraduate management students. Data were collected through questionnaires answered by the participants after the end of the experience of use, and also via content analysis of their conversations inside their WhatsApp® groups. The results indicate five main educational affordances of MIM that can be considered in management education: interactivity, knowledge sharing, sense of presence, collaboration and ubiquity. The article also explores the limitations of this tool and provides suggestions of good practices of MIM use for teaching and learning.