Learning Analytics Overview: Academic Approach and Machine Learning Possibilities

In the Covid-19 era, traditional lecture-based teaching has been undergoing changes in learning design, learners' engagement, and technology integration. Online learning has become an integral part of education around the globe due to its flexibility in learning with respect to place and time. These online courses are available to larger audiences and enable students to have more freedom over the study process. However, freedom also means that instructors have less control to keep students making progress on the course. The flexibility of online courses is encouraging the students to enrol with a few clicks but most of these students are dropping out due to losing interest in the course contents within a few weeks. On the contrary, online learning produces large amounts of data that can be used to follow the learning process and give useful insights for both teachers and students. Learning analytics algorithms utilize these data to identify the factors and parameters that can explain learners' dropout rate, learning performance, as well as suggest possible actions to intrigue learners' active engagement. To conduct further research on the parameters affecting learners' participation in an online course, it is essential to find out the previous research works, best practices, and research trends of learning analytics. In the scope of this work, the authors formulated a search query to generate a pool of most relevant papers from the Scopus database and, hence, identified seven clusters which illustrate the landscape of the learning analytics domain. The authors also employed the Latent Dirichlet allocation (LDA) topic modeling algorithm which is a form of text data mining and statistical machine learning approach to compare the similarities with the clusters generated as a part of literature review. The authors further analyzed the papers in each cluster to identify the parameters which are significant to build a predictive model on learners' dropout rate. This work not only provides a baseline to conduct further research to find out the parameters affecting learners' retention rate but also introduces a systematic methodology to validate the findings of the literature review with a data-driven algorithmic approach. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Systematic Assessment and Illustration of Students' Online Discussion Engagement

During Covid-19, most of the university courses have been transited to distance education and online teaching. It is unfortunate but true that most of this distance teaching lacks the active participation of learners, thus failing to keep their attention throughout the teaching time. According to "Dale's Cone of Learning,” students only remember 20 percent of the lecture without the involvement of any active participation. So it has become critical to find ways to engage these distance learners actively. The online discussion forum can be utilized as the primary tool to intrigue the active engagement of the learners. Therefore, it is also necessary to measure the students' active engagement in online course discussion forums. Digitalization of the teaching process allows access to a large amount of data representing learners' behavior. Every click can be observed and analyzed, which allows automating the assessment of the learning process. This paper aims to employ an existing approach introduced by the authors in previous work to translate learner's engagement quantitatively based on their online discussion activity, which can be further utilized for assessment and understanding the interaction dynamics within the course. The discussion forum data from three cohorts of an online course on "Systematic Creativity and TRIZ basics” at LUT University, Finland, is analyzed via employing Social Network Analysis and natural language processing (NLP). Learners' engagement in the discussion forums is assessed by focusing on two main criteria: the number of meaningful words used and the centrality measure of network analysis. As a result, the assessment of 50+ students' discussion forum activity depicts a strong correlation between the meaningful words used by the students and their interaction (degree centrality and eigenvector centrality). © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

A Unified Decision-Making Technique for Analysing Treatments in Pandemic Context

The COVID-19 pandemic has triggered a global humanitarian disaster that has never been seen before. Medical experts, on the other hand, are undecided on the most valuable treatments of therapy because people ill with this infection exhibit a wide range of illness indications at different phases of infection. Further, this project aims to undertake an experimental investigation to determine which treatments for COVID-19 disease is the most effective and preferable. The research analysis is based on vast data gathered from professionals and research journals, making this study a comprehensive reference. To solve this challenging task, the researchers used the HF AHP-TOPSIS Methodology, which is a well-known and highly effective Multi-Criteria Decision Making (MCDM) technique. The technique assesses the many treatment options identified through various research papers and guidelines proposed by various countries, based on the recommendations of medical practitioners and professionals. The review process begins with a ranking of different treatments based on their effectiveness using the HF-AHP approach and then evaluates the results in five different hospitals chosen by the authors as alternatives. We also perform robustness analysis to validate the conclusions of our analysis. As a result, we obtained highly corroborative results that can be used as a reference. The results suggest that convalescent plasma has the greatest rank and priority in terms of effectiveness and demand, implying that convalescent plasma is the most effective treatment for SARS-CoV-2 in our opinion. Peepli also has the lowest priority in the estimation. © 2022 Tech Science Press. All rights reserved.

Catering for the point-of-care testing explosion

The ease of performing a laboratory test near to the patient, at the point-of-care, has resulted in the integration of point-of-care tests into healthcare treatment algorithms. However, their importance in patient care necessitates regular oversight and enforcement of best laboratory practices. This review discusses why this oversight is needed, it’s importance in ensuring quality results and processes that can be placed to ensure point-of-care tests are chosen carefully so that both oversight can be maintained and patient care is improved. Furthermore, it highlights the importance of delivering focused webinars and continuing education in a variety of formats. © 2021 International Federation of Clinical Chemistry and Laboratory Medicine. All rights reserved.

Transition of an Interactive, Hands-on Learning Tool to a Virtual Format in the Covid-19 Era

The 2020 coronavirus pandemic necessitated the transition of courses across the United States from in-person to a virtual format. Effective delivery of traditional, lecture-based courses in an online setting can be difficult and determining how to best implement hands-on pedagogies in a virtual format is even more challenging. Interactive pedagogies such as hands-on learning tools, however, have proven to significantly enhance student conceptual understanding and motivation;therefore, it is worthwhile to adapt these activities for virtual instruction. Our team previously developed a number of hands-on learning tools called Low-Cost Desktop Learning Modules (LCDLMs) that demonstrate fluid mechanics and heat transfer concepts-traditionally utilized by student groups in a classroom setting, where they perform qualitative and quantitative experiments and interactively discuss conceptual items. In this paper we examined the transition of the LCDLM hands-on pedagogy to an entirely virtual format, focusing on a subset of results with greater detail to be shown at the ASEE conference as we analyze additional data. To aid the virtual implementations, we created a number of engaging videos under two major categories: (1) demonstrations of each LCDLM showing live data collection activities and (2) short, animated, narrated videos focused on specific concepts related to learning objectives. In this paper we present preliminary results from pre- and post- implementation conceptual assessments for the hydraulic loss module and motivational surveys completed for virtual implementations of LCDLMs and compare them with a subset of results collected during hands-on implementations in previous years. Significant differences in conceptual understanding or motivation between hands-on and virtual implementations are discussed. This paper provides useful, data-driven guidance for those seeking to switch hands-on pedagogies to a virtual format. © American Society for Engineering Education, 2021

Progress in the Nationwide Dissemination and Assessment of Low-Cost Desktop Learning Modules and Adaptation of Pedagogy to a Virtual Era

The development of tools that promote active learning in engineering disciplines is critical. It is widely understood that students engaged in active learning environments outperform those taught using passive methods. Previously, we reported on the development and implementation of hands-on Low-Cost Desktop Learning Modules (LCDLMs) that replicate real-world industrial equipment which serves to create active learning environments. Thus far, miniaturized venturi meter, hydraulic loss, and double-pipe and shell & tube heat exchanger DLMs have been utilized by hundreds of students across the country. It was demonstrated that the use of DLMs in face-to-face classrooms results in statistically significant improvements in student performance as well as increases in student motivation compared to students taught in a traditional lecture-only style classroom. Last year, participants in the project conducted 45 implementations including over 600 DLMs at 24 universities across the country reaching more than 1,000 students. In this project, we report on the significant progress made in broad dissemination of DLMs and accompanying pedagogy. We demonstrate that DLMs serve to increase student learning gains not only in face-to-face environments but also in virtual learning environments. Instructional videos were developed to aid in DLM-based learning during the COVID-19 pandemic when instructors were limited to virtual instruction. Preliminary results from this work show that students working with DLMs even in a virtual setting significantly outperform those taught without DLM-associated materials. Significant progress has also been made on the development of a new DLM cartridge: a see-through 3D-printed miniature fluidized bed. The new 3D printing methodology will allow for rapid prototyping and streamlined development of DLMs. A 3D-printed evaporative cooling tower DLM will also be developed in the coming year. In October 2020, the team held a virtual implementers workshop to train new participating faculty in DLM use and implementation. In total, 13 new faculty participants from 10 universities attended the 6-hour, 2-day workshop and plan to implement DLMs in their classrooms during this academic year. In the last year, this project was disseminated in 8 presentations at the ASEE Virtual Conference (June 2020) and American Institute of Chemical Engineers Annual Conference (November 2019) as well as the AIChE virtual Community of Practice Labs Group and a seminar at a major university, ultimately disseminating DLM pedagogy to approximately 200 individuals including approximately 120 university faculty. Further, the former group postdoc has accepted an instructor faculty position at University of Wisconsin Madison where she will teach unit operations among other subjects;she and the remainder of the team believe the LCDLM project has prepared her well for that position. In the remaining 2.5 years of the project, we will continue to evaluate the effectiveness of DLMs in teaching key heat transfer and fluid dynamics concepts thru implementations in the rapidly expanding pool of participating universities. Further, we continue our ongoing efforts in creating the robust support structure necessary for large-scale adoption of hands-on educational tools for promotion of hands-on interactive student learning. © American Society for Engineering Education, 2021

Analyzing the Implications of Healthcare Data Breaches through Computational Technique

The contributions of the Internet of Medical Things (IoMT), cloud services, information systems, and smart devices are useful for the healthcare industry. With the help of digital healthcare, our lives have been made much more secure and effortless and provide more convenient and accessible treatment. In current, the modern healthcare sector has become more significant and convenient for the purpose of both external and internal threats. Big data breaches affect clients, stakeholders, organisations, and businesses, and they are a source of concern and complication for security professionals. This research examines the many types and categories of big data breaches that companies face. In addition, the study's main purpose is to investigate and draw conclusions from healthcare big data breaches, with the goal of improving healthcare big data confidentiality. From the beginning of 2020-21, both years, practically our entire world moved online due to the COVID-19 pandemic. The coronavirus pandemic dramatically increased the extent of use of technology. Hacking/IT incidents, followed by unauthorised internal disclosures, are the most typical attacks behind healthcare data breaches, according to the report. This has become a main enticement for healthcare data theft and misuse. The number of healthcare big data breaches, the number of records exposed, and the resulting significant commercial losses are increasing. In the report, they analyze and investigate the number of healthcare big data breaches, the number of records exposed during the COVID-19 pandemic. Also, the study assesses the correctness of the datasets in order to achieve a dynamic digital healthcare data breaches environment using fuzzy based computational technique.

Successful reservoir fluid characterization and testing while overcoming the challenges of falling oil price and a pandemic: A first for an integrated brown field alliance project in Sarawak, Malaysia

A brown field, offshore Sarawak, Malaysia, with multiple sub-layered laminated sands of varied pressure regimes and mobility ranges, was challenged by depletion, low mobility and uncertainty in the current fluid types and contacts. Optimal dynamic fluid characterization and testing techniques comprising both Wireline and Logging While Drilling (LWD) were applied in nine development wells to acquire reliable formation pressure data and collect representative fluid samples including fluid scanning. Some of the latest technologies were deployed during the dual crises of falling oil price and the Covid-19 pandemic. The S-profile wells were drilled using oil-base mud (OBM) with an average deviation of 60 degrees. Formation Pressure While Drilling (FPWD), Fluid Sampling While Drilling (FSWD) and wireline formation testing, and sampling were all utilized allowing appropriate assessment of zones of interest. Various probe types such as Conventional Circular, Reinforced Circular, Elongated, Extra-Elongated and Extended Range Focused were used successfully, ensuring that the right technology was deployed for the right job. Formation pressure and fluid samples were secured in a timely manner to minimize reservoir damage and optimize rig time without jeopardizing the data quality. As a classified crisis due to the pandemic, rather than delaying the operations, a Remote Operations Monitoring and Control Center was set-up in town to aid the limited crew at rig site. A high success rate was achieved in acquiring the latest formation pressure regimes, fluid gradients, scanning and sampling, allowing the best completion strategy to be implemented. With the selection of the appropriate probe type at individual sands, 336 pressure tests were conducted, 44 fluid gradients were established, 27 fluid identification (fluid-id / scanning) pump-outs were performed, and 20 representative formation fluid samples (oil, gas, water) were collected. Amongst the Layer-III, Layer-II and Layer-I sands, Layer-I was tight, with mobility < 1.0 mD/cP. Wireline focused probe sampling provided clean oil samples with 1.4 to-3.7 wt. % OBM filtrate contamination. The water samples collected from Layer-II during FSWD proved to be formation water and not injection water. The wells were thus completed as oil producers. Reliable fluid typing and PVT quality sampling at discrete depths saved rig time and eliminated the requirement of additional runs or services including Drill Stem Testing (DST). This case study has many firsts. It is the first time where latest fluid characterization and testing technologies in both Wireline and LWD were deployed for an alliance project in Malaysia and that too during dual crises of falling oil price and the pandemic aftermath. Overcoming various challenges including limited rig site manpower, there was no delay in completing the highly deviated wells with tight formations in a single drilling campaign and provided rig time savings. For the purpose of this case study, two wells have been discussed. First well used the wireline focused sampling technology and the second used the FSWD technology. © 2021, Society of Petroleum Engineers.

Impact assessment of covid-19 pandemic through machine learning models

Ever since its outbreak in the Wuhan city of China, COVID-19 pandemic has engulfed more than 211 countries in the world, leaving a trail of unprecedented fatalities. Even more debilitating than the infection itself, were the restrictions like lockdowns and quarantine measures taken to contain the spread of Coronavirus. Such enforced alienation affected both the mental and social condition of people significantly. Social interactions and congregations are not only integral part of work life but also formthe basis of human evolvement. However, COVID-19 brought all such communication to a grinding halt. Digital interactions have failed to enthuse the fervor that one enjoys in face-to-face meets. The pandemic has shoved the entire planet into an unstable state. The main focus and aim of the proposed study is to assess the impact of the pandemic on different aspects of the society in Saudi Arabia. To achieve this objective, the study analyzes two perspectives: The early approach, and the late approach of COVID-19 and the consequent effects on different aspects of the society. We used a Machine Learning based framework for the prediction of the impact of COVID-19 on the key aspects of society. Findings of this research study indicate that financial resources were the worst affected. Several countries are facing economic upheavals due to the pandemic and COVID-19 has had a considerable impact on the lives as well as the livelihoods of people. Yet the damage is not irretrievable and the world's societies can emerge out of this setback through concerted efforts in all facets of life. © 2021 Tech Science Press. All rights reserved.

Modifying surgical practice in the times of current COVID-19 pandemic

In the times of current coronavirus disease 2019 (COVID-19) pandemic, the surgical practice is suffering. The present report summarises the impact of this pandemic on our surgical services and the changes that have been promulgated for the resumption of services with the purpose of providing valuable information for our surgical colleagues worldwide. Almost six months have passed since this pandemic started, and the total number of confirmed cases has exceeded 7 million;and over 400 thousand lives have been claimed till now. We need to find ways to continue providing essential medical services to patients, while fighting with this pandemic since it might take longer than expected to end.

Modifying Surgical Practice in the Times of Current COVID-19 Pandemic

In the times of current coronavirus disease 2019 (COVID-19) pandemic, the surgical practice is suffering. The present report summarises the impact of this pandemic on our surgical services and the changes that have been promulgated for the resumption of services with the purpose of providing valuable information for our surgical colleagues worldwide. Almost six months have passed since this pandemic started, and the total number of confirmed cases has exceeded 7 million;and over 400 thousand lives have been claimed till now. We need to find ways to continue providing essential medical services to patients, while fighting with this pandemic since it might take longer than expected to end. Key Words: COVID-19, Pandemic, Surgery, Personal protective equipment, N95 masks.