Addressing Online-Learning Challenges Through Smartphone-Based Gamified Learning Platform

Remote learning has been in the shadows of mainstream higher education institutions (HEI), with classroom/physical presence taking center stage. The Covid-19 pandemic disrupted the prevalent modes of education and pushed remote learning to the forefront. While remote learning has its advantages, there are also downsides, such as lack of learner engagement, learning fatigue, etc., resulting in less than satisfying learning outcomes. The pandemic also showed that simply moving existing teaching artifacts and methods to the virtual realm is not entirely adequate, especially for topics requiring experiential learning such as innovation and entrepreneurship. This project attempts to address some of these critical challenges by building a smartphone application platform for remote learning, emphasizing personalized and gamified learning. The project team adopted a creative approach to realize this ambitious project during the challenging pandemic by engaging current university students in all the implementation teams, eliminating the need to obtain external resources and funding. The student teams were motivated as the project was integrated with their regular university coursework. The gamified smartphone application with Design Thinking as the first learning module was developed and tested for functionality and usability. This project has received encouraging user feedback and provides a platform for developing and testing more engaging methods in the future for personalized remote learning, using artificial intelligence (AI) and machine learning (ML). © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Stress Data Collection and Analysis Using 'Mind Scale' with the Post-Covid World

In this paper, stress data collection and analysis using 'Mind Scale™' is proposed. A fingertip pulse wave sensor module is utilized along a smartphone application. Biological signals such as pulse, voice and facial expression are analyzed with questionnaire and managed in the cloud. With the post-covid world, this system helps us to detect our mental health condition for new lifestyle. © 2023 IEEE.

A Smartphone based Remote-Lab cum Topic-Specific Learning Management System

A smartphone application has been developed to help students perform laboratory experiments remotely and on the go. The students need to use their smartphones or tablets to connect with the teacher's smartphone, which in turn is interfaced with the actual experiment through a data-acquisition setup. The students may interact and seek help from the teacher at every step of the experiment. The teacher may provide the students with all the information and resources from within the application itself. The teacher may also manage the progress of learning of the experimental topic by each individual student. Such an interactive remote learning approach to laboratory experiments and related topics may prove very helpful for both the teachers and the students, especially in these times of the new normal. © 2022 IEEE.

Fully autonomous domino capillaric circuit for instrument-free, quantitative detection of SARS-CoV-2 in saliva

Rapid, sensitive, quantitative and patient-friendly diagnostic tools have yet to be developed for COVID-19 continued monitoring at the point-of-care. Here, we present an instrument-free capillary microfluidic chip coupled to a lateral flow module that is compatible with a smartphone application for quantitative detection of SARS-CoV-2 from saliva samples. The microfluidic chip is fully autonomous, and performs aliquoting, sample metering, and sequential delivery of reagents. The limit of detection is 0.07 ng/mL for recombinant nucleocapsid protein in saliva. This rapid antigen test provides results in less than 1 hour, without sacrificing analytical sensitivity. © 2021 MicroTAS 2021 - 25th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.

Evaluating the Marketing Strategy of Sports and Fitness Enterprises based on 4C Marketing Theory

With the COVID-19 outbreak, there is an increasing focus on sports and fitness needs. Due to the need of epidemic prevention and control, fitness at home has gradually become a popular lifestyle. With the rapid development of smart phone application technology, artificial intelligence and Internet of Things, many enterprises have developed sports and fitness apps. These apps provide training courses for users, and customizes personalized training plans for them in combination with smart wearable devices. Keep App, a sports and fitness app developed by Keep Company, has the most users in China at present. It has created a technology platform for users to experience smart sports at home from multiple aspects, and has gained considerable income in operation. Taking Keep company as an example, this paper analyzes the marketing environment of the sports and fitness industry by using PEST model and Porter's Five Forces model, and puts forward optimization suggestions for Keep company's marketing strategy from the aspects of customer's need strategy, customer's cost strategy, convenience strategy and communication strategy by using 4C marketing theory. © 2022 ACM.

Gamification: A Motivation Metric Based in a Markov Model

The current situation in the world with the COVID-19 pandemic has reinforced a pre-existing trend based on increasing the use of gamification tools in education to motivate students. In this work, a study based on a Markov model is proposed to assess motivation during the training process in higher education. The evolution of Faculty of Business Administration graduates when using a gamified smartphone application (HEgameApp) has been measured. The behavior of graduates is assessed through collaboration in fora created by HegameApp, and the recognition given by their classmates. A utility function is defined to obtain a statistical estimator used in the assignment of motivational states of the study participants. In addition, a decrement function is assigned to the value of the components of the utility function to estimate the time variation of motivation during the process of knowledge assimilation. The proposed solution shows that when graduates are involved in using the app, they significantly increase their academic outcomes and satisfaction while receiving the lectures. In addition, the positive feedback perceived through the application fora has a measurable effect on their motivation. © 2022. International Journal of Emerging Technologies in Learning. All Rights Reserved.

Designing to Fight Pandemics: A Review of Literature and Identifying Design Patterns for COVID-19 Tracing Apps

Throughout the pandemic, digital contact tracing using smartphone applications (or apps) has been endorsed by many authorities across the globe as a tool to limit the spread of COVID-19. Consequently, to deploy contact tracing in large populations, multiple contact tracing apps have been developed and deployed globally. However, due to the relative recency of the COVID-19 pandemic as well as the suddenness of the need for contact tracing at this scale, app designers are often left with no systematic guidelines. Designers today lack guidelines on what factors might affect perceptions and adoption of their apps. They also lack a knowledgebase of features that could be appropriate to include in their app for a given context. To address this gap, we conducted a review of the academic literature on attitudes towards and adoption of COVID-19 response apps, as well as a feature review of a diverse set of international tracing apps. Our investigation yielded a set of design patterns which can be used readily by designers of contact tracing apps. Our work lays the foundation to identify opportunities for new contextual feature design and use. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

A Design Science Approach to Blood Donation Apps

The COVID-19 pandemic has put additional pressure on the healthcare systems worldwide. It also led to a significant shortage of blood products. Delaying surgeries resulted in an increased demand at peak times that aligned with a decrease in blood donations at the same time. While being crucial for many surgeries and also certain types of treatments, blood cannot be produced artificially, but healthcare systems rely on voluntary donations. The relatively short shelf-life of most products makes a close matching of demand and supply necessary. We argue that smartphone applications can help to motivate donors to donate blood when necessary, giving access to all relevant information and services. By applying the design science research methodology, we derived design principles for effective smartphone applications and present a conceptual model in the form of mock-ups. We performed two design cycles and evaluated the design principles and the conceptual model with regular, lapsed, first-time and non-donors from Germany in a focus group discussion. © 2022, Springer Nature Switzerland AG.

Privacy Concerned on Contact-Tracing Application during COVID-19

The COVID-19 pandemic has greatly affected humanity by destabilizing the world economy through strain on hospital systems and deaths. Medical personnel is working around the clock to establish vaccines. On the other hand, technology contributes to the fight against the virus by tracking COVID-19 infections. Many digital contact tracking smartphone applications have been created to address this epidemic successfully. However, the applications lack transparency, raising worries about their privacy. Contact tracing has been employed to stop the spread of the disease. When battling the coronavirus epidemic, computerized contact tracking has quickly emerged as an essential tool. Therefore, the research conducted in this paper focuses on the challenges of tracking applications to analyze the perspective view of privacy issues. Besides, the paper proposes policies for data privacy to aid in making the tracking applications more effective and successful. © 2022 IEEE.

Dagang Yuk Yuk As Smartphone Application for MSME Product Sales

Many MSMEs manually close their businesses in today's competition, especially those caused by the COVID19 pandemic, and besides that, the lack of technology implementation is even more aggravating. Like it or not, Micro, Small, and Medium Enterprises (MSMEs) must equip their businesses with the application of technology, and unfortunately, there are still many MSMEs that have not been able to take advantage of the benefits of technological developments. Many companies see this condition as an opportunity;for example, Gojek and Grab partner with MSME players to make it easier to trade their products or services. In this paper, a smartphone application for MSMEs called 'Dagang Yuk Yuk, ' which consists of activities such as Login, Create Order, Input Delivery Location, Select Courier, and Select Payment Method has been proposed. Dagang Yuk Yuk tries to give different ideas for implementing MSME actors where this application is only for MSME players as part of an MSME business unit. This paper discusses the application's design using use case diagrams to describe the business process, while class diagrams model the database design. This application was developed using Arduino studio and MySQL database for database storage. © 2022 IEEE.

Software Engineering for Estimation of Social Distancing in Pandemic Times

This paper present a model of software engineering to estimate the social distancing with realistic inputs. This might be incorporated in a smart-phone application in order to get an exact estimate of the values of social distancing in times of global pandemic. Attention is paid on the measurement of outdoor scenarios where wind velocity would play an important role to move the aerosols at distances beyond the known social distances. Thus, the dehydration time emerges also as a predictor of risk to get the infection of virus. The proposed software has capabilities to yield numeric values of risk in terms of probabilities. It is expected that once the associated computational program is running then the permanent assessment of potential scenarios would give concrete values of social distancing. In this manner one expects that these values are uploaded at an Internet network. © 2021 IEEE.

On the Performance and Effectiveness of Digital Contact Tracing in the Second Wave of COVID-19 in Italy

Contact-tracing smartphone applications have been developed and used as a complement to manual contact tracing in the COVID-19 pandemic. The goal of these apps is to trace contacts between people and notify the mobile phone owners when one of their contacts tested positive. People who receive a notification should behave as exposed people, take a test, and possibly isolate themselves until they receive the result. Unfortunately, identifying contacts based on distance is technically a daunting task: apps can be configured conservatively (a very small number of people are notified, limiting the effectiveness of the app) or they may be more tolerant and produce a high number of notifications but also of false positives. We review the data available from Immuni, the Italian app, which provides detailed figures on the notifications sent and the positive users, and we show that Immuni was configured to generate a very large amount of notifications. We estimate the testing resources that the health system would have needed if the app was downloaded by 100%of the adult population, and every notified person would require a test. In such conditions, Immuni would have generated a number of tests orders of magnitude higher than what was available. We compare the performance of Immuni with the currently available literature on other apps and observe that contact-tracing apps had a limited impact on the second wave of the COVID-19 pandemic. As contact tracing exposes citizens to privacy risks, we discuss some ways to reshape the goal of the apps to achieve a better tradeoff between social benefit and risk. IEEE

Revising College Algebra Instruction to Accept and Incorporate the Use of Smart Phone Applications

The unavoidable transition to online education due to Covid-19 pandemic has impacted instruction at all grades and in all subject areas, including college level Mathematics courses. One of the issues that has been faced is the inability to proctor exams properly. Calculators with Computer Algebra Systems and their corresponding smart phone applications can provide not only answers to most problems, but they also provide solution steps. Mathematics departments at many institutions have established policies which regulated the use of calculators and smart phones in lectures and exams. However, lack of proper proctoring in online courses makes it possible for students to pass a course, even with a decent grade, without learning the concepts. On the other hand, as the use of computers became more common, many skills previously considered as required are not required anymore, such as learning how to use logarithmic tables to evaluate logarithms. In this study, we first demonstrate the capabilities of smart phone applications and provide tips for writing procedural problems that are not easily solvable by these apps. We show examples of problems that are solvable by the apps and suggestions to revise them. Second, we discuss general suggestions on how to revise the College Algebra instruction, especially for engineering students. Our suggestions aim to fill in the gaps that could potentially be created when these apps are commonly used among students. In summary, we review and revise College Algebra instruction and assessments to accept and incorporate the use of smart phone applications. Revised topics, together with effective assessment strategies will potentially improve learning outcomes, especially when the course is taught online. Our work concentrates on revision of College Algebra topics for Engineering students, but our strategy can be applied to revise other mathematics topics for any major. © American Society for Engineering Education, 2021

Infection Detection through Temperature Monitoring

This paper describes the theory behind a smartphone application designed to detect COVID-19 infections through temperature monitoring. COVID-19 infections can cause a temperature increase typically around 0.5 C over a slow, moderate, nonlinear multi-day course averaging 5 days. To enable detection of this increase, filtering techniques are applied to simultaneously establish a base temperature and to detect a COVID-typical deviation from that base temperature. Numerical simulations are developed to assess the effectiveness of the application in detecting the presence of an infection in individuals and in groups. The measure of effectiveness is the number of new-infections incurred before the initial infection is detected. It is observed that group testing and group analysis becomes increasingly effective as the infection rate is increased, e.g. R0 ≥ 3. If the infection rate is low, e.g. R0 ≤ 1.1, group analysis becomes ineffective because, at any given time, too few people are infected simultaneously to be detectable in the group average. The effectiveness of individual testing and the individual analysis is unaffected by the infection rate. This result is significant since it has to be expected that widespread vaccination as well as social distancing efforts significantly reduce the infection rate making outbreaks challenging to spot. © 2022, American Institute of Aeronautics and Astronautics Inc.. All rights reserved.