Methodological Strategy for the Development of Academic Motivation of First-year High School Students in the Face of the New Normal

Academic demotivation is a determining factor in the risk of dropping out of school, it prevents the student from maintaining a behavior oriented to student achievement, low self-esteem and the formation of an erroneous self-concept;which became evident in the face of the changes in the educational context as a result of Covid-19. In view of the academic demotivation shown by the students when returning to face-to-face classes, the objective of the research was to design a methodological strategy for the development of the students' academic motivation in the face of the new normality. The sample consisted of 126 students, and the research approach was mixed. The method used was the survey, the results of which show that 54.76% of the students feel unmotivated to continue their studies. Based on the results obtained, a methodological strategy was designed for the development of students' academic motivation.

Design Thinking Methodology in university teaching for the development and learning achievements in architecture

The present study analyzes the relevance of the design thinking methodology, in English Design Thinking, a collaborative work strategy to maximize collective creativity, in university students of the second semester of the architecture career of the composition II subject, at the Technological University Metropolitan of Chile. The classes were taught remotely (on-line) during the pandemic caused by the coronavirus. The methodology is descriptive and the study is part of the approach of self-directed experience and field study from virtual scenarios, applying the stages: Empathize, define, devise, prototype and devise, which allowed enriching knowledge in education from teaching-learning, improving evidence of learning achievements. A questionnaire was applied to a sample of 104 students;as a result, 61 answers that show the understanding and support of the Design Thinking methodology from the technical and analytical to the architectural activities. The student body managed to develop creativity, systematization and technical skills through the application of research instruments that contribute to the creation of architectural composition projects, placing the social needs and hopes of the user or target audience at the center of decisions © 2023, Revista de Ciencias Sociales.All Rights Reserved.

Digital Global Classroom, a Collaborative Online International Learning (COIL) Approach: An Innovative Pedagogical Strategy for Sustainable Competency Development and Dissemination of SDGs in Engineering Higher Education

One of the most popular strategies to develop skills such as collaborative work, critical thinking, and problem-solving is the application of Collaborative Online International Learning (COIL), in which Professors from at least two universities from different countries and cultures develop a period known as "Global Classroom” (GC) in which, through the Challenge-Based Learning (CBL) approach, they solve a real challenge, using digital communication tools. This study held four-week global courses between groups from the Tecnológico de Monterrey in Mexico and groups from the Corporación Universitaria Minuto de Dios in Colombia. The challenges were related to two fundamental issues in sustainability: 1) Management of natural resources and climate change and 2) Biomimetics. Students were able to solve the challenges, develop skills to communicate effectively through online interaction with people from different cultures and disciplines, and use technological tools that facilitate distance learning in multicultural virtual environments. Current teaching models involve active and experiential learning, developing soft and hard skills. The GC experience is a tool that allowed continuity in the preparation of students during the COVID-19 pandemic. The use of GC is available to those interested as a valuable tool to provide students with the opportunity to live sustainable international experiences and promote the Sustainable Development Goals (SDG). © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Unveiling the Process of Collaborative Learning Through the Use of Digital Whiteboard Historical Action Logs

The Covid-19 pandemic has forced many educational institutions to transit from face-to-face to online delivery of lessons. Precluded from meeting face-to-face in a classroom due to pandemic curbs, a digital whiteboard affords both teacher and learners to be collaborating and completing a task from home instead. In this paper, we first used a survey to assess learner's acceptance and use of digital whiteboard. We next web-scraped and visualized historical action logs recorded by the digital whiteboarding tool to uncover the process of problem-solving between and within the teams. This is significant as social-loafing and free-riding are typically difficult to detect and prevent in collaborative learning. In addition, instructors traditionally evaluate only the product but not the process of collaborative learning as most collaborative work of learners occur outside scheduled teaching hours. From the results of the survey, we can conclude that the digital whiteboard is accepted by the learners. It also encourages collaboration and leads to higher learning motivation of learners. From the visualizations of the historical action logs, we were able to discover differing interaction and collaboration practices among the teams as well as the contributions of team members within each team (e.g. some teams exhibiting uneven effort distribution). We believe that our findings are significant as to the best of our knowledge, this is the first study that uses historical action logs from digital whiteboard to gain insights into the process and evidence of collaborative learning through visualization techniques. © 30th International Conference on Computers in Education Conference, ICCE 2022 - Proceedings.

SUPPORTING RURAL OUTPATIENTS THROUGH A WEB-BASED CONVERSATIONAL USER INTERFACE

Even before the current (2020/2021) pandemic began, Conversational User Interfaces (CUI) had been seen as a valuable way to ease the burden on medical staff in many countries. In times of restricted direct contact with people, the need for online or virtual tools to connect patients with physicians has become even more visible. In addi-tion, these restrictions hamper the training conditions for prospective doctors. This paper describes the design and implementation of a CUI covering patients' minor complaints of the Ear, Nose, and Throat (ENT), which can be correlated with infection by COVID-19. The purpose of this study is to provide pilot test results for an online anamnesis and diagnosis tool supporting the cooperative work of specialists and non-specialists at their workplaces. We have designed and created the cooperative online anamnesis and diagnosis system (COLDS) using 1) a knowledge-based system for the anamnesis mainly of complaints related to ENT including the eyes, 2) a knowledge base of disorders regard-ing ENT and eyes, and 3) a user interface that assists patients as well as cooperative processes involving non-specialists and specialists. COLDS is part of a clinical decision support system. The system has been evaluated in a two-tier pilot test process set in a real-life environment: Tier 1 was concerned with the usability of the system;whereas Tier 2 involved medical specialists to evaluate the outcome and recommendations created by the system based on an adapted Objective Structured Clinical Examination (OSCE) framework. Medical interns and doctors evaluated the system with a five-point Likert scale and the results show that 4.38 for the ease of system and 4.51 for overall satisfac-tion with the system at the confidence interval 95%. © 2023 ICIC International.

Toward Trustworthy AI: Blockchain-Based Architecture Design for Accountability and Fairness of Federated Learning Systems

Federated learning is an emerging privacy-preserving AI technique where clients (i.e., organizations or devices) train models locally and formulate a global model based on the local model updates without transferring local data externally. However, federated learning systems struggle to achieve trustworthiness and embody responsible AI principles. In particular, federated learning systems face accountability and fairness challenges due to multistakeholder involvement and heterogeneity in client data distribution. To enhance the accountability and fairness of federated learning systems, we present a blockchain-based trustworthy federated learning architecture. We first design a smart contract-based data-model provenance registry to enable accountability. Additionally, we propose a weighted fair data sampler algorithm to enhance fairness in training data. We evaluate the proposed approach using a COVID-19 X-ray detection use case. The evaluation results show that the approach is feasible to enable accountability and improve fairness. The proposed algorithm can achieve better performance than the default federated learning setting in terms of the model's generalization and accuracy.

Smart Virtual Environment To Support Collaborative Medical Diagnosis

Since the start of coronavirus pandemic (COVID-19), remote collaboration is increasingly becoming an important requirement in the healthcare sector. This is due to the fact that new information and communication technologies (ITC) can offer more flexibility in time and space. Therefore, we present in this paper a virtual environment that aims to support remote collaborative medical diagnosis. This proposal is mainly based on cognitive studies carried out in the medical field. Moreover, to support medical decision-making, we have integrated an intelligent system into our virtual environment using deep learning technologies. © 2022 IEEE.

SUPPORTING RURAL OUTPATIENTS THROUGH A WEB-BASED CONVERSATIONAL USER INTERFACE

Even before the current (2020/2021) pandemic began, Conversational User Interfaces (CUI) had been seen as a valuable way to ease the burden on medical staff in many countries. In times of restricted direct contact with people, the need for online or virtual tools to connect patients with physicians has become even more visible. In addi-tion, these restrictions hamper the training conditions for prospective doctors. This paper describes the design and implementation of a CUI covering patients’ minor complaints of the Ear, Nose, and Throat (ENT), which can be correlated with infection by COVID-19. The purpose of this study is to provide pilot test results for an online anamnesis and diagnosis tool supporting the cooperative work of specialists and non-specialists at their workplaces. We have designed and created the cooperative online anamnesis and diagnosis system (COLDS) using 1) a knowledge-based system for the anamnesis mainly of complaints related to ENT including the eyes, 2) a knowledge base of disorders regard-ing ENT and eyes, and 3) a user interface that assists patients as well as cooperative processes involving non-specialists and specialists. COLDS is part of a clinical decision support system. The system has been evaluated in a two-tier pilot test process set in a real-life environment: Tier 1 was concerned with the usability of the system;whereas Tier 2 involved medical specialists to evaluate the outcome and recommendations created by the system based on an adapted Objective Structured Clinical Examination (OSCE) framework. Medical interns and doctors evaluated the system with a five-point Likert scale and the results show that 4.38 for the ease of system and 4.51 for overall satisfac-tion with the system at the confidence interval 95%. © 2023 ICIC International.

Visual Management (VM) supporting collaborative practices in infrastructure engineering design

Managing the design of complex engineering systems requires an organisational structure and an information system to support collaboration among all stakeholders. Technological developments in information management have the potential to facilitate interactions across physical boundaries, even more during the Covid-19 pandemic. Visual Management (VM) is an information management strategy, as well as a means for communication between individuals, supporting collaborative work. However, there is a lack of effective understanding of how digital VM can support infrastructure engineering design. The adoption of digital collaborative VM in the context addressed is new, under rapid evolution, and there is limited understanding of how the users embrace VM while interacting with it. The aim of the paper is to explore the adoption of VM, focusing on digital whiteboards, to support collaborative practices in design processes. The ongoing investigation is carried out in collaboration with an infrastructure design and consultancy company, and follows the action research approach. The VM effectiveness was investigated by analysing the whiteboards applicability to diverse functions and comparing digital and manual implementations. Initial findings include understanding digital whiteboards as a means for collaboration among individuals with different perceptions to establish a common point of view, as it allows the information to be transferred across time and space, identifies abnormalities, and supports problem-solving. By creating a common ground, it has the potential to support complex and emergent interactions in the collaborative space.

The perceived impact of project ECHO networks in Northern Ireland for health and social care providers, patients, and the health system: A qualitative analysis.

This study assesses the perceived impact and benefits of Project ECHO (Extension for Community Healthcare Outcomes), a tele-mentoring intervention for health and social care providers, patients and the health system in Northern Ireland. Having access to a specialist, a space to share experiences, and being able to disseminate up-to-date best practice were all cited as improving provider knowledge as well as improving quality of care for patients. Healthcare providers reported being more confident in managing patients and that relationships had been improved between different levels of the health system. ECHO was described as improving access to education and training by removing geographic and time barriers. This is one of the first studies to qualitatively analyse impact across a number of different clinical and social care ECHO networks. The results strongly indicate the perceived benefit of ECHO in improving provider, patient and health system outcomes such as increased healthcare provider knowledge and confidence to manage patients at primary levels of the health system. This has implications for future service design, particularly within the context of COVID-19 in which virtual and online training is necessitated by social distancing requirements.

Collaborative Federated Learning for Healthcare: Multi-Modal COVID-19 Diagnosis at the Edge

Despite significant improvements over the last few years, cloud-based healthcare applications continue to suffer from poor adoption due to their limitations in meeting stringent security, privacy, and quality of service requirements (such as low latency). The edge computing trend, along with techniques for distributed machine learning such as federated learning, has gained popularity as a viable solution in such settings. In this paper, we leverage the capabilities of edge computing in medicine by evaluating the potential of intelligent processing of clinical data at the edge. We utilized the emerging concept of clustered federated learning (CFL) for an automatic COVID-19 diagnosis. We evaluate the performance of the proposed framework under different experimental setups on two benchmark datasets. Promising results are obtained on both datasets resulting in comparable results against the central baseline where the specialized models (i.e., each on a specific image modality) are trained with central data, and improvements of 16% and 11% in overall F1-Scores have been achieved over the trained model trained (using multi-modal COVID-19 data) in the CFL setup on X-ray and Ultrasound datasets, respectively. We also discussed the associated challenges, technologies, and techniques available for deploying ML at the edge in such privacy and delay-sensitive applications.

Decentralised Federated Learning for Hospital Networks with application to COVID-19 Detection

Federated Learning (FL) is a distributed machine learning technique which enables local learning of global machine learning models without the need of exchanging data. The original FL algorithm, Federated Averaging (FedAvg), is extended in this work by means of consensus theory. Differently from standard FL algorithms, the resulting one, named FedLCon, does not need a coordinating server, which represents a single failure point and needs to be trusted by all the clients. Furthermore, the consensus paradigm is also applied to the Adaptive Federated Learning (AdaFed) algorithm, which extends FedAvg with an adaptive model averaging procedure. Performance comparison tests are performed over a real-world COVID-19 detection scenario. Author

Use of Virtual Social Networks by University Students in Times of Covid-19

The main objective of the research was to determine how the main virtual social networks are used in times of Covid-19 by university students. The research has been developed under the positivist paradigm framed in the quantitative approach, with a descriptive design. A 28-item questionnaire was prepared on the use of virtual social networks (RSV) in times of Covid-19 (adapted by the group of researchers), which was applied to a sample of 474 students from 10 public and private universities in the country. The results allow us to show that the vast majority of students (82.5%) have access to the internet from home and of these, 67.9% of students connect to the internet through their cell phone for a space 3 to 6 hours in the vast majority of cases. Regarding the use of virtual social networks, we can affirm that all students make use of some of them, most notably WhatsApp. And that of the virtual social networks that are most used in academic use is WhatsApp followed by YouTube.

A Toolkit to Support the Design of Blended Learning Courses

Academics' exposure to online learning solutions during the COVID-19 pandemic has positively changed their perception of online learning. Educational institutions have also realized the untapped potentials of blended learning. Therefore, it is almost certain that blended learning will become the new normal for course delivery in higher education in the Post-COVID-19 era. However, the existence of two modes of delivery, i.e., face-to-face and online, in addition to the large number of components that can be integrated into blended courses, raises two design challenges: (i) deciding the most appropriate proportion of online components to be integrated into a blended course;and (ii) selecting the most appropriate delivery methods to help students achieve the course outcomes. The majority of academics lack the institutional support and the tools to help them face these design challenges. To address this gap, this study presents a toolkit that can assist academics in designing successful blended learning courses. The toolkit was built based on knowledge extracted from experts in course design and online learning via two Delphi studies. It was evaluated in terms of effectiveness, efficiency, satisfaction, and quality of outcomes. The evaluation results show that in addition to providing an appropriate design, the toolkit can foster a better understanding of the different criteria that should be considered when designing a blended course.

Cell Based Raft Algorithm for Optimized Consensus Process on Blockchain in Smart Data Market

Due to the explosive increase in IoT devices and traffic, big data is developing into smart data that helps the data science experts understand human activities, through the relationship between mobility and resource application of the users in public spaces. For example, smart data markets help to predict crimes or understand the cause of COVID-19 infections. For these smart services, the users agree to the privacy policy so that the personal and sensitive information can be collected by a third party. But the conditions of the privacy policy do not specify whether the information of the users can be tracked. To ensure data transparency, many systems are applying consortium/private blockchains with raft algorithm. The raft algorithm requires nodes to check countless messages for a single transaction. Eventually, as the number of nodes increases, the overall system degradation is derived from the burden of the leader node. This paper proposes a method to process the collected transactions by dividing a certain amount of transactions into cells, without any extra protocol. The proposed scheme also uses the federated learning model with high accuracy and data privacy, in order to determine the optimized cell size in a blockchain system that should lead to consensus on multiple servers. Therefore, the proposed CBR (Cell-based Raft) consensus algorithm proposes a protocol that reduces the number of messages, without interfering with the concept of the existing raft algorithm, in order to maintain stable throughput in the smart data market where massive transactions occur.

REIMAGINING EDUCATION IN NEW NORMAL POST COVID-19 ERA: THE VIEWPOINT OF HIGHER EDUCATION INSTITUTIONS

The importance of information technology in education cannot be overstated because of its huge influence on human lives. Because to the shutdown of higher education institutions, which creates impediments to students' learning, the usage of information techniques has increased during the current COVID-19 epidemic. Additionally, teachers and educators are experimenting with various e-learning platforms in order to give their students with more convenient learning experience possible. Since this is a new trend, teachers and new students alike are getting used to this growth of e learning technique. According to the "Technology Acceptance Model", User satisfaction and perceived ease of use are the two most critical factors of technology adoption (Webb, 2019). Even though icebreaker/introduction discussions and collaborative work using digital communication tools ranked highly in the teaching and learning changes in process, students and instructors alike found that sending regular pronouncements or email alerts and providing feedback on all assignments were the most effective engagement strategies. Because of this, we may conclude that students' well-being and academic performance benefit from student involvement in an e learning environment.

To avoid dropout: let student teach! Second act

In an IUT, "Institut Universitaire de Technologie"students are trained to become technicians after 2 years of study. Due to different reasons, the background level of incoming students is becoming lower and above all disparate. A special tutorage system introduced in 2014 to avoid resignations of first year bachelor students allows the first-year students to benefit from individual and collective support of second-year students in disciplines considered as difficult. During the first COVID confinement, three students, then in the first year, offered us a new concept of tutoring. As part of their tutored 2nd year project, they would like to write first-year exam corrections, but also organise collaborative work sessions for the 2nd year. We accepted this proposal, and student engagement was beyond our expectations. Spontaneously, as the teaching conditions returned to normal (100% face-to-face courses), a group of 3 students asked us if they could take part in this project again this year. The paper presents the organisation of the project in each of these two academic years, the commitment of the students to the project, and the feedback of their trainees. © 2022 IEEE.

Precariousness and Hope: Digital Everyday Life of the Undocumented Migrants Explored Through Collaborative Photography

The article explores the digital everyday life of recently or currently undocumented migrants in times of Covid-19 in Finland. It is based on an empirical case study on a collaborative photographic exhibition and workshop including visual images, diaries, interviews, and discussions. The analysis explores the ways in which a photography exhibition and a workshop may depict meaningful moments in digital everyday life as well as open up an understanding of the various vulnerabilities that emerge in the life of the undocumented, as expressed by themselves. The study demonstrates the fundamental importance of communication rights for people in precarious life situations, expressed by themselves in visual images. The insight produced multidimensionally in images, discussions, and interviews illustrate how digital media environment exposes to coerced visibility and requires constant struggle for communicative rights. These struggles take place on the material infrastructural level of devices, chargers, and access, but also on the level of self-expression and connection on social media platforms. Finally, the article discusses the emancipatory potential of a collaborative exhibition and workshop as a way to encounter and deal with increasingly vulnerable life situations. It points out the relevance of collaborative work as a research method, in providing knowledge from experience as well as space of recognition.

Finding Social and Environmental Justice in the Fashion Production Chain in Brazil: When Fashion is Created with Nature by Women in Their Communities

Brazil covers a large territory, and although only 15% of its population is distributed in rural areas (IBGE Educa 2015), rural dwellers take on the chief responsibility for conserving local biodiversity. This article uses empirical research with a qualitative approach to present four cases of consolidated communities working with Amazonian rubber, regenerative cotton, weaving and lacework. It shows how rural communities pursue solutions for sustainable livelihoods in their own place of origin through the production of raw materials and products for the fashion chain, ensuring food security, income generation, maintenance of local biomes and gender justice. Particularly, this study examines the role of women beyond their families in ensuring work equity and better income distribution. Design appears as a positive agent, transforming ancestral and artisanal culture and knowledge into product innovation with added value to ensure production viability as well as enhancing community wellbeing.

Mining Valuable Collaborations from Event Data Using the Recency-Frequency-Monetary Principle

Collaborative work leads to better organizational performance. However, a team leader’s view on collaboration does not always match reality. Due to the increased adoption of (online) collaboration systems in the wake of the COVID pandemic, more digital traces on collaboration are available for a wide variety of use cases. These traces allow for the discovery of accurate and objective insights into a team’s inner workings. Existing social network discovery algorithms however, are often not tailored to discover collaborations. These techniques often have a different view on collaboration by mostly focusing on handover of work, resource profile similarity, or establishing relationships between resources when they work on the same case or activities without any restrictions. Furthermore, only the frequency of appearance of patterns is typically used as a measure of interestingness, which limits the kind of insights one can discover. Therefore we propose an algorithm to discover collaborations from event data using a more realistic approach than basing collaboration on the sequence of resources that carry out activities for the same case. Furthermore, a new research path is explored by adopting the Recency-Frequency-Monetary (RFM) concept, which is used in the marketing research field to assess customer value, in this context to value both the resource and the collaboration on these three dimensions. Our approach and the benefits of adopting RFM to gain insights are empirically demonstrated on a use case of collaboratively developing a curriculum. © 2022, Springer Nature Switzerland AG.