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This article presents an exploratory research, with a qualitative approach, on the use of (un)plugged activities to teach computing and mathematic concepts during the social isolation period imposed by the Covid-19 pandemic. The objective of this research was to analyze the use of such activities as extra resources in the context of remote education to teach computational thinking and mathematics skills to 6-to-9-year-old children. The results showed children's great engagement in the activities, and the acceptance of unplugged activities by both the children and their families. © 2023, Centro de Estudos Educacao e Sociedade - CEDES. All rights reserved.
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COVID-19 has challenged educators not only in Ukrainian universities but throughout the whole world to keep abreast with the rapid emergence of new technologies, adapt the education system to online needs, and use blended learning as a necessity of the transformed education environment. We carried out two case studies aimed at gauging the students' perception, experience, and satisfaction level on the pandemicinduced online EFL learning via a Google Forms questionnaire in 2020-2021 a.y. and 2021-2022 a.y. at Taras Shevchenko National University of Kyiv (Ukraine). The first case conducted a 16-question online survey, and an analysis unit was the responses of 112 first-year students studying English as L2 and majoring in Computer Science and Cybernetics at the University of Kyiv under the Coronavirus lockdown reality. The second case encompassed 80 respondents and was fulfilled through the same 16-question online survey under similar study conditions. The sample groups were undergraduate students of the same age (17-18 y. o.) and the English language level (B1+) enrolled in the university with similar admissions criteria, prerequisites, and curricula. The survey's participation was voluntary and anonymous. The respondents gave feedback on three question categories: EFL online learning effectiveness, technical provision satisfaction, self-organization, and confidence level. The opinions were not fully homogeneous but the majority of Computer Science and Cybernetics undergraduates in both case studies pointed out that the online EFL course was effective. The first survey findings revealed that the first-year university learners had a predominately positive attitude towards online education, describing English lessons as well-structured and engaging. Our second investigation demonstrated that apart from staff readiness, confidence, students' Internet accessibility, and motivation, the undergraduates have indicated tiredness of online meetings, pointing out that they have a lack of live communication. The obtained study results can help in understanding EFL teachers how to continue teaching and learning during such unprecedented times and to ensure a high level of education, responding to the current students' needs and priorities for successful online classes. [ FROM AUTHOR] Copyright of Romanian Journal for Multidimensional Education / Revista Romaneasca pentru Educatie Multidimensionala is the property of Lumen Publishing House and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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A variety of patient care and intelligent health systems can benefit from the implementation of artificial intelligence as a tool to aid caregivers. Machine learning and deep learning are two types of AI that are increasingly being used in the medical industry. Artificial intelligence methods require a large amount of clinical data from a range of imaging modalities for correct disease diagnosis. In addition, AI has greatly enhanced the quality of hospital stays, allowing patients to be released sooner and complete their recoveries at home. This article aims to provide the information on the field of AI subset i.e., machine learning-based disease detection with information that will aid them in making better decision making. This helps the researchers to classify the medical conditions in patients with a prominent dataset.
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ASEAN is predicted to be the world's largest single market by 2030, after the US, China, and the EU. This study aims to discover research performance in all ASEAN countries, including identifying output levels, research focus, and influential authors in the region. The approach used in this study is a bibliometric analysis of publications indexed in the WoS database for the past two decades (2002–2021). Of the more than 20,000 documents analyzed, it was indicated that each ASEAN country has exclusive and non-exclusive keywords. Singapore has the highest number of citations among the other ASEAN countries.
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We introduce "Ricerca Operativa Applicazioni Reali" (ROAR;in English, "Real Applications of Operations Research"), a three-year project for higher secondary schools. Its main aim is to improve students' interest, motivation, and skills related to Science, Technology, Engineering, and Mathematics disciplines by integrating mathematics and computer science through operations research. ROAR offers examples and problems closely connected with students' everyday life or with the industrial reality, balancing mathematical modeling and algorithmics. The project is composed of three teaching units, addressed to grades 10, 11, and 12. The implementation of the first teaching unit took place in Spring 2021 at the scientific high school IIS Antonietti in Iseo (Brescia, Italy). In particular, in this paper, we provide a full description of this first teaching unit in terms of objectives, prerequisites, topics and methods, organization of the lectures, and digital technologies used. Moreover, we analyze the feedback received from students and teachers involved in the experimentation, and we discuss advantages and disadvantages related to distance learning that we had to adopt because of the COVID-19 pandemic.
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We are moving toward a future in which digital practices are becoming more ubiquitous. Also, there is evidence to suggest that innovative digital practices are changing the face of 21st-century learning environments. Critical to 21st-century teaching and learning success is continued emphasis on learner preferences, shaped by innovative digital technology-driven learning environments alongside teacher awareness, knowledge, and preparedness to deliver high-impact instruction using active learning pedagogies. Thus, the purposeful and selective use of digital learning tools in higher education and the incorporation of appropriate active learning pedagogies are pivotal to enhancing and supporting meaningful student learning. "Innovative Digital Practices and Globalization in Higher Education" explores innovative digital practices to enhance academic performance for digital learners and prepare qualified graduates who are competent to work in an increasingly global digital workplace. Global competence has become an essential part of higher education and professional development. As such, it is the responsibility of higher education institutions to prepare students with the knowledge, skills, and competencies required to compete in the digital and global market. Covering topics such as design thinking, international students, and digital teaching innovation, this premier reference source is an essential resource for pre-service and in-service teachers, educational technologists, instructional designers, faculty, administrators, librarians, researchers, and academicians.
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After release of Web 2.0 in 2004 user spawned contents on the internet eminently in abundant review sites, online forums, online blogs, and many other sites. Entire user generated contents are considerable bunches of unorganized text written in different languages that encompass user emotions about one or more entities. Mainly predictive analysis exerts the existing data to forecast future outcomes. Currently, a massive amount of researches are being engrossed in the area of opinion mining, also called sentiment analysis, opinion extraction, review analysis, subjective analysis, emotion analysis, and mood extraction. It can be an utmost choice whilst perceiving the meaning and patterns in prevailing data. Most of the time, there are various algorithms available to work with polling. There are contradictory opinions among researchers regarding the effectiveness of algorithms. We have compared different opinion mining algorithms and presented the findings in this paper.
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The streams of social media big data are now becoming an important issue. But the analytics method and tools for this data may not be able to find the useful information from this massive amount of data. The question then becomes: how do we create a high-performance platform and a method to efficiently analyse social networks' big data;how to develop a suitable mining algorithm for finding useful information from social media big data. In this work, we propose a new hierarchical big data analysis for understanding human interaction, and we present a new method to measure the useful tweets of Twitter users based on the three factors of tweet texts. Finally, we use this test implementation score, in order to detect useful and classification tweets by interested degree.
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This article reviews the possibility of using the Tinkercad Internet service for online study of the subjects connected with microprocessor systems. During the global coronavirus pandemic, online classes based on the Internet technologies have become virtually the only effective method of learning. However, while lectures can be taught successfully with the help of video conferences such as Zoom, Skype, Microsoft Teams, Google Meet etc., it is almost impossible to perform laboratory and practical work in the field of designing microprocessor systems with the help of these tools. Therefore, the authors suggest a new approach to practicums on the subjects related to microprocessor systems using tools of the Tinkercad Internet service. The existing methods and means of remote work with breadboard Arduino have been analyzed. The advantages of the Tinkercad Internet service in comparison with other tools of remote work have been disclosed. The service capability for microprocessor systems design has been considered. The article provides examples of elaborated lab works by means of the Tinkercad Internet service. Available capabilities and instruments in the system have been detailed. The process of learning based on the Tinkercad Internet service has been developed. Consequently, the use of the Tinkercad Internet service during e-learning gives the possibility to do lab works and microprocessor system design practicums without actual equipment, and the methods suggested by the authors assure the quality of students' awareness in this direction. The prospective direction of this Internet service application can be the design of 3D printing models and their use during e -learning of other subjects, in particular Physics (Electrics section), Theoretical Basics of Electrical Engineering (DC section), as well as other sciences related to electronic circuit design.
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This panel is the evolution of a Technology that Educators of Computing Hail (TECH) Birds of a Feather session held at SIGCSE for seven years, grew into popular panels for many years [2-4, 6, 7], and served as a springboard for a regular column in ACM Inroads [1, 5, 9]. It will provide a chance for seasoned middle school, high school, and university educators to showcase the technologies they can't live without, what problems they solve, and how to use them. This year, we asked our panelists to highlight any technology in particular that helped them survive (and possibly even thrive!) during their remote teaching.
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Introduction. In 2020, the first two weeks of the enforced transformation of all the levels of school education, which was initiated as one of the measures against the Coro- navirus disease (COVID-19), revealed a range of issues hampering the appropriate distance education. The absence of the methodological basis for conducting online classes in the Kazakh pedagogical community defined the need to study and enhance forms and technologies that would be efficient to use to interact with students during the transition of the national educa- tion system to distance education. Aim. The aim of this research lies in defining efficient methods for distance teaching of computer science in the Kazakh secondary school students in terms of ensuring the mainte- nance of the quality of knowledge and the academic progress of students at the sufficient level corresponding to that of the traditional in-person education. Methodology and research methods. A total of five educators and 320 students of three Kazakh schools took part in the study. At the moment of the experiment, the students were aged 12 to 18 years old. The participants were divided into seven groups according to the edu- cational level (5th-11th forms) in order to make it more convenient to trace qualitative changes in the academic progress depending on the selected method for distance teaching of computer science. The authors conducted three control evaluations of the quality of knowledge in each of the 320 participants. The t-test for unpaired samples for every group was conducted to prove the statistical certainty of the calculated average reference values, which were required to con- firm the viability of the conducted research. The analysis of the data obtained at the concluding stage of the experiment allowed to compare them with the reference values calculated at the preliminary stage of the research in question. For the comparison, The authors applied the Mann-Whitney U test for independent samples.Results. The preliminary analysis of the quality of knowledge related to the discipline of computer science in the participants revealed generally high and average level of both ac- quisition of theoretical information and development of the subject-related skills, which was registered based of the results of in-person education. The leading experience of the specialists composing the authors' initiative research group allowed developing a structural scheme for an online lesson. The lessons applying this scheme were conducted up to the end of the academic quarter. By conducting the Mann-Whitney U test, we discovered that the obtained average values of the quality of teaching computer science to the participants statistically increased (I group - Uemp = 6.49 (p s 0.05), II group - Uemp = 7.46 (p s 0.05), III group - Uemp = 6.05 (p s 0.01), IV group - Uemp = 6.71 (p s 0.05), V group - Uemp = 6.91 (p s 0.01), VI group - Uemp = 6.65 (p s 0.05), VII group - Uemp = 6.21 (p s 0.05)). Despite temporary fall in the efficiency of teaching computer science registered during the transition to the distance model, it was man- aged to achieve the level of academic progress and acquisition of knowledge corresponding to that of in-person education. Scientific novelty. TThe significance of the collected and analysed data was statistically proved. The data confirmed the efficiency of the use of defined and adapted approaches and teaching techniques, which were able to compensate the absence of traditional in-person les- sons, while preventing the fall in the academic progress and the quality of knowledge in stu- dents. Practical significance. The obtained results evidence the success of the arrangements aimed at the enhancement of the methods for distance teaching of computer science in the Kazakh secondary school students during the transition to distance education enforced due to the pandemic.
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Early in spring 2020, universities world-wide suddenly moved their courses online in response to the COVID-19 pandemic. A number of researchers have studied the impact of this sudden move on the mental health and education of the effected students. The Center for Collegiate Mental Health reported that a third of students visited a college counseling center in 2020 due to mental health issues from the pandemic. Sixty eight percent of those seeking services for any reason indicated that the pandemic hurt their "motivation and focus." Sixty six percent indicated that the pandemic had a negative impact on academics. In a follow-up study, the Center found a significant increase in "academic distress" from 2019 to 2020. However, not all researchers found a negative impact. A study of at-risk undergraduates found that moving courses online did not necessarily demotivate disadvantaged students. This paper provides another view of the impact of moving courses online. The test performance of five semesters of a Computer Systems course is examined;in two of those semesters the course was offered online due to the pandemic. In addition, students in one online section were surveyed to determine what aspects, if any, of the online course should be retained after the course resumed face-to-face. Our study found that a larger percentage of the students in the online sections failed the tests and an analysis of test results confirms, with a 90% confidence, that overall online learners score at least 5 points lower on tests. In addition, in a survey of students in one online section, students reported that they felt their grades would have been higher had the course been face-to-face. However, most students reported that lab sessions, but not class sessions, should continue to be offered online.
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This paper reports the results of a study on the implementation of a sustainable teaching model based on the OBE (Outcome-Based Education) concept and the TSEM (Teach, Study, Evaluate, and Manage) framework in computer science and technology at NingboTech University, China. In the context of digital education, the OBE concept and the TSEM framework are integrated to explore sustainable teaching and learning models based on "artificial intelligence and education”. Based on the core concept of engineering professional education accreditation, the course is designed by using the PCCM (Professional Competency Correlation Matrix) method to build a model based on big data analysis, deepen the classroom teaching reform of "artificial intelligence and education”, and explore the integrated digital sustainable teaching mode of "teaching, learning, evaluation, and management”. The aim of this study is to explore the effectiveness of the teaching model based on OBE and the TSEM framework on students' sustainable development. The results show that students deepen their learning in computer science while enhancing their own learning initiative, teamwork skills, innovation skills, and awareness of sustainable development. Research shows that our teaching model plays an important role in the development of student sustainable education, enhancing student engineering practice and innovation capabilities and cultivating applied innovative talents. The efficacy of the teaching model based on the OBE concept and the TSEM framework for improving students' competence in sustainable education warrants further investigation.
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PurposeThis study aims to comprehend the application of analytics in the supply chain during the ongoing COVID-19 crisis and identify the emerging themes.Design/methodology/approachThe author downloaded a list of research articles on the application of analytics to the supply chain from SCOPUS, conducted a systematic literature review for exploratory analysis and proposed a framework. Notably, the author used the topic modeling technique to identify research themes published during the ongoing COVID-19 crisis and thereby underscore some future research directions.FindingsThe author found that artificial intelligence, machine learning, internet of thing and blockchain are trending topics. Additionally, the author identified five themes by topic modeling, including the theme "Social Media information in Supply chain.”Research limitations/implicationsThe results were derived from a data set extracted from SCOPUS. Thus, the author excluded all studies not listed in SCOPUS from the analysis. Future research with articles indexed in other databases should be investigated to get a more holistic perspective of specific themes.Practical implicationsThis study provides a deeper understanding and proposes a framework for applications of analytics in the supply chain that researchers could use for future research and industry practitioners to implement in their organizations to make a more sustainable and resilient supply chain.Originality/valueThis study provides exploratory information from published articles on the use of analytics in the supply chain during the COVID-19 crisis and generates themes that help understand the emerging and underpinned area of research.
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Contribution: Adaptation and application of a methodology to introduce Informatics from an early age to students living in disadvantaged areas in Peru and analysis of its effects. Background: On the on hand, during the COVID-19 pandemic, students living in disadvantaged areas in Peru were confined to their home under the supervision of their family and without access to computers. On the other hand, the multistage sequencing knowledge transmission methodology (L2T2L), first proposed in JolasMATIKA (Basque Country), to introduce Informatics topics using CS Unplugged from university to school had shown to be effective. Research Question: Does the introduction from an early age into Informatics affect the appreciation of students living in disadvantaged areas about what Informatics is and their attitude toward it? Is the methodology used appropriate for times of pandemic? Methodology: A pilot project based on the L2T2L methodology was introduced at the Public School of the Religious Association Br. Thomas Helm S.M. (Peru) for primary and secondary education during the 2020/2021 pandemic academic year. University engineering students from the UTEC University were in charge of initiating the transmission of Informatics concepts to teachers of secondary and primary education who transmitted the knowledge to their respective students, using mobile phones. Surveys were used to gather data at the beginning and the end of the experience. Findings: A methodology adequate for introducing Informatics from an early age and for reducing the digital divide between technologically advanced communities and more disadvantaged communities. Students and family unit members changed their opinion about Informatics. IEEE
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The COVID-19 pandemic has been challenging for college faculty, with evidence that it has the potential to exacerbate pre-pandemic gender inequities in work demands (Tugend, 2020). The impact of the pandemic may be particularly difficult for women in male-dominated STEM fields such as computer science that pose additional challenges and had high attrition rates among women faculty pre-pandemic (NSF, 2019; Weisgram & Diekman, 2017). The present study examined the mechanisms through which gender may have implications for changes in turnover intentions due to the pandemic among computer science faculty, with a focus on changes in work-family conflict and workplace attitudes. A total of 317 tenure-line and non-tenure line computer science faculty across the U.S. (54.26% women, 49.84% tenured) completed a survey that included items examining whether the pandemic changed work-family conflict, work-related attitudes (job satisfaction, sense of belonging, burnout), and turnover intentions. Results of analyses indicated that identifying as a woman indirectly predicted larger increases in turnover intentions due to the pandemic, through increased work-family conflict, burnout at work, and decreased feelings of job satisfaction. The results suggest that the pandemic has the potential to increase women's attrition from computer science faculty positions, further exacerbating their underrepresentation.
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Artificial intelligence development and research leaders in business, industry, and nations gain a major competitive edge. Additionally, it is clear that nations with a well-established national artificial intelligence policy have an edge over others, both technologically and economically. To further their artificial intelligence capability, nations also seek to develop a strategy, vision, structure, and working environment that encourages collaboration between the public sector, private industry, and educational institutions. Artificial intelligence is thought to be a tool that will help bridge the gap between powerful and developing countries growing in the future. Using data from "The Global AI Index” for 2021, this study aims to examine and analyze the present state of artificial intelligence management in 62 nations in terms of talent, infrastructure, business environment, development and research government policy, and commercial efforts. The research used PROMETHEE, which is widely used in multi-criteria decision-making evaluations, and its geometric representation, the GAIA plane. This study also found that the United States of America is the world leader in artificial intelligence (AI) research and development as well as AI investment. The United Kingdom, China, Israel, Canada, the Netherlands, South Korea, and Germany all rank well. China is rapidly catching up to the USA. At the very bottom of the list are nations such as Armenia, Kenya, Egypt, South Africa, and Pakistan. Turkey's values are more similar to those of nations towards the bottom of the list than of those in the top half. There is a significant gap between the top three countries and the rest of the world in all parameters included in the survey. Except for the ‘State Strategy' category, Turkey scores quite low compared to the top-performing countries. Decision makers are expected to address the identified global challenges of the study by creating a more comprehensive national AI strategy, both financially and in terms of content.
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The Postgraduage Certificate in Information Technology at the University of Auckland is a bootcamp-style transition programme for students without prior programming experience. The programme's part-time variant, designed for working professionals, has traditionally been offered with intensive evening classes, with extensive tutor and instructor support. Spurred on by the COVID-19 pandemic, our University has moved this part-time variant fully online. Benefits of the online offering include a wider, more inclusive audience and flexibility of student learning schedules. However, it has introduced several pedagogical challenges, including but not limited to how instructors can continue to provide meaningful support, feedback, and student engagement in an online environment. In this paper, we reflect on our experience, analyse qualitative and quantitative feedback such as student evaluations and grades, and provide recommendations for those wishing to undertake a similar transformation in the future. © 2023 ACM.
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Research Problem. Computer science (CS) education researchers conducting studies that target high school students have likely seen their studies impacted by COVID-19. Interpreting research findings impacted by COVID-19 presents unique challenges that will require a deeper understanding as to how the pandemic has affected underserved and underrepresented students studying or unable to study computing.Research Question. Our research question for this study was: In what ways has the high school computer science educational ecosystem for students been impacted by COVID-19, particularly when comparing schools based on relative socioeconomic status of a majority of students?Methodology. We used an exploratory sequential mixed methods study to understand the types of impacts high school CS educators have seen in their practice over the past year using the CAPE theoretical dissaggregation framework to measure schools' Capacity to offer CS, student Access to CS education, student Participation in CS, and Experiences of students taking CS.Data Collection Procedure. We developed an instrument to collect qualitative data from open-ended questions, then collected data from CS high school educators (n = 21) and coded them across CAPE. We used the codes to create a quantitative instrument. We collected data from a wider set of CS high school educators (n = 185), analyzed the data, and considered how these findings shape research conducted over the last year.Findings. Overall, practitioner perspectives revealed that capacity for CS Funding, Policy & Curriculum in both types of schools grew during the pandemic, while the capacity to offer physical and human resources decreased. While access to extracurricular activities decreased, there was still a significant increase in the number of CS courses offered. Fewer girls took CS courses and attendance decreased. Student learning and engagement in CS courses were significantly impacted, while other noncognitive factors like interest in CS and relevance of technology saw increases.Practitioner perspectives also indicated that schools serving students from lower-income families had (1) a greater decrease in the number of students who received information about CS/CTE pathways;(2) a greater decrease in the number of girls enrolled in CS classes;(3) a greater decrease in the number of students receiving college credit for dual-credit CS courses;(4) a greater decrease in student attendance;and (5) a greater decrease in the number of students interested in taking additional CS courses. On the flip-side, schools serving students from higher income families had significantly higher increases in the number of students interested in taking additional CS courses. © 2022 Association for Computing Machinery.
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This paper reports on the design, development and first use experience of Mariotel: a free-software project for deploying virtual remote computer science labs simply accessible from ordinary web browsers. Mariotel platform has been developed during the first generalized lockdown period due the Covid-19 pandemic situation. Simplicity has been the main principle that guided the design and development process of Mariotel. We show that this principle has largely contributed to the quick adoption of this new platform. The system has been successfully used at USPN since 2020. 42 different teachers have used the platform in order to supply ensure 9989 lab sessions, each has in average three hour duration. © 2022 IEEE.