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Journal articles on the topic 'Data science applications in education'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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1

DE VEAUX, RICHARD, ROGER HOERL, RON SNEE, and PAUL VELLEMAN. "TOWARD HOLISTIC DATA SCIENCE EDUCATION." STATISTICS EDUCATION RESEARCH JOURNAL 21, no. 2 (2022): 2. http://dx.doi.org/10.52041/serj.v21i2.40.

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Holistic data science education places data science in the context of real world applications, emphasizing the purpose for which data were collected, the pedigree of the data, the meaning inherent in the daa, the deploying of sustainable solutions, and the communication of key findings for addressing the original problem. As such it spends less emphasis on coding, computing, and high-end black-box algorithms. We argue that data science education must move toward a holistic curriculum, and we provide examples and reasons for this emphasis.

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Volkova, Nataliia P., Nina O. Rizun, and Maryna V. Nehrey. "Data science: opportunities to transform education." CTE Workshop Proceedings 6 (March 21, 2019): 48–73. http://dx.doi.org/10.55056/cte.368.

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The article concerns the issue of data science tools implementation, including the text mining and natural language processing algorithms for increasing the value of high education for development modern and technologically flexible society. Data science is the field of study that involves tools, algorithms, and knowledge of math and statistics to discover knowledge from the raw data. Data science is developing fast and penetrating all spheres of life. More people understand the importance of the science of data and the need for implementation in everyday life. Data science is used in business

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Hursen, Cigdem, and Cizem Bas. "Use of Gamification Applications in Science Education." International Journal of Emerging Technologies in Learning (iJET) 14, no. 01 (2019): 4. http://dx.doi.org/10.3991/ijet.v14i01.8894.

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In this research, the impact of gamification applications in science education on the science learning motivation of students has been determined and the opinions of students and parents on applications have been discussed. A total of 16 students and their parents partic-ipated in the study. The research was conducted on 4th grade primary students and em-ployed a mixed method consisting of both qualitative and quantitative elements. The moti-vation of students for learning science was obtained through quantitative data, whereas the opinions of students and parents on the usage of gamification

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Keßler, Carsten, Mathieu d'Aquin, and Stefan Dietze. "Linked Data for science and education." Semantic Web 4, no. 1 (2013): 1–2. http://dx.doi.org/10.3233/sw-120091.

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ilhan, Nail. "Education and artificial intelligence." International Journal of Education and Artificial Intelligence 1, no. 1 (2024): 1–3. https://doi.org/10.5281/zenodo.14867972.

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Abstract Research in the field of education has an important place in science and society. In recent years, there has been a significant increase in the number of researches in the field of educational sciences and artificial intelligence, and many journals publish special issues in this field. The reflections of artificial intelligence, from preschool to graduate education, are revealed by many studies.  Academic journals on artificial intelligence and education contribute to this field. The aim of the "International Journal of Educational and Artificial Intelligence" (IJEDAI), the first

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Virkus, Sirje, and Emmanouel Garoufallou. "Data science and its relationship to library and information science: a content analysis." Data Technologies and Applications 54, no. 5 (2020): 643–63. http://dx.doi.org/10.1108/dta-07-2020-0167.

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PurposeThe purpose of this paper is to present the results of a study exploring the emerging field of data science from the library and information science (LIS) perspective.Design/methodology/approachContent analysis of research publications on data science was made of papers published in the Web of Science database to identify the main themes discussed in the publications from the LIS perspective.FindingsA content analysis of 80 publications is presented. The articles belonged to the six broad categories: data science education and training; knowledge and skills of the data professional; the

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Alonso-Fernández, Cristina, Antonio Calvo-Morata, Manuel Freire, Iván Martínez-Ortiz, and Baltasar Fernández-Manjón. "Applications of data science to game learning analytics data: A systematic literature review." Computers & Education 141 (November 2019): 103612. http://dx.doi.org/10.1016/j.compedu.2019.103612.

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Rogers, L., and P. Wild. "Data-logging: effects on practical science." Journal of Computer Assisted Learning 12, no. 3 (1996): 130–45. http://dx.doi.org/10.1111/j.1365-2729.1996.tb00046.x.

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Fodouop Kouam, Arthur William. "My Data Are Ready, How Do I Analyze Them: Navigating Data Analysis in Social Science Research." International Journal of Scientific Research and Management (IJSRM) 12, no. 03 (2024): 1730–41. http://dx.doi.org/10.18535/ijsrm/v12i03.sh03.

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This paper offers a practical guide for researchers to effectively analyze their data in social science research, addressing the challenges and pitfalls commonly encountered in data analysis. By exploring various data analysis techniques, highlighting key challenges such as data quality issues and statistical assumptions violations, and providing practical tips and guidelines, this study fills a gap in the existing literature by offering a comprehensive approach to navigating data analysis in social science research. The significance of this study lies in its potential to improve the quality a

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İlik, Ş. Şenay, and Esme Hacieminoglu. "Evaluation of Elementary Science Teachers’ Perceptions Regarding Inclusive Education Applications." Journal of Education and Training Studies 7, no. 10 (2019): 19. http://dx.doi.org/10.11114/jets.v7i10.4396.

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The purpose of this study is to investigate the problems and suggestions of the elementary science teachers having students with special needs in the inclusive education applications. The present study is a descriptive study which determines the opinions of elementary science teachers regarding inclusive education. Thirty seven in-service science teachers who have been working in schools where inclusive education is applied in different cities of Turkey participated in the study. Data were collected throughstructured interview form. Thirty-seven interview forms were completed with thirty-seven

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Ergün, Ayşegül, and Gülbin Kıyıcı. "The effect of design based science education applications of science teacher candidates on their perceptions of engineering education and engineer." Pegem Eğitim ve Öğretim Dergisi 9, no. 4 (2019): 1031–62. http://dx.doi.org/10.14527/pegegog.2019.033.

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The purpose of this study was to determine the effect of Design Based Science Education (DBSE) applications on the perceptions of science teacher candidates about engineering education and engineers. In the quantitative part of the study in which the mixed method was involved, a semi-experimental design with single group pre-test post-test was used while a case study design was adopted in the qualitative part of the study. The study group of the research consisted of 52 juniors who were receiving education at a university in the Aegean Region in the 2016-2017 academic year. The quantitative da

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Hannon, Daniel, Esa Rantanen, Ben Sawyer, et al. "A Human Factors Engineering Education Perspective on Data Science, Machine Learning and Automation." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 63, no. 1 (2019): 488–92. http://dx.doi.org/10.1177/1071181319631248.

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The explosion of data science (DS) in all areas of technology coupled with the rapid growth of machine learning (ML) techniques in the last decade create novel applications in automation. Many working with DS techniques rely on the concept of “black boxes” to explain how ML works, noting that algorithms find patterns in the data that humans might not. While the mathematics are still being developed, the implications for the application of ML, specifically to questions of automation, also are being studied, but still remain poorly understood. The decisions made by ML practitioners with respect

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Shin, SuYeong. "Datafication of Education and Machine Learning Techniques in Education Research: A Critical Review." Institute of Educational Research Chonnam National University 46, no. 1 (2024): 215–40. http://dx.doi.org/10.35510/jer.2023.46.1.215.

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The aim of the study is to discuss the technical and ethical considerations regarding the current applications of the emerging data science techniques in the field of education. Based on the literature review, this study provides an overview of machine learning approaches that have been used to answer to educational research agenda in South Korea. By comparing the logical features of these computational techniques to the conventional statistical methodologies, the authors highlight the unique challenges and opportunities associated with educational data science and discuss what that means to d

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Landon-Murray, Michael. "Big Data and Intelligence: Applications, Human Capital, and Education." Journal of Strategic Security 9, no. 2 (2016): 94–123. http://dx.doi.org/10.5038/1944-0472.9.2.1514.

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Šlekienė, Violeta, and Loreta Ragulienė. "SCIENCE LEARNING SYSTEMS NEWLY RECEIVED BY LITHUANIAN SCHOOLS AND THEIR POTENTIAL APPLICATIONS IN TEACHING PHYSICS." Problems of Education in the 21st Century 50, no. 1 (2012): 108–16. http://dx.doi.org/10.33225/pec/12.50.108.

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Wider knowledge update is always a big challenge for schools. In the event of changes in the curriculum, a question naturally arises: where teachers and students will get new teaching materials. It is necessary to renew textbooks and other teaching tools and to help teachers learn how to work with new knowledge. Natural science laboratory material base in secondary schools has been renewed by implementation of the project "Infrastructure of technology arts and natural sciences”. However, to achieve the desired result, it is necessary to find out whether there is sufficient infrastructure, whet

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Paul, Sudeepa, Doeyl Sah, Rupsa Das, et al. "COMPONENTS OF DATA SCIENCE AND ITS APPLICATIONS." International Journal of Engineering Applied Sciences and Technology 7, no. 5 (2022): 237–40. http://dx.doi.org/10.33564/ijeast.2022.v07i05.039.

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It is difficult to define data science in a formal way because it is expanding rapidly and revolutionizing many industries. The most basic definition of data science, however, is the process of drawing out useful information from unstructured data. It is being applied to any human endeavor for which there is sufficient data because it is a result of scientific discovery. There have been significant and spectacular accomplishments, and even more sweeping claims have been made. Along with the advantages, there are also challenges and risks. However, a term alone cannot explain what data science

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K Dhananjaya Kumar. "Data Science: A Concept, Applications, Challenges, Technol-ogies and Case Studies for Engineers." Journal of Information Systems Engineering and Management 10, no. 19s (2025): 287–92. https://doi.org/10.52783/jisem.v10i19s.3022.

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The data is a future life, science is a prove itself, data science is a prove future life itself, this paper present data science is a part of computer science engineers, they predict future life how to become successful. Data science used in several fields like medical, trades, digital marketing, stock marketing, education, government and private sectors many other fileds to determine how its successful to predict for socitial life. In data science use billions of technologies like machine learning, artificial intelligence, predictive modelling, cyber security, robotics, networks, industrial

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Miao, Kehua, Jie Li, Wenxing Hong, and Mingtao Chen. "A Microservice-Based Big Data Analysis Platform for Online Educational Applications." Scientific Programming 2020 (June 3, 2020): 1–13. http://dx.doi.org/10.1155/2020/6929750.

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The booming development of data science and big data technology stacks has inspired continuous iterative updates of data science research or working methods. At present, the granularity of the labor division between data science and big data is more refined. Traditional work methods, from work infrastructure environment construction to data modelling and analysis of working methods, will greatly delay work and research efficiency. In this paper, we focus on the purpose of the current friendly collaboration of the data science team to build data science and big data analysis application platfor

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Bayo, A., M. J. Graham, D. Norman, et al. "La Serena School for Data Science: multidisciplinary hands-on education in the era of big data." Proceedings of the International Astronomical Union 15, S367 (2019): 458–60. http://dx.doi.org/10.1017/s1743921321000107.

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AbstractLa Serena School for Data Science is a multidisciplinary program with six editions so far and a constant format: during 10-14 days, a group of ∼30 students (15 from the US, 15 from Chile and 1-3 from Caribbean countries) and ∼9 faculty gather in La Serena (Chile) to complete an intensive program in Data Science with emphasis in applications to astronomy and bio-sciences.The students attend theoretical and hands-on sessions, and, since early on, they work in multidisciplinary groups with their “mentors” (from the faculty) on real data science problems. The SOC and LOC of the school have

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Trivedi, Nripesh. "Data mining." International Journal of Scientific Research and Management (IJSRM) 12, no. 03 (2024): 1094. http://dx.doi.org/10.18535/ijsrm/v12i03.ec07.

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Data Mining Data mining is about finding patterns in the data [1]. In this paper, I put forward an important insight about similarity in branches of computer science and data mining. All branches of computer science could be termed as a procedure to carry out data mining. In this paper, I detail that. The computer works by finding patterns in the input and output [2]. Artificial Intelligence works by finding the patterns of functions of the related variables [3]. Machine learning works by mathematical justification of machine learning methods and results [4]. That is the pattern followed in ma

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Nazarenko, Alexander. "Crystallography Education for Non-Science College Students." Acta Crystallographica Section A Foundations and Advances 70, a1 (2014): C1268. http://dx.doi.org/10.1107/s2053273314087312.

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New applications of crystallographic methods made it necessary to teach crystallography to students with limited background in physics and chemistry. In this case, classic approach to crystallography with mandatory study of space group and physics of X-ray diffraction is not feasible. We suggest an alternative direction: (1) introduction to experimental procedures and data collection for polycrystalline and (possibly) monocrystalline samples, (2) raw data processing and use of databases for identification of known crystalline materials. Instead of establishing a crystal structure of a new comp

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Lydia Velázquez-García. "AI-Based Applications Enhancing Computer Science Teaching in Higher Education." Journal of Information Systems Engineering and Management 10, no. 2 (2025): 14–32. https://doi.org/10.52783/jisem.v10i2.920.

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The incorporation of Artificial Intelligence (AI) in higher education has gained significant attention as it presents new opportunities to improve the teaching and learning process. This paper aims to analyze how AI applications can support the teaching and learning of computer science in higher education. By reviewing various scientific publications, this paper offers an in-depth analysis of how AI-driven tools and applications have been successfully integrated into computer science courses. Key AI applications considered include intelligent tutoring systems, assessment, performance predictio

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Chen, Nian-Shing, Chengjiu Yin, Pedro Isaias, and Joseph Psotka. "Educational big data: extracting meaning from data for smart education." Interactive Learning Environments 28, no. 2 (2020): 142–47. http://dx.doi.org/10.1080/10494820.2019.1635395.

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Sunarya, Eksa Nursafira, Riandi, and Irma Rahma Suwarma. "Educational Tools for Sustainable Growth in Science Education: Literature Review." Pedagogia: Jurnal Ilmiah Pendidikan 16, no. 2 (2024): 131–39. https://doi.org/10.55215/pedagogia.v16i2.21.

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The idea of learning apps for Education for Sustainable Development (ESD) has recently made major strides. However, many people are unsure of what learning applications for ESD are, why they are necessary, and how to utilize them. The literature review on ESD-based science learning applications is so wide that many researchers need more time and a longer process to locate the relevant data sources. This study aims to give a summary or literature review of the significance of ESD-based learning apps for students in schools. The researcher's summary article highlights the fundamental difficultie

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Stoyanov, Emanuil, and Bozhidar Stoyanov. "GRAPHIC INTERPRETATION OF DIGITAL PRODUCTS AND APPLICATIONS IN STEGANOGRAPHY." Journal Scientific and Applied Research 8, no. 1 (2015): 64–73. http://dx.doi.org/10.46687/jsar.v8i1.180.

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Today, the generation of digital data is easier than it has ever been. These are the so-called digitally born products – documents, images, audio and video recordings, software, e-books, digital models, maps, etc. They are more and more widely employed nowadays in a variety of fields, such as business, science, art, education, digital communications, national security, intelligence service, military science, etc. Their global application has brought forth the need for their being reliably protected and has made it an issue of paramount importance in the modern world of information. This necess

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Joshi, Ankush, and Haripriya Tiwari. "An Overview of Python Libraries for Data Science." Journal of Engineering Technology and Applied Physics 5, no. 2 (2023): 85–90. http://dx.doi.org/10.33093/jetap.2023.5.2.10.

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In this era Python is the most popular as well as in -demand language for Data Science due to the number of libraries available for data processing, analysis and data visualization. The aim of this review paper is to give the overview of different available libraries. For this we grouped 48 different libraries in 3 different categories which are Data Collection, Data Analysis & Processing and Data Visualization. For comparison we use the GitHub community base (Stars, Forks and commits) as well as their properties and functionalities.

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Cavas, Bulent. "INDUSTRY 4.0 AND SCIENCE EDUCATION." Journal of Baltic Science Education 18, no. 5 (2019): 652–53. http://dx.doi.org/10.33225/jbse/19.18.652.

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Industry 4.0 and its applications are one of the most important issues of countries that want to keep their competitiveness in the field of scientific, technological and innovation in today's world. The Countries that are not able to adapt to Industry 4.0 processes will not be able to develop scientifically and technologically or keep up with current innovation processes. One of the aims of this paper is to explain the concept of industry 4.0 to our readers in a comprehensible manner and to show how much science education is actually related to industry 4.0. In a general sense, Industry 4.0 or

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Avila-Garzon, Cecilia. "Applications, Methodologies, and Technologies for Linked Open Data." International Journal on Semantic Web and Information Systems 16, no. 3 (2020): 53–69. http://dx.doi.org/10.4018/ijswis.2020070104.

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Advances in semantic web technologies have rocketed the volume of linked data published on the web. In this regard, linked open data (LOD) has long been a topic of great interest in a wide range of fields (e.g. open government, business, culture, education, etc.). This article reports the results of a systematic literature review on LOD. 250 articles were reviewed for providing a general overview of the current applications, technologies, and methodologies for LOD. The main findings include: i) most of the studies conducted so far focus on the use of semantic web technologies and tools applied

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Alkhalil, Adel, Magdy Abd Elrahman Abdallah, Azizah Alogali, and Abdulaziz Aljaloud. "Applying Big Data Analytics in Higher Education." International Journal of Information and Communication Technology Education 17, no. 3 (2021): 29–51. http://dx.doi.org/10.4018/ijicte.20210701.oa3.

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Higher education systems (HES) have become increasingly absorbed in applying big data analytics due to competition as well as economic pressures. Many studies have been conducted that applied big data analytics in HES; however, a systematic review (SR) of the research is scarce. In this paper, the authors conducted a systematic mapping study to address this deficiency. The qualitative and quantitative analysis of the mapping study resulted in highlighting the research progression over the last decade, and identification of three major themes, 12 subthemes, 10 motivation factors, 10 major chall

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Castañeda, Linda, and Lesley Gourlay. "Data ecosystems in education: opportunities and challenges." Edutec. Revista Electrónica de Tecnología Educativa, no. 86 (December 21, 2023): 1–5. http://dx.doi.org/10.21556/edutec.2023.86.3071.

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The integration of ecosystems that promote the massive use of data and the large-scale processing of this data into educational processes represent an unprecedented social challenge. This change, which we could consider paradigmatic, has been promoted by various factors which mutually magnify each other's effects. In recent years the massive collection and storage of data has intensified through ubiquitous technologies, which co-exist with human actors. In addition, we have witnessed an increase in the intentional processing power of this data at a speed unimaginable a few years ago (thr

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Sebastián-López, María, and Rafael de Miguel González. "Mobile Learning for Sustainable Development and Environmental Teacher Education." Sustainability 12, no. 22 (2020): 9757. http://dx.doi.org/10.3390/su12229757.

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Outdoor learning has, for a long time, been an important instructional resource in school education, usually embedded in the natural sciences and social sciences curricula. Teaching geography, geology, or biology beyond the traditional classroom allows students to interact with physical and social environments for meaningful learning. Mobile devices that are based on geospatial technologies have provided more accurate data, but also a combined instructional design with other WebGIS, map viewers, or geographic information system (GIS) layers, which are useful to foster education for sustainable

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VEREȘ, Sanda, Ana-Simona ILIE, and Paula Maria BUDA. "Use of Films, Platforms, and Educational Applications in Primary Education." Romanian Review of Geographical Education 13, no. 1-2 (2024): 46–67. https://doi.org/10.23741/rrge20244.

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The purpose of this study is to investigate primary school teachers' perceptions regarding the frequency of using educational platforms, digital applications, and videos for teaching science and geography. Data collection was carried out through a questionnaire survey in which 107 primary school teachers voluntarily participated. The analysis included: the frequency with which teachers use videos in science lessons, from various sources; the frequency of students using digital games and videos from various sources; the frequency of teachers creating/editing videos; the frequency of teachers us

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Lu, Mingxia. "Big Data Optimization and Applications in Running Efficiency of Higher Education." Scientific Programming 2022 (January 5, 2022): 1–10. http://dx.doi.org/10.1155/2022/1044800.

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The world is undergoing great changes that have not been seen at present; colleges and universities can only adapt to social development with a more active and open attitude. Meanwhile, colleges and universities strive to obtain more social resources during the process of gradually embedding social funds into the operation system of universities. In such a backdrop, we establish an optimization model for university running efficiency under limited funds, where the objective function is quadratic and restraint condition is linear. With the help of optimization theory, we have obtained the optim

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Hoh, Yin Kiong. "Applications of Artificial Intelligence in Life Sciences." American Biology Teacher 87, no. 3 (2025): 165–72. https://doi.org/10.1525/abt.2025.87.3.165.

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Artificial intelligence (AI) encompasses the science and engineering behind creating intelligent machines capable of tasks that typically rely on human intelligence, such as learning, reasoning, decision-making, and problem-solving. By analyzing vast amounts of data, identifying patterns, and making predictions that were once impossible, AI has rapidly advanced in recent years. This progress owes much to the availability of extensive data, powerful computing devices, and innovative algorithms. Life sciences explore the study of living organisms and their interactions with the environment. Thes

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Crocetta, Corrado, Maurizio Carpita, and Paola Perchinunno. "Data Science and Its Applications to Social Research." Social Indicators Research 156, no. 2-3 (2021): 339–40. http://dx.doi.org/10.1007/s11205-021-02634-6.

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Sagena, Unggul, Haziq Idris, Aiman Fariq, Omar Khan, and Sunarno Sunarno. "Interdisciplinary Approaches in Legal Studies: Combining Social Science and Data Science." Rechtsnormen: Journal of Law 2, no. 4 (2024): 369–79. https://doi.org/10.70177/rjl.v2i4.1258.

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Background. The integration of interdisciplinary approaches in legal studies is increasingly recognized as essential for addressing complex societal issues. Combining social science and data science offers innovative ways to analyze legal phenomena, providing deeper insights and more robust solutions. Purpose. This study aims to explore the benefits and challenges of integrating social science and data science in legal studies. The research seeks to identify effective interdisciplinary methodologies, evaluate their impact on legal research outcomes, and propose frameworks for their implementat

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Ahadi, Alireza, Abhay Singh, Matt Bower, and Michael Garrett. "Text Mining in Education—A Bibliometrics-Based Systematic Review." Education Sciences 12, no. 3 (2022): 210. http://dx.doi.org/10.3390/educsci12030210.

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Advances in Information Technology (IT) and computer science have without a doubt had a significant impact on our daily lives. The past few decades have witnessed the advancement of IT enabled processes in generating actionable insights in various fields, encouraging research based applications of modern Data Science methods. Among many other fields, education research has also been adopting different analytical approaches to advance the state of education systems. Moreover, developments in software engineering and web-based applications have made collection of education data possible at large

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Sensoy, Onder, and Halil Ibrahim Yildirim. "Impact of Technological Pedagogical Content Knowledge Based Education Applications on Prospective Teachers’ Self-Efficacy Belief Levels Toward Science Education." Journal of Education and Training Studies 6, no. 10 (2018): 29. http://dx.doi.org/10.11114/jets.v6i10.3433.

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The purpose of this study is to examine the impact of technological pedagogical content knowledge-based education applications on prospective teachers’ self-efficacy belief levels toward science education. The study was conducted on the 3rd year prospective science teachers of a public university and continued for 14 weeks. In the study, quasi -experimental method, pretest-posttest experimental design with a control group. The research was performed in the Instructional Technologies and Material Design courses during the education year of 2015-2016. In the research, one of the classes of the 3

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Alan, Burcu, Fikriye Kirbağ Zengin, and Gonca Keçeci. "USING STEM APPLICATIONS FOR SUPPORTING INTEGRATED TEACHING KNOWLEDGE OF PRE-SERVICE SCIENCE TEACHERS." Journal of Baltic Science Education 18, no. 2 (2019): 158–70. http://dx.doi.org/10.33225/jbse/19.18.158.

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In this research the effects of STEM applications, which are aimed to support the integrated teaching knowledge of pre-service science teachers on the problem solving skills of pre-service science teachers were examined. The research was carried out in scope of the mixed method design of convergent parallel design. The research was conducted with pre-service science teachers of experimental group (n=31) and control group (n=31) who were studying at Fırat University. STEM applications including Algodoo were carried out with the pre-service teachers in the experimental group for one term. The da

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ERDEM, Alaattin, Burcu ANILAN, and Zeynep KILIÇ. "STEM Experiences of Science Teachers and Fifth Grade Students." Acta Didactica Napocensia 14, no. 2 (2021): 318–32. http://dx.doi.org/10.24193/adn.14.2.23.

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"Abstract: The aim of this study is to reveal the opinions of science teachers and fifth grade students on STEM education and applications, which form the basis of the field of Science and Engineering applications. Qualitative data collection tools were used in the study. Data were collected using an open-ended questionnaire prepared with open-ended questions used in phenomenology research. The obtained data were analyzed by descriptive analysis method. The results of the analysis of the data showed that teachers experienced some problems during the application, but they saw it as an especiall

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CETINKAYA-RUNDEL, MINE, MINE DOGUCU, and WENDY RUMMERFIELD. "5Ws AND 1H OF TERM PROJECTS IN THE INTRODUCTORY DATA SCIENCE CLASSROOM." STATISTICS EDUCATION RESEARCH JOURNAL 21, no. 2 (2022): 4. http://dx.doi.org/10.52041/serj.v21i2.37.

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Many data science applications involve generating questions, acquiring data and preparing it for analysis—be it exploratory, inferential, or modeling focused—and communicating findings. Most data science curricula address each of these steps as separate units in a course or as separate courses. Open-ended term projects, on the other hand, allow students to put each of these steps into practice, sequentially and iteratively. In this paper we discuss what we mean by data science projects, why they are crucial in introductory data science courses, who works on these projects and how, when in the

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Hannon, Daniel, Esa Rantanen, Ben Sawyer, et al. "The Education of the Human Factors Engineer in the Age of Data Science." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 64, no. 1 (2020): 480–84. http://dx.doi.org/10.1177/1071181320641109.

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The continued advances in artificial intelligence and automation through machine learning applications, under the heading of data science, gives reason for pause within the educator community as we consider how to position future human factors engineers to contribute meaningfully in these projects. Do the lessons we learned and now teach regarding automation based on previous generations of technology still apply? What level of DS and ML expertise is needed for a human factors engineer to have a relevant role in the design of future automation? How do we integrate these topics into a field tha

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Ishamuddin Mustapha, Vichayanan Rattanawiboonsom, and Ruankwan Intanon. "Data-Driven Insights in Higher Education: Exploring the Synergy of Big Data Analytics and Mobile Applications." International Journal of Interactive Mobile Technologies (iJIM) 17, no. 20 (2023): 21–37. http://dx.doi.org/10.3991/ijim.v17i20.45037.

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This study explores the potential for transformation that may be achieved via the use of big data analytics and mobile apps in the context of higher education, specifically emphasizing the role of data-driven decision-making. Within the contemporary educational landscape, characterized by the increasing impact of digital technology and mobile devices, institutions of higher education are actively investigating innovative strategies. That enhances effectiveness, customizes learning experiences to suit individual students, and develops overall student accomplishments. The main objective of this

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Oliver, Jeffrey C., and Torbet McNeil. "Undergraduate data science degrees emphasize computer science and statistics but fall short in ethics training and domain-specific context." PeerJ Computer Science 7 (March 25, 2021): e441. http://dx.doi.org/10.7717/peerj-cs.441.

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The interdisciplinary field of data science, which applies techniques from computer science and statistics to address questions across domains, has enjoyed recent considerable growth and interest. This emergence also extends to undergraduate education, whereby a growing number of institutions now offer degree programs in data science. However, there is considerable variation in what the field actually entails and, by extension, differences in how undergraduate programs prepare students for data-intensive careers. We used two seminal frameworks for data science education to evaluate undergradua

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Li, Yanjie, and He Mao. "Study on Machine Learning Applications in Ideological and Political Education under the Background of Big Data." Scientific Programming 2022 (March 10, 2022): 1–9. http://dx.doi.org/10.1155/2022/3317876.

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With the development of big data and data mining technology, machine learning has been applied in many fields. However, there are a large number of difficulties for students who majored in ideological and political education. It is very necessary for those students to integrate machine learning technology into ideological and political education courses. In this paper, we introduced how to integrate machine learning into ideological and political education courses in class. Firstly, we explained what teachers should do before/in/after class for teaching machine learning courses and what studen

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Sharma, Aarti, Amal Al-Haidose, Maha Al-Asmakh, and Atiyeh M. Abdallah. "Integrating Artificial Intelligence into Biomedical Science Curricula: Advancing Healthcare Education." Clinics and Practice 14, no. 4 (2024): 1391–403. http://dx.doi.org/10.3390/clinpract14040112.

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The integration of artificial intelligence (AI) into healthcare practice has improved patient management and care. Many clinical laboratory specialties have already integrated AI in diagnostic specialties such as radiology and pathology, where it can assist in image analysis, diagnosis, and clinical reporting. As AI technologies continue to advance, it is crucial for biomedical science students to receive comprehensive education and training in AI concepts and applications and to understand the ethical consequences for such development. This review focus on the importance of integrating AI int

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Hachmeister, Nils, Katharina Weiß, Juliane Theiß, and Reinhold Decker. "Balancing Plurality and Educational Essence: Higher Education Between Data-Competent Professionals and Data Self-Empowered Citizens." Data 6, no. 2 (2021): 10. http://dx.doi.org/10.3390/data6020010.

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Data are increasingly important in central facets of modern life: academics, professions, and society at large. Educating aspiring minds to meet highest standards in these facets is the mandate of institutions of higher education. This, naturally, includes the preparation for excelling in today’s data-driven world. In recent years, an intensive academic discussion has resulted in the distinction between two different modes of data related education: data science and data literacy education. As a large number of study programs and offers is emerging around the world, data literacy in higher edu

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Yamamoto, Naoki, Akio Ishida, Kazuki Ogitsuka, Nobuhiro Oishi, and Jun Murakami. "Development of Online Learning Material for Data Science Programming Using 3D Puzzle." International Journal of Information and Education Technology 11, no. 4 (2021): 154–63. http://dx.doi.org/10.18178/ijiet.2021.11.4.1505.

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In multidimensional data processing, one of the important data structures is a higher-order tensor or a multidimensional array. In general, the processing related to the higher-order tensor is so complicated that we have been developing understanding support tools for it using 3D puzzles from the viewpoint of making students interested. However, although these tools have been tried by students in graduation studies and other some occasions, their introduction into lectures was one issue. Therefore, in this study, we developed a new programming exercise material for the higher-order tensor, whi

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Ibrahim, Umar. "Assessing the Impact of Mobile Applications on Student Engagement in ICT and Computer Science Education." International Journal of Applied and Advanced Multidisciplinary Research 2, no. 3 (2024): 221–32. http://dx.doi.org/10.59890/ijaamr.v2i3.1533.

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This study investigates the impact of mobile applications on student engagement in the realms of Information and Communication Technology (ICT) and Computer Science Education. As the integration of mobile applications in educational settings becomes increasingly prevalent, understanding their influence on student engagement is crucial for optimizing learning experiences. The study employs assess the effectiveness of selected mobile applications aligned with the curriculum. Data analysis focuses on measuring and evaluating student engagement levels. The results reveal shedding light on the impl

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Jeon, In-Seong, Sukjae Joshua Kang, and Seong-Joo Kang. "A Staged Framework for Computer Vision Education: Integrating AI, Data Science, and Computational Thinking." Applied Sciences 14, no. 21 (2024): 9792. http://dx.doi.org/10.3390/app14219792.

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Computer vision education is increasingly important in modern technology curricula; yet, it often lacks a systematic approach integrating both theoretical concepts and practical applications. This study proposes a staged framework for computer vision education designed to progressively build learners’ competencies across four levels. This study proposes a four-staged framework for computer vision education, progressively introducing concepts from basic image recognition to advanced video analysis. Validity assessments were conducted twice with 25 experts in the field of AI education and curric

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