Bibliografías temáticas / Data processing in higher education

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Literatura académica sobre el tema "Data processing in higher education"

Autor: Grafiati

Publicado: 4 de junio de 2021

Última modificación: 20 de febrero de 2023

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Artículos de revistas sobre el tema "Data processing in higher education"

Zörög, Zoltán, Tamás Csomós, and Csaba Szűcs. "ERP systems in higher education." Applied Studies in Agribusiness and Commerce 6, no. 3-4 (November 30, 2012): 103–9. http://dx.doi.org/10.19041/apstract/2012/3-4/14.

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In the past few decades data processing and in-company communication has changed significantly. First there were only a few computers purchased at companies, therefore departments developed applications that covered corporate administration which lead to so called isolated solutions. These days with the spread of electronic data processing the greatest problem for companies is not gaining information – since they can be found in all sorts of databases and data warehouses as internal or external information – rather producing information that is necessary in a given situation. What can help to

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García-Vélez, Roberto Agustín, Martín López-Nores, Gabriel González-Fernández, Vladimir Espartaco Robles-Bykbaev, Manolis Wallace, José J. Pazos-Arias, and Alberto Gil-Solla. "On Data Protection Regulations, Big Data and Sledgehammers in Higher Education." Applied Sciences 9, no. 15 (July 31, 2019): 3084. http://dx.doi.org/10.3390/app9153084.

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Universities in Latin America commonly gather much more information about their students than allowed by data protection regulations in other parts of the world. We have tackled the question of whether abundant socio-economic data can be harnessed for the purpose of predicting academic outcomes and, thereby, taking proactive actions in student attention, course planning and resource management. A study was conducted to analyze the data gathered by a private university in Ecuador over more than 20 years, to normalize them and to parameterize a Multi-Layer Perceptron neural network, whose best-p

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Pratsri, Sajeewan, and Prachyanun Nilsook. "Design on Big data Platform-based in Higher Education Institute." Higher Education Studies 10, no. 4 (October 8, 2020): 36. http://dx.doi.org/10.5539/hes.v10n4p36.

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According to a continuously increasing amount of information in all aspects whether the sources are retrieved from an internal or external organization, a platform should be provided for the automation of whole processes in the collection, storage, and processing of Big Data. The tool for creating Big Data is a Big Data challenge. Furthermore, the security and privacy of Big Data and Big Data analysis in organizations, government agencies, and educational institutions also have an impact on the aspect of designing a Big Data platform for higher education institute (HEi). It is a digital learni

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Amare, Meseret Yihun, and Stanislava Simonova. "Learning analytics for higher education: proposal of big data ingestion architecture." SHS Web of Conferences 92 (2021): 02002. http://dx.doi.org/10.1051/shsconf/20219202002.

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Research background: Higher education institutions are generating multiple formats of data from diverse sources across the globe. The data ingestion layer is responsible for collecting data and transform for analysis. Learning analytics plays a vital role in providing decision-making support and selection of suitable timely intervention. The lack of tailored big-data ingestion architectures for academics led to several implementation challenges. Purpose of the article: The purpose of this article is to propose data ingestion architecture enabled for big data learning analytics. Methods: The st

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Zhang, Guolei, Jia Li, and Li Hao. "Cloud Computing and Its Application in Big Data Processing of Distance Higher Education." International Journal of Emerging Technologies in Learning (iJET) 10, no. 8 (December 14, 2015): 55. http://dx.doi.org/10.3991/ijet.v10i8.5280.

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In the development of information technology the development of scientific theory has brought the progress of science and technology. The progress of science and technology has an impact on the educational field, which changes the way of education. The arrival of the era of big data for the promotion and dissemination of educational resources has played an important role, it makes more and more people benefit. Modern distance education relies on the background of big data and cloud computing, which is composed of a series of tools to support a variety of teaching mode. Clustering algorithm can

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Prykhodko, Kseniia, Olena Khil, Olena Pobirchenko, Oksana Umrixina, Vera Kalabska, and Olha Bobyr. "Art education on big data and digital platforms base of higher education institutions." International journal of health sciences 6, no. 1 (February 21, 2022): 357–65. http://dx.doi.org/10.53730/ijhs.v6n1.4440.

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The study aimed to identify Big Data components and the role of the digital platform used for art education. In addition, the aim can be considered a definition of participants' role in the educational process in a broad application of Big Data and digital platforms. In conducting the research, a comprehensive approach was actively used, as well as descriptive methods, qualitative and quantitative ways of monitoring. We used questionnaires to get the necessary information, studied the essential literary sources, collected and analyzed data, and summarized the results. After summarizing the inf

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Matto, George. "Big Data Analytics Framework for Effective Higher Education Institutions." Tanzania Journal of Engineering and Technology 41, no. 1 (July 16, 2022): 10–18. http://dx.doi.org/10.52339/tjet.vi.768.

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There has been an increased dependency on Information and Communication Technologies (ICTs) in undertaking various activities in Higher Education Institutions (HEIs) ecosystems. Because of that, huge volumes of data have increasingly been generated. There have been, for instance, considerable amounts of data generated through electronic platforms involved in students’ admission and registration process, students’ academic records management, teaching and learning data, curriculum related data, and several other administrative data. Analysis of data generated from these platforms stands to give

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Handayani, Erna, Siswoyo Haryono, and Akhmad Darmawan. "Transformation of entrepreneur education programs (EEPS) of Indonesia’s higher education." International Journal of Research in Business and Social Science (2147- 4478) 10, no. 1 (February 11, 2021): 180–88. http://dx.doi.org/10.20525/ijrbs.v10i1.976.

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The Entrepreneurship Education Program (EEPs) of Indonesia’s higher education has not been effective. The study aims to identify the extent to which EEPs in Indonesia was developed and propose several alternative schemes. The research uses the methodology of traditional narrative literature review and interviews with young entrepreneurs as the output of the EEPs higher education program in Indonesia. The analysis technique is done with an interactive model with steps of data collection, data reduction, data presentation, verification, and conclusions. The literature study is intended for the l

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Zhang, Xining. "Big Data Model of Higher Education Online Teaching Based on Intelligent Algorithm." Mobile Information Systems 2022 (August 25, 2022): 1–11. http://dx.doi.org/10.1155/2022/2492952.

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With the continuous development of society, the demand for processing large-scale data in many fields is increasing. Traditional processing training techniques have many limitations for big data analysis applications. Therefore, how to transform big data into general-purpose information becomes particularly important. This research mainly discusses the big data model analysis of higher education online teaching based on intelligent algorithms. The process of the experiment is to access how trainers interact or receive information stimulation in videos and courseware and how to cause relatively

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Said, Hanna Mohammad. "Data Mining and Knowledge Discovery in Big Data for Decision Making in Higher Education." Bioscience Biotechnology Research Communications 14, no. 4 (December 25, 2021): 2013–19. http://dx.doi.org/10.21786/bbrc/14.4.93.

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Artificial intelligence and data mining plays a fundamental role in improving the intelligence of education through special standards for improving teaching quality, better learning experience, predictive teaching, assessment method, effective decision-making, and improved data analysis. BD (Big Data) are also used to assess, detect, and anticipate decision-making, failure risk, and consequences to improve decision-making and maintain high-quality standards. According to the findings of this study, certain universities and governments have adopted BD to help students transition from traditiona

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Tesis sobre el tema "Data processing in higher education"

Al-Mashaqbeh, Ibtesam. "Computer applications in higher education : a case study of students' experiences and perceptions." Virtual Press, 2003. http://liblink.bsu.edu/uhtbin/catkey/1263918.

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The purpose of this qualitative study was to describe the educational experiences with computers of nine female international graduate students at Ball State University. Their experiences with computers before they came to the United States, their current use of computers during their study at Ball State University, challenges faced related to the use of computers during their graduate study in the United States, and the support received from the university to help them overcome these barriers were described. Descriptions of ways computers supplemented and enriched the experiences of female in

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Brotherton, Jason Alan. "Enriching everyday activities through the automated capture and access of live experiences : eClass: building, observing and understanding the impact of capture and access in an educational domain." Diss., Georgia Institute of Technology, 2001. http://hdl.handle.net/1853/8143.

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Bennett, Sandra M. "Exploring the relationship between continuing professional education and job satisfaction for information technology professionals in higher education." Thesis, University of North Texas, 2006. https://digital.library.unt.edu/ark:/67531/metadc5296/.

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The study had four main hypotheses that examined the relationships between job satisfaction and the reasons for attending continuing professional education (CPE). The purpose of this study was to examine the relationships between training and job satisfaction with the objective of adding to the body of knowledge related to both job satisfaction and training and development. Participation Reasons Scale was used to measure the reasons for attending CPE activities, and the Job in General Scale and Job Descriptive Index was used to measure job satisfaction. The surveys were administered over the I

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Phipps, Owen Dudley. "The use of a database to improve higher order thinking skills in secondary school biology: a case study." Thesis, Rhodes University, 1994. http://hdl.handle.net/10962/d1003696.

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The knowledge explosion of the last decade has left education in schools far behind. The emphasis in schools must change if they are to prepare students for their future lives. Tertiary institutions as well as commerce and industry need people who have well-developed cognitive skills. A further requirement is that the school leaver must have skills pertaining to information processing. The skills that are required are those which have been labelled higher order thinking skills. The work of Piaget, Thomas and Bloom have led to a better understanding of what these skills actually are. Resnick se

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Berry, William Lee. "The use of computer technology to compare and analyze community college dissertations." FIU Digital Commons, 1989. http://digitalcommons.fiu.edu/etd/1655.

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A purpose of this research study was to demonstrate the practical linguistic study and evaluation of dissertations by using two examples of the latest technology, the microcomputer and optical scanner. That involved developing efficient methods for data entry plus creating computer algorithms appropriate for personal, linguistic studies. The goal was to develop a prototype investigation which demonstrated practical solutions for maximizing the linguistic potential of the dissertation data base. The mode of text entry was from a Dest PC Scan 1000 Optical Scanner. The function of the optical sca

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Yusof, Normah. "An empirical study of the use of computer-based material for the teaching of the listening skill in English as a second language to students of a higher education institution in Malaysia." Thesis, University of Hull, 1999. http://hydra.hull.ac.uk/resources/hull:3881.

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The primary concern of the present study was to investigate the effective uses of computer-based software in teaching the listening skill in English as a Second Language (ESL) at higher education institutions. It aimed to find out if computer-based software can be used as a teacher replacement or supplement, either at the beginning or end of the listening lesson. This study also aimed to measure students' motivational reactions to instructional materials, to examine students' computer background, to examine any significant relationships between any of the variables and also to see if there are

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Zhang, Zhidong 1957. "Cognitive assessment in a computer-based coaching environment in higher education : diagnostic assessment of development of knowledge and problem-solving skill in statistics." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=102853.

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Diagnostic cognitive assessment (DCA) was explored using Bayesian networks and evidence-centred design (ECD) in a statistics learning domain (ANOVA). The assessment environment simulates problem solving activities that occurred in a web-based statistics learning environment. The assessment model is composed of assessment constructs, and evidence models. Assessment constructs correspond to components of knowledge and procedural skill in a cognitive domain model and are represented as explanatory variables in the assessment model. Explanatory variables represent specific aspects of student's per

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Jenkins-Todd, Derone I. (Derone Ilene). "Determination of Author Characteristics and Content of Educational Computing Articles in Community/Junior College Serials Literature, 1977-1991." Thesis, University of North Texas, 1993. https://digital.library.unt.edu/ark:/67531/metadc278735/.

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The study was undertaken: (a) to categorize the contents of educational computing articles using a taxonomy developed by Knezek, Rachlin, and Scannell (1988), (b) to examine the trends in educational computing subject matter addressed in community/junior college journals between 1977 and 1991, and (c) to identify and analyze specific characteristics of contributing authors and their employing institutions which might explain writing and publication biases.

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Jacobs, Carmen. "A framework for successful SOA adoption in selected South African universities." Thesis, Rhodes University, 2013. http://hdl.handle.net/10962/d1008366.

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The demand for systems i·ntegration has become more and more significant in higher education as institutions want systems that provide coherent information with data that is up to date and not redundant and can seamlessly support the end user experience. Institutions have become more reliant on information systems to support both administrative functions and those involved in teaching, learning and research, but because each department supports a diverse array of computing platforms and applications, it becomes very difficult to integrate these systems. SOA is classified as an innovative appro

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Charoensri, Pijarn. "Technology Infusion in Career Services at U.S. Institutions of Higher Education in the Southwest." Thesis, University of North Texas, 1998. https://digital.library.unt.edu/ark:/67531/metadc278087/.

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The purpose of this study was to examine the use of computer and communications technologies at four-year public/private college and university career centers that are members of the Southwest Association of Colleges and Employers (SWACE). The findings of this study reveal that (a) all career centers are now using computer and telecommunications technologies for at least one office function; (b) small institutions do not use technologies as much as large institutions because they have fewer financial resources, less technical support from institutions, fewer personnel, and they also need t

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Libros sobre el tema "Data processing in higher education"

Savel'ev, A. Ya. Higher education and computerisation. Moscow: Progress Publishers, 1989.

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Savelʹev, A. I͡A. Higher education and computerisation. Moscow: Progress, 1989.

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International Conference on Software Engineering in Higher Education. Software engineering in higher education. Edited by King G. Southampton, UK: Computational Mechanics Publications, 1994.

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International Conference on Software Engineering in Higher Education (2nd 1995 Alicante, Spain). Software engineering in higher education II. Edited by Usó J. -L, Mitic P, and Sucharov L. J. Southampton, UK: Computational Mechanics Publications, 1996.

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Lane, Jason E. Building a smarter university: Big data, innovation, and analytics. Albany: State University of New York Press, 2014.

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Frankel, Martin M. Integrated Postsecondary Education Data System glossary. Washington, D.C: Center for Education Statistics, Office of Educational Research and Improvement, U.S. Dept. of Education, 1987.

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(Program), Nercomp. Journal of computing in higher education. Ashfield, Mass: Paideia Publishers, 1989.

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A, Shields Mark, ed. Work and technology in higher education: The social construction of academic computing. Hillsdale, N.J: Lawrence Erlbaum Associates, 1995.

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S, Lenth Charles, ed. Using national data bases. San Francisco, CA: Jossey-Bass, 1991.

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Diana, Oblinger, and Rush Sean C, eds. The learning revolution: The challenge of information technology in the academy. Bolton, Mass: Anker, 1997.

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Capítulos de libros sobre el tema "Data processing in higher education"

He, Linhua. "Innovation and Entrepreneurship Education in Higher Vocational Colleges Under Big Data." In Data Processing Techniques and Applications for Cyber-Physical Systems (DPTA 2019), 979–84. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1468-5_113.

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Huang, Jui-Chan, and Kuo-Min Ko. "Cultivation of Innovative Talents in Higher Education Based on Big Data." In Data Processing Techniques and Applications for Cyber-Physical Systems (DPTA 2019), 177–82. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1468-5_23.

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He, Linhua. "Innovation and Entrepreneurship Education in Higher Vocational Colleges Under the Background of “Internet+”." In Data Processing Techniques and Applications for Cyber-Physical Systems (DPTA 2019), 1321–26. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1468-5_155.

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Bezrukov, Artem, and Dilbar Sultanova. "Data Processing and Visualization with Matlab: Introducing an IT Component to Training Chemical Engineers." In Mobility for Smart Cities and Regional Development - Challenges for Higher Education, 1048–58. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-93907-6_111.

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Li, Jiang, and Xiaohua Ke. "Application of Big Data Technology to Ideological and Political Education in Institutions of Higher Learning." In Data Processing Techniques and Applications for Cyber-Physical Systems (DPTA 2019), 505–15. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1468-5_62.

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Kurkovsky, Anatoly. "Sustainability, Big Data, and Local Community: A Simulation Case Study of a Growing Higher Education Institution." In Advances in Parallel & Distributed Processing, and Applications, 859–72. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69984-0_62.

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Proteasa, Viorel, and Andreea Vertes-Olteanu. "How to Cope with GDPR for Graduate Tracking: A Discussion at the Intersection of Law and Policy and Two Solutions." In Higher Education in Romania: Overcoming Challenges and Embracing Opportunities, 193–210. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94496-4_10.

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AbstractResearch on higher education, and not only, has used data collected for administrative purposes—register data, to answer various policy-relevant questions. The employability of university graduates is one of such questions, which have been pending, especially in those countries whose higher education massified in the last decades. The promise of register data relies on its objective nature and apparent low cost: researchers are basically processing data that is collected for administrative purposes. In spite of these advantages, register data is still underused. Data protection restrictions, especially the alignment to the General Data Protection Regulation, are reported to temper the thrust towards making administrative data available as micro-data for secondary use. We consider that the policy dialogue would benefit from a transdisciplinary exploration of the solutions found in the EU to counter such reservations to the use of register for research. We propose an analysis at the intersection of policy studies and law of two solutions found in the EU to make register data available to researchers. We attempt to address two related questions: how are the processes designed? How is the GDPR compliance put into practice? We used structured observations of primary and secondary literature to collect our data. Our aim is to enrich the debate surrounding register data as a basis for policy-relevant research and, pragmatically, to indicate policy solutions that can be easily adjusted to national contexts in the EU and put on the table of decision-makers.

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Pacheco, Renata Martins, Ariane Laurenti, Bruno Eduardo dos Santos Silva, Iascara Mattes, and Sara Meireles. "Diagnosis of Chemical and Special Waste Management in a Higher Education Institution: A Methodology for Data Acquisition and Processing." In World Sustainability Series, 205–17. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-76885-4_14.

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Callaert, Julie, Elisabeth Epping, Gero Federkeil, Ben Jongbloed, Frans Kaiser, and Robert Tijssen. "Data Collection." In Higher Education Dynamics, 125–33. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-3005-2_8.

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Jones, Kevin Anthony, and Ravi S. Sharma. "Data Model and Collection." In Higher Education 4.0, 103–19. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6683-1_5.

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Actas de conferencias sobre el tema "Data processing in higher education"

Gautam, Sidharth. "Role of Data Analysis in Higher Education." In 2021 6th International Conference on Signal Processing, Computing and Control (ISPCC). IEEE, 2021. http://dx.doi.org/10.1109/ispcc53510.2021.9609509.

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Prodanov, Goran. "CODE OF CONDUCT FOR THE PROCESSING OF PERSONAL DATA IN HIGHER EDUCATION." In PROTECTION OF THE PERSONAL DATA AND THE DIGITALIZATION 2021. University publishing house "Science and Economics", University of Economics - Varna, 2021. http://dx.doi.org/10.36997/ppdd2021.172.

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The research objectives of this study are the legal framework, the practical benefits and the necessity for the development and possible adherence by controllers or processors of personal data in higher education to a Code of Conduct referred to in Article 40 of the GDPR. The study is part of an extended research at the time of development, related to the issues under consideration, which is aimed at developing a draft code. Its purpose is to provoke a discussion between stakeholders and interested parties, to be amended if necessary, and subsequently submitted for approval by the supervisory

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Lee, Taerim. "A deep learning analytics to facilitate sustainability of statistics education." In Decision Making Based on Data. International Association for Statistical Education, 2019. http://dx.doi.org/10.52041/srap.19306.

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Deep Learning Analytics uses predictive models that provide actionable information. It is a multidisciplinary approach based on data processing, AI technology-learning enhancement, educational data mining, and visualization. The problem is that embracing DLA(Deep Learning Analytics) in evaluating data in higher education diverts educators’ attention from clearly identifying methods, benefits, and challenges of using DLA in higher education. Predictive models including random forest (RF), support vector machines (SVM), logistic regression (logistic), and Deep Learning were trained and their per

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Shtymak, Anatolii, Pavlo Mulesa, and Mykola Malyar. "Procedure for Determination of Professional Competence of a Higher Education Institution Graduate." In 2020 IEEE Third International Conference on Data Stream Mining & Processing (DSMP). IEEE, 2020. http://dx.doi.org/10.1109/dsmp47368.2020.9204112.

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Verma, Seema, Jitendra Pandey, and Alavikunhu Panthakkan. "Data Analytics and Knowledge Management in a learning environment for Higher Education." In 2022 5th International Conference on Signal Processing and Information Security (ICSPIS). IEEE, 2022. http://dx.doi.org/10.1109/icspis57063.2022.10002568.

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Adshead, Deborah Alison. "Embedding Information Rights into Higher Education in the UK." In Third International Conference on Higher Education Advances. Valencia: Universitat Politècnica València, 2017. http://dx.doi.org/10.4995/head17.2017.5272.

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Estimates suggest that a data breach costs an organisation over $4 million and that the total global cost of breaches will soon exceed $2 trillion. Hacking is part of the problem but errors in processing by individuals are still the most reported reasons for data breaches in the UK. With predictions of more jobs involving data processing in the future and the exponential growth in accessible personal data, it is increasingly important that this problem is taken more seriously. This Information Commissioner’s Office (ICO) sponsored research constitutes stage one of a study into the teaching of

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Suhre, Cor, Koos Winnips, Vincent De Boer, Pablo Valdivia, and Hans Beldhuis. "Students’ experiences with the use of a social annotation tool to improve learning in flipped classrooms." In Fifth International Conference on Higher Education Advances. Valencia: Universitat Politècnica València, 2019. http://dx.doi.org/10.4995/head19.2019.9131.

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To support the development and dissemination of more activating educational practices, pilot studies were launched on the use of the social annotation tool Perusall. During 2016-2017 several managers of higher education course units worked with Perusall in classes of a size varying from 10 to more than hundred students. To assess the usefulness and effectiveness of Perusall we focused on two related aspects (1) perception by students of Perusall as an appropriate tool to support the processing of the study texts and (2) the impact of student engagement in Perusall on students’ examination resu

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Liao, Xiaoling. "Asset Management Mode of Higher Vocational Colleges Based on Big Data Technology." In CIPAE 2021: 2021 2nd International Conference on Computers, Information Processing and Advanced Education. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3456887.3456894.

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Barana, Alice, Luigi Di Caro, Michele Fioravera, Francesco Floris, Marina Marchisio, and Sergio Rabellino. "Sharing system of learning resources for adaptive strategies of scholastic remedial intervention." In Fourth International Conference on Higher Education Advances. Valencia: Universitat Politècnica València, 2018. http://dx.doi.org/10.4995/head18.2018.8232.

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This paper presents a model for school remedial, focusing on improving the digital materials sharing process for the diversification of tutoring strategies. The model involves the characterization of materials for automatic assessment shared within a community of tutors. The characterization expects materials to be linked with natural language descriptors explicating their intended instructional objectives. The possibility of implementing a recommendation system on the basis of natural language processing techniques is discussed taking in consideration an analysis of the application of the mod

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Prieto Sanz, Helena. "Do text discussions improve the academic skills of students of HE? Andorra University case." In Sixth International Conference on Higher Education Advances. Valencia: Universitat Politècnica de València, 2020. http://dx.doi.org/10.4995/head20.2020.11211.

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Reading is a core competency in learning processes of higher education as a tool for accessing discipline-specific knowledge. The aim of this case study is to analyse the impact of text group discussions on the academic skills of students at the Universitat d’Andorra (UdA). Qualitative techniques -non-participant observation, interviews and discussion groups- were applied to UdA students and faculty. Five student groups belonging to the Bachelor of Teaching and Learning (BTL), Bachelor of Computer Science (BCS) and Bachelor of Business Administration (BBA) were studied. After processing the da

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Informes sobre el tema "Data processing in higher education"

Volkova, Nataliia P., Nina O. Rizun, and Maryna V. Nehrey. Data science: opportunities to transform education. [б. в.], September 2019. http://dx.doi.org/10.31812/123456789/3241.

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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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Falfushynska, Halina I., Bogdan B. Buyak, Hryhorii V. Tereshchuk, Grygoriy M. Torbin, and Mykhailo M. Kasianchuk. Strengthening of e-learning at the leading Ukrainian pedagogical universities in the time of COVID-19 pandemic. [б. в.], June 2021. http://dx.doi.org/10.31812/123456789/4442.

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Distance education has become the mandatory component of higher education establishments all over the world including Ukraine regarding COVID-19 lockdown and intentions of Universities to render valuable knowledge and provide safe educational experience for students. The present study aimed to explore the student’s and academic staff’s attitude towards e-learning and the most complicated challenges regarding online learning and distance education. Our findings disclosed that the online learning using Zoom, Moodle, Google Meet, BigBlueButton and Cisco has become quite popular among the students

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Chowdry, Haroon, Anna Vignoles, Alissa Goodman, Lorraine Dearden, and Claire Crawford. Widening participation in Higher Education: analysis using linked administrative data. IFS, June 2008. http://dx.doi.org/10.1920/re.ifs.2005.0069.

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Slade, Sharon. Applications of Student Data in Higher Education: Issues and Ethical Considerations. Ithaka S+R, September 2016. http://dx.doi.org/10.18665/283891.

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Slade, Sharon. Applications of Student Data in Higher Education: Issues and Ethical Considerations. Ithaka S+R, September 2016. http://dx.doi.org/10.18665/sr.283891.

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Radecki, Jane, and Rebecca Springer. Research Data Services in US Higher Education: A Web-Based Inventory. Ithaka S+R, November 2020. http://dx.doi.org/10.18665/sr.314397.

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Shalatska, Hanna, Olena Zotova-Sadylo, Olexandr Makarenko, and Larysa Dzevytska. Implementation of E-assessment in Higher Education. [б. в.], November 2020. http://dx.doi.org/10.31812/123456789/4466.

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The purpose of the study is to develop the methodical recommendations for test-designers to cope with challenges of organizing on-line assessment process. In order to achieve this goal we have to reveal the strengths and weaknesses of e-assessment activities based on analysis of the universities practice. To find out students’ attitude to the issue of the study we have drawn up the questionnaire. The survey results confirm that e-assessment is rated as priority activity by learners thanks to individual approach to teaching/learning process, easily accessible and fast feedback, as well as inter

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Hinrichs, Peter L. State Appropriations and Employment at Higher Education Institutions. Federal Reserve Bank of Cleveland, November 2022. http://dx.doi.org/10.26509/frbc-wp-202232.

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This paper studies the impacts of state appropriations on staffing and salaries at public higher education institutions in the United States using employment and revenue data from the Integrated Postsecondary Education Data System, along with an instrumental variables strategy borrowed from Deming and Walters (2018) and Chakrabarti, Gorton, and Lovenheim (2020). The instrument sidesteps the potential endogeneity of state appropriations for a given institution in a given year by interacting an institution’s historical reliance on state appropriations with total state appropriations for all high

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Moretti, Enrico. Estimating the Social Return to Higher Education: Evidence From Longitudinal and Repeated Cross-Sectional Data. Cambridge, MA: National Bureau of Economic Research, August 2002. http://dx.doi.org/10.3386/w9108.

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Mayfield, Colin. Higher Education in the Water Sector: A Global Overview. United Nations University Institute for Water, Environment and Health, May 2019. http://dx.doi.org/10.53328/guxy9244.

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Higher education related to water is a critical component of capacity development necessary to support countries’ progress towards Sustainable Development Goals (SDGs) overall, and towards the SDG6 water and sanitation goal in particular. Although the precise number is unknown, there are at least 28,000 higher education institutions in the world. The actual number is likely higher and constantly changing. Water education programmes are very diverse and complex and can include components of engineering, biology, chemistry, physics, hydrology, hydrogeology, ecology, geography, earth sciences, pu

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