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Journal articles on the topic 'Data processing in higher education'
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1
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 solve this situation? It is informatics, more precisely ERP systems which have substituted software that provided isolated solutions at companies for decades. System based thinking is important in their application beside the fact that only data absolutely necessary for managerial decisions must be produced. This paper points out why we consider practice oriented teaching of ERP systems in higher education important.
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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-performing configuration would be used as a benchmark for the comparison of more recent and sophisticated Artificial Intelligence techniques. However, an extensive scan of hyperparameters for the perceptron—exploring more than 12,000 configurations—revealed no significant relationships between the input variables and the chosen metrics, suggesting that there is no gain from processing the extensive socio-economic data. This finding contradicts the expectations raised by previous works in the related literature and in some cases highlights important methodological flaws.
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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 learning platform that is an online instruction and the use of digital media for educational reform including a module provides information on functions of various modules between computers and humans. 1) Big Data architecture is a framework for an architecture of numerous data which consisting of Big Data Infrastructure (BDI), Data Storage (Cloud-based), processing of a computer system that uses all parts of computer resources for optimal efficiency (High-Performance Computing: HPC), a network system to detect the target device network. Thereafter, according to Hadoop’s tools and techniques, when Big Data was introduced with Hadoop's tools and techniques, the benefits of the Big Data platform would provide desired data analysis by retrieving existing information, to illustrate, student information and teaching information that is large amounts of information to adopt for accurate forecasting.
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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 study reviews existing literature to examine big-data ingestion tools and frameworks; and identify big-data ingestion challenges. An optimized framework for the real world learning analytics application was not yet in place at global higher educations. Consequently, the big-data ingestion pipeline is experiencing challenges of inefficient and complex data access, slow processing time, and security issues associated with transferring data to the system. The proposed data ingestion architecture is based on review of recent literature and adapts best international practices, guidelines, and techniques to meet the demand of current big-data ingestion issues. Findings & value added: This study identifies the current global challenges in implementing learning analytics projects. Review of recent big data ingestion techniques has been done based on defined metrics tuned for learning analytics purposes. The proposed data ingestion framework would increase the effectiveness of collecting, importing, processing and storing of learning data. Besides, the proposed architecture contributes to the construction of full-fledged big-data learning analytics ecosystem of higher educations.
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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 provide an effective evaluation method for students' personality characteristics and learning status in distance education. However, the traditional K-means clustering algorithm has the characteristics of randomness, uncertainty, high time complexity, and it does not meet the requirements of large data processing. In this paper, we study the parallel K-means clustering algorithm based on cloud computing platform Hadoop, and give the design and strategy of the algorithm. Then, we carry out experiments on several different sizes of data sets, and compare the performance of the proposed method with the general clustering method. Experimental results show that the proposed algorithm which is accelerated has good speed up and low cost. It is suitable for the analysis and mining of large data in the distance higher education.
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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 information obtained, it became clear that the Big Data use and digital platforms for art education allowed the transfer of the classical educational process to digital media and created the necessary environment for intellectualizing the educational process. In the future, it is worth considering and searching for options on how to get rid of the gaps in the use of information technology for art education. Relevant issues can be viewed as the problems of security, confidentiality, ethical component, compatibility, data storage, and processing problems, and the acute experienced personnel shortage.
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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 students, lecturers, HEIs Management, policy makers and implementers, and other stakeholders useful insights that would help in improving HEIs’ effectiveness. Unfortunately, literature have identified several challenges associated with existing big data analytics frameworks in HEIs. It was on this line that the present study, which was based on desk research, was carried out to propose an effective big data framework for analytics of such data. The proposed framework is composed of five stages; data collection, data pre-processing, data storage, data analytics, and data visualization. The stages were arranged systematically to address the identified challenges in the existing frameworks. Effective implementation of this framework will help HEIs to make a productive use of various data they generate. This will ultimately be beneficial to not only HEIs but also to aspired students, labour market, the government and the public at large.
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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 latest research information that evaluates the effect of EEPs on the formation of EM and the formation of new entrepreneurs. Furthermore, the information is verified by the results of the interview data processing. Entrepreneurship education for multidisciplinary students, business incubators, funding provision, and program sustainability studies is the result of research as a proposal for the development of higher education EEPs. This program is part of a long-term solution to addressing labor problems in Indonesia.
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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 lasting changes in cognitive behavior. From the experimental research, we discovered the law of practical training and finally provided personalized teaching support services according to the needs and abilities of the trainers. On the other hand, the online training algorithm for big data analysis is studied, the methods needed to solve the big data mining task are discussed, and the online course training is recommended in many ways. Experimental data show that the algorithm of large-scale online training behavior data analysis on the behavior analysis results of online trainers is conducive to the improvement of online trainers’ learning efficiency. The experimental results show that the algorithm of large-scale online training behavior data analysis can show good model analysis performance, which is conducive to the prediction of the training personnel, and the prediction accuracy reaches about 90%. It is found that the algorithm that implements large-scale online training behavior data analysis can effectively categorize the relationship between the trainee’s visits. Through innovative data analysis methods, fast, efficient, and timely analysis of big data streams is realized.
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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 traditional to smart digital education. Many obstacles remain in the way of complete adoption, including security, privacy, ethics, a scarcity of qualified specialists, data processing, storage, and interoperability. Learning today is getting smarter, thanks to the rapid development of the use of data and knowledge for big data analysis. Besides delivering real-world knowledge discovery applications, specialized data mining methodologies, and obstacles have real-world applications. Therefore, this article aims to explain the current concept of an intelligent learning environment in higher education. It explores the main criteria, and presents evaluation methods through the use of the proposed model.
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Daraio, Cinzia, Renato Bruni, Giuseppe Catalano, Alessandro Daraio, Giorgio Matteucci, Monica Scannapieco, Daniel Wagner-Schuster, and Benedetto Lepori. "A Tailor-made Data Quality Approach for Higher Educational Data." Journal of Data and Information Science 5, no. 3 (July 9, 2020): 129–60. http://dx.doi.org/10.2478/jdis-2020-0029.
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AbstractPurposeThis paper relates the definition of data quality procedures for knowledge organizations such as Higher Education Institutions. The main purpose is to present the flexible approach developed for monitoring the data quality of the European Tertiary Education Register (ETER) database, illustrating its functioning and highlighting the main challenges that still have to be faced in this domain.Design/methodology/approachThe proposed data quality methodology is based on two kinds of checks, one to assess the consistency of cross-sectional data and the other to evaluate the stability of multiannual data. This methodology has an operational and empirical orientation. This means that the proposed checks do not assume any theoretical distribution for the determination of the threshold parameters that identify potential outliers, inconsistencies, and errors in the data.FindingsWe show that the proposed cross-sectional checks and multiannual checks are helpful to identify outliers, extreme observations and to detect ontological inconsistencies not described in the available meta-data. For this reason, they may be a useful complement to integrate the processing of the available information.Research limitationsThe coverage of the study is limited to European Higher Education Institutions. The cross-sectional and multiannual checks are not yet completely integrated.Practical implicationsThe consideration of the quality of the available data and information is important to enhance data quality-aware empirical investigations, highlighting problems, and areas where to invest for improving the coverage and interoperability of data in future data collection initiatives.Originality/valueThe data-driven quality checks proposed in this paper may be useful as a reference for building and monitoring the data quality of new databases or of existing databases available for other countries or systems characterized by high heterogeneity and complexity of the units of analysis without relying on pre-specified theoretical distributions.
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Jurgena, Inese, and Dagnija Cēdere. "Students’ Ideas on Innovations in Higher Education." Journal of Pedagogy and Psychology "Signum Temporis" 8, no. 1 (December 1, 2016): 30–36. http://dx.doi.org/10.1515/sigtem-2016-0014.
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Abstract The academic staff plays a key role in the implementation of innovations, striving to introduce changes in the process of education and involving students in this process. The aim of this article is to analyse the ideas of students and pre-service teachers, on the role of innovations in the work of the academic staff at the institutions of higher education. The research is based on the analysis of scientific literature, regulatory documents, studies and surveys. The analytical data processing software SPSS was used for the analysis of the data. Having analysed the data of the survey involving the first-year students and pre-service teachers, enrolled both in the full-time and part-time studies at RTTEMA, the authors conclude that readiness for innovative activity and active involvement in the creation, acquisition and application of innovations is an essential factor for amending the traditional activity of the academic staff. The authors gained convincing evidence of the idea that in pedagogy the term innovation refers to the process of renewal, educational reforms, the selection of the most appropriate material (idea, activity, form, method, means, concept, or programme) and their practical implementation, i.e. the creation, acquisition and application of innovations in the pedagogical practice.
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Pidbutska, Nina, and Anastasia Knysh. "ASSESSMENT OF RESEARCH SKILLS AND SKILLS OF MATHEMATICAL PROCESSING OF DATA OF STUDENTS OF I-III LEVELS OF HIGHER EDUCATION SPECIALTY “PSYCHOLOGY”." Theory and practice of social systems management, no. 3 (October 4, 2021): 106–15. http://dx.doi.org/10.20998/2078-7782.2021.3.09.
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The article is devoted to the topical problem of researching the level of development of research skills and abilities of mathematical data processing in future psychologists studying at different levels of higher education. The study involved three levels of higher education and five doctors ofpsychology as experts. Respondents (n = 75) were asked to perform a practical task aimed at demonstrating their ability to transform a simple practical question into a research model that would take into account all the necessary steps and methods of mathematical data processing. The analysis of the results indicates the presence of statistically significant differences and levels of development of research skills and abilities of mathematical data processing. It was determined that the highest rate is for applicants for the third, and the lowest - for the second level of higher education.
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Abe, Shota, Akio Ishida, Jun Murakami, and Naoki Yamamoto. "Development of Online Learning Materials for Tensor Data Processing Exercises." International Journal of Information and Education Technology 12, no. 3 (2022): 194–202. http://dx.doi.org/10.18178/ijiet.2022.12.3.1604.
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Tensor decomposition is used in a wide range of research fields; however, its theory is difficult to understand. Therefore, basic education is essential when using it in programming. Currently, there are few Japanese universities that provide education on tensor decomposition; however, some overseas universities have already conducted it, and online learning materials are also substantial. Therefore, in this paper, we have developed online learning materials for basics and programming exercises of higher-order singular value decomposition (HOSVD), which is one of tensor decomposition, for the purpose of increasing the learning materials for tensor decomposition education. Our learning material is created on Microsoft Teams, and students can access this material channel and work on exercises on demand while watching explanatory videos including CG animation. As a result of the trial of this learning material, it was found that the students who used it can generally understand the processes related to tensor decomposition and can perform basic programming of them.
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Vincze, Szilvia, and Zoltán Bács. "International students in Hungarian higher education." Applied Studies in Agribusiness and Commerce 14, no. 3-4 (December 31, 2020): 113–32. http://dx.doi.org/10.19041/apstract/2020/2-3/13.
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Overall, higher education in Hungary is popular with students from abroad, even if there are significant differences in terms of its structure. The ever-faster increase in the annual headcount of the international student body serves as proof to this statement. The expansion of the size of the body of international students is of special importance in higher education since in 2016 the Hungarian government set the objective of having 40,000 international students by 2023 (EMMI, 2016).
Numerous studies have been published on this topic, usually focusing on specific issues, including, for example, the countries from which we receive most of the students, the most popular majors, possible economic advantages due to the presence of a great number of international students, and how internationalization takes place in higher education in Hungary.
By means of processing data published by the Hungarian Educational Authority [Oktatási Hivatal], this paper aims to present the changes in the number of international students in Hungary over the past ten years. This also includes the discussion of the structure of these changes related to a variety of issues such as relations, types of institutions and their ownership, levels and types of programs, as well as gender proportions. However, even with this effort, the officially available statistics are suitable for presenting a properly detailed assessment of the situation only to a limited extent.
JEL code: I23
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Aliyev, Ulukbek, and Nurlan Kurmanov. "HIGHER EDUCATION IN THE REPUBLIC OF KAZAKHSTAN: PROBLEMS AND IMPROVEMENT METHODS." CBU International Conference Proceedings 3 (September 19, 2015): 141–49. http://dx.doi.org/10.12955/cbup.v3.595.
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The paper investigated the current state of higher (business) education in the Republic of Kazakhstan. The research methodology is based on the processing of secondary data, which allows a preliminary analysis of the problems of the education system. The authors give an estimate of the current system of business education in Kazakhstan. The authors conclude that the education system of Kazakhstan is currently under development, competitiveness of the economy largely depends on the quality of education and further growth is impossible without well-educated and trained personnel.
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Gapon, Valentyna, and Olena Barabash. "MONITORING OF INDICATORS OF EQUIPMENT AND MATERIAL PROCUREMENT OF HIGHER EDUCATION INSTITUTIONS." Educational Analytics of Ukraine, no. 1 (2021): 39–54. http://dx.doi.org/10.32987/2617-8532-2021-1-39-54.
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The authors studied the legal documents on the collection and processing of sectoral reports on the logistics of higher education institutions (HEI). The purpose of the article is to conduct a comparative analysis of the state of logistics of the HEIs of the Ministry of Education and Science of Ukraine using specific statistical and financial indicators. The method of system and structural-hierarchical analysis is applied in the work, it was used to develop the information model of information collection and processing, the methodology and technology of information databases formation; a statistical method for determining the relationships between indicators and developing a system of analytical indicators. For the information and analytical support, the data from the databases «Legal Entities» and «Financial and Economic Reporting» are used, formed using common methodological principles. Analytical indicators make it possible to assess the condition of academic buildings and dormitories, make it possible to identify technically obsolete facilities in need of repair, modernization or decommissioning. To do this, a number of indicators have been calculated and presented, including the provision of space in academic buildings and dormitories per full-time student, the average annual cost of maintaining one square meter of building area, the coefficient of wear and tear, etc. Analytical data are formed based on the financial results of the HEIs for the year 2019 in Ukraine as a whole, for each group of the HEIs and each institution of higher education. The obtained results make possible operational monitoring of the working efficiency of academic buildings and dormitories. The proposed framework of data processing, storage and usage provides high-quality analytical information when making management decisions on logistics issues of the HEIs. The topic of further research should be the development of the information and analytical system combining and using indicators of two information databases, namely «Legal Entities» and «Financial and Economic Reporting».
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Tarigan, Thomas Edison, Robby C. Buwono, and Sri Redjeki. "Extraction Opinion of Social Media in Higher Education Using Sentiment Analysis." bit-Tech 2, no. 1 (October 30, 2019): 11–19. http://dx.doi.org/10.32877/bt.v2i1.92.
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The purpose of this research is to extract social media Twitter opinion on a tertiary institution using sentiment analysis. The results of sentiment analysis will provide input to universities as a form of evaluation of management performance in managing institutions. Sentiment analysis generated using the Naïve Bayes Classifier method which is classified into 4 classes: positive, normal, negative and unknown. This study uses 1000 data tweets used for training data needs. The data is classified manually to determine the sentiment of the tweet. Then 20 tweet data is used for testing.
The results of this study produce a system that can classify sentiments automatically with 75% test results for sentiment, some obstacles in processing real-time tweets such as duplicate tweets (spam tweets), Indonesian structures that are quite complex and diverse.
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Lorenzo de Reizábal, Margarita, and Manuel Benito Gómez. "Learning Analytics and Higher Music Education: Perspectives and Challenges." ARTSEDUCA, no. 34 (December 7, 2022): 219–28. http://dx.doi.org/10.6035/artseduca.6831.
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Continually monitoring student learning, improving tutoring, predicting academic risks such as performance drops or dropouts, assessing more objectively or understanding the behavior of student groups are some of the tasks that have been beyond the reach of music teachers. The current technology of massive data processing (Big Data) and its analysis (Learning Analytics-LA) allows to achieve these goals with relative ease. The possibility of extracting individual behavior patterns facilitates attention to diversity, reduces school dropout and failure, and opens the possibility of implementing new educational strategies. The phenomenon of data-based education has led to different types of studies. This paper reflects on three trends or fundamental perspectives in the use of the collection of massive information applied to learning and teaching. We offer an overview of research and applications of Learning Analytics specifically in the field of music education, as well as a reflection on its possible practical uses in higher music education in conservatories. For this purpose, we discuss some practical examples of how this technological methodology could be incorporated into music and music education research, and its influence on possible new educational paradigms that lead to innovation on teaching-learning process through new technological resources.
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Xu, Baoliang. "Application of Edge Computing and Data Mining Processing System in Preschool Education Courses." Mobile Information Systems 2022 (September 30, 2022): 1–9. http://dx.doi.org/10.1155/2022/7872897.
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With the deepening of reform and opening up, my country’s preschool education has entered a vigorous development. At the same time, higher requirements are put forward for the field of preschool education. Preschool education is an important part of education, and preschool education is the foundation of basic education. However, the informatization construction in the field of preschool education in my country has just started. In order to implement the planning requirements of the Ministry of Education on strengthening the informatization construction of preschool education, build a digital platform, improve children’s quality, promote the harmonious development of children’s body and mind, improve professional ethics and the professional level of preschool education practitioners with the help of modern new media, and meet the professional development and sense of achievement, acquisition, and satisfaction of preschool education practitioners. Taking multiple measures to ensure the diversified needs of preschool education practitioners is the important and only means for the stable, comprehensive, and sustainable development of preschool education. The data visualization platform of IOT architecture designed in this paper for edge computing ensures the application of massive data in preschool education courses, ensures the stability of system data transmission, and realizes the visualization of IOT terminal data. Therefore, the introduction of data mining technology in this paper can improve the utilization of resources, provide support for teachers, students, and ordinary users, and enhance the versatility of the preschool education resource platform.
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Crompton, Helen, and Donggil Song. "The Potential of Artificial Intelligence in Higher Education." Revista Virtual Universidad Católica del Norte, no. 62 (January 2021): 1–4. http://dx.doi.org/10.35575/rvucn.n62a1.
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Artificial Intelligence (AI) is seeping into many aspects of our everyday lives, with common internet applications, smartphones and even household appliances. Within education, AI is a rapidly emerging field and there is a strong potential for AI to greatly extend and enhance teaching and learning in higher education (Crompton et al., 2020). AI is defined as “computing systems that are able to engage in human-like processes such as learning, adapting, synthesizing, self-correction and use of data for complex processing tasks” (Popenici & Kerr, 2017). In the Horizon Report 2020 report (Brown et al., 2020), AI is listed as one of six technologies with the potential for high impact in higher education. The Horizon Report (2020), is an annual publication that examines the major trends in educational technology that are shaping global higher education. This paper will highlight some of the ways AI is supporting both students and faculty members including bespoke learning, intelligent tutoring systems, facilitating collaboration, and automated grading. This is followed by a section on ethical implications.
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Gunawan, I. Ketut, Ninda Lutfiani, Qurotul Aini, Fitria Marwati Suryaman, and Abas Sunarya. "Smart Contract Innovation and Blockchain-Based Tokenization in Higher Education." Journal of Education Technology 5, no. 4 (November 26, 2021): 636. http://dx.doi.org/10.23887/jet.v5i4.40665.
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Blockchain which includes smart contract and tokenization features is the latest technology in the world, especially Indonesia. Smart contracts and tokenization make it very easy for users and can maintain valid data security, but there are still many universities that have not implemented the system so they have to involve many parties and costs. The problem taken in this study is the payment process for transactions such as credit and data processing that is vulnerable to illegal data leakage. This study aims to develop a smart contract system and blockchain tokenization in universities in the payment transaction process. The method used in this research is literature review analysis and testing method. The implementation of smart contracts and tokenization can replace third parties as security guards of transaction data with all Blockchain users paying attention and ensuring the integrity of the entire process and activity. This of course can avoid problems that arise from the presence of third parties in the transaction process. So it can be concluded that the implementation of smart contracts and Blockchain tokenization in payment transactions is the right solution to be applied in the payment transaction process at universities.
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Galyna, PIATNYTSKA. "HIGHER EDUCATION BRANDING." Herald of Kyiv National University of Trade and Economics 138, no. 4 (September 10, 2021): 118–36. http://dx.doi.org/10.31617/visnik.knute.2021(138)10.
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Background. The increasing intensity of competition in the international market for higher education services leads to an increase in the importance of brands of higher education institutions (HEIs) and the branding of national higher education in general. The aim of this study is to determine the target setting and the main objectives of the country’s higher education branding in the international market of educational services. Materials and methods. Methods of comparative and critical analysis, analytical processing of the collected data, graphical display of trends and interrelations, synthesis, etc. are used to achieve the purpose and accomplish the assigned tasks. Results. Analysis of the dynamics of appeals to the Google-system with queries to search for such words and phrases as: "Brand"; "Higher education"; "University" showed that after a sharp decline in the number of brand and branding queries in March 2020, the trend of increasing attention to this concept among Internet users began to grow again. At the same time, in the last months of 2021, there is a trend towards a decline in requests for higher education and universities. The risk of such a situation for the development of existing universities lies in the fact that the latter is happening against the background of the periodic introduction of quarantine restrictions and the loss of the opportunity to establish constant offline communications with students and youth audience. On the basis of a critical analysis, comparison and systematization of the existing definitions of the concepts of "branding of higher education" and "brand of higher education", it is proposed to understand the process of "branding of higher education" as a process aimed at implementing the strategy for the development of higher education, strengthening the identity of the higher education system of the country in the international market of educational services, support competitiveness of the higher education sector by establishing effective communications with all stakeholder groups both within the country and abroad. It has been substantiated that the "brand of a higher education institution" should be understood as a specific model of ideas and value characteristics about the HEI and its educational services in the minds of stakeholders. It is emphasized that the process of the higher education branding should be aimed at forming the value of the brand. This requires the following tasks, the implementation of which: 1) will create a strong competitive brand of higher education in the country, which will help solve educational problems and meet the needs of the labor market, especially within the country; 2) provide preconditions for further geographical diversification in the provision of educational services of the country’s HEIs; 3) will increase the volume of foreign and domestic investment in the educational and scientific space of the country. Along with this, the factors that should be paid attention to in the process of higher education branding and which were formed under the influence of Globalization 4.0 and the manifestation of the consequences of the COVID crisis were identified. Considering the level of development of the higher education system in the country, the choice of one of the following branding strategies for higher education is envisaged: internal orientation; internal-external orientation; external-internal orientation. It is established that Ukraine must now implement a strategy of internal-external orientation of higher education branding. It was noted that it would be better to track the results of higher education branding through special assessment and monitoring of changes in the Global Tertiary Education Brand Index and by region. Conclusion. The problem of the higher education branding, as evidenced by the results of the study, is far from simple and requires the setting of specific tasks, the completion of which should contribute to the achievement of the goal of maximizing the value of the country’s higher education brand. In the process of higher education branding and specific HEIs branding the interests of various groups of stakeholders as well as changes that taking place in the international market of educational services (including due to Globalization 4.0 and the effects of the pandemic) should be taken into account. The results of the study can be further used to develop and substantiate methodological approaches to determining the Global Tertiary Education Brand Index and the corresponding country indices, by which it will be possible to track imbalances and competitive advantages in the development of higher education in the regions of the country. Keywords: branding, brand management, higher education, brand of higher education institution, risks, strategies of higher education branding, digitalization, the market of educational services.
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Irwan, Irwan, Rusnardi Rahmat Putra, Krismadinata Krismadinata, and Nizwardi Jalinus. "Introduction to questionnaire data patterns using Perceptron Algorithm for lecturer improvement and development in higher education." INVOTEK: Jurnal Inovasi Vokasional dan Teknologi 21, no. 1 (February 2, 2021): 1–10. http://dx.doi.org/10.24036/invotek.v21i1.743.
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This artificial neural network research article aimed to overview the current teaching process focusing on lecturer performance using the perceptron algorithm, improving the teaching process, developing the lecturer based on the perceptron algorithm's results, evaluating the speed and accuracy of the perceptron algorithm in evaluating performance lecturer and learning the rules of the perceptron algorithm in processing assessment criteria for lecturers in tertiary institutions. In this case, the perceptron algorithm was used to recognize the questionnaire data input patterns. The perceptron algorithm was trained and tested to recognize input data patterns so that this neural network could identify input data patterns from questionnaire data.
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Arma Putra, Feby, and Bambang Dwi Suseno. "Industrial Revolution 4.0 as a Strategic Issue of Higher Education." International Journal of Scientific Research and Management 10, no. 02 (February 16, 2022): 3045–51. http://dx.doi.org/10.18535/ijsrm/v10i2.em05.
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This study aims to explore strategic issues of the industrial revolution 4.0 in the higher education environment, accompanied by an in-depth analysis with the perspective of change management and how they adapt. The method used is SWOT analysis by scanning the environment through non-probability sampling using snowball data collection with the help of Google forms so that stakeholders can respond through a multimedia platform. The results of data processing in the form of index numbers by contrasting strengths and weaknesses as well as opportunities and threats. The final result is the ordinate point 2.93, 013 which is in quadrant 1 with good internal strength but has not been able to seize opportunities, which requires more adequate consolidation of resources. It was concluded that private higher education in Banten Province at a young age still requires strengthening in terms of human resources, finances, stable intake of students and educational infrastructure that must be updated according to the demands of the industrial revolution 4.0.
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Utari, Nadia, and Riki Mukhaiyar. "ALTERNATIVE CONCEPTS TO IDENTIFY THE CHARACTERISTICS OF VOCATIONAL TECHNOLOGY EDUCATION CURRICULUM." JURNAL PENDIDIKAN TEKNOLOGI KEJURUAN 3, no. 1 (February 24, 2020): 60–63. http://dx.doi.org/10.24036/jptk.v3i1.4323.
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Higher education is expected to produce excellent graduates to meet the needs of educated and skilled personnel in the era of industry 4.0. One way of higher education to adjust the development of Science and Technology in the era of industry 4.0 is by enriching the curriculum. Curriculum enrichment can be done by adding a new course, the Image Processing course. Image Processing is a course in Electrical Engineering which discusses data processing and analyze data in the form of images to be used as important information as requested. Image processing courses are widely used in daily life, implementation of image processing courses are found in smartphones, parking systems, medical, television and many others that utilize image processing subjects. The characteristics of this study compared two different groups: the Non-LPTK University (Lembaga Pendidikan Tenaga Kependidikan/ Educaitonal Institutions of Educatinal Staff) with the LPTK University to looking for characteristics in covering different subjects with the characteristics of vocational education, but it is related to the characteristics of vocational education in considering matching subjects with digital characteristics in the field of vocational education studies. Curriculum enrichment aims to improve the quality of higher education learning which leads to improve the quality of graduates. The researcher used a qualitative research with a comparative method ex post facto. This research is expected to be a pattern for other universities in applying curriculum enrichment methods.
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Sharma, Hari Maya. "Gender in Nepalese Higher Education Curriculum: An Example from Tribhuvan University." Educator Journal 10, no. 1 (July 27, 2022): 93–104. http://dx.doi.org/10.3126/tej.v10i1.46732.
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This paper analyses the course entitled 'English Language Teaching (ELT) practices and materials' offered by Tribhuvan University for Master's level in English education from a gender perspective. The main objective of the paper is to explore and analyse gender inequalities underlying in the processing and production of the course. Taking the course documents as the primary source of data, this paper found that the course falls short in gender mainstreaming and has revealed gender-blindness in content selection and recommended/reference materials encouraging gender inequality during the course development process as well as in its production.
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Agustiani, Riza, Hartatiana Hartatiana, and Ambarsari Kusuma Wardani. "Mathematics students’ writing skills: Assesment in higher education with Rasch model." International Journal on Teaching and Learning Mathematics 1, no. 2 (December 22, 2018): 90–102. http://dx.doi.org/10.18860/ijtlm.v1i2.6749.
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The aim of this research is to describe the students’ scientific writing skills of mathematics education. This research is descriptive qualitative research. Research subject is choosen by using purposive sampling technique. Research subject is choosen based on variety of batch, grade point average (GPA) dan Thesis Processing Duration (TPD). Data collection techniques in this research are document studies (documentation methods) and interviews. The document study was carried out by 2 researchers (chairman and researcher members) and 2 other lecturers of Mathematics Education Study Program to obtain data about writing scientific work for research subjects. The interview was conducted after the results of the first data analysis were obtained as confirmation media and deeper exploration of the profile of the research subjects. This study provides an overview of the carrying capacity of the GPA characteristics, the value of Indonesian Language, the value of Research Methods, and TPD. The four characteristics do not significantly support the students’ cientific writing skills of the mathematics education study program.
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Anastasia, Lenshy Aprisilia, Benny Pinontoan, and Luther Alexander Latumakulita. "Design Web-Based Information System of Tri Dharma Higher Education for Lecturer." Operations Research: International Conference Series 3, no. 1 (February 6, 2022): 23–31. http://dx.doi.org/10.47194/orics.v3i1.130.
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Tri dharma of higher education consisting of education & teaching, research, and community service which must upheld by every lecturer at universities in Indonesia. Lecturer who has implemented the tri dharma of higher education need these tri dharma files for promotion and lecturer performance report to get allowance. It is important to have an online system to store those files. In this research we develop a web-based information system for processing lecturer tri dharma activities data using Rapid Application Development (RAD) Method which started from requirement planning, system design, and implementation.
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Harjadi, Dikdik, and Dewi Fatmasari. "Implementation of Integrated Marketing Communication in Image of Private Higher Education." TRIKONOMIKA 16, no. 2 (December 28, 2017): 63. http://dx.doi.org/10.23969/trikonomika.v16i2.638.
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This study aimed to examine the implementation of integrated marketing communication conducted by private universities in Kuningan Regency and analyze the influence of integrated marketing communication performance which includes advertising, sales promotion, personal selling, public relation, and direct marketing on private university image. The method used was descriptive and verificative method conducted by collecting primary data in the field from private university students in Kuningan Regency. Based on the results of data processing and hypothesis testing, it was known that integrated marketing communication consisting of advertising, personal selling, sales promotion, public relation, and direct marketing simultaneously and partially had a positive and significant impact on private university image. The simultaneous influence is 38.7%, which meant there was still much influence outside the implementation of integrated marketing communication that affected private university image. The biggest influence was sales promotion.
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Mohamed Nafuri, Ahmad Fikri, Nor Samsiah Sani, Nur Fatin Aqilah Zainudin, Abdul Hadi Abd Rahman, and Mohd Aliff. "Clustering Analysis for Classifying Student Academic Performance in Higher Education." Applied Sciences 12, no. 19 (September 21, 2022): 9467. http://dx.doi.org/10.3390/app12199467.
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There are three income categories for Malaysians: the top 20% (T20), the middle 40% (M40), and the bottom 40% (B40). The government has extended B40′s access to higher education to eliminate socioeconomic disparities and improve their lives. The number of students enrolled in bachelor’s degree programmes at universities has risen annually. However, not all students who enrolled graduated. Machine learning approaches have been widely used and improved in education. However, research studies related to unsupervised learning in education are generally lacking. Therefore, this study proposes a clustering-based approach for classifying B40 students based on their performance in higher education institutions (HEIs). This study developed three unsupervised models (k-means, BIRCH, and DBSCAN) based on the data of B40 students. Several data pre-processing tasks and feature selection have been conducted on the raw dataset to ensure the quality of the training data. Each model is optimized using different tuning parameters. The observational results have shown that the optimized k-means on Model B (KMoB) achieved the highest performance among all the models. KMoB produced five clusters of B40 students based on their performance. With KMoB, this study may assist the government in reducing HEI drop-out rates, increasing graduation rates, and eventually boosting students’ socioeconomic status.
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Aris, Aris, Tiya Puspita Firdaus, and Neha Nurseha. "APLIKASI PROGRAM QUALITY CONTROL BARANG UNTUK MENUNJANG PELAPORAN PADA BAGIAN TEKNIK PERGURUAN TINGGI RAHARJA." Journal CERITA 4, no. 2 (August 1, 2018): 159–68. http://dx.doi.org/10.33050/cerita.v4i2.639.
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Data processing system of Higher Education Raharja needs the best and integrated to facilitate decision making and create good service standard. Especially if the data is related to Control and Quality. Data and information easily accessible to support the performance of each section. As in theEngineering section, In data processing Engineering section still can not provide the best service to meet the strategic information needs required to support reporting on the management of Higher Education Raharja. It takes a long time to generate information data items as required, this happens because it has not been integrated with the management and information processing can not be effective and efficient, With the design method using UML, as well as making the application program using PHP programming language website based .So can help in reporting data goods engineering section for management that can improve the performance of engineering section for Higher Education Raharja so as to provide good and faster service.
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Nasir, Muhammad, Syeh Hawib Hamzah, and Muhammad Khairul Rijal. "ANATOMICAL ANALYSIS OF ISLAMIC RELIGIOUS EDUCATION CURRICULUM AT GENERAL HIGHER EDUCATION IN INDONESIA." Ta'dib 24, no. 1 (June 28, 2021): 53. http://dx.doi.org/10.31958/jt.v24i1.2827.
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This article explores the anatomical characteristics of the Islamic Education Curriculum based on personal and community development in General Higher Education in Indonesia. This research is a qualitative study, words or actions of people observed and interviewed are the main data sources. The primary data sources of this study were elements of faculty leaders, heads of study programs, students, and lecturers of Islamic Religious Education. This study illustrates how the anatomical characteristics of Islamic Higher Education of General Islamic Education curriculum support strengthening personal and community development. The research findings show that the learning achievements of graduates, the content and teaching materials, the learning process or learning experience, and the assessment model illustrated in the curriculum structure, strongly support the development of responsibilities as individuals of Allah's servants and as Khalifah fi al-ardh. The aspect of personal development is the aspect of tathwir al-nafsi in the form of individual monotheism which includes the teaching of Islamic belief, strengthening of mahdhah and others. The aspect of tathwir al-ijetimaiy, illustrated in the strengthening of student social monotheism in the form of al-amr bi al-makruf wa al-nahy an al-mungkar, the human concept as caliph, democracy, science, technology, art, harmony, civil society, welfare, religious people, Islamic culture, Islamic political system, and democracy. The learning process is still dominated by increasing the understanding of the propositions, concepts, and theories with the teaching model of information processing. The internalization process through practice with social and humanistic teaching models still needs to be improved.
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Fu, Xinyi. "Design of a Higher Education Question and Answer System Based on Multimodal Adversarial Networks." Mathematical Problems in Engineering 2022 (September 5, 2022): 1–9. http://dx.doi.org/10.1155/2022/7453653.
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Higher education question and answer system is a current research hotspot in the field of natural language processing and artificial intelligence, which can return accurate answers directly and also allow users to input in natural language, avoiding the need to return large collections of valid and invalid data links for users to filter twice. In recent years, deep learning techniques have made great progress in the field of natural language processing, thus making it possible to apply it in the field of teaching and learning in junior high school. Most of the traditional quiz systems based on traditional retrieval techniques have problems such as insufficient semantic portrayal of text, inability to extract semantic features in context, and poor processing of complex utterances. In order to fill the gap and deficiencies of question and answer systems in junior high school teaching, this paper applies multimodal and adversarial network-related technologies to build a multimodal adversarial network-based question and answer system for higher education. The experimental results show that the principles of the traditional application system and the multimodal adversarial system designed in this paper are similar, but the current application system is relatively more effective.
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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, which is supposed to be used in data science subjects, by using a 3D puzzle. This learning material is also composed of Microsoft Teams, and students can access the material remotely to learn programming. In this paper, several students actually tried this material. As a result, it was found that the students themselves could create and submit assignment reports by viewing explanatory videos and performing exercises. From this, it is expected that this material will be able to introduce to data science courses, including online use.
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Parnikova, Galina, and Svetlana Antsupova. "Individual Educational Trajectories in Higher Education Institution - Global Challenges for Regions." E3S Web of Conferences 291 (2021): 05017. http://dx.doi.org/10.1051/e3sconf/202129105017.
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The need to introduce individualization of education in the universities of Yakutia is dictated by the need to find optimum solutions for preserving human capital in the northern territories, attracting applicants to regional universities and the labor market’s need for competitive specialists from the local population. The purpose of the study is to develop innovative approaches to the educational process in regional universities in the context of global challenges. Research methods: analysis and processing of data from an array of theoretical sources and educational practice; modeling. Scientific novelty of the research: a personality-oriented model of education at the university has been built, taking into account the regional specifics and factors affecting the formation of individual educational trajectories of students.
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Alsuwaiket, M., A. H. Blasi, and R. A. Al-Msie'deen. "Formulating Module Assessment for Improved Academic Performance Predictability in Higher Education." Engineering, Technology & Applied Science Research 9, no. 3 (June 8, 2019): 4287–91. http://dx.doi.org/10.48084/etasr.2794.
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The choice of an effective student assessment method is an issue of interest in Higher Education. Various studies [1] have shown that students tend to get higher marks when assessed through coursework-based assessment methods which include either modules that are fully assessed through coursework or a mixture of coursework and examinations than assessed by examination alone. There are a large number of educational data mining (EDM) studies that pre-process data through conventional data mining processes including data preparation process, but they are using transcript data as they stand without looking at examination and coursework results weighting which could affect prediction accuracy. This paper proposes a different data preparation process through investigating more than 230,000 student records in order to prepare students’ marks based on the assessment methods of enrolled modules. The data have been processed through different stages in order to extract a categorical factor through which students’ module marks are refined during the data preparation process. The results of this work show that students’ final marks should not be isolated from the nature of the enrolled module’s assessment methods. They must rather be investigated thoroughly and considered during EDM’s data pre-processing phases. More generally, it is concluded that educational data should not be prepared in the same way as other data types due to differences as data sources, applications, and types of errors in them. Therefore, an attribute, coursework assessment ratio (CAR), is proposed to be used in order to take the different modules’ assessment methods into account while preparing student transcript data. The effect of CAR on prediction process using the random forest classification technique has been investigated. It is shown that considering CAR as an attribute increases the accuracy of predicting students’ second-year averages based on their first-year results.
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Murialti, Neng, Dwi Widiarsih, Ranti Darwin, Muhammad Hidayat, M. Fikry Hadi, and Mizan Asnawi. "UPAYA MENINGKATKAN KOMPETENSI GURU DALAM TEKNIK PENGOLAHAN DATA PENELITIAN." Jurnal Pengabdian UntukMu NegeRI 3, no. 1 (May 30, 2019): 33–39. http://dx.doi.org/10.37859/jpumri.v3i1.1106.
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Higher Education other than as an educational institution that has the main task of carrying out the process of education and teaching, also has other tasks namely carrying out research and community service. Quality improvement of human resources of a nation means encouraging the improvement of the quality of the nation itself so that it has the ability to compete with countries in the world. The education world is one of the spearheads in the effort to improve the quality of human resources. So improving the quality of human resources must be supported by improving the quality of educators (teachers), because qualified teachers will be able to produce students who are also qualified. Efforts to improve the quality of human resources can be implemented jointly in the world of education. Lecturer of Development Economics Study Program Faculty of Economics and Business UMRI tries to help increase teacher competency in Pekanbaru City PGRI Vocational School, through training in the use of SPSS software as a teacher data processing research tool. After conducting data processing training with SPSS software, it is expected that the teacher assemblies can produce quality research to support education and teaching activities at Vocational High School level.
Keywords: SPSS, Increased Teacher Competency, improving the quality of HR.
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Bahar, Abdulkadir, and Mehmet Ali Ozturk. "An Exploratory Study on the Relationship between Creativity and Processing Speed for Gifted Children." International Education Studies 11, no. 3 (February 25, 2018): 77. http://dx.doi.org/10.5539/ies.v11n3p77.
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This study explored the relationship between processing speed and five dimensions of creativity, which were fluency, originality, elaboration, abstractness of titles, and resistance to premature closure (RPC). It is the first empirical study that examines this relationship, also relating it to gender and level of giftedness. Data came from 133 gifted students at grades one through four in three private schools in Istanbul, Turkey. Creativity was measured through the Torrance Test of Creative Thinking – Figural. Scores from the Coding subtest of the Wechsler Intelligence Scale for Children were used as the data on processing speed. The findings showed that girls had significantly higher scores in processing speed, elaboration, abstractness of titles, and RPC. There were no significant differences in fluency and originality. While fluency and originality were the only two subscores correlated with processing speed for boys (both positively correlated), four subscores were correlated with processing speed for girls (all four negatively correlated). Girls had higher processing speed scores in the group of low giftedness, but not in the group of high giftedness. A distinct finding about the boys of high giftedness was the high positive interrelationships among originality, fluency, and processing speed, which were not there for boys of low giftedness or girls of high giftedness. With its findings, the study supports some of the previous explanations around the topic, and generates new hypotheses to be tested experimentally.
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Pidbutska, Nina, Anastasiia Knysh, Yulia Chebakova, Iryna Shtuchenko, and Olena Babchuk. "Motivation Behind the Preference of Distance Education of Higher Education Students." Journal of Education Culture and Society 13, no. 1 (June 30, 2022): 201–10. http://dx.doi.org/10.15503/jecs2022.1.201.210.
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Aim. The aim of the study is to investigate into the motives of learning that are inherent in students with different attitudes to distance learning. The main objectives of the study are as follows: to analyze the attitude to different forms of distance learning of students of higher education institutions; to investigate the main forms of scientific motivation of students of higher education institutions; to compare how the scientific motivation of students with different attitudes to distance learning differs.
Methods. The study involved 211 students majoring in science (physics, chemistry). The study uses the following methods: 1) attitude questionnaire; 2) Science Motivation Questionnaire II; 3) statistical methods. The following is used for statistical data processing: descriptive statistics methods (to measure the percentage of people with different attitude towards organization of distance learning); ANOVA (to compare levels of science motivational types of students with different preferences in educational models).
Results. It was determined that 38% of students are positive about distance education and see great opportunities for its implementation. But only 22.75% of students consider distance learning the best option of educational process organisation, and 21.8% are in favor of an exclusive face-to-face format. The most popular form among students is mixed form of education (55.45%). Students with a positive attitude to distance education are characterized by the highest scores on intrinsic motivation, self-efficacy and career motivation. Therefore, proponents of distance education are mostly students who have a good understanding of their own goals and learning needs, plan their career advancement, and are well-organized in terms of educational and professional development.
Conclusions. Distance forms of education cannot completely replace traditional ones. But it is already becoming obvious that their use in a mixed format can increase the effectiveness of the educational process. Students' sympathy for the mixed format should be taken into account by the developers of educational programs and university administrations in order to improve the quality of education and meet the requirements of the times.
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Lu, Liping, and Jing Zhou. "Research on Mining of Applied Mathematics Educational Resources Based on Edge Computing and Data Stream Classification." Mobile Information Systems 2021 (March 25, 2021): 1–8. http://dx.doi.org/10.1155/2021/5542718.
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Facing the massive data of higher education institutions, data mining technology is an intelligent information processing technology that can effectively discover knowledge from the massive data and can discover important information that people have previously ignored from the huge data information. This article is dedicated to the development of applied mathematics education resource mining technology based on edge computing and data stream classification. First of all, this article establishes a resource system architecture suitable for existing applied mathematics education through edge computing technology, which can effectively improve the efficiency of data mining. Secondly, the data stream classification algorithm is used for information extraction and classification integration of massive applied mathematical education data. This method provides potential and valuable information for decision-makers and education practitioners. Finally, the simulation and performance test of the system verify that it has the functions of mathematical information mining and data processing. This system will provide strong support for applied mathematics education reform.
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Sun, Xiaokang, Xiangshu Huang, Hui Yu, and Xirui Liu. "Construction of Mathematics Teaching Environment Based on Big Data on the Wisdom Cloud Platform of Higher Vocational Education." Journal of Electrical and Computer Engineering 2022 (June 7, 2022): 1–11. http://dx.doi.org/10.1155/2022/4348613.
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As a public basic course in the system of higher vocational colleges, mathematics has received more and more attention from education administrators. However, there are still problems in higher education that mathematics teaching resources are scatter and data are difficult to integrate. Big data (DT) and smart clouds are the burgeon of intelligent technology, which has provided support for teaching informatization and teaching data integration in colleges and universities. This article aims to solve the problems of mathematics teaching in higher vocational education, such as more content and less class hours, difficult, higher vocational education due to the expansion of enrollment, and the decline in mathematics teaching quality, and build a smart cloud platform based on big data mathematics instructing environment system and mathematics wisdom instructing. The reconstruction of the environment is the deep integration of information technology and mathematics instructing, which can promote the deep integration of information technology with teaching, management, and environment. The experiments in this article show that the application of the smart cloud platform to mathematics teaching can greatly increase students' enthusiasm for learning and improve the school's mathematics teaching level, and the improvement rate of students' performance can reach 99.89%. The research in this article is of great significance to the adjustment of mathematics teaching environment in higher professional education.
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Grammenou, Kassiani, Karagiorgos Ioannis, Nikolaos Blanas, Heidy Tzika, Kleio Tzoumerkioti, and Alexandra-Antonia Sideridou. "Marketing in Higher Education: Postgraduate Programs in Technological Educational Institute of Thessaly." Academic Journal of Interdisciplinary Studies 6, no. 3 (November 27, 2017): 65–72. http://dx.doi.org/10.1515/ajis-2017-0022.
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Abstract The Departments of Higher Education that have incorporated postgraduate courses in their curriculum must acquire provision and adaptability mechanisms so that the courses can correspond to the current and future needs of their students. Important factors, such as many disadvantages that the extremely competitive postgraduate courses abroad face, compared to the postgraduate courses in Greece, lead the potential students to choose the Greek ones. This research paper aims to find the right methodology for the postgraduate courses to attract more students. Specifically the research will be conducted through questionnaires, using Likert method and SPSS system for the processing of data. Our goal is to collect primary data from active postgraduate students of the Technological Educational Institute of Thessaly. The results of the research will serve as useful tools for the administrative members of both Higher Education Universities and Technological Education Institutes, as well for the teachers, since they can showcase the Greek postgraduate courses in comparison to the ones abroad.
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Miguel-Eguía, Valentin, Juana Coello, Alberto Martínez, M. Carmen Manjabacas, and Antonio Calatayud. "Learning Strategies for Deep-Drawing Processes in the European Higher Education Area Context." Materials Science Forum 692 (July 2011): 74–82. http://dx.doi.org/10.4028/www.scientific.net/msf.692.74.
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A traditional educational strategy for teaching sheet stamping processes consists in theoretical planning. Having experimental media available to conduct stamping processes in university teaching laboratories is not that usual. In this work Problem Based Learning is carried out. Students must evaluate some data from deep-drawing experiences that have been previously done by the teaching team. The innovation proposal starts with deep-drawing experimental demonstrations performed by an experimental device that has been designed in the laboratory for researching and teaching aims. Processing the information that students acquire helps them to analyse the main deep-drawing technological fundamentals.
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Basri, Muhammad, and Muhammad Azwar Paramma. "EFL Students’ Perspective on the Usefulness of ICT based Learning in Indonesian Higher Education." ELT Worldwide: Journal of English Language Teaching 6, no. 2 (October 31, 2019): 105. http://dx.doi.org/10.26858/eltww.v6i2.10515.
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The study explores the perception of the EFL students in English Language Teaching through ICT based learning at Universitas Negeri Makassar. It employs a descriptive study using purposive sampling techniques by taking 57 respondents from university students. The online questionnaire used to collect data on the perception of students on the ICT based Learning of English Language Teaching. The method of descriptive in terms of percentage has been used for data processing, and the deduction method has been used to analyze and interpret data. The result of this study indicates the positive perception those university students hold on the use of the Learning Management System in English Language Teaching. Further study can refer to this Acceptance Model in determining a suitable ICT integrated learning program between the reality and user expectations of the program used.
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Ahrens, Andreas, Jelena Zascerinska, Parulkumari P. Bhati, Mihails Zascerinskis, and Anastasija Aleksejeva. "COMPARATIVE STUDIES OF COVID-19 IMPACT ON STUDENTS’ VIEWS ON DIGITAL HIGHER EDUCATION." SOCIETY. INTEGRATION. EDUCATION. Proceedings of the International Scientific Conference 5 (May 28, 2021): 19–29. http://dx.doi.org/10.17770/sie2021vol5.6277.
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Higher education sector has been significantly adapting to the new situation created by the COVID-19 pandemic. Despite students are often referred to, students are rarely at the centre of the concerns being raised. The research aim is to compare students’ views on digital higher education in light of COVID-19 underpinning the identification of issues in digital higher education in light of COVID-19. The research implies theoretical and empirical methods. The exploratory empirical study was carried out. Semi-structured interviews serves as the data collection method. Content analysis was applied to the obtained data for data processing. The theoretical analysis allows finding that digital environment in higher education is not limited by only a technical aspect of its organisation. Digital environment also implies students’ health, financial and economic situation, etc. The empirical findings contribute to the conclusion that digital higher education in light of COVID-19 is negatively evaluated by students. The most common issues faced by students are identified. The research question is newly formulated. Directions of further research are proposed. The novelty of the paper is presented by the identified issues in digital higher education in light of COVID-19.
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Saputri, Agatha, and Endang Mulyani. "The Impact of Academic Information System to Students’ Satisfaction in Higher Education." Studies in Educational Management 12 (September 2022): 1–9. http://dx.doi.org/10.32038/sem.2022.12.01.
Full textAbstract:
Academic information systems reflect the quality of management of a college and are one of the efforts of educational institutions to provide quality services to provide convenience and comfort to students. There are obstacles such as the difficulty of controlling the scheduling of courses and information that is less updated on academic information systems. This study aims to determine how much influence the academic information system has on student satisfaction. This study uses a type of research based on a quantitative approach. The research subjects were bachelor and graduate school students from Universitas Negeri Yogyakarta. The data collection method used a questionnaire. Data processing techniques and data analysis using simple linear regression formulas. The results showed that (i) there was a significant influence between the implementation of academic information systems on the level of satisfaction of Universitas Negeri Yogyakarta bachelor and graduate school students amount 41% (ii) supporting and inhibiting factors perceived by students in the implementation of academic information systems found in speed, timeliness, and ease of access. This article has empirical contributions related to academic information systems in higher education and can be used as insights for policy holders in universities in making policies.
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Sutanto, Sutanto, Yul Hendra, and Miftahul Jannah. "SISTEM INFORMASI PENGOLAHAN DATA KULIAH KERJA MAHASISWA DI LP3M UNIVERSITAS BANTEN JAYA BERBASIS WEB." Journal of Innovation And Future Technology (IFTECH) 3, no. 1 (February 4, 2021): 19–30. http://dx.doi.org/10.47080/iftech.v3i1.1144.
Full textAbstract:
Student Work Lecture (KKM) is one of the programs in higher education at Banten Jaya University (UNBAJA). Thematic KKM activities, is one form of integrating education, research, and community service activities. The current KKM data processing system is that students come directly to the relevant work units to register and report, Field Supervisors are also parties associated with KKM participants when collecting KKM assessments and their journals must come directly to the relevant work units. The purpose of this research is to design a system for KKM data processing in order to facilitate students, Field Supervisors and other relevant parties. This research development method uses System Development Life Cycle (SDLC) with the Rapid Application Development (RAD) model. The proposed system is a KKM data processing system that is done computerized and online where students can register and report as well as Field Supervising Lecturers as well as easily collect assessments and journals provided by the system without coming directly to the relevant work units.
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Lin, Wenjun, Haiyu Song, Gonçalo Almeida, and António Godinho. "Latent trait analysis for teacher career development and capacity improvement in higher education institutions." CADMO, no. 2 (January 2022): 46–62. http://dx.doi.org/10.3280/cad2021-002005.
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This study shows the influence of human resource management practices on the academic and non-academic staff and its impact on the higher education institution's goals. A questionnaire based on the Cranet survey was used to gather data from 240 employees (academic and non-academic staff) from a public higher education institution. A phi-k correlation algorithm was used to verify the underlying correlation coefficients, statistical significance, and outliers within multiple data types. This algorithm allows a more personalized, understandable approach to reveal the human resource management practices that significantly impact the teacher career development and capacity improvement. In addition, the use of background variables to identify the groups of respondents allows the algorithm to discern the multidimensional data for a more personalized human resource management approach. Human resource management practices involving training development and staff were correlated to the institution's goals. The phi-k correlation proved to be a suitable tool to shape structural models and latent trait analysis between multiple data types, which can overcome the drawbacks of Pearson and Cramer correlations when processing non-linear data. The presented research contributes to the literature by using the phi-k algorithm to process multiple data types. The proposed study with the phi-k algorithm is the first time applied to higher education institutions.
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Saal, Leah Katherine, Takashi Yamashita, Donita M. Shaw, and Kristen H. Perry. "An exploration of U.S. adults’ information processing skills and political efficacy." Journal of Adult and Continuing Education 26, no. 2 (June 4, 2019): 178–202. http://dx.doi.org/10.1177/1477971419852750.
Full textAbstract:
As recent debates about the role of social media in election outcomes suggest, understanding the association between information processing skills and political efficacy in the U.S. is a significant inquiry for adult and continuing education. Data from the Programme for the International Assessment of Adult Competencies were used to explore relationships between U.S. participants’ information processing skills and political efficacy. Given the impact of certain demographic characteristics on political efficacy, the study also analyzed whether the relationship between information processing skills and self-reported political efficacy varied across levels of cultural engagement, formal educational attainment, or immigrant status. The results illustrate that higher levels of literacy, numeracy, and problem solving in technology-rich environments are associated with higher political efficacy for U.S. participants. Our research is framed in both cognitive and critical lenses, and we provide implications for practice in adult and continuing education settings.