Text and data mining in higher education and public research

This study uses case studies from researchers in the UK and France to assess the value of a copyright exception for text and data mining, and identify the steps needed to realise its potential. It was commissioned by the ADBU, the French association of directors and senior staff in university and research libraries, and delivered by Research Consulting, a UK consultancy specialising in the management and dissemination of research

Issues in Information Systems Education: A Text Mining Approach

Issues related to teaching and learning of information systems concepts have been of great interest to IS academics since the inception of the discipline over 60 years ago. A major issue is the curriculum, which has received continued research interest since it was first discussed in the literature in the early 1970s (Ashenhurst, 1972). Under the sponsorship of major professional organizations, first The Association for Computing Machinery (ACM) and then the Association for Information Systems (AIS), a series of model curricula have been developed, culminating with the release of IS2020 in 2021. The interdisciplinary nature of the field and the ever-changing landscape of technology, dictate that curriculum remains a central issue for the years to come. However, the curriculum is but one aspect of any education. Education can be defined as conducive learning, in which learning is both guided and intended (Frick, 2020). Guided learning is learning facilitated by a teacher and can include a carefully prepared learning environment. Intended learning is learning chosen by the learner. Consequently, equal emphasis should be given to the study of the teacher, the learner, and the environment in which IS education transpires. Additional IS education issues have been proposed. For example, Topi (2019) discusses five areas for further research in addition to curriculum: The role of IS as an academic discipline, the IS environment, IS education quality improvement, the visibility and impact of IS education research, and the implications of technology-based solutions. It will be interesting to assess how well the various issues have been addressed in the literature to obtain a better understanding of the state of IS education and to provide directions for future research. Text mining can be defined as “the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources” (Hearst, 2003). The use of text mining has experienced explosive growth in recent years with applications ranging from security to biomedicine. It has also been applied as a literature review tool by several researchers. In IS, Talafidaryani (2020) conducted a topic modeling of the dynamic capabilities literature and identified seven themes. We propose that a similar analysis be performed on the publications of the Journal of Information Systems Education, the premier IS education journal, to identify major IS education issues. References Ashenhurst, R. L. (1972). Curriculum Recommendations for Graduate Professional Programs in Information Systems. Communications of the ACM, 15(5), 364–398. Frick, T. W. (2020, in press). Importance of educology for improving educational systems. In J. M. Spector, B. B. Lockee, and M. D. Childress (Eds.), Learning, Design, and Technology: An International Compendium of Theory, Research, Practice and Policy: Systems Thinking and Change (E. Kowch, Section Ed.). Basel: Springer Nature Switzerland AG. Hearst, M. (2003). What is text mining? Available at https://people.ischool.berkeley.edu/~hearst/text-mining.html Talafidaryani, M. (2020). A text mining-based review of the literature on dynamic capabilities perspective in information systems research. Management Research Review, Vol. 44 No. 2, pp. 236-267. Topi, H. (2019). Invited Paper: Reflections on the Current State and Future of Information Systems Education. Journal of Information Systems Education, 30(1), 1-9

Comparative Analysis of Indonesian Text Mining News Online Classification Using the K-Nearest Neighbor and Random Forest Algorithm

The rapid development of internet technology today makes many news media grow pretty rapidly. Newspaper companies have utilized internet technology to spread the latest news online through online mass media. Hundreds of thousands of stories are written and published daily on online-based Indonesian news portals, making it difficult for readers to find the news topics they want to read. In making it easier for readers to find the news they are looking for, news needs to be classified according to its respective categories, such as education, current news, finance, and sports. So to classify categories, a text classification method is needed or often called Text Mining. Text mining is a data mining classification technique for processing text using a computer to produce helpful text analysis. In this study, a comparison of 2 methods for developing texts was carried out to get accuracy above 80%

Metoda Text Mining Untuk Pencarian Kata Di Internet

— Higher Education IT field has produced many graduates. However, the number of graduates is still not meet the labor needs of IT industry in the world Indonesia, especially the World Bank. IT graduates from universities that have the capability, instead of working abroad. While that has the ability under the standard as operators and programmers, many printed by the College. Synergy between education and industry is still not ideal. Which, this happens due to the lack of link and match between the curriculum of universities between education and industry, causing shortages of IT human resources. Here workforce mapping application that uses the ICT field text mining techniques in order to provide the information required by the College, especially for curriculum improvement College forward in order to balance the needs of the market. Keywords — text mining, basis data, filtering, stemmin

Qualitative Text Mining in Student’s Service Learning Diary

teacher education[[abstract]]Since Harvard University emphasized the important characters of college students, the service learning courses or activities is driving in educational system especially in higher education in order to building up the students global caring characters. This paper used the text mining technology to analyze the diary of the pre-service teachers attending the service learning activities. The purpose of this paper is to appear and analyze the service learning activities in order to finding out the learning outcome of students as well as providing a reflection of the service learning activities. The significance of this study is to provide a reflection and strategy form the practical data driven and using qualitative text mining technology. In other words, this study combined the Ground theory and text mining technology to find a storyline for reflection and to suggest some rare and important factors for improving the service learning activities.[[sponsorship]]National University of Kaohsiung[[conferencetype]]國際[[conferencedate]]20120926-20120928[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]Kaohsiung City , Taiwa