Introducing New Mass Screening in Institutional Research Based on Eduinformatics

Authors

  • Kunihiko Takamatsu Tokyo Institute of Technology
  • Akira Ito Kobe Tokiwa University
  • Takafumi Kirimura Hirosaki University
  • Katsuhiko Murakami The University of Tokyo
  • Yasuhiro Kozaki Osaka Kyoiku University
  • Aoi Kishida Kobe City Nishi-Kobe Medical Center
  • Ikuhiro Noda Kobe Tokiwa University
  • Nao Ichikawa Kobe Tokiwa University
  • Kenya Bannaka Kobe Tokiwa University
  • Ryosuke Kozaki Hyogo University of Teacher Education
  • Masato Omori Kobe Tokiwa University
  • Yasuo Nakata Kobe Tokiwa University
  • Kenichiro Mitsunari Kobe Tokiwa University

DOI:

https://doi.org/10.52731/lir.v001.043

Keywords:

mass screening, first-year education, text mining, digital transformation (DX), Eduinformatics

Abstract

In recent years, student information has accumulated due to the increasing number of remote lectures during the COVID-19 pandemic and the digital transformation (DX) of education. Student information data were analyzed by faculty members. We propose a system called “mass screening” in this study, which follows a 2-steps method. First, we analyzed all the students at the university scale and department. Then, we returned the analysis reports to faculty members at Kobe Tokiwa University to prepare true tailor-made education. The university raised SSP, and the student support policy was able to raise early alerts for students.

References

K. Takamatsu, K. Murakami, T. Kirimura, K. Bannaka, I. Noda, L. R.-J. Wei, K. Mitsunari, M. Seki, E. Matsumoto, M. Bohgaki, A. Imanishi, M. Omori, R. Adachi, M. Yamasaki, H. Sakamoto, K. Takao, J. Asahi, T. Nakamura, et al., “‘Eduinformatics’: A new education field promotion,” Bull. kobe Tokiwa Univ., vol. 11, pp. 27–44, 2018, doi: 10.20608/00000958.

K. Takamatsu, Y. Kozaki, K. Murakami, A. Sugiura, K. Bannaka, K. Mitsunari, M. Omori, and Y. Nakata, “Review of Recent Eduinformatics Research,” in IEEE/IIAI International Congress on Applied Information Technology 2019, 2019, pp. 27–32. doi: 10.1109/AIT49014.2019.9144820.

K. Takamatsu, I. Noda, B. Kenya, T. Nakagawa, Y. Kozaki, K. Mitsunari, M. Omori, R. Adachi, and Y. Nakata, “A New Concept of ICT on Eduinformatics in Higher Education,” in 6th International Congress on Information and Communication Technology, Springer Nature, 2022, pp. 693–700. doi: 10.1007/978-981-16-2377-6_64.

K. Takamatsu, K. Murakami, Y. Kozaki, K. Bannaka, I. Noda, K. Mitsunari, M. Omori, and Y. Nakata, “A New Academic Field Needed in the Age of Information and Communication Technology,” in 5th World Conference on Smart Trends in Systems, Security and Sus-tainability (WorldS4 2021), Intelligent Sustainable Systems, Springer Nature, Springer Nature, 2022, pp. 139–147. doi: 10.1007/978-981-16-6309-3_15.

Y. Iwaki and S. Hiromichi, “Trend of Institutional Research Organizations,” Kansai Univ. J. High. Educ., vol. 8, pp. 93–101, 2017.

K. Takamatsu, K. Murakami, I. Noda, K. Bannaka, Y. Nakata, Y. Kozaki, A. Kishida, H. Kabutoya, K. Mitsunari, and M. Omori, “New Proposal of University Reform by Sig-nificant Other Groups in Eduinformatics,” Int. J. Institutional Res. Manag., vol. 5, no. 1, pp. 96–105, 2021, doi: 10.52731/ijirm.v5.i1.681.

Y. Nakata, K. Murakami, Y. Kozaki, T. Kirimura, A. Sugiura, K. Bannaka, and K. Takamatsu, “New Proposal to Compare Student Data in Institutional Research,” in Ad-vanced Applied Informatics (IIAI-AAI), 2019 8th International Institute of Applied In-formatics (IIAI) International Congress on. Institute of Electrical and Electronics Engineers (IEEE), 2019, pp. 404–407. doi: 10.1109/IIAI-AAI.2019.00089.

K. Takamatsu, K. Murakami, Y. Kozaki, A. Kishida, K. Bannaka, K. Mitsunari, M. Omori, and Y. Nakata, “Introducing new criteria for IR, using student data compared analysis based on Eduinformatics,” in Advanced Applied Informatics (IIAI-AAI), 2020 9th International Institute of Applied Informatics (IIAI) International Congress on. Institute of Electrical and Electronics Engineers (IEEE), 2020, pp. 378–384. doi: 10.1109/IIAI-AAI50415.2020.00083.

UNESCO, “Learning Analytics,” 2012. [Online]. Available: https://iite.unesco.org/pics/publications/en/files/3214711.pdf

N. Kondo, M. Okubo, and T. Hatanaka, “Early Detection of At-Risk Students Using Machine Learning Based on LMS Log Data,” in 2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI), 2017, pp. 198–201. doi: 10.1109/IIAI-AAI.2017.51.

K. Murakami, K. Takamatsu, Y. Kozaki, A. Kishida, K. Bannaka, I. Noda, J. Asahi, K. Takao, K. Mitsunari, T. Nakamura, and Y. Nakata, “Predicting the Probability of Student Dropout through EMIR Using Data from Current and Graduate Students,” in Advanced Applied Informatics (IIAI-AAI), 2018 7th International Institute of Applied Informatics (IIAI) International Congress on. Institute of Electrical and Electronics Engineers (IEEE), 2018, pp. 478–481. doi: 10.1109/IIAI-AAI.2018.00103.

T. Kirimura, K. Mitsunari, T. Kunisaki, T. Gozu, K. Takamatsu, K. Bannaka, and Y. Nakata, “Effectiveness of first year experience’s course ‘Manaburu’ at Kobe Tokiwa University for university students by using textual analysis,” Bull. Kobe Tokiwa Univ., vol. 11, pp. 193–208, 2018, doi: 10.20608/00000972.

Y. Nakata, Y. Kozaki, K. Mitsunari, T. Kunisaki, K. Bannaka, T. Gozu, I. Noda, and K. Takamatsu, “Ensuring Equal Evaluation among Teachers in First-Year Education Courses through Rubrics: A Multiple Comparison Analysis,” in International Conference on Ed-ucation, Psychology, and Learning (ICEPL2018), 2018, pp. 40–46.

Y. Nakata, Y. Kozaki, K. Bannaka, M. Kondo, Y. Mizokoshi, K. Mitsunari, and K. Takamatsu, “Sustainability of Equal Evaluations Among Teachers of First-Year Students in Higher Education,” IEEE/IIAI Int. Congr. Appl. Inf. Technol. 2019, pp. 21–26, 2019, doi: 10.1109/AIT49014.2019.9144816.

Y. Nakata, K. Bannaka, K. Murakami, Y. Kozaki, K. Mitsunari, and K. Takamatsu, “Evaluation of a First-Year Course Using Factor Analysis,” in Advanced Applied Infor-matics (IIAI-AAI), 2020 9th International Institute of Applied Informatics (IIAI) Inter-national Congress on. Institute of Electrical and Electronics Engineers (IEEE), 2020, pp. 385–390. doi: 10.1109/IIAI-AAI50415.2020.00084.

Q. Le and T. Mikolov, “Distributed representations of sentences and documents,” in International conference on machine learning, 2014, pp. 1188–1196.

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Published

2022-08-25