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Submitted
Jun 3, 2022
Accepted
Apr 22, 2023
Published
Apr 27, 2023
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Abstract

Online learning environments have attracted attention of many educators especially in recent years since COVID-19 is still ongoing situation. Meanwhile, the various resources are becoming more and more available in online. In this study, some available online resources were used to create the system checkable for some writing abilities and the depth of understanding for Japanese writing tasks. The system was also made to provide some evaluation scores without depending the number of characters. The demonstration of system were given after the integration and implementation of some modules customized using online resources. The data sheet in the system finally saved the written content for 67 students. The writing task was given as the writing of summarization for what a student understand in a class. The following features were demonstrated from the analytical findings of online system developed in this study. The effectiveness of some available online resources was indicated through the demonstration of system checkable for some writing abilities and the depth of understanding for Japanese writing tasks. It was definite that the system was also made to provide some evaluation scores without depending the number of characters.

Keywords

Online Evaluation System Writing Task Key Word Key Sentence Latent Semantic Analysis Engineering Education

Article Details

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How to Cite
Sekine, T., & Takahashi, K. (2023). Development of online system checkable for Japanese writing tasks . Journal of E-Learning and Knowledge Society, 19(1), 13-18. https://doi.org/10.20368/1971-8829/1135687

References

  1. Ajay HB, Tillett PI, Page EB. (1973). Analysis of essays by computer (AEC-II) (No. 8-0102). Washington, DC: U.S. Department of Health, Education, and Welfare, Office of Education, National Center for Educational Research and Development.
  2. Dong F, Zhang Y, Yang J. (2017). Attention-based recurrent convolutional neural network for automatic essay scoring. In: Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017), pp. 153–162.
  3. Foltz PW, Laham D, Landauer TK. (1999). The Intelligent Essay Assessor: Applications to Educational Technology. Interactive Multimedia Electronic Journal of Computer-Enhanced Learning, 1, 2, http://imej.wfu.edu/articles/1999/2/04/index.asp
  4. Hasebe, Y., Lee, J. (2015). Introducing a Readability Evaluation System for Japanese Language Education. The 6th International Conference on Computer Assisted Systems For Teaching & Learning Japanese (CASTEL/J).
  5. Hirao, R., Arai, M., Shimanaka, H., Katsumata, S., Komachi, M. (2020). Automated Essay Scoring System for Nonnative Japanese Learners, the 12th Language Resources and Evaluation Conference, pp. 1250–1257.
  6. Iori, I. (2016). The Enterprise of Yasashii Nihongo : For a Sustainable Multicultural Society in Japan, Hitotsubashi review of arts and sciences, 10, pp. 4-19.
  7. Ishioka, T., Kameda, M. (2006). Automated Japanese Essay Scoring System based on Articles Written by Experts, the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, pp. 233–240.
  8. Ishioka, T., (2016). Computer-based Writing Tests, The journal of the Institute of Electronics, Information and Communication Engineers, 99(10), pp. 1005-1011. (in Japanese)
  9. Landauer, T.K., Foltz, P.W., Laham, D. (1998) An introduction to latent semantic analysis, Discourse Processes, 25, pp. 259-284.
  10. Lau, R.W.H., Yen, N.Y., Li, F., Wah, B. (2014). Recent development in multimedia e-learning technologies, World Wide Web, 17, pp. 189–198.
  11. Lee, J., Hasebe, Y. (2017). jWriter Learner Text Evaluator, URL: https://jreadability.net/jwriter/.
  12. Ouadoud, M., Rida, N., Chafiq, T. (2021). Overview of E-learning Platforms for Teaching and Learning, International Journal of Recent Contributions from Engineering, Science & IT, 9(1), pp. 50–70.
  13. Powers, D. E., Burstein, J. C., Chodorow, M., Fowles, M. E., & Kukich, K. (2002). Stumping e-rater: challenging the validity of automated essay scoring. Computers in Human Behavior, 18(2), pp. 103–134.
  14. Ramesh, D., Sanampudi, S.K. (2022). An automated essay scoring systems: a systematic literature review. Artificial Intelligence Review, 55, pp. 2495–2527.
  15. Shermis MD, Mzumara HR, Olson J, Harrington S. (2001). On-line grading of student essays: PEG goes on the World Wide Web. Assess Eval High Educ 26(3), pp. 247–259.
  16. Slavuj, V., Kovačić, B., Jugo, I. (2016). Adaptive Ε-learning system for language learning: Architecture overview, 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), pp. 951-955.
  17. Tanaka, M., Tsubone, Y., (2019). New Writing Feedback: A Collaborative Approach Utilizing Human and Machine Evaluation, CAJLE 2019 Proceedings, pp. 315-324. (in Japanese)
  18. Tsubakimoto, M., Nakamura, M., Kishi, M. (2007). A Fundamental Examination of the Report Assessment Method Focusing on Key sentences and Key words, Journal of Science Education in Japan, 31, pp. 210-219.
  19. Van Steendam, E., Tillema, M., Rijlaarsdam, G., Van den Bergh, H. (Eds.) (2012). Measuring Writing: Recent Insights into Theory, Methodology and Practices.