최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기Journal of the Korean Society of Mathematical Education. Series A. The Mathematical Education, v.62 no.3, 2023년, pp.435 - 455
오세준 (이화여자대학교사범대학부속이화.금란고등학교)
This study primarily focused on the development of an Explainable Artificial Intelligence (XAI) model to discern and analyze papers with significant impact in the field of mathematics education. To achieve this, meta-information from 29 domestic and international mathematics education journals was u...
Adadi, A., & Berrada, M. (2018). Peeking inside the black-box: a survey on explainable artificial intelligence (XAI). IEEE access, 6, 52138-52160.?https://doi.org/10.1109/access.2018.2870052
Alonso, J. M. (2020). Teaching explainable artificial intelligence to high school students. International Journal of Computational Intelligence?Systems, 13(1), 974-987. https://doi.org/10.2991/ijcis.d.200715.003
Andrade-Molina, M., Montecino, A., & Aguilar, M. S. (2020). Beyond quality metrics: defying journal rankings as the philosopher's stone of?mathematics education research. Educational Studies in Mathematics, 103(3), 359-374. https://doi.org/10.1007/s10649-020-09932-9
Arik, S. O., & Pfister, T. (2021, May). Tabnet: Attentive interpretable tabular learning. In Proceedings of the AAAI conference on artificial?intelligence, 35(8), 6679-6687. https://doi.org/10.3390/rs14030716
Arrieta, A. B., Diaz-Rodriguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., ... & Herrera, F. (2020). Explainable Artificial Intelligence?(XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI. Information Fusion, 58, 82-115. https://doi.org/10.1016/j.inffus.2019.12.012
Bollen, J., Rodriquez, M. A., & Van de Sompel, H. (2006). Journal status. Scientometrics, 69(3), 669-687. https://doi.org/10.1007/s11192-006-0176-z
Brin, S., & Page, L. (1998). The anatomy of a large-scale hypertextual web search engine. Computer Networks and ISDN Systems, 30(1-7), 107-117. https://doi.org/10.1016/s0169-7552(98)00110-x
Chung, K. (2022). The effects of explainable artificial intelligence education program based on AI literacy. Journal of The Korean Association of?Artificial Intelligence Education, 3(1), 1-12. https://doi.org/10.52618/aied.2022.3.1.1
DARPA. (2016). Broad Agency Announcement, Explainable Artificial Intelligence (XAI). DARPA-BAA-16-53, 7-8.
Funk, R. J., & Owen-Smith, J. (2017). A dynamic network measure of technological change. Management Science, 63(3), 791-817. https://doi.org/10.1287/mnsc.2015.2366
Garfield, E. (2009). From the science of science to Scientometrics visualizing the history of science with HistCite software. Journal of Informetrics,?3(3), 173-179. https://doi.org/10.1016/j.joi.2009.03.009
Gonzalez-Alcaide, G., Valderrama-Zurian, J. C., & Aleixandre-Benavent, R. (2012). The impact factor in non-English-speaking countries.?Scientometrics, 92(2), 297-311. https://doi.org/10.1007/s11192-012-0692-y
Haensly, P. J., Hodges, P. E., & Davenport, S. A. (2008). Acceptance rates and journal quality: An analysis of journals in economics and finance.?Journal of Business & Finance Librarianship, 14(1), 2-31. https://doi.org/10.1080/08963560802176330
Hamilton, W. L., Ying, R., & Leskovec, J. (2017). Representation learning on graphs: Methods and applications. arXiv preprint arXiv:1709.05584.
Inhaber, H., & Przednowek, K. (1976). Quality of research and the Nobel prizes. Social Studies of Science, 6(1), 33-50. https://doi.org/10.1142/9789814299381_0002
Lundberg, S. M., & Lee, S. I. (2017). A unified approach to interpreting model predictions. Advances in Neural Information Processing Systems, 30.
Mariani, M. S., Medo, M., & Zhang, Y. C. (2016). Identification of milestone papers through time-balanced network centrality. Journal of?Informetrics, 10(4), 1207-1223. https://doi.org/10.1016/j.joi.2016.10.005
Molnar, C. (2020). Interpretable machine learning, Lulu. com.
Nivens, R. A., & Otten, S. (2017). Assessing journal quality in mathematics education. Journal for Research in Mathematics Education, 48(4), 348-368. https://doi.org/10.5951/jresematheduc.48.4.0348
Park, H. Y., Son, B. E., & Ko, H. K. (2022). Study on the mathematics teaching and learning artificial intelligence platform analysis. Journal of?the Korean Society of Mathematics Education Series E: Communication of Mathematics Education, 36(1), 1-21. https://doi.org/10.7468/jksmee.2022.36.1.1
Price, D. (1963). Little science, big science... and beyond (Vol. 480). Columbia University Press.
Sarigol, E., Pfitzner, R., Scholtes, I., Garas, A., & Schweitzer, F. (2014). Predicting scientific success based on coauthorship networks. EPJ Data?Science, 3, 1-16. https://doi.org/10.1140/epjds/s13688-014-0009-x
Stolerman, I. P., & Stenius, K. (2008). The language barrier and institutional provincialism in science Drug and Alcohol Dependence, 92(1-3),?1-2. https://doi.org/10.1016/j.drugalcdep.2007.07.010
Weis, J. W., & Jacobson, J. M. (2021). Learning on knowledge graph dynamics provides an early warning of impactful research. Nature?Biotechnology, 39(10), 1300-1307. https://doi.org/10.1038/s41587-021-00907-6
Williams, S. R., & Leatham, K. R. (2017). Journal quality in mathematics education. Journal for Research in Mathematics Education, 48(4), 369-396.
Zhou, Y., Li, Q., Yang, X., & Cheng, H. (2021). Predicting the popularity of scientific publications by an age-based diffusion model. Journal of?Informetrics, 15(4), 101177. https://doi.org/10.1016/j.joi.2021.101177
Zhu, X., Turney, P., Lemire, D., & Vellino, A. (2015). Measuring academic influence: Not all citations are equal. Journal of the Association for?Information Science and Technology, 66(2), 408-427. https://doi.org/10.1002/asi.23179
*원문 PDF 파일 및 링크정보가 존재하지 않을 경우 KISTI DDS 시스템에서 제공하는 원문복사서비스를 사용할 수 있습니다.
Free Access. 출판사/학술단체 등이 허락한 무료 공개 사이트를 통해 자유로운 이용이 가능한 논문
※ AI-Helper는 부적절한 답변을 할 수 있습니다.