CHI TIẾT NGHIÊN CỨU …
Tiêu đề
Building a New Data Science Program Based on an Existing Computer Science Program
Tác giả
Oudshoorn M.J.; Titus K.J.; Suchan W.K.
Năm xuất bản
2020
Source title
Proceedings - Frontiers in Education Conference, FIE
Số trích dẫn
1
DOI
10.1109/FIE44824.2020.9273934
Liên kết
Tóm tắt
Data Science is an emerging program of study which, by its very nature, is interdisciplinary. This paper explores the challenge of introducing a data science program, given an established computer science program, within a liberal arts institution which has a large general education core. In addition to the challenge of creating a new program, there are several other major challenges surrounding the fact that the discipline of data science continues to evolve, and accreditation criteria are currently being developed. © 2020 IEEE.
Từ khóa
computer science; curriculum development; data science
Tài liệu tham khảo
Danyluk A., Leidig P., Buck S., Cassel L., McGettrick A., Qian W., Servin C., Wang H., Computing Competencies for Undergraduate Data Science Curricula, (2019); Danyluk A., Leidig P., Cassel L., An update on the ACM data science taskforce, Proceedings of the 51st ACM Technical Symposium on Computer Science Education, Ser. SIGCSE'20, pp. 635-636, (2020); De Veaux R.D., Agarwal M., Averett M., Baumer B.S., Bray A., Bressoud T.C., Bryant L., Cheng L.Z., Francis A., Gould R., Et al., Curriculum guidelines for undergraduate programs in data science, Annual Review of Statistics and Its Application, 4, 1, pp. 15-30, (2017); Demchenko Y., Belloum A., Los W., Wiktorski T., Manieri A., Brocks H., Becker J., Heutelbeck D., Hemmje M.L., Brewer S., Edison data science framework: A foundation for building data science profession for research and industry, 17th IEEE International Conference on Cloud Computing Technology and Science. IEEE, November, pp. 588-593, (2016); Karbasian H., Johri A., Insights for curriculum development: Identifying emerging data science topics through analysis of Q&A communities, Proceedings of the 51st ACM Technical Symposium on Computer Science Education, Ser. SIGCSE'20, pp. 192-198, (2020); (2018); Parrish A., Jones L., Leidig P., Raj R., Sculpting accreditation criteria for data science-a working session, Proceedings of the 51st ACM Technical Symposium on Computer Science Education, (2020); Criteria for Accrediting Computing Programs. Effective for Review during the 2019-20 Accreditation Cycle, (2018); Computer science curricula 2013, ACM Press and IEEE Computer Society Press; Clear A., Parrish A.S., Impagliazzo J., Zhang M., Computing curricula 2020: Introduction and community engagement, Proceedings of the 50th ACM Technical Symposium on Computer Science Education, Ser. SIGCSE '19, pp. 653-654, (2019); Impagliazzo J., Pears A.N., The CC2020 project-computing curricula guidelines for the 2020s, 2018 IEEE Global Engineering Education Conference (EDUCON), pp. 2021-2024, (2018); Adams J.C., Creating a balanced data science program, Proceedings of the 51st ACM Technical Symposium on Computer Science Education, Ser. SIGCSE'20, pp. 185-191, (2020); Data Science Academic Resource Kit, (2020); Deb D., Smith R.M., Fuad M., Infusing data science across disciplines, Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education, Ser. ITiCSE '19, (2019); Deb D., Jones E., University-wide adoption of data science, Proceedings of the 51st ACM Technical Symposium on Computer Science Education, Ser. SIGCSE'20; Hassan I.B., Liu J., Data science academic programs in the U.S, J. Comput. Sci. Coll, 34, 7, pp. 56-63, (2019); Ramamurthy B., A practical and sustainable model for learning and teaching data science, Proceedings of the 47th ACM Technical Symposium on Computing Science Education, Ser. SIGCSE '16, pp. 169-174, (2016); Rosenthal S., Chung T.R., A data science major: Building skills and confidence, Proceedings of the 51st ACM Technical Symposium on Computer Science Education, Ser. SIGCSE'20, pp. 178-184, (2020); Van Dusen E., Suen A., Carson C., Innovation in undergraduate data science education, Proceedings of the 51st ACM Technical Symposium on Computer Science Education, Ser. SIGCSE'20; Havill J., Embracing the liberal arts in an interdisciplinary data analytics program, Proceedings of the 50th ACM Technical Symposium on Computer Science Education, Ser. SIGCSE '19, pp. 9-14, (2019); Clear A., Parrish A., Frezza S., Impagliazzo J., Pears A., Takada A., Topi H., Van der Veer G., Cuadros-Vargas E., Vichare A., Waguespack L., Wang P., Zhang M., Alrumaih H., Bogoyavlenskaya O., Decker A., Durant E., Exter M., Gordon S., Hayashiguchi E., Le Blanc R., Leidig P., Lunt B., McMillin B., McVeety T., Marshall L., Mead N., Moro M., Simon B.T., Tymann P., Viola B., Zwebrn S., Computing Curricula, (2020); Gautam A., Bortz W., Tatar D., Abstraction through multiple representations in an integrated computational thinking environment, Proceedings of the 51st ACM Technical Symposium on Computer Science Education, Ser. SIGCSE'20, pp. 393-399, (2020); Mir D.J., Mishra S., Ruvolo P., Pollock L., Engen S., How do faculty partner while teaching interdisciplinary csx courses: Models and experiences, J. Comput. Sci. Coll, 32, 6, pp. 24-33, (2017); Sloan R.H., Barr V., Bort H., Guzdial M., Libeskind-Hadas R., Warner R., CS X meets CS 1: Strongly themed intro courses, Proceedings of the 51st ACM Technical Symposium on Computer Science Education, Ser. SIGCSE'20, pp. 960-961, (2020); Sloan R.H., Taylor C., Warner R., Initial experiences with a CS law introduction to computer science (cs 1), Proceedings of the 2017 ACM Conference on Innovation and Technology in Computer Science Education, Ser. ITiCSE '17, pp. 40-45, (2017); Berger-Wolf T., Igic B., Taylor C., Sloan R., Poretsky R., A biology-themed introductory CS course at a large, diverse public university, Proceedings of the 49th ACM Technical Symposium on Computer Science Education, Ser. SIGCSE '18, pp. 233-238, (2018); Carr V., Jones M., Wei B., Interdisciplinary computing: Applied computing for behavioral and social sciences, Proceedings of the 51st ACM Technical Symposium on Computer Science Education, Ser. SIGCSE'20, pp. 400-406, (2020)
Nơi xuất bản
Institute of Electrical and Electronics Engineers Inc.
Hình thức xuất bản
Conference paper
Open Access
Nguồn
Scopus