Software curriculum transformation at the University Level

Michael Dorin, Mario Chong, Juan Machuca

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Many software-related degrees exist, and a diversity of programs makes it difficult for candidates to choose where they wish to study. Selecting the wrong program costs students time, money, and considerable effort. Though several institutions have created curriculum guidelines for data science related programs, an overall consensus on program content does not exist at either the undergraduate or graduate levels. This paper examines the most common course requirements, such as data mining, machine learning, mathematics, software engineering, data analysis, and data visualization. We then compare the requirement analysis against the specifics of data science related programs offered at the Universidad de Lima, the Universidad Pacifico, and the University of St. Thomas. The results show that all three universities have active programs worth consideration and give students a model of what to look for when selecting their programs.
Original languageEnglish
Title of host publicationEDUNINE 2020 - 4th IEEE World Engineering Education Conference
Subtitle of host publicationThe Challenges of Education in Engineering, Computing and Technology without Exclusions: Innovation in the Era of the Industrial Revolution 4.0, Proceedings
EditorsClaudia da Rocha Brito, Melany M. Ciampi
Place of PublicationNueva York
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)978-1-7281-6638-4
DOIs
StatePublished - 1 Mar 2020
EventEDUNINE 2020 - 4th IEEE World Engineering Education Conference: The Challenges of Education in Engineering, Computing and Technology without Exclusions: Innovation in the Era of the Industrial Revolution 4.0, Proceedings -
Duration: 1 Mar 2020 → …

Conference

ConferenceEDUNINE 2020 - 4th IEEE World Engineering Education Conference: The Challenges of Education in Engineering, Computing and Technology without Exclusions: Innovation in the Era of the Industrial Revolution 4.0, Proceedings
Period1/03/20 → …

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Keywords

  • Data science
  • adult education
  • career changes
  • information engineering

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