Propagating AI knowledge across university disciplines - the design of a multidisciplinary AI study module

Samuli Laato, Henna Vilppu, Juho Heimonen, Antti Hakkala, Jari Björne, Ali Farooq, Tapio Salakoski, Antti Airola

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

11 Citations (Scopus)

Abstract

The on-going AI revolution has disrupted several industry sectors and will keep having an unprecedented impact on all areas of society. This is predicted to force a major proportion of the workforce to re-educate itself during the next few decades. Consequently, this has led to a growing demand for multidisciplinary AI education also for students outside computer science. Therefore, a 25 credit (ECTS) cross-disciplinary study module on AI, targeting students in all faculties, was designed. We present findings from the design and implementation of the study module as well as students' initial perceptions towards AI at the beginning of the study module. Enrollment for the first implementation of the study module began in autumn 2019. The student distribution (N=144) between faculties was the following: natural sciences (n=37), social sciences (n=23), law (n=17), education (n=17), economics (n=16), medicine (n=10), humanities (n=10) and open university (n=14). Based on a survey distributed to students (N=34), the primary reason for enrolling to study AI was interest towards the subject, followed by the need of AI skills at work and relevance of AI in society.
Original languageEnglish
Title of host publication2020 IEEE Frontiers in Education Conference (FIE)
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages1-9
Number of pages9
ISBN (Electronic)9781728189611
DOIs
Publication statusPublished - 4 Dec 2020

Keywords

  • AI
  • study module
  • cross-disciplinary
  • multi-disciplinary
  • education

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