Data science education in iSchools across the Asian-Pacific region

Tang, Rong; Jiang, Jie; Maurici-Pollock, Danielle

Permalink

https://hdl.handle.net/2142/123060 Copy

Description

Title

Data science education in iSchools across the Asian-Pacific region

Author(s)

• Tang, Rong
• Jiang, Jie
• Maurici-Pollock, Danielle

Issue Date

2023-09

Keyword(s)

• Asian-pacific Region Ischools
• Big Data
• Course Offering
• Course Topics
• Curriculum
• Data Mining
• Data Science Education
• Data Visualization
• Education Programs/schools

Abstract

In this poster, we report preliminary findings of our investigation of data science education in iSchools around the world. For our analysis, we randomly sampled 20 iSchools within the regions of Asian-Pacific, European, and North American. We report here the findings from the 20 iSchools in the Asian Pacific region: these iSchools come from 9 different countries/areas, including China (n=9), Korea (n=3), New Zealand (n=2), Australia (n=1), Malaysia (n=1), Thailand (n=1), Indonesia (n=1), Philippines (n=1), and Taiwan, China (n=1). Of 20 iSchools, 15 had DS course information, with an average of 8.13 per program, range 1-21, and mode 4. The majority of the programs offered DS courses at both the undergraduate and graduate levels (n=11, 73.33%), three (20.00%) offered at the graduate level only, one (6.67%) only offered at the undergraduate level. In terms of the course coverage, there were 30 unique topics, with 15 topics included in multiple iSchools’ curriculum, and the remaining 15 were uniquely offered by one iSchool. The most common course topics were Data Structure or Data Organization (n=10, 66.67%), Data Mining & Data Warehouse (n=9, 60.00%), Data Visualization (n=6, 40.00%), Introduction to Data Science (n=6, 40.00%), Machine Learning (n=6, 40.00%), and NLP Text Analysis/Text Mining (n=5, 33.33%). Other repeated topics include Research Data Management, Big Data, AI, Programming, Data governance, Data Analytics, and more. Examples for unique course topics were blockchain, Data Asset Management, Data Security, UX, and more. Further coding and analysis for all three regions are in progress.

Series/Report Name or Number

Proceedings of the ALISE Annual Conference, 2023

Type of Resource

text

Language

eng

Handle URL

https://hdl.handle.net/2142/123060

DOI

https://doi.org/10.21900/j.alise.2023.1277

Copyright and License Information

• Copyright 2023 Rong Tang, Jie Jiang, Danielle Maurici-Pollock
• This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (https://creativecommons.org/licenses/by-sa/4.0/).

Owning Collections