@Article{RJMT-11-2,
author = {Youngju, Nielsen, L. and Sang-Gu, Lee and Kyoung, Ko, Ho and Lee, Jae, Hwa and Youngju, Nielsen, L. and Kyoung, Ko, Ho},
title = {Case Study of an Online Course on Introductory Mathematics for Artificial Intelligence},
journal = {Research Journal of Mathematics & Technology},
year = {2022},
volume = {11},
number = {2},
pages = {92--108},
abstract = {<p style="text-align: justify;">Artificial Intelligence (AI) is one of the most crucial factor affecting future career choice of students.
Accordingly, we offered students a semester-long Introductory Mathematics for Artificial Intelligence
course. The course was developed to provide undergraduate students with various majors to navigate
their career opportunities in AI-related jobs. This paper presents the newly published textbook and an
online mathematics laboratory that integrated effective technology for this introductory course. In
addition, we introduce a process-driven evaluation method based on the Problem/Project-Based
Learning (PBL) report that worked well for this course. We also share trails of communications with
our students and added the results of our students&#39; performance analysis using principal component
analyses (PCA) with the data generated from the class.</p>},
issn = {},
doi = {https://doi.org/2022-RJMT-21149},
url = {https://global-sci.com/article/90796/case-study-of-an-online-course-on-introductory-mathematics-for-artificial-intelligence}
}