TEACHING ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN MARKETING. Issue 2 (3rd April 2021)
- Record Type:
- Journal Article
- Title:
- TEACHING ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN MARKETING. Issue 2 (3rd April 2021)
- Main Title:
- TEACHING ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN MARKETING
- Authors:
- Thontirawong, Pipat
Chinchanachokchai, Sydney - Abstract:
- ABSTRACT: In the age of big data and analytics, it is important that students learn about artificial intelligence (AI) and machine learning (ML). Machine learning is a discipline that focuses on building a computer system that can improve itself using experience. ML models can be used to detect patterns from data and recommend strategic marketing actions. This paper shows how marketing educators can introduce AI and ML concepts in their marketing classes and incorporate a cloud-based platform (AzureML Studio) by teaching students to create ML models for customer churn prediction. The results showed that the assignment improved student's learning. The students also reported other positive outcomes as reflected in the perceived career preparation, traditional learning goals, use of time, and overall satisfaction.
- Is Part Of:
- Marketing education review. Volume 31:Issue 2(2021)
- Journal:
- Marketing education review
- Issue:
- Volume 31:Issue 2(2021)
- Issue Display:
- Volume 31, Issue 2 (2021)
- Year:
- 2021
- Volume:
- 31
- Issue:
- 2
- Issue Sort Value:
- 2021-0031-0002-0000
- Page Start:
- 58
- Page End:
- 63
- Publication Date:
- 2021-04-03
- Subjects:
- Artificial intelligence -- machine learning -- teaching innovation -- data analytics -- big data -- customer churn
Marketing -- Study and teaching -- United States -- Periodicals
658.8007 - Journal URLs:
- http://www.tandfonline.com/loi/mmer20#.Vvpz5VL2aic ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/10528008.2021.1871849 ↗
- Languages:
- English
- ISSNs:
- 1052-8008
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5381.641970
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 19626.xml