The IUP Journal of Operations Management
Application of Quality Management Tools in Student Retention: A Case Study from International School, Duy Tan University

Article Details
Pub. Date :Feb, 2021
Product Name : The IUP Journal of Operations Management
Product Type : Article
Product Code : IJOM20221
Author Name : Huynh Linh Lan
Availability : YES
Subject/Domain : Management
Download Format : PDF Format
No. of Pages : 11



Student retention is not only holding students until graduation but also helping them succeed at university. Every year, a large percentage of Vietnamese students drop out of schools due to many reasons. Educators can create a clear strategy for retention if they have a good understanding of their students. That understanding is driven by the data available to them within their learning management system and analytics tools. Thus this study utilized the quality management tools combined with group discussion and direct interview of 300 students. The paper also suggests some administrative implications to build the process used in learner motivation and retention.


The knowledge and training a student receives at college will prepare for the real world and a student who is turned off from the educational system may not have opportunities to acquire wealth and happiness. Moreover, the negative college experience could make a person shy away from formal learning approach in the future (Astin et al., 2012). Some factors that affect student retention were discovered in many studies such as institutional program, student-faculty relationship, students' capacity, welcoming environment, student support services and learning resources (Berge and Huang, 2004; Styron, 2010; and O'Keeffe, 2013).

To manage the dropout rate, universities have developed many strategies. Ackerman and Schibrowsky (2007) suggested using the customer relationship marketing to implement retention programs. However, this approach meets some difficulties, while not everyone will be comfortable applying the concept from business in the field of education. Others suggest some tools in student retention such as data mining (Lin, 2012) and machine learning (Delen, 2010). Crosling et al. (2009) proposed the view