ABSTRACT
Use of digital payments has risen exponentially in the recent past especially due to the COVID-19 pandemic. This is because online payment methods offer many benefits in performing their day-to-day transactions and paying utility bills such as electricity bills, water bills, telephone bills and etc. Knowing when a consumer will perform a specific online transaction, or bill payment is beneficial t o a n o nline payment platform to plan marketing campaigns since targeted marketing has become very prevalent nowadays. However, predicting this is not an easy task since thousands of transactions are happening in each and every minute of an online payment platform. This paper presents the results of a study that investigated predicting the customer personalized, utility bill payment type wise next payment date of a financial c ompany i n S ri Lanka by using machine learning techniques. This is accomplished by analyzing not only online transaction history but also customer characteristics and a holiday calendar which is specific t o Sri Lanka. At the end of the study, it was identified t hat XGBoost Regressor is the most suitable machine learning algorithm, etc deal with this scenario which provided 91.02% accuracy. These predictions will be used for sending personalized reminders and discount offers to customers without sending general common notifications w hen t hey a re p lanning t o d o a n o nline payment. Such reminders and offers will be notified o n t he m obile devices of the customers and, ultimately both customers and the business owners will be benefited by this. © 2022 IEEE.
ABSTRACT
Teamwork is an important skill valued by corporate employers across the globe. As such, it is crucial for students to learn teamwork for the purpose of securing a job and performing well in corporate environments. In addition to certain technical skills, essential 21st-century skills include communication, collaboration, critical thinking, and creativity. A well-known learning theory that helps students learn these skills is cooperative learning. Cooperative learning posits that when students collaborate within teams to solve complex problems, their creativity and critical thinking skills are improved as a result. Implementing cooperative learning in the past several months has been challenging due to the COVID-19 pandemic. The sudden shift from face-to-face to online instruction, has left a void for newer pedagogical approaches to teach teamwork. In this full paper, we investigate the impact of cooperative learning during the Spring 2020 semester by studying team retrospectives written by students enrolled in a system analysis and design course. The pedagogical foundation for the system analysis and design course was cooperative learning. The course required students to work in teams to develop a software prototype. The project was divided into four milestones and each team was required to submit a team retrospective detailing overall planning, task allocation, group processes, and strategies for improvement. The first two milestones were completed during face-to-face instruction, while teams met online for the last two milestones due to the shift to online instruction. To investigate team effectiveness, a rubric based on the Goals, Roles, Processes and Interpersonal relations (GRPI) model of team effectiveness was created and team retrospectives were scored using that rubric. We used a mixed-method approach to explore the following research questions: 1) What was the impact on team effectiveness when instruction changed from face-to-face to online due to the COVID-19 pandemic? 2)What strategies were adopted by teams to navigate the sudden change in instruction? To address the first research question, we performed inferential statistics to compare the impact of team effectiveness between face-to-face and online instruction. To address the second research question, we conducted a thematic analysis to understand the qualitative differences of team effectiveness for face-to-face and online instruction. Our results demonstrate a significant increase in teamwork effectiveness for online instruction. In addition, our thematic analysis shows particular strategies adopted by teams that led to improved team effectiveness in the online instruction environment. © American Society for Engineering Education, 2021