The Correlation Between Gamification Methods, Interactive Technologies and Student Motivation, Based on Data Analysis Online Courses on the Open Education Platform

In this study, I aim to analyze the motivation of students who have completed the “Python for Data Extraction and Processing” course on the “Open Education” platform based on a classification of the current impact of gamification methods and interactive technologies on intrinsic and extrinsic motivation in online courses that focus on programming and data analysis. To achieve my goal, I will use a mixed-methods approach that includes the following methods of analysis: archival research, secondary data collection, surveying, and case study research. As a result, I will be able to propose recommendations to improve “Python for Data Extraction and Processing” students’ motivation and will create a template for future case studies in the field. In the first chapter, I will cover the difference between interactive technologies, and the frameworks at their basis; I will review the results of my previous analysis of trends in programming courses. In the second chapter, I will discuss different approaches to designing online courses, theories that explain learner motivation, and how these factors affect the technologies I analyze in this study. The third chapter will culminate the first half of my research; I will create a holistic categorization of teaching technologies and intrinsic and extrinsic motivation, considering their underlying frameworks, course lengths, and user demographics. Using this categorization to find correlations between data points, I will then implement these results in my final fifth chapter, where I analyze the “Python for Data Extraction and Processing” course. I will present my survey results and provide recommendations to improve students’ motivation.