Analysis of the conversational agent on mathematics through data science

Introduction: The conversational agent on mathematics is a technological tool that updates the educational practices because users can obtain the information visually and textually. Objective: The general aim of this mixed research is to analyze the conversational agent on mathematics through Data Science. Methods: This web application presents the basic concepts of financial mathematics, considering the user's questions in voice and text form. The participants are 19 educators who completed the master’s degree in teaching for Higher Education at the National Autonomous University of Mexico during the 2024 school year. Results: The results of the linear regression, a machine learning algorithm, indicate that the use of the conversational agent positively influences motivation and active role. Likewise, the decision tree algorithm established two models to predict the motivation and active role, considering the use of this application and user characteristics. The benefits of the conversational agent on mathematics are the interaction through voice and text, the resolution of doubts, personalized learning, and ease of use. Conclusion: In conclusion, teachers can incorporate the conversational agent into school activities because this tool offers the flexibility of time and space, encourages autonomy, and facilitates learning.