A sequential exploratory analysis of ai chatbots in supporting the web development comprehension skills of btvted-cp students/ Laurence De Guzman, Gracelle Joyce R. Fabre, John Emmanuel A. Francisco, and Roberto M. Santos.--

Bachelor's thesis

College Of Industrial Education.--
Bachelor of technical vocational teacher education major in computer programming: Technological University of the Philippines,
2025.

Includes bibliographic references and index.

In response to the rising demand for web development expertise,
educational institutions are seeking innovative strategies to equip students with
the skills required in the tech industry. This study addresses this need by
focusing on Bachelor of Technical and Vocational Teacher Education Major in
Computer Programming (BTVTED-CP) students at the Technological University
of the Philippines – Manila.
The primary aim is to assess how AI chatbots can aid students with
diverse programming backgrounds in overcoming comprehension challenges in
web development through real-time feedback and interactive guidance. The
study adopts a DBR method approach, starting with qualitative interviews to
gather initial insights, followed by iterative testing to improve the researchers’
product and synthesize the evaluation of the chatbot’s impact on learning
outcomes. A web-based coding support tool was developed by the researchers
and evaluated for usability among both novice and experienced learners.
The findings revealed that 82% of students reported improved
comprehension of web development concepts after using the AI chatbot, with a
25% average increase. Qualitative analysis highlighted that the chatbot was
particularly effective in simplifying complex topics and enhancing learner
engagement. The usability evaluation showed an average rating of 4.6 out of 5,
indicating high satisfaction with the tool’s design and functionality.