Over the years, learning has shifted from a conventional classroom environment to a digital space due to an increased interest in e-learning and swift innovations in information technology. This has brought the attention of many individuals and institutions to delve into building various approaches for adaptive e-learning technologies. Most existing e-learning systems are teacher-based, time-wasting and do not monitor learners’ progress levels. This paper presents a type-1 rule-based fuzzy logic model to implement an adaptive e-learning system by identifying students’ prior knowledge, learning style, and learning pace. The system was designed with Object-Oriented Analysis and Design Methodology and implemented using PHP, JavaScript, and MySQL technologies. A total of 31 first-year students of the University of Nigeria, Nsukka, participated in the evaluation of the software. The pre-test measured the students' prior knowledge, and the performance of each student was mapped. The system monitors students’ engagement levels and performance to improve learning outcomes. It also has an ‘Ask Teacher’ feature, which allows a student to ask the teacher questions outside the forum and the student’s feedback form. Each chapter has a pre-test to test the student’s existing knowledge, well-explained chapter content in text and audio-visual format, and a post-test to test their performance at the end of each chapter. After participating in the experiment, a questionnaire was used to collect the general students’ views on online-adaptive learning. The study implies that it assists students, teachers, and universities to have seamless learning and offers a quick feedback mechanism for the university’s decision-making.