This study focused on the development of the word level classification vocabulary learning (WCVL) system and the measurement of its effectiveness in terms of the potential of the system and learners' improvement in learning English material through the WCVL system. There are many ways to improve reading comprehension for those learning English as a foreign language. Learning vocabulary is one way of improving reading comprehension. The more vocabulary learners apprehend, the more deeply they understand English texts. It is suggested that learners improve their reading comprehension if they understand unknown words before reading a text. The WCVL system was designed based on the constructivism education theory and cognitive theory of multimedia learning. It was developed using the waterfall software development methodology. The NLP-compromise JavaScript library was used for morphological analysis to extract words in an English text. The extracted vocabulary was classified into 12 difficulty levels based on the SLV12000 vocabulary database. The system displays only the words whose levels are higher than the students' estimated vocabulary level. It also adds Japanese and Thai meanings. The WCVL system provides six types of exercises, including spelling, dictation, multiple choices, true/false, matching, and flashcards, for students to learn unknown words and collect learned vocabulary in the user's database. To make the system available on any device, responsive web design was employed, which adapts to the user's device system environment depending on the screen size and type of operating system. This study investigated a new approach to learning unknown words through various vocabulary practices using the WCVL system. In addition, questionnaires were used to evaluate the effectiveness of the proposed system by collecting responses from Thai and Japanese students.