Purpose: This study proposed and examined the effectiveness of e-learning content design by considering two different subjects (mathematics and reading) and areas (metropolitan and rural). This study also investigated several variables, i.e., students' satisfaction, motivation, and experience, that influenced learning abilities. Moreover, we suggest ways of improving the effectiveness of e-learning for different kinds of students, subjects, and areas. Methodology: The participants were recruited from 263 randomly selected students in secondary-school grades 9-10 (15 years old). One hundred and thirty-eight students were from a public metropolitan school in Bangkok province, and 125 were from a public rural school in Suphanburi province. The main testing method was divided into two procedures. First, pilot testing was conducted to confirm the reliability, validity, and internal consistency of the program and the exam questions, followed by field testing methods, which researchers used to identify the effectiveness of content design. Data analysis involved a quantitative research approach using a paired "t"-test to find the difference in scores between the pre- and post-tests. Analysis of variance (ANOVA) was used to analyse and find the relationships between improvements in scores and variables. Findings: The results indicated that the selected patterns of content and design were effective in mathematics and reading subjects and in both rural and metropolitan areas. In addition, the academic achievement, accumulated (overall) grade point average (GPAX), significantly influenced improvements in reading subjects, and the intelligence indicator (IQ) had a significant effect on mathematic subjects in both areas. Furthermore, students' satisfaction had an effect on learning abilities in most student groups. Significance: This pattern of design content may be significant for both instructors and program designers. This study provided a way of designing effective e-learning content that integrated effective indicators to identify potential students and improve their abilities. This pattern can be integrated with active learning. This blended learning model might be the new solution to solving problems with low-performing students in rural areas.