In the realm of Science, Technology, Engineering, and Mathematic (STEM) education, computer programming stands as a vital discipline, amalgamating cross-disciplinary knowledge and fostering the capacity to solve real-world problems via fundamental concepts and logical methodologies inherent to computer science. Recognizing the important of computer programming, numerous countries have mandated it as a compulsory course to augment the competitiveness of K-12 learners. Nevertheless, the inherent complexity of computer programming for K-12 learners often goes unacknowledged. Constraints imposed by the course format, coupled with a low instructor-learner ratio, frequently inhibit learners' ability to resolve course-related issues promptly, thereby creating difficulties in the affective domain. While precision education tools do exist to ascertain learners' needs, they are largely research-oriented, thereby constraining their suitability for deployment in pragmatic educational settings. Addressing this issue, our study introduces the precision education-based timely intervention system (PETIS), an innovative tool conceived to enhance both programming skills and affective learning in K-12 learners. Our research investigates the influence of PETIS on learners' performance and evaluate its efficacy in facilitating computer programming education in K-12 environments.Quantitative results demonstrate that the application of the precision education-based timely intervention system (PETIS) proposed by this research significantly improves programming skills and affective-domain learning objectives for K-12 learners. Similarly, qualitative results indicate that PETIS is beneficial for both teaching and learning in K-12 computer programming courses.These results not only confirm that timely intervention and feedback improve K-12 learners' programming skills and affective-domain learning objectives in computer programming courses, but also yield implications as to the feasibility of applying precision education in real-world STEM scenarios.