Implementation of Automatic Correction Algorithm Method in the Pseudolearn Application for Web-Based Python Programming Learning

Rapid advances in information and communication technology are reshaping society, requiring individuals to adapt to digitalization for relevance and efficiency. In education, this shift is evident as technology enhances the learning process and improves the quality of education globally. Autocorrect tools are increasingly relied upon in educational environments, especially in the teaching of programming languages, which has become an essential skill in the digital age. Among programming languages, Python stands out for its versatility and ease of use, aiding in problem solving and the development of critical thinking. Pseudocode, which serves as a bridge between algorithmic concepts and programming languages, simplifies learning and understanding for beginners and programmers. However, manually grading student answers poses a challenge for educators, leading to the integration of auto-correction features. Automation simplifies the evaluation process, improving efficiency and objectivity. Winnowing algorithm is an algorithm for auto-correction, chosen for its ability to quickly match student answers with key answers, implemented in the Pseudolearn application to provide auto-correction. This integration aims to support students in identifying coding errors and strengthen their understanding of fundamental Python algorithms. The method to process the data from this research is using One Way ANOVA. The result of the data processing was a significance of 0.046 and an increase in the average student score from 39.54 to 78.18 for the experimental group and 35 to 52.72 for the control group. Thus it can be concluded that the use of automatic correction has a positive impact compared to using the conventional way.