Combining Building Block Process With Computational Thinking Improves Learning Outcomes of Python Programming With Peer Assessment

Abstract

The capability of computer programming language logic is one of the basics of technical education. How to improve students “interest in program logic design and help overcome students” fears of coding has become vital for educators. Cultivating practical talents with information technology application and basic programming development will become one of the important topics in the department of information related science. The objective of this research is to improve the ability of learning basic programming courses by using Zuvio interactive software. Zuvio employs the mathematical logic of computational thinking to analyze problems and enhance learners’ interest in learning programming skills through a graphical interface tool with building blocks. It uses innovative interactive teaching to use peer and self-assessment to study the content of the course. Zuvio improves the design ability of different groups of class learning Python programming. In line with the innovative teaching policy of the schools and the current stage of the learner’s learning model, learning effectiveness can be achieved. The research results were analyzed by midterm and final experimental group scores, and the progress of the experimental group’s scores was examined through descriptive statistics. The average and standard deviation of the assessment were used to analyze the progress of the experimental group students in the programming course. In the classroom, assessment criteria were set up as the basis for peer assessment scoring. After the midterm and final exams, the teacher assessment and peer assessment scores were analyzed for cognitive differences, and possible learning differences were analyzed. The students’ professional ability was examined to see if it met the professional standards required by the course, and whether innovative teaching methods could improve the learning outcomes of learners with different professional backgrounds in Python programming.