Investigation Of Metacognitive Awareness In Learning Programming Course Using Multiple Criteria Decision Making Algorithm: TOPSIS

Abstract

Writing computer program is regarded as a difficult skill to master by both specialists and students. Metacognition has been identified as a fundamental figure in becoming an effective computer programming student. Metacognition is defined in instructive brain science as the observation and control of one's discernment exercises. To perceive the inter correlation analysis, 1145 engineering students used the metacognitive awareness Inventory (MAI), Brain Dominance, Multiple Intelligence, Kolb's learning style identification, and Big-five personality assessments. It is considered, in addition to descriptive statistics of metacognitive awareness, to understand how it corresponded with their exhibition in a Python programming course on a stratified sample of 125 students evaluated using SOLO taxonomy adopted for programming course. The outcome of correlation test revealed that of the declarative, procedural, and conditional knowledge subcomponents of Knowledge about cognition, there is a significant association with Declarative knowledge in the students' positive performance in python programming. The findings also revealed a positive relationship between learning python programming and planning, information management system, debugging strategies, and evaluation. The descriptive statistics for the metacognitive awareness inventory subcomponents are also discussed in this paper. This study consists of two major components namely metacognitive modeling, which suggests a self-questionnaire for incorporating metacognition into classroom sessions, activities and assessment, and also TOPSIS algorithm which provides best decision based on priorities.