E-Learning: Analysis of Student Teacher Errors in Statistics Problems
Abstract
Statistics is taught in schools, but students commonly make mistakes when faced with statistical problems. This study aimed to describe the errors made by student teacher candidates when solving statistical problems using e-learning media. A qualitative descriptive approach was used. Questionnaires and interviews were used to collect the data. 20 students were asked questions via e-learning media. Based on student errors, 4 students were selected for interviews. These interviews were conducted via WhatsApp. The APOS mental mechanism was used in the error analysis tool, which had five stages: interiorization, coordination, reversal, encapsulation, and deencapsulation. According to the findings, the three biggest mistakes were made during the de-encapsulation, reversal, and encapsulation stages. To overcome student errors, online computer-assisted learning using moving object animation is recommended.
Keywords: e-learning, student teacher candidate errors, statistics
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