Improved Learning Outcomes of Descriptive Statistics Through the Test Room and Data Processing Features in the Mobile Learning Model

Abstract

Descriptive statistics plays an important role in processing and presenting data. Therefore descriptive statistics is one of the topics that must be mastered by all students, including Informatics Engineering students. Unfortunately, the high mathematical content in this topic is often considered as a threat to students. It makes them get bored and distracted their attention to other things, mostly to their smartphones. This study conducted to develop a mobile-based descriptive statistical learning media that facilitate student work feedback. The feedback was given through the Test Room and Data Processing Features. The media was developed using the prototyping method. The analysis is done by conducting interviews, distributing questionnaires, and trying similar applications. Verification is done using the blackbox testing method, which provides input and sees the output. Validation is done by analyzing the results of examinations from two groups of students, the treated group and the control group. The validation results show that the learning outcome from the treated group was improved. The percentage of students who experienced an increase in exam scores from the treated group was 144% greater than the control group.