Analysis of Experimental Log Data on Pseudolearn in Pseudo-Code Algorithm Learning

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Vivin Ayu Lestari, Banni Satria Andoko, Moch Zawaruddin Abdullah, Deasy Sandhya Ikawati, Muhammad Afrizal Hamimudin

2024 Proceedings - IEIT 2024 - 2024 International Conference on Electrical and Information Technology Conference paper Cited by 1 Quartile

Abstract

One of the advantages of technological development is the ease of accessing information to create new learning innovations for students. PseudoLearn is one of the learning media innovations to help students understand the basic concepts of programming logic. Beginner students usually struggle when learning early programming learning concepts. PseudoLearn is a learning application developed to construct programming knowledge by solving problems presented in pseudo-code. This application is equipped with a data log that can find out the history of student activities when interacting with the application. There are 2 hypotheses of this research, H1: There is a relationship between the amount of time and the number of steps students use when learning programming logic using PseudoLearn, H2: There is a relationship between student performance and time spent learning programming logic using PseudoLearn. 61 students majoring in Information Technology, State Polytechnic of Malang were involved in the experiment. Pearson correlation analysis was used to prove the study's hypothesis. The results of the experiment are the same as the hypothesis, where in the pearson correlation test there is a positive correlation relationship between time and steps, as well as student performance and time. It states that students who take a long time to complete case studies, then perform many experimental steps. Students who have good performance spend a long time studying. This proves that smart students tend to spend a long time learning. © 2024 IEEE.

Affiliations

Politeknik Negeri Malang, Malang, Indonesia; State Polytechnic of Malang, Malang, Indonesia