Design of Interactive Whiteboard to Support E-Learning

Prasetya, Didik Dwi; Ashar, Muhammad

doi:10.2991/icovet-17.2017.26

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2024

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“…With the advent of information and communication technology (ICT), educational institutions have been encouraged to use artificial intelligence to improve learning efficiency and flexibility, resulting in better academic outcomes. One of the implementations is the existence of Computer-based Exams [3]. In vocational secondary education, computer-based tests (CBT) are used to evaluate exams.…”

Section: Introductionmentioning

confidence: 99%

Educational Data Mining: Multiple Choice Question Classification in Vocational School

Sucipto,

Dwi Prasetya,

Widiyaningtyas

2024

matrik

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Data mining on student learning outcomes in the education sector can overcome this problem. This research aimed to provide a solution for selecting quality multiple choice questions (MCQ) using the results of students’ mid-semester exams in vocational high schools using a Data Mining approach. The research method used was the Cross-Industry Standard Process for Machine Learning (CRISP-ML) model. Steps to assess the accuracy of analyzing the difficulty level of questions based on student profile data and midterm test results. The data used in this research were the findings of basic computer tests on mid-term exams in mathematics disciplines at vocational high schools. This research used several classification algorithms, including SVM, Naive Bayes, Random Forest, Decision Three, Linear Regression, and KNN. The results of evaluating the classification

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Section: Introductionmentioning

confidence: 99%