Rapid Artificial Diagnostic Test in Intelligent Teacher Assistant System (ITAS) to Identify Misconceptions on Kinematics

DOI

10.2991/978-2-38476-012-1_39How to use a DOI?

Keywords

Rapid artificial diagnostic test; Intelligent Teacher Assistant System; Misconceptions; Kinematics

Abstract

Errors in interpreting a concept can occur because students are still in the process of understanding. The experience gained through observation and reasoning has not been able to form complete knowledge, so students often experience errors in interpreting a concept. Therefore, errors in interpreting a concept that is not following the concept of science must be assessed as early as possible by the teacher. This research is a research development that produces a product using a four-level diagnostic test based on artificial intelligence. The purpose of this study was to see the development process and the diagnostic feasibility level of a four-level test using an Intelligent Teacher Assistant System (ITAS) based on the responsive website, the subject of developed Kinematics. This research was conducted at a senior high school in Tanjung Jabung Barat. Four validators of Physics Education lecturers carried out the feasibility test at Jambi University and one physics subject teacher at senior high school in Tanjung Jabung Barat. The result of the feasibility level of the media by media experts is 93.28% (category “very feasible”). In contrast, the test results or user responses obtained a value of 80.43% (category “very feasible”). Based on what was done, the development of a four-level test diagnostic using Matlab, Python Programming, Orange Data Mining, and a responsive website to identify high school student misconceptions on the subject of statistical fluids in total on the aspects of software engineering and visual communication can be categorized as”very feasible”, so that it can be used to support the learning process of students in class.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Sutrisno Sutrisno
AU  - Maison Maison
AU  - Jefri Marzal
AU  - Wawan Kurniawan
PY  - 2023
DA  - 2023/03/29
TI  - Rapid Artificial Diagnostic Test in Intelligent Teacher Assistant System (ITAS) to Identify Misconceptions on Kinematics
BT  - Proceedings of the Mathematics and Science Education International Seminar 2021 (MASEIS 2021)
PB  - Atlantis Press
SP  - 316
EP  - 324
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-012-1_39
DO  - 10.2991/978-2-38476-012-1_39
ID  - Sutrisno2023
ER  -