INVESTIGATE THE UTILITY OF A MISCONCEPTION DETECTION APPLICATION AS AN EARLY DETECTION TOOL BASED ON FIVE-TIER DIAGNOSTICS TEST

Research into misconceptions is crucial in the field of education, particularly in subjects like chemistry, which are complex and prone to misunderstandings. Misconceptions—ideas held by individuals that deviate from established scientific understanding—can arise from various sources, including students, teachers, textbooks, and instructional methods. These inaccuracies can hinder effective learning and need to be addressed to enhance educational outcomes. Identifying and remediating misconceptions is challenging, requiring specialized tools and methods. Therefore, research into misconceptions aims to uncover and correct these misunderstandings to improve teaching strategies and student comprehension. Therefore, the research in this article is concerned with the practicality of the application of chemical representation diagnostic tests to identify chemical misconceptions, particularly on chemical equilibrium and chemical bonding materials. This research was carried out at Surabaya State University participated by 24 students from the Chemistry Education Study Program. In this research, the practicality of the chemical misconception diagnostic test application was obtained at 98.6% which indicates that the application is practical to use. In addition, obtained data on student diagnostic results, namely: 88.3% did not understand the concept; 10.4% had misconceptions; and 1.3% understood the concept on the topic of chemical bonding. Keywords: misconceptions, five-tier diagnostic test, chemical bonding, online application

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Publication Details

Journal
JCER (Journal of Chemistry Education Research)
Published
2025-06-29
DOI
https://doi.org/10.26740/jcer.v9n1.p45-51
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
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article

INVESTIGATE THE UTILITY OF A MISCONCEPTION DETECTION APPLICATION AS AN EARLY DETECTION TOOL BASED ON FIVE-TIER DIAGNOSTICS TEST

Muchlis Muchlis, Bertha Yonata, Findiyani Ernawati Asih, Dian Novita et al.
JCER (Journal of Chemistry Education Research)
Online Learning and Analytics
article

INVESTIGATE THE UTILITY OF A MISCONCEPTION DETECTION APPLICATION AS AN EARLY DETECTION TOOL BASED ON FIVE-TIER DIAGNOSTICS TEST

Muchlis Muchlis, Bertha Yonata, Findiyani Ernawati Asih, Dian Novita, Rudianto Artiono
article en

Abstract

Research into misconceptions is crucial in the field of education, particularly in subjects like chemistry, which are complex and prone to misunderstandings. Misconceptions—ideas held by individuals that deviate from established scientific understanding—can arise from various sources, including students, teachers, textbooks, and instructional methods. These inaccuracies can hinder effective learning and need to be addressed to enhance educational outcomes. Identifying and remediating misconceptions is challenging, requiring specialized tools and methods. Therefore, research into misconceptions aims to uncover and correct these misunderstandings to improve teaching strategies and student comprehension. Therefore, the research in this article is concerned with the practicality of the application of chemical representation diagnostic tests to identify chemical misconceptions, particularly on chemical equilibrium and chemical bonding materials. This research was carried out at Surabaya State University participated by 24 students from the Chemistry Education Study Program. In this research, the practicality of the chemical misconception diagnostic test application was obtained at 98.6% which indicates that the application is practical to use. In addition, obtained data on student diagnostic results, namely: 88.3% did not understand the concept; 10.4% had misconceptions; and 1.3% understood the concept on the topic of chemical bonding. Keywords: misconceptions, five-tier diagnostic test, chemical bonding, online application

JCER (Journal of Chemistry Education Research)Vol. 9(1)
Universitas Negeri Surabaya (ID)
Openalex Percentile: Top 84%
Online Learning and Analytics
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