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All Journal EduChemia: Jurnal Kimia dan Pendidikan
Shidiq, Ari Syahidul
Sebelas Maret University
Chemical Engineering, Chemistry & Bioengineering Chemistry Education Materials Science & Nanotechnology

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AI-Powered Automated Assessment: Aiken Index Analysis of Content Validity Scientific Literacy Asesment Putri, Bela Anisa; Yamtinah, Sri; Shidiq, Ari Syahidul; Widarti, Hayuni Retno; Wiyarsi, Antuni
EduChemia: Jurnal Kimia dan Pendidikan Vol 10, No 1 (2025)
Publisher : Department of Chemistr Education Faculty of Teacher Training and Education Universitas Su

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30870/educhemia.v10i1.30640

Abstract

This study aims to analyze the content validity of the Scientific Literacy Asesment (SLA) instrument, which integrates ethnochemistry based on artificial intelligence through expert agreement based on the Aiken index so that the instrument can measure what should be measured. The research method used is a qualitative descriptive method based on the results of content validity calculated through the Aiken formula. Content validity data were obtained from 10 experts, namely, chemistry education lecturers from UNS, UNY, and UM and high school chemistry teachers in Surakarta, through focus group discussions (FGDs). Content validity is assessed by a score of 1 – 4, namely, irrelevant (TR) with a score of 1; less relevant (KR) with a score of 2; quite relevant (CR) with a score of 3; and relevant (R) with a score of 4 for each question item with aspects measured, namely, aspects of content, language, and construct.  Based on the calculation, 15 questions were declared valid with an Aiken index value ≥ 0.73.
Co-Authors Antuni Wiyarsi Hayuni Retno Widarti Putri, Bela Anisa Sri Yamtinah