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All Journal REiD (Research and Evaluation in Education) International Journal of Robotics and Control Systems
Kardanova, Elena
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Control & Systems Engineering Education Electrical & Electronics Engineering

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A Systematic Review of the Use of Technology in Educational Assessment Practices: Lesson Learned and Direction for Future Studies Retnawati, Heri; Kardanova, Elena; Sumaryanto, Sumaryanto; Prasojo, Lantip Diat; Jailani, Jailani; Arliani, Elly; Hidayati, Kana; Susanti, Mathilda; Lestari, Himmawati Puji; Apino, Ezi; Rafi, Ibnu; Rosyada, Munaya Nikma; Tuanaya, Rugaya; Dewanti, Septinda Rima; Sotlikova, Rimajon; Kassymova, Gulzhaina Kuralbayevna
International Journal of Robotics and Control Systems Vol 4, No 4 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i4.1572

Abstract

Previous studies have demonstrated that technology helps achieve learning outcomes. However, many studies focus on just one aspect of technology’s role in educational assessment practices, leaving a gap in studies that examine how various aspects affect the use of technology in assessments. Hence, through a systematic work, we analyzed the extent and manner in which technology is integrated into educational assessments and how education level, domain of learning, and region may affect the use of technology. We reviewed empirical studies from two major databases (i.e., Scopus and ERIC) and a national journal whose focus and scope are on educational measurement and assessment, following PRISMA guidelines for systematic reviews. The findings of the present study are directed towards emphasizing the roles of technology in educational assessment practices and how these roles are adapted to varying educational contexts such as the level of education, the three domains of learning (i.e., cognitive, psychomotor, and affective), and the setting in which the assessment was conducted. These findings not only highlight the current roles of technology in educational assessment but also provide a roadmap for future research aimed at optimizing the integration of technology across diverse educational contexts.
A comparison of the stability of ability parameter estimation based on the maximum likelihood and Bayesian estimation: A case study of dichotomous scoring test results Putri, Faradila Ilena; Retnawati, Heri; Kardanova, Elena
REID (Research and Evaluation in Education) Vol. 11 No. 1 (2025)
Publisher : Graduate School of Universitas Negeri Yogyakarta & Himpunan Evaluasi Pendidikan Indonesia (HEPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/reid.v11i1.89463

Abstract

This research is related to Item Response Theory (IRT), which is essential for determining the best method for estimating participants' abilities on a test measuring English listening ability. This study aims to (1) determine the characteristics of the test device measuring English listening ability, (2) determine the effect of the length of the test on the stability of the ability estimation using the maximum likelihood (ML) method, (3) determine the effect of test length on the stability of the ability estimation using the Bayes method, and (4) compare the stability of the ability estimate between ML and Bayes. This research is an exploratory descriptive study using a simulation approach. The best model is selected to generate data. The result of the generation is the actual ability (θ) and the participant's response, which is estimated with the maximum likelihood and Bayes, which produces the estimated ability with 10 replications, and is compared with calculating the MSE (mean square error). The method with a smaller MSE is stable and has a better estimation method. The results show that (1) the 2PL model is the best, (2) the length of the test affects the stability of the ability estimation in the ML method and the most stable case when the test contains 46 items, (3) the length of the test affects the stability of the ability estimate in the Bayes method and it is most stable when the test contains 46 items, and (4) the Bayes method is better and more accurate for estimating ability.
Co-Authors Apino, Ezi Elly Arliani Heri Retnawati Himmawati Puji Lestari Jailani Jailani Kana Hidayati Kassymova, Gulzhaina Kuralbayevna Lantip Diat Prasojo M. Rafi Mathilda Susanti Putri, Faradila Ilena Rosyada, Munaya Nikma Septinda Rima Dewanti Sotlikova, Rimajon Sumaryanto Sumaryanto, Sumaryanto Tuanaya, Rugaya