Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
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This Author published in this journals
All Journal Online Learning in Educational Research Indonesian Journal of Pedagogy and Teacher Education
Hera Anis Kartika
Universitas Bengkulu
Education

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Unveiling the Dual Nature of AI in Grading: A Systematic Review of Benefits and Mitigation Strategies for Algorithmic Bias Eko Risdianto; Rince Aida Rostika; Ahmad Zabidi Abdul Razak; Hera Anis Kartika; Jeni Fitria
Online Learning In Educational Research (OLER) Vol. 5 No. 1 (2025): Online Learning in Educational Research
Publisher : CV FOUNDAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/oler.v5i1.695

Abstract

The use of Artificial Intelligence (AI) in educational evaluation optimizes learning outcomes. This research seeks to address the advantages and difficulties of implementing AI within academic evaluation frameworks with particular emphasis on the algorithmic bias problem and its implications for fairness in education. The absence of a thorough grasp of algorithmic bias, particularly how it can be utilized as a weapon against equitable education, reveals an important gap. We conduct a Systematic Literature Review (SLR) and bibliometric analysis on 121 articles sourced from Scopus published between 2021 to 2025 to trace the trends and examine the impacts and biases of AI on grading systems. The data demonstrates a significant increase in publications beginning 2018, concentrating on topics such as educational applications of AI, automated grading systems, and machine learning. The findings further indicate that though AI improves efficiency and consistency of the evaluations, it heightens the chances of biased outcomes because of non-diverse training data, prejudiced developers, and socio-cultural frameworks that could worsen the situation for already marginalized learners. In summary, this study highlights the critical gaps in bias mitigation strategies arising from the lack of ethical design frameworks, antecedent-free algorithms, and educator prep courses aimed at combating bias. These outcomes serve as benchmarks for the creation of more reliable and comprehensive AI systems for assessments and shift subsequent investigations to focus validation on different cultures and the incorporation of just AI design paradigms
Needs Analysis of Physics Learning Media Development Based on Augmented Reality Technology for High School Students Hera Anis Kartika; Andik Purwanto; Eko Risdianto
Indonesian Journal of Pedagogy and Teacher Education Vol. 1 No. 2 (2023): Indonesian Journal of Pedagogy and Teacher Education
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/ijopate.v1i2.116

Abstract

This study aims to examine what educators and learners require in order to create augmented reality-based educational materials for high school students. Descriptive research is one of the study methods used in research and development (RND). The data collection used is by conducting literature studies, observations, interviews and filling out questionnaires. This research instrument consists of observation sheets, interview sheets, and questionnaire sheets. Both quantitative and qualitative data analysis were the methods employed for the data analysis. The findings of the analysis of student needs questionnaires showed that, on average, 69% of the category agreed to the development of augmented reality-based learning media. These findings are based on observations made during teacher interviews, which indicate that the learning media used are still conventional and cause students to struggle with understanding learning materials. Thus, it follows that the utilization of learning materials based on augmented reality is required as a supporting medium in the educational process.
Co-Authors Ahmad Zabidi Abdul Razak Andik Purwanto Eko Risdianto Jeni Fitria Rince Aida Rostika