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All Journal Online Learning in Educational Research Asian Journal of Science Education
Kartika, Hera Anis
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Education Social Sciences Other

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Development of Physics E-Books Assisted by Flipbook and Augmented Reality (AR) to Increase Learning Motivation of High School Students Kartika, Hera Anis; Purwanto, Andik; Risdianto, Eko
Asian Journal of Science Education Vol 6, No 1: April, 2024
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/ajse.v6i1.36294

Abstract

The initial observation results indicate that students are less active in the learning process and easily give up when faced with tasks deemed difficult. This study aims to describe the feasibility of physics e-books aided by flipbooks and augmented reality (AR), describe students' responses and describe students' learning motivation after the implementation of physics e-books aided by flipbooks and augmented reality (AR). This research is a type of development research using the ADDIE model. Sampling was done using purposive sampling techniques consisting of students from the Eleventh-grade science 3 class at Public High School 7 in Kota Bengkulu. The instruments used were observation sheets, teacher interview sheets, validation sheets, student response questionnaires, and pretest and posttest student learning motivation questionnaires, with data collection techniques including interviews, questionnaires, and documentation. Data were analyzed using quantitative data analysis. The research results show that the feasibility test criteria for physics e-books were obtained with a very good category. Students also responded very well to the developed physics e-books. Based on the analysis of student learning motivation questionnaires using the Gain value, it was found that students experienced an increase in learning motivation after using the developed physics e-books. Therefore, it can be concluded that physics e-books aided by flipbooks and augmented reality (AR) are highly suitable for use as learning media and can enhance students' learning motivation, especially in dynamic fluid materials
Unveiling the Dual Nature of AI in Grading: A Systematic Review of Benefits and Mitigation Strategies for Algorithmic Bias Risdianto, Eko; Rostika, Rince Aida; Razak, Ahmad Zabidi Abdul; Kartika, Hera Anis; Fitria, Jeni
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
Co-Authors Andik Purwanto Eko Risdianto Fitria, Jeni Razak, Ahmad Zabidi Abdul Rostika, Rince Aida