Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Online Learning in Educational Research Finger : Jurnal Ilmiah Teknologi Pendidikan
Rince Aida Rostika
Universitas Bengkulu
Computer Science & IT Education Languange, Linguistic, Communication & Media Social Sciences Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Development of Virtual Reality Learning Media Based on the Kuula Platform Assisted by ClassPoint on Fluid Material to Improve Cognitive Learning Outcomes of Grade XI High School Students Rince Aida Rostika; Eko Risdianto; Bodi Gunawan; Mageswaran Sanmugam; Mohammad Qais Rezvani; Sultan Hammad Alshammari
FINGER : Jurnal Ilmiah Teknologi Pendidikan Vol. 5 No. 1 (2026): Finger : Jurnal Ilmiah Teknologi Pendidikan
Publisher : CV. Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/finger.v5i1.616

Abstract

Background: The rapid advancement of ICT (information and communication technology) during the Fourth Industrial Revolution offers great potential to transform physics learning, especially for abstract topics such as fluid matter. Limited laboratory facilities and suboptimal learning schedules in many schools can hinder students' understanding and cognitive learning outcomes.Objectives: This research seeks to: (1) ascertain the viability of the developed media, (2) measure the improvement in high school students' cognitive learning outcomes, and (3) determine students' responses to the learning media.Method: The ADDIE model (Analysis, Design, Development, Implementation, and Evaluation) was used in this research and development (R&D) study. The learning media developed was a 360° Virtual Reality video based on the Kuula platform integrated with ClassPoint. The trial was conducted on 39 eleventh-grade students utilizing a pretest-posttest approach in a single group. Data were collected through media and subject matter expert validation sheets, cognitive learning outcome tests, and questionnaires for student responses. Validation and student response data were subjected to descriptive and quantitatively analysis, while improvements in cognitive learning outcomes were analyzed using N-Gain scores.Results: Expert validation produced an average feasibility score of 90.16% (highly feasible). Students' cognitive learning outcomes improved significantly, with a high category N-Gain score of 0.83. The media received a highly favorable response from students, with an average score of 91.37% (very good).Conclusion: The virtual reality learning media based on the Kuula platform assisted by ClassPoint that was developed was declared highly feasible and effective in raising high school students’ cognitive learning outcomes on fluid material, particularly Archimedes' Principle. This media is an innovative alternative for schools with limited laboratory facilities.
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
Co-Authors Ahmad Zabidi Abdul Razak Bodi Gunawan Eko Risdianto Hera Anis Kartika Jeni Fitria Mageswaran Sanmugam Mohammad Qais Rezvani Sultan Hammad Alshammari