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Eva Ulfiani
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Computer Science & IT Education

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Journal : Information Technology Education Journal

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Development of an Android-Based Educational Game with Gamification for Algorithms and Data Structures Gita Damayanti; Miraekel Lebang Malik; Firdayani Syarifuddin; Ibnu Hajar Manippi; Eva Ulfiani; Era Fasira
Information Technology Education Journal Vol. 3, No. 2, Mei (2024)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v3i2.2401

Abstract

This study aims to develop and evaluate an Android-based educational game incorporating gamification elements for teaching Algorithms and Data Structures (ADS). ADS is recognized as a fundamental yet challenging subject in computer science education due to its abstract concepts and dynamic processes. Traditional lecture-based instruction often results in low engagement and limited conceptual understanding. Therefore, this study proposes a gamified mobile learning solution to enhance student motivation and learning outcomes. A Research and Development (R&D) approach using the ADDIE model was employed to design and develop the application, followed by a quasi-experimental non-equivalent control group pretest–posttest design to evaluate its effectiveness. Participants consisted of 74 undergraduate students divided into an experimental group (n = 38) using the Android-based gamified application and a control group (n = 36) receiving conventional instruction. Data were analyzed using paired and independent samples t-tests with a significance level of 0.05. Results indicated a significant difference in posttest scores (t = 6.64, p < 0.001), with the experimental group achieving a higher mean (M = 82.47) compared to the control group (M = 71.28). The effect size was large (Cohen’s d = 1.54). Motivation scores were also higher in the experimental group (M = 4.31), and usability evaluation yielded an excellent System Usability Scale (SUS) score of 81.45. The study is limited to a single institution and short intervention duration. This research contributes empirical evidence that gamified Android-based learning can significantly improve cognitive achievement and motivation in ADS courses.
Effectiveness of Online Group Interventions with Digital Literacy and Internet Ethics E-Modules for Preventing Cyberbullying among Students Henri Gunawan Risal; Firdayani Syarifuddin; Ibnu Hajar Manippi; Hilda Suci Ramadhani; Jessy Angel Casey Ampulembang; Eva Ulfiani
Information Technology Education Journal Vol. 3, No. 1, Januari (2024)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v3i1.02422

Abstract

This study investigates the effectiveness of online group interventions assisted by e-modules on digital literacy and ethical online behavior to prevent cyberbullying among university students. Cyberbullying remains a pervasive issue in higher education, yet scalable interventions that combine knowledge acquisition and behavioral engagement are limited. This research aims to address this gap by evaluating whether a structured microlearning and chatbot-supported online program can enhance students’ knowledge, ethical awareness, and preventive behavioral intentions. An experimental study with pretest-posttest control group design was conducted involving 80 undergraduate students randomly assigned to intervention (n = 40) and control groups (n = 40). The intervention included interactive e-modules, scenario-based discussions, and AI chatbot support over a three-week period. Data were collected on digital literacy, ethical awareness, and behavioral intentions using validated Likert-scale instruments. Statistical analysis was performed using paired t-tests, independent t-tests, and effect size calculations to evaluate intervention outcomes. The intervention group demonstrated significant improvement compared to the control group in digital literacy (mean increase 30.2 points, Cohen’s d = 2.31), ethical awareness (mean increase 1.23, d = 2.10), and behavioral intention to prevent cyberbullying (mean increase 1.30, d = 2.18). Usability scores were high (SUS = 84.2 ± 6.3), and engagement metrics correlated positively with learning outcomes (r = 0.62, p < 0.001). The study demonstrates the potential of scalable online group interventions to enhance preventive digital behavior in higher education. Limitations include a single-institution sample, short intervention duration, and reliance on self-reported behavioral intentions. Future research should examine long-term effects, multi-institutional samples, and objective behavioral measurements. This research provides empirical evidence supporting the integration of e-modules, interactive group sessions, and chatbot support for cyberbullying prevention, contributing to digital citizenship education. The framework offers a practical, scalable, and adaptable model for universities seeking to promote safe and ethical online behavior.
The Effect of Peer Instruction with Concept Tests on Model Evaluation Topics (Confusion Matrix, ROC-AUC) in Reducing Student Misconceptions: A Quasi-Experimental Study Hilda Suci Ramadhani; Angel Casey Ampulembang; Eva Ulfiani; Fina Maulina; Era Fasira; Karmila
Information Technology Education Journal Vol. 3, No. 2, Mei (2024)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v3i2.2403

Abstract

This study aims to examine the effect of Peer Instruction combined with Concept Tests on reducing students’ misconceptions in model evaluation topics, specifically Confusion Matrix and ROC-AUC. Students frequently misinterpret evaluation metrics, particularly in imbalanced datasets, leading to flawed analytical reasoning. This study argues that structured peer discussion and targeted conceptual questioning significantly reduce such misconceptions compared to conventional lecture-based instruction. Design/methods/approach – A quasi-experimental non-equivalent control group pretest–posttest design was employed involving 68 undergraduate students (35 experimental, 33 control) enrolled in a Machine Learning course. A validated two-tier diagnostic test consisting of 20 items was used to measure misconceptions. The experimental group received Peer Instruction with 15 Concept Tests across three sessions, while the control group received conventional lectures. Data were analyzed using paired and independent samples t-tests and normalized gain (α = 0.05). Findings – The experimental group’s misconception level decreased from 58.43% to 21.57%, while the control group decreased from 56.88% to 39.64%. The normalized gain was significantly higher in the experimental group (g = 0.74) compared to the control group (g = 0.38), t(66) = 11.62, p < 0.001, with a large effect size (d = 1.82). Research implications/limitations – The study was limited to one institution and short-term intervention, which may restrict generalizability and long-term retention conclusions. Originality/value – This study provides empirical evidence supporting the effectiveness of Peer Instruction in machine learning education and introduces a diagnostic framework for measuring misconception reduction in Confusion Matrix and ROC-AUC topics.
Co-Authors Angel Casey Ampulembang Era Fasira Fina Maulina Firdayani Syarifuddin Gita Damayanti Henri Gunawan Risal Hilda Suci Ramadhani Ibnu Hajar Manippi Jessy Angel Casey Ampulembang Karmila Miraekel Lebang Malik