From Chalkboard to Dashboard: Leveraging Real-Time Analytics for Evidence-Based Education Management in Rural Schools
Downloads
Background. The growing demand for evidence-based decision-making in education highlights the importance of real-time data in guiding school management practices. Rural schools, however, often face unique challenges such as limited access to resources, inadequate infrastructure, and insufficient monitoring systems, making it difficult for administrators and teachers to evaluate progress effectively. Transitioning from traditional chalkboard practices to data-driven dashboards provides opportunities to address these challenges by leveraging analytics to improve educational outcomes and equity.
Purpose. This study aimed to examine how real-time analytics can be integrated into rural school management to support evidence-based decision-making. Specifically, it explored the potential of dashboard systems to enhance monitoring of student performance, teacher effectiveness, and resource allocation in under-resourced contexts.
Method. The research adopted a mixed-method design involving 15 rural schools. Quantitative data were collected through digital dashboards tracking attendance, assessment scores, and teacher engagement, while qualitative insights were obtained from interviews with school leaders and educators. Data were analyzed using descriptive statistics and thematic coding.
Results. Findings indicate that dashboards significantly improved administrators’ ability to identify learning gaps, monitor teacher performance, and allocate resources more effectively. Teachers reported greater confidence in instructional planning when provided with real-time feedback. However, challenges such as internet connectivity and digital literacy remained barriers.
Conclusion. The study underscores the transformative potential of dashboards in rural education. By embracing real-time analytics, schools can shift towards a culture of evidence-based management that fosters accountability, inclusivity, and improved learning outcomes.
Ahmed, W. S. (2024). Digital forensics architecture for real-time automated evidence collection and centralization: Leveraging security lake and modern data architecture. Journal of Intelligent Systems, 33(1). https://doi.org/10.1515/jisys-2024-0109
Ajimon, S. T. (2024). Applications of LLMs in Quantum-Aware Cybersecurity Leveraging LLMs for Real-Time Anomaly Detection and Threat Intelligence. Leveraging Large Language Models for Quantum Aware Cybersecurity, Query date: 2025-08-22 02:44:20, 201–246. https://doi.org/10.4018/979-8-3373-1102-9.ch007
Arora, S. (2024). AI-Driven DDoS Mitigation at the Edge: Leveraging Machine Learning for Real-Time Threat Detection and Response. 2nd IEEE International Conference on Data Science and Network Security Icdsns 2024, Query date: 2025-08-22 02:44:20. https://doi.org/10.1109/ICDSNS62112.2024.10690930
Ashok, G. V. (2024). A Novel Framework Leveraging Machine Learning (ML) Techniques, Coupled with Lightweight Deep Learning Mechanisms for Real-Time Call Drop Prediction in Mobile Networks. International Journal of Intelligent Systems and Applications in Engineering, 12(15), 323–332.
Babu, C. V. S. (2023). Cloud-enabled fire safety in Industry 5.0 smart factories: Leveraging IoT and sensor networks for real-time monitoring and proactive prevention. Emerging Technologies in Digital Manufacturing and Smart Factories, Query date: 2025-08-22 02:44:20, 150–166. https://doi.org/10.4018/979-8-3693-0920-9.ch009
Banerjee, A. (2024). AI-Driven Symptom Checker: Leveraging Big Data Technologies for Real-Time Healthcare Triage and Diagnostics. 5th International Conference on Sustainable Communication Networks and Application Icscna 2024 Proceedings, Query date: 2025-08-22 02:44:20, 1289–1293. https://doi.org/10.1109/ICSCNA63714.2024.10864063
Bhati, N. (2024). Advanced Real-Time Simulation Framework for the Physical Interaction Dynamics of Production Lines Leveraging Digital Twin Paradigms. Simulation Techniques of Digital Twin in Real Time Applications Design Modeling and Implementation, Query date: 2025-08-22 02:44:20, 319–343. https://doi.org/10.1002/9781394257003.ch15
Bostani, A. (2024a). Adaptive Energy Management System for Electric Vehicle Charging Stations: Leveraging AI for Real-Time Grid Stabilization and Efficiency. E3s Web of Conferences, 591(Query date: 2025-08-22 02:44:20). https://doi.org/10.1051/e3sconf/202459104002
Bostani, A. (2024b). AeroNeuro-GlobalNet: Leveraging LEO Satellite Constellations and 5G/6G Networks for Real-Time Emotional Monitoring of Transport Operators. 2024 IEEE Global Conference on Artificial Intelligence and Internet of Things Gcaiot 2024, Query date: 2025-08-22 02:44:20. https://doi.org/10.1109/GCAIOT63427.2024.10833530
Chakraborty, S. K. (2023). Development of an optimally designed real-time automatic citrus fruit grading–sorting machine leveraging computer vision-based adaptive deep learning model. Engineering Applications of Artificial Intelligence, 120(Query date: 2025-08-22 02:44:20). https://doi.org/10.1016/j.engappai.2023.105826
Chandre, P. (2024). Adaptive Behavioral Authentication for Fraud Detection: Leveraging Real-Time User Behavior to Enhance Financial Security. 2024 1st International Conference on Data Computation and Communication Icdcc 2024, Query date: 2025-08-22 02:44:20, 539–545. https://doi.org/10.1109/ICDCC62744.2024.10961554
Dili, G. (2024). Demystifying the Data: Leveraging Explainable AI for Real -Time Monitoring and Decision-Making in Vertical Hydroponics Farms. Icacc International Conference on Advances in Computing and Communications, 2024. https://doi.org/10.1109/ICACC63692.2024.10845548
Geng, Y. (2025). Accurate Real-Time Wind Power Forecasting with TTP-Net: Leveraging Temporal and Spatial Modeling for Enhanced Prediction. Distributed Generation and Alternative Energy Journal, 40(1), 165–192. https://doi.org/10.13052/dgaej2156-3306.4017
Haddad, S. (2024). A Scalable Real-Time Monitoring System for East-West PV Systems Leveraging the Internet of Things. 2024 International Conference on Advances in Electrical and Communication Technologies Icaecot 2024, Query date: 2025-08-22 02:44:20. https://doi.org/10.1109/ICAECOT62402.2024.10828963
Jameil, A. K. (2025). A digital twin framework for real-time healthcare monitoring: Leveraging AI and secure systems for enhanced patient outcomes. Discover Internet of Things, 5(1). https://doi.org/10.1007/s43926-025-00135-3
Jaulkar, S. (2024). A Real-Time News App in Salesforce: Leveraging Omni-Channel Chatbots in Salesforce for Enhanced User Engagement. 2024 2nd World Conference on Communication and Computing Wconf 2024, Query date: 2025-08-22 02:44:20. https://doi.org/10.1109/WCONF61366.2024.10692051
Kamarthi, H. (2022). BACK2FUTURE: LEVERAGING BACKFILL DYNAMICS FOR IMPROVING REAL-TIME PREDICTIONS IN FUTURE. Iclr 2022 10th International Conference on Learning Representations, Query date: 2025-08-22 02:44:20. https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85146811777&origin=inward
Khan, R. A. (2025). AgilePilot: DRL-Based Drone Agent for Real-Time Motion Planning in Dynamic Environments by Leveraging Object Detection. 2025 International Conference on Unmanned Aircraft Systems Icuas 2025, Query date: 2025-08-22 02:44:20, 185–192. https://doi.org/10.1109/ICUAS65942.2025.11007799
Malik, S. (2024). Data-Driven Decision-Making: Leveraging the IoT for Real-Time Sustainability in Organizational Behavior. Sustainability Switzerland, 16(15). https://doi.org/10.3390/su16156302
Marques, T. (2024). Applying deep learning to real-time UAV-based forest monitoring: Leveraging multi-sensor imagery for improved results. Expert Systems with Applications, 245(Query date: 2025-08-22 02:44:20). https://doi.org/10.1016/j.eswa.2023.123107
Mehta, S. (2024). Anomaly Detection in IoT Networks: Leveraging Federated Learning for Real-Time Threat Response. 2024 5th IEEE Global Conference for Advancement in Technology Gcat 2024, Query date: 2025-08-22 02:44:20. https://doi.org/10.1109/GCAT62922.2024.10923971
Mittal, S. (2024). AI and Social Media Analytics: Leveraging Real-Time Data for Entrepreneurial Growth. Improving Entrepreneurial Processes Through Advanced AI, Query date: 2025-08-22 02:44:20, 267–290. https://doi.org/10.4018/979-8-3693-1495-1.ch012
Mridha, M. J. H. (2025). A Real-Time ETP Outlet Monitoring Framework Leveraging Environmental IoT, Colorimetry, and Learning Theory. IEEE Access, 13(Query date: 2025-08-22 02:44:20), 98729–98746. https://doi.org/10.1109/ACCESS.2025.3576826
Mujuni, D. (2024). Beyond diagnostic connectivity: Leveraging digital health technology for the real-time collection and provision of high-quality actionable data on infectious diseases in Uganda. Plos Digital Health, 3(8). https://doi.org/10.1371/journal.pdig.0000566
Obe, R. (2023). Accelerating Real-Time Imaging for Radiotherapy: Leveraging Multi-GPU Training with PyTorch. Proceedings 22nd IEEE International Conference on Machine Learning and Applications Icmla 2023, Query date: 2025-08-22 02:44:20, 1727–1734. https://doi.org/10.1109/ICMLA58977.2023.00262
Papanashi, S. (2024). Adaptive Traffic Signal Timing: Leveraging YOLOv10 and Computer Vision for Real-Time Optimization. 8th IEEE International Conference on Computational System and Information Technology for Sustainable Solutions Csitss 2024, Query date: 2025-08-22 02:44:20. https://doi.org/10.1109/CSITSS64042.2024.10817018
Pradeesh, D. A. (2023). Advanced Interoperable Framework for Real-Time Predictive Analysis Leveraging Machine Learning and IoT in Smart Health Monitoring Systems. International Conference on Electrical Computer and Energy Technologies Icecet 2023, Query date: 2025-08-22 02:44:20. https://doi.org/10.1109/ICECET58911.2023.10389275
Prakash, J. (2024). AI-Driven Real-Time Feedback System for Enhanced Student Support: Leveraging Sentiment Analysis and Machine Learning Algorithms. International Journal of Computational and Experimental Science and Engineering, 10(4), 1567–1574. https://doi.org/10.22399/ijcesen.780
Qawasmeh, S. A. D. (2025). Beyond Firewall: Leveraging Machine Learning for Real-Time Insider Threats Identification and User Profiling. Future Internet, 17(2). https://doi.org/10.3390/fi17020093
Said, M. A. (2025). A NEW PARADIGM IN FRAUD DETECTION: LEVERAGING SOCIAL MEDIA TO PREDICT MCCS IN REAL TIME. Journal of Theoretical and Applied Information Technology, 103(8), 3494–3505.
Sarkar, S. (2024). Advancing Urban Evacuation Management: A Real-Time, Adaptive Model Leveraging Cloud-Enabled Big Data and IoT Surveillance. 2024 4th International Conference on Intelligent Technologies Conit 2024, Query date: 2025-08-22 02:44:20. https://doi.org/10.1109/CONIT61985.2024.10626540
Serepas, F. (2024). A Comprehensive Approach to Real-Time and Batch Processing for Energy-Efficient IoT Homes: Leveraging Lambda Architecture and Data Lakes. 15th International Conference on Information Intelligence Systems and Applications Iisa 2024, Query date: 2025-08-22 02:44:20. https://doi.org/10.1109/IISA62523.2024.10786715
Sharma, S. (2024). Adaptive Threat Detection: Leveraging Machine Learning for Real-Time Cybersecurity. 3rd International Conference on Advances in Computing Communication and Materials Icaccm 2024, Query date: 2025-08-22 02:44:20. https://doi.org/10.1109/ICACCM61117.2024.11059081
Siddika, A. (2025). Emotion Recognition and Analysis System (ERAS): Leveraging Advanced AI for real-time Emotion Detection in Social Media Content. 2025 International Conference on Electrical Computer and Communication Engineering Ecce 2025, Query date: 2025-08-22 02:44:20. https://doi.org/10.1109/ECCE64574.2025.11013817
Soykan, B. (2025). A Proof-of-Concept Digital Twin for Real-Time Simulation: Leveraging a Model-Based Systems Engineering Approach. IEEE Access, 13(Query date: 2025-08-22 02:44:20), 58899–58912. https://doi.org/10.1109/ACCESS.2025.3557367
Thakkar, C. P. b. (2025). Advanced Real-Time Face Detection and Recognition Leveraging YOLO-CNN. Iet Conference Proceedings, 2025(7), 1692–1698. https://doi.org/10.1049/icp.2025.1697
Trong, T. D. (2024). An Autonomous Scheme Leveraging Deep Learning Techniques to Adjust the Gimbal Camera Angle in Real-Time for Victim Positioning by Drone. International Conference on Advanced Technologies for Communications, Query date: 2025-08-22 02:44:20, 393–400. https://doi.org/10.1109/ATC63255.2024.10908310
Wei, J. (2024). BloodPatrol: Revolutionizing Blood Cancer Diagnosis—Advanced Real-Time Detection Leveraging Deep Learning & Cloud Technologies. IEEE Journal of Biomedical and Health Informatics, Query date: 2025-08-22 02:44:20. https://doi.org/10.1109/JBHI.2024.3496294
Ye, Z. (2025). ASO Visual Abstract: Leveraging Deep Learning in Real-Time Intelligent Bladder Tumor Detection During Cystoscopy-A Diagnostic Study. Annals of Surgical Oncology, 32(5), 3229–3229. https://doi.org/10.1245/s10434-025-17143-w
Copyright (c) 2025 Yance Manoppo, Leny Sopia Latuny

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
 
						















