Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Krishnan, Divya R.; Yadav, Suneetha; Biswas, Pritha; Basha, Md Shaik Amzad; Prathiba, L. Title A name given to the resource Bridging the Rural Digital Divide: Machine-Learning-Driven Predictive Modeling of Digital Literacy Program Outcomes Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 2025 International Conference on Information, Implementation, and Innovation in Technology, I2ITCON 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/I2ITCON65200.2025.11210709" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/I2ITCON65200.2025.11210709</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105026312898?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105026312898?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Krishnan D.R., Christ (Deemed to be University), Department of Professional Studies, Bengaluru, India; Yadav S., Rgm College of Engineering and Technology, Nandyal, India; Biswas P., Christ (Deemed to be University), Department of Professional Studies, Bengaluru, India; Basha M.S.A., Gitam School of Business, Gandhi Institute of Technology and Management (Deemed to be University), Hyderabad, India; Prathiba L., Ashoka Women Engineering College (Autonomous), Kurnool, India Description An account of the resource The research project performed multiple regression model evaluations to assess how effective digital literacy schemes are in rural education settings. Training program achievements relied on predicted educational proficiency scores while program evaluation relied on both comprehensive participant demographic details and process training statistics. Our study examined numerous regression approaches from basic Linear Regression forms through advanced Random Forest and Gradient Boosting models and concluded with complex methods including Stacking and XGBoost. The research analyzed prediction accuracy and model explanatory power using Mean Squared Error (MSE) and Rsquared (R2) values during the evaluation process. Multiple feature applications were the best fit for the deterministic ensemble techniques which exhibited superior performance but alternatively different analytical models displayed stable prediction results. This research proposes educational method advancement through machine learning approaches capable of creating custom solutions targeting rural user requirements. This study delivers key information to stakeholders in its combined study of digital education enhancements and sophisticated learning evaluation data analysis techniques. 2025 IEEE. Subject The topic of the resource Digital Literacy; Educational Outcomes Prediction; Machine Learning; Predictive Modeling; Rural Education Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833153482-0; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online