E-khool LMS
e-khool LMS [1] is a learning management system specifically designed for online engineering education[2] and schools. Employing artificial intelligence (AI) technologies, the platform boasts five patents [3] and is hosted on the Amazon Web Services (AWS) cloud infrastructure. Furthermore, e-khool LMS adheres to the stringent security standards established in North America including ISO/IEC 27001, part of the growing ISO/IEC 27000 family of standards .
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| Type | Private |
|---|---|
| Industry | Edtech |
| Founded | 13-01-2016 |
| Founder | Binu Dennis and B R Rajakumar |
Area served | Worldwide |
| Services | Learning Management System |
| Parent | Resbee Info Technologies (P) Ltd |
| Subsidiaries | MAAZTER Learning App |
| Website | https://ekhool.com/ |
History
Resbee Info Technologies (P) Ltd, established in 2016, is an Indian information technology (IT) firm specializing in the development of advanced e-learning solution.[4] Their flagship offering, e-khool Learning Management System (LMS) software, caters to the learning needs of universities, industries, academic institutions, and students.[5] In 2017, the e-khool LMS platform [6] transitioned to a Software as a Service (SaaS) subscription model and was hosted on Amazon Web Services (AWS) infrastructure to provide a scalable solution. By 2020, the incorporation of artificial intelligence (AI) features further enhanced the e-khool LMS software, enabling a more customized learning experience for users.[7]
Research
e-khool LMS (Learning Management System) is an online platform designed for educational researchers to conduct research in the field of online learning. The system offers various features and tools, which allows researchers to investigate different aspects of the online learning experience, including learner performance prediction, course recommendation, learner privacy, and learner sentiment analysis. The data generated by e-khool LMS serves as a valuable resource for researchers aiming to improve and understand the online learning experience.
Learner Performance Prediction: Using the data associated with the e-khool LMS, researchers can analyze and predict learner performance within an online learning environment.[8] By studying factors such as time spent on activities, interaction with course materials, and quiz scores, researchers can develop models to predict future performance, identify at-risk students, and suggest personalized learning paths for individual learners.
Course Recommendation: e-khool LMS provides data that can be used by researchers to develop course recommendation systems.[9][10] By analyzing learners' preferences, past performance, and course completion rates, these systems can suggest relevant and appropriate courses for individual learners. This not only enhances the overall learning experience but also helps institutions in providing tailored content to meet the diverse needs of their students.
Learner Privacy: The data collected by e-khool LMS can also be used to investigate learner privacy in online learning environments.[11] Researchers can study the implications of data sharing, privacy policies, and security measures to ensure the protection of learners' personal information. This is especially important as online learning platforms continue to grow in popularity and more sensitive information is being shared and stored online.
Learner Sentiment Analysis: Learner sentiment analysis is another area of research that benefits from the data provided by LMS.[12] By analyzing learners' emotions, opinions, and attitudes towards course materials, instructors, and the overall learning experience, researchers can gain valuable insights into the factors that contribute to learner satisfaction and engagement. This information can be used to improve course design and delivery, ultimately enhancing the learning experience for students.
Patents
e-khool LMS Software is an Artificial Intelligence (AI)-based learning platform that incorporates patented technologies for enhanced learning experiences and adaptability in various industries and academic institutions worldwide. Developed by Binu Dennis and Rajakumar B.R, e-khool LMS features several innovative technologies designed to improve online learning, security, and accessibility.
Patented technologies
- IN application 201941041633, Binu Dennis & Rajakumar B.R, "Emotion based LMS for Certified expert identification and device access control" : This technology utilizes emotion recognition to identify experts and control access to devices, enhancing security and efficiency in the learning environment.
- IN application 201941040679, Binu Dennis & Rajakumar B.R, "Electronic documentation of live lectures for smart classrooms": This patent covers a method for electronically documenting live lectures, making it easier for students and educators to access and review lecture materials.
- IN application 201941034801, Binu Dennis & Rajakumar B.R, "On-Device malware app protector" : This technology provides protection against malware on users' devices, ensuring a safe learning environment.
- IN application 201941035325, Binu Dennis & Rajakumar B.R, "A Novel Overlap CAPTCHA for online security system" : This patent presents a new type of CAPTCHA system designed to enhance the security of online systems.
- IN application 201941002437, Binu Dennis & Rajakumar B.R, "Face and Emotion based locker security system": This technology uses face and emotion recognition to secure lockers and storage systems, enhancing security in educational institutions and other environments.
- IN application 201941035203, Binu Dennis & Rajakumar B.R, "System for IoT device authentication": This patent covers a system for authenticating Internet of Things (IoT) devices, ensuring secure and reliable connections.
Adaptability
e-khool LMS is designed to be adaptable for use in various industries and academic institutions around the world. Its patented technologies provide enhanced security, accessibility, and learning experiences that cater to a wide range of users.
Awards and Recognition
The e-khool LMS software has been widely recognized for its innovative approach and effectiveness in the field of e-learning and artificial intelligence. Some of its key awards and accolades include:
- In 2020, e-khool LMS was named among the ''20 Most Promising Elearning Solution Providers'' by CioReviewIndia, a leading technology magazine that provides information about enterprise solutions that can redefine the business goals of enterprises.[13]
- The system has been listed under the ''Top Featured Companies Dominating the Market'' by Research Nester, an esteemed market research and consulting firm that offers comprehensive research reports and strategic recommendations.[14]
- In 2022, e-khool LMS was ranked as one of the ''Top 20 Hottest AI Startups In India'' by Analytics India Magazine, a prominent platform that covers the analytics, artificial intelligence, data science, and big data landscape in India.[15]
- In 2023, viestories, a platform that showcases and celebrates innovative startups, praised the LMS software by listing it among the ''Top 20 Best Innovative AI Startups in India'' for the year 2023.[7]
References
- "e-khool LMS". e-khool LMS.
- "Course complexity in engineering education using E-learner's affective-state prediction". Kybernetes.
- "e-khool LMS patents".
- "Resbee Info Technologies Private Limited Information - Resbee Info Technologies Private Limited Company Profile, Resbee Info Technologies Private Limited News on The Economic Times". The Economic Times. Retrieved 2023-03-23.
- "e-khool LMS".
- Binu, D.; Rajakumar, B. R. (2021-02-17). Artificial Intelligence in Data Mining: Theories and Applications. Academic Press. ISBN 978-0-12-820616-4.
- "Top 20 Best Innovative AI startups in India in 2023". 2023-02-12. Retrieved 2023-03-23.
- Alzubi, Ahmad (March 2022). "Learner performance prediction in the e-learning platform using the optimized deep long short-term memory classifier". International Journal of Wavelets, Multiresolution and Information Processing. 20 (2): 2150051. doi:10.1142/S021969132150051X. ISSN 0219-6913. S2CID 243854878.
- Vijaya, P.; Selvi, M. (2022-05-30). "An Approach Using E-Khool User Log Data for E-Learning Recommendation System". Journal of Information & Knowledge Management. 21 (3). doi:10.1142/s0219649222500411. ISSN 0219-6492. S2CID 249262545.
- Banbhrani, Santosh Kumar; Xu, Bo; Lin, Hongfei; Sajnani, Dileep Kumar (2022-04-19). "Taylor-ChOA: Taylor-Chimp Optimized Random Multimodal Deep Learning-Based Sentiment Classification Model for Course Recommendation". Mathematics. 10 (9): 1354. doi:10.3390/math10091354. ISSN 2227-7390.
- Shivashankar, Mohana; Mary, Sahaaya Arul (May 2021). "Privacy preservation of data using modified rider optimization algorithm: Optimal data sanitization and restoration model". Expert Systems. 38 (3). doi:10.1111/exsy.12663. ISSN 0266-4720. S2CID 233433366.
- A., Pandiaraj; C., Sundar; S., Pavalarajan (2022-01-05). "Sentiment analysis on newspaper article reviews: contribution towards improved rider optimization-based hybrid classifier". Kybernetes. 51 (1): 348–382. doi:10.1108/K-08-2020-0512. ISSN 0368-492X. S2CID 233647104.
- "20 Most Promising Elearning and Gamification Solution Providers - 2020 | Vendors". education.ciotechoutlook.com. Retrieved 2023-03-23.
- "Online Coaching Software Market Size | Demand Analysis & Opportunity Outlook 2030". www.researchnester.com. Retrieved 2023-03-23.
- Raibagi, Kashyap (2022-10-06). "20 Hottest AI Startups In India 2022". Analytics India Magazine. Retrieved 2023-03-23.
