Raj-eGyan2.0

Analiza I Pregled Android Aplikacija: Raj-eGyan2.0, Razvijen Od DoIT&C, GoR. Navedeno U Kategoriji Obrazovanje. Trenutna Verzija Je 2022.006, Ažurirana Na 07/11/2022 . Prema Recenzijama Korisnika Na Google Playu: Raj-eGyan2.0. Postignute Više Od 659 Instalacije. Raj-eGyan2.0 Trenutno Ima 1 Recenzija, Prosječna Ocjena 5.0 Zvijezda

eGyan2.0 is intended to provide extensive coverage through conformance to Universal Design of Learning with focus on Multiple Intelligence Model of learning besides multi-dimensional cognitive assessment framework.
Rajasthan Govt is committed to offer new capabilities to the community of teachers / Subject matter experts for enabling them to create extensive digital content in Hindi and English. It is also aimed to contextualize International English content into reusable Hindi equivalent, even various Dialects, by using simple to use tools without need of prior technical indulgence.
Flexible, customizable, and scalable for capabilities such as
1. Parent teachers Collaboration framework to enable visibility of all the classes/topics made available through school connected app. The app would provide links to prescribed courseware and video related to topic covered in the day. There by giving parents, who are not competent in subjects, a possibility to understand and help their wards grasp completely.
2. Blended Teaching or Flipped Classroom Model of learning - Where in Teachers would be able to provide a personal touch to the learning of each learner. Teacher's may assign courses and assessments, inform students of new events, activities. Also, they will be able to view submitted assessments and provide Grades along with feedback and Notes.
3. Assessment frameworks, which can be extended to specialized stream, generate reports for Learners and Teachers for having highest levels of learning and contributions. All teachers with most recommended/viewed course would be felicitated / incentivized for their contribution in future.
4. Multi dimensional learning analytics eGyan would expect to become a full fledged cognitive learning platform where in personalized assessment and Recommendation engine capabilities would be expected as future customization.

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