Slashie – Online Learning App
Overview of Slashie
Slashie is a mobile application that facilitates the online learning system for a diverse demography. The application is divided into two panels, one for the mentors and another for mentees. Experts from different fields and segments can give their mentorship classes or sessions to the knowledge seeking mentees. The platform also enables building a community for different categories.
Discovery
Everyone in the post-pandemic period, whether they admit it or not, now believes that the future resides in the digital sphere. The educational system has been seriously jeopardized among other fields. As a result of this demand, a plethora of MOOCs (Massive Open Online Course) covering a wide range of subjects have emerged online. In a short amount of time, however, its usefulness faded since the preloaded videos did not permit opportunity for doubt clearance and interaction. Slashie began the process of developing a space where professionals in a given subject may talk to students individually.
Case Study
Client’s Overview
Jamie Tan, a prominent Singaporean female entrepreneur, founded and owns Slashie. Ms. Jamie leads Flying Cape, a Singaporean edtech business with ambitious plans to improve the island nation’s educational infrastructure. Her work in the field of educational technology has earned her coverage in a wide variety of prestigious publications.
Company’s Overview
Flying Cape is an online tuition and enrichment booking and consulting platform. The company aims to help you locate and schedule the best activities depending on your needs by collaborating with renowned scholars all over the world and guaranteed by the Best Price Guarantee.
Challenges
- An algorithm was needed for easy sorting of mentors.
- Communication channel was to be created for interaction.
- Session scheduling and notification features were to be integrated.
Solutions
- For architecting the backend of Slashie, Laravel framework was utilized.
- Flutter helped our developers to design the front-end of the mobile application.
The Results
- The experts in different fields were categorized and featured on the application accordingly.
- Machine learning was applied to create an algorithm that would enable the calculation of the matching percentage between the mentor and the mentee.
- The UI was designed to enable the mentees to like and dislike the mentors with left and right swaps.
- The application allows the chatting option, news feed updates, and pop-up notifications in order to build a social network community.
- The calendar page was integrated with the application to help the mentees schedule their mentors and help the latter trace their timetable.
- Two types of sessions were hosted on the application: one-to-one and one-to-many.
Milestones
Our team of seasoned professionals who have years of experience in mobile application development were able to deliver the project within a short span of 4 months.
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