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NUS Class Bot - NUS CP3108B Project

Project Supervisor: A/P Martin Henz. Project Advisor: Tobias Wrigstad

Student Developers: Chaitanya Baranwal and Raivat Shah. Co-Founders: Advay Pal, Chaitanya Baranwal and Raivat Shah

The Problem

Currently, the attendance taking process in NUS is the same old concept from the 1980s: either pass a sheet around for sign or do a roll-call of names. However, both these problems are prone to cheating by students as it is easy to be a proxy for someone. Furthermore, it is also a hassle for instructors to transfer the data from a physical sheet to a computer based record for further marking. Both the above methods also consume about 5 minutes of precious class time for each tutorial session. Usually, an NUS class has 10 tutorials per semester and this leads to a waste of 5 x 10 = 50 minutes each semester of students and teaching assistants. Since attendance and participation are important for learning and assessment at SoC, we thought of building a cool solution to this problem.

The Solution

NUS Class Bot is a Telegram Bot to solve the above mentioned problem. The bot stores the attendance data collected in real-time on a Google Spreadsheet, which is setup during deployment and shared with module staff. The solution connects three different services: Telegram, Python and Google Spreadsheets to collect the attendance data. The solution uses redis to stores multiple mappings to match a Telegram user with a row on Google Spreadsheets. The solution is currently deployed Amazon Web Services (AWS). The connection is illustrated in the following diagram:

diagram

The bot on this repository has been specifically designed for use with CS1101S, an expertial introductory programming module for CS Freshman at NUS-SoC. Here's a basic work-flow:

  1. Tutor counts number of student present in the class.
  2. Tutor starts taking attendance using /start_session (num of students).
  3. Bot gives the Tutor a Token of 8 digits.
  4. Tutor shares the Token with the students present in the classroom by writing it on a white board.
  5. Students mark attendance using /attend (Token). If the classroom is already full (number of students indicated in step 2 is reached), or if the Token is incorrect, the attendance is not marked and the Student is informed of the same. If there's a problem, the Student can approach the Tutor, who can immediately check on the Google Sheet.
  6. Tutor finishes the process by sending /stop_session to the bot.

Optional: The tutor can also choose to comment on a student's performance in a particular session using /comment

Here's a comprehensive summary of all the command supported by the bot and their function:

Command For user Function
/setup <student number> Student To register student's username with the bot's database (onetime process) through matric number
/attend <token> Student To mark attendance, supplying the attendance token
/attendance_reflection Student To check attendance data for reflection sessions till date.
/start_session <num students> Tutor To mark the attendance for num students for 1 class, generates the attendance token
/stop_session Tutor To stop taking attendance for current session.

The bot is currently used by the staff of CS1101S for tutorials, reflection sessions and staff meetings. Thus, the bot currently has approximately 600+ active users.

Development Process

The development process for the bot can effectively be divided into the following phases: ideation, prototyping, testing and final development. Ideation consisted of formulating the system design for the bot, following which a minimum viable product (prototype) was developed. The prototype was tested in some tutorials before using it over a wide scale. The success of the bot in those particular tutorial classes motivated us to scale it up, which consisted of developing a Telegram Bot designed especially for the module CS1101S.

  1. Ideation Phase: This phase involved formulating the design of our bot, ranging from the workflow to the way it addresses the automation of attendance taking (without allowing students absent from the tutorial to mark their attendance). Some of the design decisions characteristic of the bot included generating a hash token based on the timestamp of the computer, and limiting the usage of the hash token by counting the number of students present. Since hash tokens differ significantly even with minor changes in the input, we can be reaonsably sure that tokens generated are not the same at any point of time. The second important design decision was passing the number along with the command start_session. This serves as a quick way to ensure that students do not pass the token outside of class, since if someone outside the class marks an attendance, someone inside will not be able to do so. We have mainly not had cases of attendance token being passed outside, so this solution seems to be working fine.

  2. Prototyping Phase: The next phase involved actually creating the bot. To create the bot, we chose the API python-telegram-bot for its ease of use (and our familiarity with Python). For data storage, we chose Redis over other services like SQL databases because all our data is effectively stored using dictionaries, and Redis seems to be a lightweight and popular choice for persistent storage of key-value dictionaries. To develop a minimum viable product, we hardcoded the Tutor Telegram usernames and Google Sheet ID simply to get the bot up and running. The priority during this phase was to implement core functionalities like integration with Google Sheets and setting up the bot workflow.

  3. Testing Phase: After setting up the basic skeleton for the bot, we decided to test it unofficially during some tutorials. This was mainly to gain user feedback, understand the various test cases and discover unnoticed bugs. Advay tested the bot during his tutorial, and we also conducted "mock" tutorial sessions at our residential college. We discovered important bugs during this phase, such as the absence of a Telegram useraname for the student and also workflow errors. The testing phase greatly helped us in making the bot more polished and user-friendly.

  4. Final development and scaling up the solution: The final phase of implementing the bot involved making changes to the bot to adhere to CS1101S's needs and workflows, as well as onboarding the huge freshman/tutor base onto the bot. Changes involved dedicating the bot to populate only certain spreadsheets, reading tutor data from JSON files, as well as deciding which week to populate attendance for based on a JSON file which charts out the different weeks in the academic year. The comment feature was included in the bot so tutors of CS1101S can comment their students on the Studio sessions. The feedback method to garner user feedback for the bot was also implemented during this phase. The attendance_studio and attendance_reflection features were implemented to allow students to check their own attendance records for studio and reflection sessions, respectively. This was necessary as the students cannot be given access to the entire Google Spreadsheet because of PDPA concerns. This phase is still ongoing, and we provide constant support to the tutors/students who face problems using the bot.

Problems & Solutions

  1. Potential data losses: The current data storage mechanism uses Redis, and even though this is persistent, it is not completely safe from any potential data losses (nothing is), be it human or system error. Keeping regular backups of the attendance data is something we are looking towards in the future.

  2. Dedicated front-end for data management: Right now tutor data is handled through a .json file, and attendance data is handled through Google Sheets. Developing a dedicated front-end for this, where tutors can go in to update attendance, and module staff can go in to update tutors would solve several workflow issues in the Telegram bot.

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