Instructor-hub is a Next.js project bootstrapped with create-next-app. It aims to address the problem of instructors having to juggle though multiple apps. Instructor-hub pulls it all together so instructors can get things done all in one place. Technologies used includes:

• Nextjs - https://nextjs.org/

• Axios - https://axios-http.com/

• Recoil - https://recoiljs.org/

• Asana Api - https://developers.asana.com/docs/how-to-use-the-api

• Postgres - https://www.postgresql.org/

• Pgcrypto - https://www.postgresql.org/docs/current/pgcrypto.html

First, run the development server:

npm run dev
# or
yarn dev

Open http://localhost:3000 with your browser to see the result.

The first pages loaded will be pages/home.js. The page auto-updates as you edit the file.

The pages/api directory is mapped to /api/*. Files in this directory are treated as API routes instead of React pages.

Some inormation will be uniqe to the environemnt in which this project is deployed or should not be shared publicly such as port numbers, api keys, etc.

Next.js uses a file named .env.local

Create the .env.local file in root directory of your project.

We've included a template (.env.template) to help you get started.

Inputs from instructors such as notes and scores are pushed to the students' cohort in Asana as well as to the database (see below). Users MUST have an asana personal access token (PAT).

To learn more about Next.js or pgcrypto, take a look at the following resources:

• Next.js Documentation - learn about Next.js features and API.
• Learn Next.js - an interactive Next.js tutorial.
• Storing secure passwords - overview of pgcrypto.

The application uses a postgres sql relational database. Within the database are 13 interconnected tables with primary and foreign keys, functions, and triggers for the functions. The functions perform updates, calculations, and data propagation purposes, and are triggered by inserting or updating data in selected columns within certain tables. While these operations could also have been performed on the client side, the developers made the decision to perform these activities within the database to improve the client user experience and performance.

The migration.sql file is organized, and comes with a table of contents that aids finding tables or functions of interest. This aids future developers in adding or modifying database tables, relationships, or features. The "gid" column that is present in several of the tables is derived from ASANA, and should aid in maintaining compatibility between ASANA and the local database.

One column (password) in one table (users) is protected by pgcrypto. The app utilizes the use the gen_salt function, to let PostgreSQL generate a random salt, and utilizes the blowfish (bf) algorithm. The syntax for entering a password is as follows:

crypt('somepassword', gen_salt('bf');

To authenticate a user, we use something similar to the following:

SELECT id FROM users WHERE username = 'someuser'
   AND password = crypt('somepassword', password);

1. Simple Bivariate Regression Analysis r^2 showing the predictive power of learn assessment scores on the student's assessed tech skills. This could easily be done by using the following postgres sql command:

SELECT regr_r2(learn_avg, tech_skills) as r2_learn_tech FROM students

It should only be done with groups of ten or more, to ensure reliability. The result is the statistical r^2, which here shows how well learn scores predict tech skills. The closer the number is to one, the more closely the former predicts the latter. It could also be turned into a percentage by multiplying the result by 100. A sample data explanation with hypothetical numbers follows:

"Cohort X average learn scores account for approximately 89% of the variance in average tech skills for students in the cohort."

This could indicate that the curriculum and assessments are relevant to the tech skills (high number), or are meaningless when it comes to student abilities (low score).