Education

Teaching and learning about math, Maple and MapleSim

Emotional intelligence (EI)

 

In research for determinant factors of development and progression, psychologists innovated a concept, called “Emotional Intelligence”. When psychologists suggested the concept of emotional intelligence and its related criteria, most people believed that intelligence quotient (IQ), was the most important factor for success. They did not show much interest in emotional intelligence tests and for many years and even to this day, most people still consider IQ as a more important factor. That is why they welcome IQ tests more than EI tests. This is while researchers have shown in their studies that the impact of emotional intelligence is much more powerful. That is why psychologists know emotional intelligence as a functional intelligence and they call it the “Mainline” or the “Smart Guidebook”. Many studies in 2019, show that EI can lead to job success. That is why organizations around the world use emotional intelligence tests, including Bar-on’s emotional intelligence test and Golman’s emotional intelligence test for screening people, especially at important posts.

Hi there! 

One of my favorite videogames is pokémon as you can probably guess from the title. As a player I always wanted to optimize my chances of obtaining the rarest and best pokémon in the game. I have been working on an application that aims to use graph theory to analyze the game Pokémon Blue. The application explores the following questions:

Which is the rarest pokémon in the game?
Where can I find an specific pokémon and with what probabilities?
What is the place with most different species of wild pokémon?

I also included algorithms for the following: Given a certain desired team

  • Find the minimum amount of places to visit to catch them and return the list of the places the player will need to visit.
  • What are the routes with best probabilities to catch each pokémon from my desired team?

Check out my application at: https://www.maplesoft.com/applications/view.aspx?SID=154565.

The following are some of the results obtained in the app:

What is the most common pokémon?

I did not only considered the amount of places a pokémon can appear in but also the probabilities of it appearing in each place.

What are the connections between pokémon and places?

In my graph, I connected a pokémon and a place if such pokémon could be caught in that place. The following is an example for the pokémon Pidgey. The weights of the edges are the probabilities of finding Pidgey in each route.

Viceversa, I did the same for how a route is connected to the pokémons in it:

 

Map of the Game
I also generated a colour coded version for the map of the game: where blue means that the place is a water route, brown means it's a cave and green means it's a tall-grass route.