AZSCI Math & Computational Thinking 3

Question 1

A student develops a computational model to simulate the spread of an invasive plant species.
The model includes variables for growth rate, seed dispersal distance, and germination probability.
When testing the model, the student notices that if the 'growth rate' variable is set to a value slightly above zero, the simulated population immediately crashes.
Which of the following is the most likely cause of this edge case behavior?

Accepted Answer

The model lacks a variable for the plant's mortality rate, causing an imbalance at low growth rates.

Answer

The time step of the simulation is too large, preventing the model from accurately calculating slow, incremental growth.

Answer

The seed dispersal algorithm is not randomized, creating an artificial pattern that hinders population spread.

Answer

The computational resources of the computer are insufficient to handle such a complex simulation.

Question 2

A team of students is using a computational model to determine the optimal placement of wind turbines in a valley. Their model accounts for wind speed, topography, and turbine efficiency. After running hundreds of simulations, they find two potential layouts that produce nearly identical energy output. To decide between them, they introduce a new constraint: minimizing the 'flicker effect' on nearby homes. This iterative process of refining a model by adding new constraints or variables is an advanced application of which computational thinking practice?

Accepted Answer

Abstraction

Answer

Decomposition

Answer

Pattern Recognition

Answer

Algorithm Design

Question 3

When analyzing a large dataset of patient recovery times, a scientist uses an algorithm to group patients based on multiple variables (age, treatment type, pre-existing conditions). The algorithm identifies a small, unexpected cluster of patients with extremely fast recovery times, despite having risk factors that suggest a poor prognosis. Which of the following computational thinking skills is most critical for the next step of the scientific investigation?

Accepted Answer

Recognizing this anomaly as a pattern that warrants further, targeted investigation.

Answer

Creating a new, more efficient sorting algorithm.

Answer

Decomposing the problem into smaller parts.

Answer

Developing an abstraction to represent the entire dataset with a single equation.

Question 4

A student is designing an algorithmic model to predict the final temperature of a mixture of two liquids. The model works perfectly for most inputs. However, when the mass of one liquid is entered as zero, the program crashes due to a 'division by zero' error. Which computational thinking practice has been insufficiently applied, leading to this failure?

Accepted Answer

Testing and Debugging

Answer

Data Collection

Answer

Pattern Recognition

Answer

Decomposition

Question 5

A biologist is modeling the complex interactions within a forest ecosystem, including predator-prey relationships, plant competition for sunlight, and the role of decomposers. To make the model computationally feasible, they represent each species with a set of simplified rules for behavior (e.g., 'if fox is near rabbit, fox moves toward rabbit'). This technique of representing complex real-world entities with simplified, rule-based agents is a hallmark of:

Accepted Answer

Agent-based modeling

Answer

Stoichiometric analysis

Answer

Linear regression analysis

Answer

Fourier transformation

Question 6

A team is developing a computational simulation of tectonic plate movement. They discover that to achieve a realistic model, they must calculate the forces between tens of thousands of interacting points on the plate boundaries. The required processing power is beyond their available computers. Which of the following represents a valid computational thinking approach to overcome this limitation?

Accepted Answer

Developing a simplified model (an abstraction) that groups points into larger segments to approximate the forces.

Answer

Manually calculating the forces for a few key points and extrapolating the results.

Answer

Concluding that the simulation is impossible without a supercomputer.

Answer

Running the simulation for a much shorter time period to reduce the total number of calculations.