Sorting histogram in python for selected sorts
Topic and Learning Outcome:
Iterative Algorithms: http://www.learnalberta.ca/ProgramOfStudy.aspx?lang=en&ProgramId=74838#900020
Essential Question:
What are sorting algorithms and how can we evaluate efficiencies for these algorithms?
Objectives:
Allow students to access sorting algorithms to test different use cases for timed runs. This will allow us to compare and contrast algorithm structure as well as algorithm efficiency.
Prior Knowledge:
Procedural (functional or method-driven) Programming.
Data Structures (static, dynamic and multidimensional).
Scaffolded Practice:
Review data structures.
Discuss random vs. almost sorted vs. reverse sorted as average, best and worst case scenarios.
Introduce algorithms 1 by 1 to understand the pattern associated with each sorting algorithm. This requires specifying print statements within the algorithms that normally would not be there so review where and why.
Possibly modify code to move away from ration histogram to absolute for certain cases to better understand the scale of difference.
Assessment and reflection:
To access a self-assessment rubric that relates to the Iterative Algorithms sorting component of this material please click here.
To access a form related to collecting data about the self assessment rubric that relates to the Object oriented component of this material please click here. This is limited to Edmonton Public School sign on but email to Lance Pedersen