Algorithms

Algorithms – step-by-step processes to complete a task involving computation – are a fundamental part of CS, and understanding them is foundational for further work in computing. In this Topic Area, students are exposed to high-level concepts related to algorithms.

FOUNDATIONAL CONTENT

Level	Learning Outcome
Remember	AL.1 – Define algorithm and explain what algorithms are used for^CT
Remember	AL.2 – Recognize that computational solutions take in information, store and process it, and produce a result
Understand	AL.3 – Describe the difference between traditional algorithms and artificial intelligence/machine learning (AI/ML) algorithms and, at a high level, describe how AI/ML algorithms work^CT
	AL.4 – Explain why/how sequence matters in an algorithm^CT
	AL.5 – Interpret algorithms^CT
Apply	AL.6 – Modify algorithms (e.g., to add functionality)^CT
	AL.7 – Investigate what is inside of an opaque system (i.e., a system whose operation is not transparent) when it is necessary to do so
	AL.8 – Apply principles of inclusive collaboration to a project involving the use of algorithms^IC
Analyze	AL.9 – Compare (at a high level) the trade-offs (e.g., speed, memory) of different algorithms^CT
Evaluate	AL.10 – Evaluate the appropriateness, reasonableness, and/or effectiveness of an algorithm for a specific task, including via algorithmic auditing^CT
Evaluate	AL.11 – Assess societal impacts of algorithms and related ethical issues (e.g., use of AI algorithms to choose job candidates, use of abstraction to obscure important context)^IE
Create	AL.12 – Compose algorithms using sequence, selection, and iteration^CT
Create	AL.13 – Design algorithms using principles of human-centered design^HCD

In the topic area tables, we use a system of superscripts to indicate which Pillars relate to which learning outcome:

Computational Thinking → CT
Human-Centered Design → HCD
Inclusive Collaboration → IC
Impacts and Ethics → IE

EXAMPLES OF INTEGRATING THE PILLARS AND DISPOSITIONS

Impacts and Ethics	Inclusive Collaboration	Computational Thinking	Human-Centered Design	Dispositions
Create an algorithm that designs congressional districts fairly Design algorithms for a chat room, considering content moderation policies	Swap algorithms across project groups to debug Design algorithms that support diverse identities (e.g., entering names in a form with various characters)	Decompose an algorithm Analyze how abstractions can lead to biased results from algorithms	Create algorithms that solve problems relevant to the student’s local context Test algorithm prototypes to ensure they meet users’ needs	Take an iterative approach to algorithm design – persist despite mistakes Reflect on personal experiences making trade-offs between privacy and transparency in a system’s design

Algorithms

FOUNDATIONAL CONTENT

EXAMPLES OF INTEGRATING THE PILLARS AND DISPOSITIONS

Access the Full Report