Theory and Fundamentals of Computer Science
In industry the routine digital work this course covers — scripting, spreadsheet and document automation, web production, basic troubleshooting — is now typically started by an AI assistant rather than typed from scratch, so the differentiating skill has shifted to stating the task precisely and verifying what comes back. The course keeps its applied-fluency identity but makes review, verification, and honest attribution of machine-generated work a graded part of every unit.
Current description → proposed description
This course allows the student to develop expertise in applying computer systems to a wide variety of personal and professional problems. Analysis of problems and synthesis of computerized solutions is emphasized. A unit approach allows the integration of current events, technology, concepts and practice. Selected topics include: web design; robotics; intermediate Word and Excel features; computer security; programming and scripting fundamentals; advanced issues in productivity software (e.g., data conversion, macros, objects, etc.); information management and presentation; PC design and build; and graphics.
This course develops practical fluency in applying computer systems to a wide variety of personal and professional problems at a time when routine digital work is increasingly performed with AI assistance. Analysis of problems and synthesis of computerized solutions remain the organizing emphasis, and a unit approach continues to integrate current events, technology, concepts, and practice. Units include web design, robotics, information management and presentation, computer security, graphics, PC design and build, intermediate Word and Excel features, and advanced productivity-software topics such as data conversion, macros, and objects. Programming and scripting fundamentals are taught alongside AI coding assistants, so that students learn to state a task precisely, test the result, and correct it rather than accept it. Throughout, students verify machine-generated work against authoritative sources, document the provenance of material they did not author, and recognize everyday risks such as data leakage into third-party services, fabricated output, and prompt injection in consumer AI tools.
What changes
- AI-assisted scripting with required review and correction
- Verification of generated output against sources and test cases
- Provenance and attribution of work the student did not author
- Everyday AI risk: data leakage, fabrication, prompt injection
- Accountability for delegated work as a stated outcome
6 proposed outcomes, mapped to 6 program outcomes
Each outcome below is written to be observable and assessable, and each is mapped to the program learning outcomes for which it produces evidence.
Students will be able to decompose an unstructured personal or professional problem into a written specification precise enough for a scripted solution or an AI assistant to act on.
PLO 4.2: writing the specification an AI assistant will act on is the proposing step of an AI-assisted solution, and the specification is judged by whether the resulting solution addresses the original problem.
Students will be able to construct automated solutions to repetitive tasks for a specific non-technical user's workflow using advanced productivity-software features such as data conversion, macros, and objects together with introductory AI-assisted scripting.
PLO 4.2: the student proposes an AI-assisted scripting and macro solution and then evaluates the working automation against the user's actual workflow it was meant to serve.
Students will be able to produce a working artifact in each of the course's hands-on units — web design, graphics, robotics, information management and presentation, and PC design and build — that satisfies a stated requirement set, using AI assistance where it is appropriate to the task and documenting where it was used.
PLO 4.2: each unit artifact is a proposed solution that the student must evaluate against a stated requirement set, including the judgment of where AI assistance was appropriate to the task and where it was not.
Students will be able to evaluate AI-generated code, text, and data transformations against authoritative sources and test cases, correcting defects before the output is adopted.
PLO 4.1: checking generated output against sources and tests is critical analysis of a data-driven outcome rather than acceptance of it. PLO 6.1: the student must interpret what an AI tool's output actually asserts and explain where and why it is wrong.
Students will be able to differentiate the everyday security and privacy risks of consumer computing and AI tools — credential hygiene, data leakage into third-party services, fabricated output, and prompt injection in browser and document assistants — and the safeguard appropriate to each.
PLO 4.1: pairing each named risk with the harm it produces and the safeguard that answers it is critical analysis of how these tools behave in practice, together with the ethical implications of handing data to them.
Students will be able to articulate, for a non-specialist audience, what a completed unit project does, where its limits lie, which portions were produced with AI assistance, when that delegation was appropriate, and what responsibility remains with them as the human author, evaluated against Christian commitments to truthfulness and to work as vocation.
PLO 5.3: the stated audience is explicitly non-specialist, requiring translation of technical and AI-assisted work into plain terms. PLO 5.1: disclosing which portions were machine-generated is the transparency and integrity requirement this outcome names. PLO 1.2: the CLO itself requires the student to weigh attribution and residual accountability against Christian commitments to truthfulness and vocation, which is the faith-guided judgment about transparency and accountability the PLO describes.
Program outcomes this course reaches
Filled cells are program learning outcomes with at least one supporting course learning outcome in this course. Sparse coverage is expected — no single course carries all eighteen.