Information Technology

Big Idea(s):

• Safe work habits and lab procedures protect people, equipment, and data in IT environments.
• Ethical technology use requires understanding privacy, intellectual property, and acceptable use.
• Responsible AI use depends on human judgment, transparency, and verification.
   

Essential Question(s):

• How do safety practices like ESD prevention and ergonomics reduce risk in IT labs?
• Why are privacy, intellectual property, and acceptable use policies essential in computing?
• How can AI tools be used ethically in academic and real-world scenarios?
   

Learning Outcomes

Key Vocabulary:

• Electrostatic Discharge (ESD)

• Ergonomics

• Acceptable Use Policy (AUP)

• Digital Citizenship

• Data Privacy

• Intellectual Property

• Bias (AI)

• Ethical Use
   

Alignment:

• CompTIA ITF+/Tech+: Security concepts, professionalism, safe computing practices

• Certiport (MOS/Adobe): Digital responsibility, document ownership, accessibility awareness

• Code.org: Digital citizenship and responsible computing practices

• CodeHS: Computing ethics and safe use of technology

Big Idea(s):

• Computer systems rely on the interaction of hardware components and operating systems.

• Operating systems manage files, settings, and applications to support users.

• Structured troubleshooting leads to accurate diagnosis and effective solutions.

Essential Question(s):

• How do hardware components and operating systems work together to run a computer?

• What role does the operating system play in managing files and system resources?

• Why is a step by step troubleshooting process critical when resolving technical issues?
   

Learning Outcomes

Key Vocabulary:

• CPU, RAM, Storage (HDD/SSD)

• Motherboard

• Peripheral

• Input / Output Device

• Operating System (OS)

• File System

• Driver

• Boot Process

• Troubleshooting

• Help Desk Ticket

Alignment:

• CompTIA ITF+/Tech+: Infrastructure, hardware, operating systems, troubleshooting

• Certiport: Device readiness and system use for productivity tools

• Code.org: Understanding computing systems and how hardware/software interact

• CodeHS: Computing systems and basic troubleshooting concepts

Big Idea(s):

• Digital productivity tools support clear, accurate, and professional communication.

• Formatting and accessibility improve the effectiveness and usability of documents.

• Industry standard documentation workflows prepare students for workplace expectations.

Essential Question(s):

• How do word processing, spreadsheet, and presentation tools communicate information effectively?

• Why do formatting and accessibility standards matter in professional documents?

• How do PDF workflows support document security and information sharing?

Learning Outcomes

Key Vocabulary:

• Formatting

• Styles

• Spreadsheet

• Formula

• Cell Reference

• Accessibility

• OCR (Optical Character Recognition)

• PDF

• Encryption

• Digital Workflow
   

Alignment:

• CompTIA ITF+/Tech+: Applications and software concepts

• Certiport MOS: Word, Excel, PowerPoint foundational skills

• Certiport Adobe: Acrobat Pro document workflows and accessibility

• Code.org / CodeHS: Application of digital tools for communication

Big Idea(s):

1. Computational thinking helps break problems into logical, manageable steps.

2. Algorithms use sequencing, variables, loops, and conditionals to complete tasks.

3. Debugging is an essential process for refining programs and problem-solving strategies.

Essential Question(s):

• How does breaking a problem into steps make it easier to solve?

• Why is debugging an important part of learning to code?

• How do loops, variables, and conditionals control the behavior of a program?

Learning Outcomes

Key Vocabulary:

• Algorithm

• Sequence

• Variable

• Loop

• Conditional

• Boolean

• Debugging

• Logic Error

• Syntax

• Program

Alignment: 

• CompTIA ITF+/Tech+: Software development concepts

• Code.org: Algorithms, sequencing, conditionals, loops

• CodeHS: Introductory programming and debugging skills

Big Idea(s):

• AI systems operate using data, algorithms, and models with defined limitations.

• Effective AI use depends on well-designed prompts and clear purpose.

• AI generated outputs must be evaluated for accuracy, bias, and relevance.

Essential Question(s):

1. How do AI systems work at a basic conceptual level?

2. What makes an AI prompt effective and purposeful?

3. Why is it important to verify AI generated information before using it?
    

Learning Outcomes

Key Vocabulary:

• Artificial Intelligence (AI)

• Machine Learning

• Prompt

• Hallucination (AI)

• Bias

• Verification

• Automation

• Dataset

• Human-in-the-Loop

Alignment:

• CompTIA ITF+/Tech+: Emerging technologies and data concepts

• Certiport: Ethical and effective use of digital tools

• Code.org: AI concepts and societal impact

• CodeHS: Introductory AI and data-driven decision making

Big Idea(s):

• IT careers require both technical knowledge and professional behavior.

• Early career exploration supports informed decisions about certifications and pathways.

• Clear communication and documentation are essential workplace skills. 

Essential Question(s):

• What entry level IT careers and certifications are available in the information technology field?

• Why is professional communication important in technical environments?

• How can documenting technical work demonstrate readiness for the workplace?
   

Learning Outcomes

Key Vocabulary:

• Career Pathway

• Certification

• Resume

• Cover Letter

• Professional Communication

• Technical Documentation

• Employability Skills

• Workplace Ethics

Alignment:

• CompTIA: IT career pathways and professional practices

• Certiport: Certification readiness and workplace application

• Code.org / CodeHS: Career exploration in computer science and IT

CTECS

• Safety and Health

• Hardware and Operating Systems

• Productivity Tools

• Programming Foundations

• Emerging Technologies

• Career Development & Employability

CompTIA Alignment (Grade 9 – Pre-A+ / ITF+ / Tech+)

This course intentionally aligns to CompTIA ITF+ and Tech+ domains as a foundational, non-exam Grade 9 experience that prepares students for CompTIA A+ Core 1 and Core 2 in Grade 10.

CompTIA ITF+ / Tech+ Domains Addressed:

• IT Concepts & Terminology – hardware, software, data, and systems (Priority Standards 1 & 2)

• Infrastructure – device components, peripherals, basic networking (Priority Standard 2)

• Applications & Software – operating systems, productivity tools (Priority Standards 2 & 3)

• Software Development Concepts – algorithms, logic, variables (Priority Standard 4)

• Security – basic cybersecurity concepts, safe and ethical use (Priority Standards 1 & 5)

A+ Readiness Skills Introduced:

• Structured troubleshooting methodology

• Help desk ticket documentation

• Device and OS navigation

• Professional technical communication

ISTE Standards (Students)

• 1.1.a – Empowered Learner: Articulate learning goals using technology

• 1.2.b – Digital Citizen: Practice safe, ethical technology use

• 1.4.a – Innovative Designer: Develop algorithms and programs

• 1.5.b – Computational Thinker: Analyze data and troubleshoot systems

• 1.6.a / 1.6.b – Creative Communicator: Create professional digital artifacts

CSTA Standards

• 1B-CS-02 – Model how hardware and software work together

• 1B-AP-08 – Compare and refine multiple algorithms

• 1B-AP-12 – Use variables and control structures

• 1B-IC-18 – Discuss computing impacts and ethics

• 1B-DA-06 – Organize and visualize data

• 1B-CS-02 – Model how hardware and software work together

• 1B-AP-08 – Compare and refine multiple algorithms

• 1B-AP-12 – Use variables and control structures

• 1B-IC-18 – Discuss computing impacts and ethics

• 1B-DA-06 – Organize and visualize data

One-Page Scope & Sequence (Grade 9) 

Priority Standards → Assessment Mapping 

Big Idea(s):

• Safety, security, and ethics are foundational to all professional IT work.

• Technical decisions have legal, ethical, and human consequences.

• Secure practices reduce risk before problems occur.
   

Essential Question(s):

• How do safety and security practices protect users, data, and systems?

• What ethical responsibilities do IT professionals have when using AI and managing data?

• How do professional standards guide decision making during incidents?
   

Learning Outcomes:

Key Vocabulary:

• Malware

• Phishing

• Authentication

• Authorization

• Least Privilege

• Data Breach

• Ethics

• Compliance
   

Alignment (as applicable):

• CompTIA (per grade mapping): A+ Core 2 (220-1102) (Semester 2).

• Certiport** (ONLY if used for documentation artifacts)**: MOS Word/Adobe Acrobat optional for producing professional technical documentation (tickets, SOPs, user guides); not required for this Priority Standard.

• Code.org** / CodeHS**: Supplemental modules for cybersecurity concepts and ethical computing.

Big Idea(s):

• Hardware reliability depends on correct installation and preventive maintenance.

• Structured troubleshooting leads to efficient and accurate problem resolution.

• Documentation is essential to sustaining system support.
   

Essential Question(s):

• How do hardware components work together to support user needs?

• Why is a systematic troubleshooting process critical in IT support?

• How does documentation improve future maintenance and support?

Learning Outcomes:

Key Vocabulary:

• BIOS/UEFI

• POST

• Power Supply (PSU)

• Expansion Card

• Cooling System

• Preventive Maintenance

Alignment (as applicable):

• CompTIA (per grade mapping): A+ Core 2 (220-1102)** (Semester 2).

• Certiport** (ONLY if used for documentation artifacts)**: MOS Word/Adobe Acrobat optional for producing professional technical documentation (tickets, SOPs, user guides); not required for this Priority Standard.

• **Code.org / **CodeHS: Supplemental modules for cybersecurity concepts and ethical computing.

Big Idea(s):

• Operating systems manage resources, security, and user interaction.

• Software stability depends on correct configuration and updates.

• Virtualization enables safe testing and flexible system management.
   

Essential Question(s):

• How do operating systems control and protect computing environments?

• What causes software failures, and how can they be prevented?

• Why is virtualization valuable for troubleshooting and system planning?

Learning Outcomes:

Key Vocabulary:

• Virtual Machine

• Hypervisor

• Patch Management

• User Account Control

• Registry

• System Image
   

Alignment (as applicable):

• CompTIA (per grade mapping): A+ Core 2 (220-1102) (Semester 2).Core 2 exam window: mid to late Semester 2.

• Certiport: Only if appropriate for documentation/productivity artifacts (e.g., MOS Word for configuration notes; PDF workflows for user guides). Not required for OS mastery.

• CodeHS: Supplemental OS concepts modules (optional).

Big Idea(s):

• Networks enable communication between devices and users.

• Connectivity problems often have multiple possible causes.

• Foundational networking knowledge prepares students for advanced infrastructure work.

Essential Question(s):

• How do data and devices move across a network?

• What steps should be taken to diagnose connectivity issues?

• Where does A+ networking end and Network+ networking begin?

Learning Outcomes:

Key Vocabulary:

• TCP/IP

• DNS

• DHCP

• Router

• Switch

• Wi-Fi Standards

• Network Topology
   

Alignment (as applicable):

• CompTIA (per grade mapping): A+ Core 2 (220-1102) (Semester 2) plus introductory Network+ coverage (N10-008/N10-009) in Semester 2.

• Certiport: Not applicable.

• **Code.org / **CodeHS: Supplemental lessons for Internet concepts, protocols, and network troubleshooting.

Big Idea(s):

• AI can enhance productivity but requires human verification.

• Automation improves efficiency while introducing new risks.

• Ethical use of AI is a professional responsibility.

Essential Question(s):

• How can AI support troubleshooting without replacing human judgment?

• What risks arise when automation is used incorrectly?

• How should IT professionals verify AI generated recommendations?

Learning Outcomes:

Key Vocabulary: 

• Automation 

• Prompt Engineering 

• AI Bias 

• Verification 

• Workflow 

• Human Oversight 

Alignment (as applicable):

• CompTIA: Not listed as a standalone CompTIA course in the Grade 10 pacing; integrated as an instructional overlay during **A+ Core ****1/Core ****2 **labs to strengthen troubleshooting, documentation quality, and verification habits.

• Certiport: Not applicable (unless students are creating optional documentation artifacts in Word/PDF).

• Code.org** / CodeHS**: Supplemental AI/data literacy and automation concept modules ****.

Big Idea(s):

• Technical skills must be paired with professionalism and communication.

• Industry certifications validate knowledge and readiness.

• Career preparation is an ongoing, reflective process.

Essential Question(s):

• How do certifications support career and postsecondary pathways?

• What professional behaviors are expected in IT workplaces?

• How can students evaluate their readiness for industry exams and careers?

Learning Outcomes:

Key Vocabulary:

• Certification

• Service Level Agreement (SLA)

• Professionalism

• Resume

• Career Pathway

Alignment (as applicable):

• CompTIA (per grade mapping): **A+ Core **1 (220-1101) certification window late Semester 1 and **A+ Core **2 (220-1102) certification window mid to late Semester 2.

• Certiport: Optional / student-choice only (use if your program expects MOS/Adobe credentials; not required for A+ readiness).

• Code.org / CodeHS: Career exploration, technical communication practice, and portfolio/capstone support.

Big Idea(s):

• OSHA-aligned safety practices protect people, equipment, and learning environments.

• Safety leadership builds accountability and professionalism in technical settings.

• Safe work habits reduce risk during repair, troubleshooting, and lab operations.

Essential Question(s):

• What are the essential safety procedures for working in an IT shop?

• How does OSHA support workplace health and safety?

• How can students model safety leadership in a shop setting?

Learning Outcomes:

Technical Vocabulary

OSHA, PPE, Ergonomics, MSDS/SDS, Lockout/Tagout, Hazard, Compliance, Fire Safety, ESD, Risk Assessment

Credential / Platform Alignment

• Credential: OSHA 10

• CompTIA: Professional safety expectations

• Certiport: Not applicable

• CodeHS / Code.org: Not applicable

Big Idea(s):

1. Programming is a structured process for solving real-world problems.

2. Well-designed code emphasizes readability, reuse, and efficiency.

3. Debugging and testing are essential for reliable software development.

Essential Question(s):

• How do functions, loops, and conditionals work together?

• What makes code efficient and reusable?

• How do programmers test and debug software?

Learning Outcomes:

Technical Vocabulary 

Function, Loop, Array, Object, Method, Class, Condition, Debug, Algorithm, Parameter, IDE 

Credential / Platform Alignment 

• CompTIA: Tech+ (coding foundations) 

• Certiport: ITS – JavaScript 

• CodeHS: Programming Pathway + platform certifications 

• Code.org: CS Principles Units 4–5 

Big Idea(s):

• Game engines combine programming and visual design. 

• Scripts, physics, and input systems control interactivity. 

• Playtesting and publishing transform prototypes into finished products. 

Essential Question(s):

• What components make up a Unity game scene? 

• How do scripts control gameplay behavior? 

• What makes a game publishable and user-friendly? 

Learning Outcomes:

Technical Vocabulary

Scene, Asset, Prefab, Rigidbody, Script, Collider, Input, UI, Build, Export, Transform

Credential / Platform Alignment

• CompTIA: Not applicable

• Certiport: Not applicable

• CodeHS: Unity modules

• Code.org: Not applicable

Big Idea(s):

1. Organized data enables accurate analysis and insights.

2. Visualizations communicate patterns and trends clearly.

3. Dashboards support technical and business decision-making.

Essential Question(s):

• How is data collected and organized?

• What insights can be found in datasets?

• How do dashboards support decisions?

Learning Outcomes:

Technical Vocabulary

Dataset, Filter, Chart, Graph, Pivot Table, Dashboard, Visualization, Correlation, Trend, Spreadsheet

Credential / Platform Alignment

• CompTIA: Tech+ (data concepts)

• Certiport / CodeHS / Code.org: Not specified

Big Idea(s):

• Structured troubleshooting improves technical support outcomes.

• Professional communication builds trust with users

• Documentation ensures consistency and accountability.

Essential Question(s):

• How do help desk systems operate?

• What makes a support technician effective?

• How are Chromebooks maintained and repaired?

Learning Outcomes:

Technical Vocabulary 

Ticket, Workflow, Troubleshoot, Warranty, Diagnostic, Powerwash, Asset Tag, SLA, Reimage

Credential / Platform Alignment

• CompTIA: A+ Core 1 & Core 2

• Certiport / CodeHS / Code.org: Not specified

Big Idea(s):

• Emerging technologies drive innovation and new careers.

• New technologies introduce ethical and societal challenges.

• Responsible innovation requires evaluation of risks and benefits.

Essential Question(s):

• What technologies are emerging today?

• How do new technologies impact society?

• What responsibilities come with innovation?

Learning Outcomes:

Technical Vocabulary

AI, IoT, Blockchain, Quantum Computing, Biotechnology, Automation, Ethics, Disruption, Prototype
 

Credential / Platform Alignment

• CompTIA: Tech+ (future technology concepts)

• CodeHS: Emerging Technologies course

Big Idea(s):

• Networks enable communication between devices and systems.

• Network design impacts performance and security.

• Diagnostic tools provide evidence for troubleshooting.

Essential Question(s):

• How do networks function?

• How does data travel across networks?

• How are networks maintained and secured?

Learning Outcomes:

Technical Vocabulary

LAN, WAN, IP Address, MAC Address, Router, Switch, Packet, Protocol, DHCP, DNS, Ethernet, Firewall

Credential / Platform Alignment

• CompTIA: Network+

• CodeHS: Networking modules

Big Idea(s):

• Server-based systems centralize control and access.

• Permissions and policies protect systems and data.

• Virtualization supports scalability and efficiency.

Essential Question(s):

• How do directory services manage access?

• How are permissions applied?

• What are the differences between client and server OS?

Learning Outcomes:

Technical Vocabulary

Server, Domain, Client, Active Directory, Group Policy, Permissions, Authentication, File Sharing, OU, DNS

Credential / Platform Alignment

• CompTIA: A+ (Core 2), Tech+, pathway to Server+/Cloud+

Big Idea(s):

• Scripting automates repetitive tasks.

• Sensors and logic enable intelligent systems.

• Testing improves automation reliability.

Essential Question(s):

• How does scripting support automation?

• How do sensors influence decisions?

• How is automation tested and refined?

Learning Outcomes:

Technical Vocabulary

Script, Loop, Condition, Variable, Sensor, Actuator, Automation, Logic, Flowchart, Debug

Credential / Platform Alignment

• CompTIA: Linux+ (automation exposure)

• CodeHS: Robotics & Automation modules

Big Idea(s):

• Identifying vulnerabilities strengthens system security.

• Ethical guidelines define responsible cybersecurity work.

• Reporting and mitigation reduce future risk.

Essential Question(s):

• What cybersecurity threats exist?

• How is penetration testing conducted ethically?

• How are vulnerabilities reported and mitigated?

Learning Outcomes:

Technical Vocabulary

Threat, Vulnerability, Exploit, Firewall, Penetration Testing, Ethical Hacking, Social Engineering, Port Scan, Encryption

Credential / Platform Alignment

• CompTIA: Security+

• CodeHS: Cybersecurity modules

Big Idea(s):

• AI systems rely on data, models, and algorithms to make decisions.

• Machine learning models are built, trained, tested, and refined.

• Responsible AI development requires technical accuracy and ethical judgment.

Essential Question(s):

• How do machine learning models learn from data?

• How does data quality affect model performance?

• How can AI systems be tested, evaluated, and improved?

Learning Outcomes:

Credential / Platform Alignment

• CompTIA Tech+ (AI concepts)

• CodeHS AI / ML modules

• Prepares for Grade 12 advanced AI, data science, or cybersecurity analysis

Big Idea(s):

• Professional success requires technical skill, leadership, and communication.

• Capstone experiences demonstrate real-world problem solving and accountability.

• Industry credentials validate readiness for employment and postsecondary pathways.

• AI can support professional growth, reflection, and preparation when used ethically.

Essential Question(s):

• How do professionals communicate technical knowledge effectively?

• What responsibilities do mentors and leaders have in technical environments?

• How does a capstone project demonstrate career readiness?

• How can AI support career planning and certification preparation responsibly?

Learning Outcomes:

Technical Vocabulary

Capstone, Portfolio, Certification, Mentorship, Leadership, Interview, Resume, Artifact, Professional Practice, Reflection

Vision of the Graduate

Work Ready – Effective Communicator – Ethical Leader – Lifelong Learner

Credential & Framework Alignment

• CompTIA: Network+, Security+ (exam preparation)

• Cisco: CCNA (optional pathway)

• Certiport: MOS (professional documentation and productivity)

• AI Integration: AI supported career planning, interview prep, and capstone reflection

Big Idea(s):

• Cybersecurity protects systems, data, and people at scale.

• Risk management balances security, usability, and organizational needs.

• Ethical decision making is critical in cybersecurity practice.

• AI plays a growing role in threat detection and analysis.

Essential Question(s):

• How do organizations identify and manage cybersecurity risk?

• What ethical responsibilities do cybersecurity professionals hold?

• How can AI support cybersecurity without increasing risk or bias?

Learning Outcomes:

Technical Vocabulary

Risk Assessment, Threat Actor, Vulnerability, Incident Response, Encryption, Zero Trust, SIEM, AI Security

Vision of the Graduate

Critical Thinker – Ethical Citizen – Problem Solver

Credential & Framework Alignment

• CompTIA: Security+

• CodeHS: Cybersecurity pathway

• Cisco / TestOut: Network Security modules

• AI Integration: AI assisted threat modeling and incident analysis

Big Idea(s):

• AI is a powerful tool that augments, not replaces, human decision making.

• Responsible AI use requires understanding limitations, bias, and ethics.

• Emerging technologies shape future careers and industries.

Essential Question(s):

• How do AI systems generate outputs and where do they fail?

• What ethical considerations guide AI use in education and industry?

• How do emerging technologies impact careers and society?

Learning Outcomes:

Technical Vocabulary

Artificial Intelligence, Model, Bias, Hallucination, Prompt, Automation, Ethics, Emerging Technology

Vision of the Graduate

Critical Thinker – Responsible Innovator – Lifelong Learner

Credential & Framework Alignment

• CompTIA: AI concepts embedded in A+, Security+

• CodeHS / Code.org: AI and data concepts

• AI Integration: AI Prompting Essentials; AI Help Desk workflows

Big Idea(s):

• Enterprise systems require automation, monitoring, and documentation.

• Advanced infrastructure supports scalability and resilience.

• AI can enhance system administration and operational efficiency.

Essential Question(s):

• How do organizations manage complex IT systems?

• Why is automation essential at enterprise scale?

• How can AI assist system administration responsibly?

Learning Outcomes:

Technical Vocabulary

Enterprise Systems, Automation, Scripting, Monitoring, Virtualization, Infrastructure, Documentation

Vision of the Graduate

Problem Solver – Work Ready – Technically Proficient

Credential & Framework Alignment

• CompTIA: Network+, Server+, Security+

• TestOut: Hybrid Server Pro

• AI Integration: AI assisted scripting and system analysis

Big Idea(s):

• AI systems rely on high quality data, algorithms, and engineered features.

• Data preparation and pipeline design directly affect model performance and reliability.

• Foundational AI concepts support advanced machine learning and enterprise integration.

• Responsible AI development begins with data integrity and transparency.

Essential Question(s):

• How does data quality influence AI system outcomes?

• What roles do algorithms and features play in model behavior?

• Why are pipelines critical for scalable and repeatable AI workflows?

• How can foundational AI decisions introduce or reduce bias?

Learning Outcomes:

Technical Vocabulary

Data, Dataset, Structured Data, Unstructured Data, Algorithm, Feature Engineering, Pipeline, Normalization, Bias, Training Data

Vision of the Graduate

Critical Thinker – Responsible Innovator – Technically Proficient

Credential & Framework Alignment

• CompTIA: AI concepts embedded in A+, Data+, Security+

• CodeHS / Code.org: AI Foundations and Data Concepts

• AI Integration: Dataset preparation, feature engineering, pipeline documentation

Big Idea(s):

• Machine learning models learn patterns from data through training and evaluation.

• Model performance must be measured, validated, and optimized.

• Deployment introduces real-world constraints and risks.

• Continuous monitoring is required to maintain reliability over time.

Essential Question(s):

• How do different machine learning approaches affect outcomes?

• What metrics best evaluate model effectiveness?

• What risks emerge when models are deployed?

• How do professionals balance performance, efficiency, and resources?

Learning Outcomes:

Technical Vocabulary

Machine Learning, Supervised Learning, Unsupervised Learning, Model, Training, Validation, Accuracy, Precision, Recall, Drift

Vision of the Graduate

Problem Solver – Critical Thinker – Lifelong Learner

Credential & Framework Alignment

• CompTIA: Data+, AI concepts embedded in Security+

• CodeHS: Machine Learning Pathways

• AI Integration: Model training, evaluation metrics, drift monitoring

Big Idea(s):

• Ethical AI requires governance, accountability, and transparency.

• AI systems can reinforce inequities without intentional safeguards.

• Regulatory and organizational policies guide responsible AI use.

• Documentation and explainability support trust and compliance.

Essential Question(s):

• Who is responsible for AI system outcomes?

• How can transparency reduce risk and misuse?

• What governance structures guide ethical AI deployment?

• How do professionals promote fairness in AI systems?

Learning Outcomes:

Technical Vocabulary

Governance, Accountability, Transparency, Interpretability, Compliance, Equity, Fairness, Explainability, Policy

Vision of the Graduate

Ethical Citizen – Responsible Innovator – Effective Communicator

Credential & Framework Alignment

• CompTIA: Security+, Ethics domains

• ISTE: Ethical AI Practices

• AI Integration: AI policy analysis, ethics case studies, governance documentation

Big Idea(s):

• AI systems introduce unique security vulnerabilities.

• Protecting data and models is critical to system integrity.

• Adversarial threats require specialized defenses.

• Monitoring and response sustain long-term AI resilience.

Essential Question(s):

• How are AI systems attacked and exploited?

• What controls protect AI data and models?

• How do organizations test AI system resilience?

• Why is continuous monitoring essential for AI security?

Learning Outcomes:

Technical Vocabulary

Adversarial Attack, Data Poisoning, Model Inversion, Integrity, Access Control, Resilience, Monitoring, Incident Response

Vision of the Graduate

Problem Solver – Ethical Citizen – Technically Proficient

Credential & Framework Alignment

• CompTIA: Security+

• Cisco / TestOut: Network and Security Concepts

• AI Integration: AI threat modeling, adversarial testing, security monitoring

Big Idea(s):

• AI systems must integrate seamlessly with enterprise environments.

• Automation reshapes workflows and professional roles.

• Validation ensures reliability and trust.

• Long-term maintenance sustains system value.

Essential Question(s):

• How do AI systems integrate with existing infrastructure?

• What operational changes result from AI automation?

• How are integrated systems validated and maintained?

• How do professionals manage AI systems over time?

Learning Outcomes:

Technical Vocabulary

Integration, Interoperability, Automation, Validation, Scalability, Version Control, Maintenance, Performance Monitoring

Vision of the Graduate

Work Ready – Problem Solver – Technically Proficient

Credential & Framework Alignment

• CompTIA: Network+, Server+, Security+

• TestOut: Enterprise and Automation Modules

• AI Integration: AI driven workflows, enterprise system validation

Big Idea(s):

• Culminating  Content Topic  project demonstrate full AI workflows and professionalism.

• Real-world problems require ethical, secure, and effective AI solutions.

• Evaluation and iteration strengthen technical outcomes.

• Culminating  Content Topic  project validate workforce and postsecondary readiness.

Essential Question(s):

• How can AI solve authentic problems responsibly?

• How do professionals justify technical design decisions?

• What metrics demonstrate solution effectiveness?

• How does a capstone project show career readiness?

Learning Outcomes:

Technical Vocabulary

Capstone, Prototype, Workflow, Deployment, Metrics, Evaluation, Documentation, Artifact, Professional Presentation

Vision of the Graduate

Work Ready – Critical Thinker – Responsible Innovator – Effective Communicator

Credential & Framework Alignment

• CompTIA: Data+, Security+ (capstone alignment)

• Certiport: MOS (documentation and presentation)

• AI Integration: End to end AI solution design, professional defense, portfolio artifacts