Learning Paths by Role
Learning Paths by Role
Not sure where to start? Find your role below and follow a curated sequence of workshops and self-paced topics.
Everyone begins with Workshop 1: Foundations & Capabilities and Workshop 2: Workflow Enhancement — they cover the prompting basics and Drexel data rules that everything else builds on. After that, your path depends on what you do.
Pick the role closest to yours, then work through the recommended sequence. Each entry links to either a workshop page or a self-paced track topic. You don’t have to do them all — start with the ones marked start here and add from there.
Admin & Operations Staff
You manage schedules, budgets, reports, events, accreditation documents, and communications. AI helps most with drafting, reformatting, and summarizing — the recurring tasks that eat your week.
| Order | Topic | Type | Why it matters for you |
|---|---|---|---|
| 1 | Workshop 1: Foundations | Workshop | Prompting basics and data rules — start here |
| 2 | Workshop 2: Workflow Enhancement | Workshop | Copilot in Word, Outlook, Excel for daily tasks |
| 3 | Data Security & Classification | Self-paced | You handle student records, budgets, and HR data — classification matters |
| 4 | Verifying AI Output | Self-paced | Catch errors before they reach a report or accreditation document |
| 5 | Workshop 3: Collaboration on Projects | Workshop | Reusable prompts and shared templates for your team |
| 6 | Design & Visual Communication | Self-paced | Flyers, event materials, and accessible visuals |
| 7 | Responsible AI | Self-paced | Disclosure norms and accountability for AI-assisted work |
| 8 | Grant Administration with AI | Self-paced | Deadline tracking, compliance checks, and budget formatting |
Workshops 1–3 plus Data Security and Verifying Output cover 80% of what admin staff need. The rest is useful but not urgent.
Research Staff & Coordinators
You manage data, run analyses, coordinate IRB submissions, track grant deadlines, and draft reports. AI accelerates the data pipeline and the writing that surrounds it.
| Order | Topic | Type | Why it matters for you |
|---|---|---|---|
| 1 | Workshop 1: Foundations | Workshop | Prompting basics and data rules — start here |
| 2 | Workshop 2: Workflow Enhancement | Workshop | Summarizing, drafting, and formatting in your daily tools |
| 3 | Data Cleaning | Self-paced | Diagnose and fix messy data faster |
| 4 | Data Security & Classification | Self-paced | You work with identifiable data — know the boundaries |
| 5 | De-identification & Synthetic Data | Self-paced | Make data safe for tools or sharing |
| 6 | Coding with AI | Self-paced | Generate, debug, and translate code (R, Stata, Python) |
| 7 | Statistical Interpretation | Self-paced | Translate models across languages and interrogate output |
| 8 | Verifying AI Output | Self-paced | Catch fabricated citations and wrong statistics |
| 9 | Workshop 3: Collaboration on Projects | Workshop | Reusable prompts for recurring research tasks |
| 10 | Literature Review | Self-paced | Search strategy and evidence synthesis |
Start with Workshops 1–2, then Data Cleaning and Data Security. Add Coding with AI and Statistical Interpretation once you’re comfortable.
Teaching Faculty
You design courses, write syllabi, create assignments, advise students, and communicate findings to multiple audiences. AI helps with content creation, assessment design, and plain-language translation.
| Order | Topic | Type | Why it matters for you |
|---|---|---|---|
| 1 | Workshop 1: Foundations | Workshop | Prompting basics and data rules — start here |
| 2 | Workshop 2: Workflow Enhancement | Workshop | Drafting, summarizing, and formatting for teaching tasks |
| 3 | Science Communication | Self-paced | Translate findings for students and the public |
| 4 | Verifying AI Output | Self-paced | Model verification habits for your students |
| 5 | Workshop 6: AI for Curriculum Development | Workshop | Assignment design and AI policies for your courses |
| 6 | Writing Your Course AI Policy | Self-paced | A clear, enforceable policy for your syllabus |
| 7 | Assignment & Assessment Design | Self-paced | Assignments that work with or despite AI |
| 8 | Responsible AI | Self-paced | Disclosure norms — for you and your students |
| 9 | AI Bias & Health Equity Audit | Self-paced | Teach students to test AI across groups |
| 10 | Multilingual Materials | Self-paced | Translate and adapt materials for diverse learners |
Workshops 1–2, then Science Communication and Verifying Output. Before fall semester, complete Workshop 6 and the Course AI Policy topic.
Research Faculty (PI / Co-I)
You design studies, write grants, publish papers, and lead research teams. AI helps most with writing, literature synthesis, and methods — but the stakes of errors are high.
| Order | Topic | Type | Why it matters for you |
|---|---|---|---|
| 1 | Workshop 1: Foundations | Workshop | Prompting basics and data rules — start here |
| 2 | Workshop 2: Workflow Enhancement | Workshop | Drafting and summarizing in your daily tools |
| 3 | Literature Review | Self-paced | Search, synthesize, and verify — not fabricate |
| 4 | Verifying AI Output | Self-paced | Catch hallucinated citations before they reach a manuscript |
| 5 | Grant Proposal Development | Self-paced | Draft aims, abstracts, and reviews of your own work |
| 6 | Manuscript Preparation & Peer Review | Self-paced | Tighten manuscripts and structure reviewer responses |
| 7 | Statistical Interpretation | Self-paced | Translate models and interrogate output |
| 8 | AI Bias & Health Equity Audit | Self-paced | Test for disparities in AI-assisted analyses |
| 9 | Responsible AI | Self-paced | Disclosure, accountability, and governance frameworks |
| 10 | Coding with AI | Self-paced | Generate and debug analysis code |
Workshops 1–2, then Literature Review and Verifying Output. Add Grant Proposal Development and Manuscript Prep when you’re writing.
Practice & Community-Facing Roles
You work with communities, run programs, create outreach materials, or do practice-based work. AI helps with communication, evaluation, and materials — but cultural competence and community trust are non-negotiable.
| Order | Topic | Type | Why it matters for you |
|---|---|---|---|
| 1 | Workshop 1: Foundations | Workshop | Prompting basics and data rules — start here |
| 2 | Workshop 2: Workflow Enhancement | Workshop | Drafting and formatting for outreach materials |
| 3 | Science Communication | Self-paced | Plain-language materials for community audiences |
| 4 | Multilingual Materials | Self-paced | Translate and culturally adapt, not just swap words |
| 5 | Design & Visual Communication | Self-paced | Flyers, social posts, and accessible visuals |
| 6 | Program Evaluation | Self-paced | Logic models and evaluation plans for your programs |
| 7 | AI Bias & Health Equity Audit | Self-paced | Test AI for disparities before using it with communities |
| 8 | Verifying AI Output | Self-paced | Don’t let AI errors reach communities |
| 9 | Data Security & Classification | Self-paced | Community data is often sensitive — know the rules |
| 10 | Keeping Your Judgment | Self-paced | Community relationships require human judgment, not AI shortcuts |
Workshops 1–2, then Science Communication and Multilingual Materials. AI Bias & Equity Audit is essential before deploying any AI-assisted tool in a community context.
Mentoring & Advising
You advise students, mentor junior colleagues, write recommendation letters, and navigate sensitive conversations. AI can help with some of these tasks, but judgment, confidentiality, and the personal relationship are paramount.
| Order | Topic | Type | Why it matters for you |
|---|---|---|---|
| 1 | Workshop 1: Foundations | Workshop | Prompting basics and data rules — start here |
| 2 | Workshop 2: Workflow Enhancement | Workshop | Drafting and summarizing for advising tasks |
| 3 | AI in Mentoring & Advising | Self-paced | Where AI helps and where it has no place |
| 4 | Responsible AI | Self-paced | Disclosure norms — when to tell a student AI helped |
| 5 | Data Security & Classification | Self-paced | Student records are FERPA-protected — know the limits |
| 6 | Verifying AI Output | Self-paced | Don’t pass AI errors along to advisees |
| 7 | Keeping Your Judgment | Self-paced | Mentoring is a human relationship — keep it that way |
| 8 | Writing Your Course AI Policy | Self-paced | Help students understand where AI is and isn’t appropriate |
Workshops 1–2, then Mentoring & Advising and Responsible AI. Data Security is essential for anyone handling student records.
Start with Workshops 1 and 2 — everyone needs those. Then try the Verifying AI Output topic (it applies to every role) and explore from there. If your role spans multiple paths, pick topics from each that match your actual work.