20250517 SJSU_Team ISSIP_Course Final_Presentation.pptx

Using AI to standardize the
onboarding process for ISSIP
ISSIP | SJSU
Onboarding
Process

ISSIP is a nonprofit organization
that focuses on advancing
service innovation and
promoting service
development. Its current
onboarding process for new
volunteers is lacking, which is
leading to significant challenges
in integrating new members
into the organization.
PROJECT
OVERVIEW

PROJECT
OVERVIEW
IMPACT
- Scalable and standardized
onboarding process for ISSIP
- Hands-on AI instructional design
experience for students
GOAL - Create a short and effective
standardized onboarding course for
ISSIP
30 learning items across 3 sections:
1. Foundational service innovation
concepts
2. ISSIP’s structure, mission, and values
3. Engagement pathways via the Give-
Get-Grow model
- Three formats of the
onboarding course
- Pre and post tests for each
course
- Self-paced web page,
instructor led presentation, AI
prompt-based course file
CONTENT STRUCTURE
DELIVERABLES
OUR SOLUTION

WHAT
WE
ARE
WORKING
ON
Despite being red,
Mars is a cold place,
not hot. It’s full of iron
oxide dust, which
gives the planet its
reddish cast
Web-based
onboarding course
new ISSIP members
can go through from
anywhere
SELF-PACED AI TUTOR LED
INSTRUCTOR
LED
Presentation format
for a traditional way
of onboarding new
ISSIP members

IMPORTANCE OF A STANDARD
ONBOARDING COURSE FOR ISSIP
- Supports ISSIP’s Mission as a global community of
practice
- Ensures all new members begin with a shared
understanding
Benefits for New Participants
- Learn ISSIP’s core values and goals
- Understand how the community operates
- Discover ways to engage (programs, events,
platforms)
- Feel welcomed, informed, and ready to
contribute
Why it Matters
- Prevents missed opportunities and
disengagement
- Ensures consistency regardless of location or
entry point
- Replaces informal mentoring with a scalable
solution
Strategic Impact
- Enables growth via conferences, partnerships,
academic programs
- Advances ISSIP’s vision of an inclusive,
collaborative, high-impact network

DEVELOPMENT OF THE DIFFERENT
COURSE FORMAT
Self-Paced HTML Version
- Features: Modular
structure, collapsible
sections, interactive
quizzes, embedded media
- Optimized for mobile and
desktop accessibility
- (insert website/demo)
Instructor-Led PowerPoint
Version
- Features: Speaker notes,
discussion prompts, group
activities, case study slide
inserts
- Designed for synchronous
delivery
- (insert presentation)
AI-Tutor Version
- Features: Conversational
flow powered by prompt
chaining
- Allows learners to explore
topics at their own pace via
Q&A with AI
- Insert small demo

LEARNING EVALUATION TOOLS
- Pre-Test/Post-Test: Multiple-choice format
with AI-assisted explanation of answers
- Reflection Prompts: Tailored for personal
and professional goal alignment
- Optional Activities:
- Service Mapping: Visualize connections
between actors and resources in a service
system
- Idea Pitching: Structured templates for
proposing new service ideas

EVALUATION CRITERIA
- Effectiveness: Learning gains measured by
test score differences and qualitative self-
assessment
- Efficiency: Confirmed course can be
completed meaningfully within 60 minutes
- Engagement: Gauged via learner feedback
on relevance, clarity, and interactivity of
materials

CHALLENGES ENCOUNTERED
- AI Output Inconsistency:
- Tone and depth varied across sessions and tools
- Redundant phrasing and inconsistent formatting required
editorial intervention
- Prompt Tuning Took Time:
- Significant trial and error to optimize outputs
- Output quality sensitive to even minor phrasing changes
- Platform Limitations:
- Tools like Google Gemini struggled with structured formatting
(e.g., tables, slide decks)
- Testing Engagement at Scale:
- Most user feedback came from a small, familiar audience
- Broader testing would offer richer insights into diverse learner
needs
- Maintaining Version Control:
- Coordination of multiple file types (HTML, slides, prompt
documents)
- Needed better naming conventions and version-tracking tools

OUR EXPERIENCE WITH AI TOOLS
AI Tool Strengths
- Rapid ideation and draft
generation
- Simplification of complex
technical or theoretical
concepts
- Easy transformation of
content formats
- (e.g., list quiz
→ →
summary)
- Encouraged divergent
thinking and creative
framing
AI Tool Limitations
- Tendency toward vague,
repetitive, or overly
generalized language
- Struggled with logical
structure and narrative
coherence in long-form
content
- Lacked cross-section
memory, leading to
redundant or disjointed
segments
- Poor visual formatting
capabilities (e.g., slide
layout, HTML design)
Future Potential of AI Tools
- Memory & Context Tracking:
Enable better long-form
consistency
- Visual Layout Integration:
Tools that design slides,
tables, or websites with
minimal manual input
- Personalized Learning Paths:
AI adapting content based on
learner background and
preferences
- Team Prompt Collaboration:
Shared spaces for prompt
design and AI session review

HINDSIGHT
What We’d Do Differently
- Test Earlier: Incorporate feedback into early
drafts, not just final products
- Define Standards Up Front: Establish format,
length, and tone guidelines for AI outputs early
in the process
- Use Automation for Version Control: Explore
tools for managing multiple drafts with clearer
tracking
Summary and Future Guidance
- The project showcased how AI can significantly
accelerate educational content creation
- With structured workflows and prompt
refinement, AI tools become powerful creative
partners
- Documenting and sharing processes will
benefit future ISSIP teams
- Investing in better testing and feedback
systems can further boost course quality and
learner impact

20250517 SJSU_Team ISSIP_Course Final_Presentation.pptx

More Related Content

Similar to 20250517 SJSU_Team ISSIP_Course Final_Presentation.pptx (20)

More from International Society of Service Innovation Professionals (20)

Recently uploaded (20)

20250517 SJSU_Team ISSIP_Course Final_Presentation.pptx