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The projects below highlight selected examples of my work across instructional design, learning experience design, and AI-enhanced learning.
Click the arrow on the right to explore the thought process behind each project, including ideation, learner and performance analysis, learning architecture, design decisions, assessment approach, and evaluation.
These case studies provide a deeper look at how I apply learning design principles to create purposeful, engaging, and effective learning experiences.
Project #1: New Manager Feedback Training
Project #1: New Manager Feedback Training
Instructional Design │ Scenario-Based Learning │ Articulate Storyline
Role
Role
Instructional Designer
Scenario-based digital learning | Articulate Storyline
Challenge
Challenge
New managers are often expected to give feedback without having much experience conducting difficult performance conversations. They may avoid the conversation, be too vague, focus on personality rather than observable behaviour, or soften the message so much that the employee is unclear about what needs to change.
The challenge was to create a short, practical learning experience that would help new managers move from understanding effective feedback principles to actually using them in a workplace conversation.
Audience
Audience
Multilingual professionals transitioning into their first management role, particularly those working in international and multicultural environments.
Objectives
Objectives
By the end of the experience, learners should be able to:
Prepare for a feedback conversation using a practical feedback framework.
Deliver clear, specific, constructive feedback focused on observable behaviour and its impact.
Adapt their communication based on an employee's response while maintaining the purpose of the conversation.
Apply the feedback approach in realistic workplace situations.
Approach
Approach
I designed the experience around practice rather than information delivery. Learners take on the role of a new manager and make decisions during realistic workplace conversations.
The experience introduces a simple Situation → Behaviour → Impact → Next Step framework, then gives learners opportunities to apply it, receive coaching, and try again.
The instructional sequence is:
Learn → Prepare → Practice → Receive feedback → Try again → Apply
Rather than presenting one "correct" communication style, the scenarios allow learners to consider clarity, context, relationship, and cultural differences when making communication decisions.
Design
Design
The experience is being developed in Articulate Storyline and uses scenario-based interactions to simulate realistic manager–employee conversations.
Key interactions include:
Selecting how to open a difficult feedback conversation.
Choosing how directly to address a performance issue.
Responding to an employee's explanation or resistance.
Identifying effective and ineffective feedback statements.
Receiving targeted coaching based on decisions.
Revisiting the conversation and applying the feedback.
Completing an integrated final scenario.
The visual design uses a clean, contemporary workplace aesthetic with concise on-screen content, strong visual hierarchy, and dialogue-driven interactions.
Portfolio documentation will include selected Storyline screens, interaction examples, and storyboard excerpts to demonstrate both the instructional thinking and the technical execution behind the experience.
Assessment
Assessment
Assessment focuses on application and decision-making rather than recall.
Learners demonstrate their understanding by:
Identifying effective versus ineffective feedback.
Selecting appropriate responses in realistic situations.
Applying the feedback framework.
Responding appropriately to an employee's explanation or resistance.
Establishing a clear next step.
The final assessment is an integrated scenario in which learners apply the approach to a realistic feedback conversation.
Reflection
Reflection
The strongest aspect of the design is the emphasis on practice and consequence. Instead of simply telling learners what effective feedback looks like, the experience gives them an opportunity to make decisions, see the impact of those decisions, receive coaching, and try again.
One area I would continue to refine is the balance between providing a practical framework and allowing enough flexibility for different workplace cultures and communication styles. I would also use learner feedback and completion data to identify where learners struggle and refine the scenarios accordingly.
The project could be further developed into a broader professional communication and leadership learning series for Elevate English Studio.
Project #2: New Program Design & Launch
Project #2: New Program Design & Launch
Learning Experience Designer/Instructional Designer │Design Team│Higher Ed
Role
Role
Instructional Designer / Learning Experience Designer — Design Team
Challenge
Challenge
The existing pre-matriculation language program required students to participate for 20 hours per week, which made it difficult for them to take credit courses at the same time. We needed to redesign the program into a 6-hour-per-week intensive learning experience that would enable students to develop the language, academic, and university skills needed to succeed in their credit courses while progressing toward their degrees.
The challenge was not simply to reduce instructional hours. The program needed to maintain meaningful learning outcomes and prepare students for the actual performance expectations they would encounter in their undergraduate courses, while also being flexible enough to accommodate students entering the program at different points in the academic year.
From an instructional design perspective, this required balancing learner needs, performance requirements, program structure, delivery constraints, and institutional goals while creating a scalable learning experience.
Audience
Audience
The program served non-native English-speaking first-year undergraduate students from a range of faculties who were new to the Canadian university system.
Learners entered with different levels of English proficiency and different levels of familiarity with Canadian university academic expectations. The design therefore needed to support both language development and the academic behaviours required for success across disciplines.
Analysis
Analysis
We began by examining the needs of the target learners and, importantly, the performance context in which they would be expected to apply what they learned.
Rather than designing the program around language instruction alone, we analyzed credit-course syllabi to identify the underlying skills and academic behaviours students would need to succeed. This included examining what students would actually be expected to understand, produce, analyze, and do in their credit courses.
This analysis helped us identify transferable performance requirements and informed the development of learning outcomes, module structure, workshop topics, and assessment activities.
The design process therefore followed a clear instructional design progression:
Learner & Performance Needs → Analysis → Learning Outcomes → Program Architecture → Learning Experiences → Assessment → Evaluation
Design Approach
Design Approach
Based on the analysis, the design team developed learning outcomes for three modules, integrating language-learning strategies with university academic strategies.
The modules were intentionally designed to operate independently rather than sequentially. This was an important program-design consideration because students could enter the program during any module. Each module therefore needed to provide a coherent learning experience without requiring completion of a previous module.
The three modules were scheduled across three academic trimesters, with workshops offered twice weekly throughout the year. This resulted in a comprehensive year-long learning experience comprising approximately 100 three-hour workshops.
The program had to balance consistency and scalability with the need to provide meaningful, applied learning experiences across a large number of workshops.
Program Scale: 3 Modules · 3 Trimesters · ~100 Three-Hour Workshops · 6 Hours/Week
My Role
My Role
As part of the design team, I led several key components of the instructional design process, including:
Learning outcome analysis and development
Workshop calendar development
Development of dozens of three-hour workshops
Alignment of workshop content with program learning outcomes and learner needs
Development of workshop-level learning materials and instructional resources
For the workshops within my scope, I developed the lesson outcomes, materials list, student guide, instructor guide, and PowerPoint deck.
The broader program was developed collaboratively, with the design team establishing a consistent structure and approach across the full workshop series.
Learning Experience Design
Learning Experience Design
The workshops addressed two interconnected areas of learner need.
Language-Learning Strategies
Representative workshops included:
Strategies for Taking Lecture Notes at University
How to Write an Academic Essay
How to Participate in Academic Discussions
Enhancing Academic Vocabulary for University Study
University Academic Skills
Representative workshops included:
Understanding Your Credit-Course Syllabus
Time Management at University
Academic Integrity & Responsible AI Use
Test-Taking Strategies
The design intentionally connected instruction to authentic university performance. Rather than focusing only on knowing a strategy, learners were given opportunities to apply strategies to the types of tasks and situations they would encounter in their credit courses.
This approach supported the broader goal of helping learners become more capable and independent academic performers, rather than simply increasing their knowledge of English or university terminology.
Assessment
Assessment
Assessment was designed to align with the program's performance-oriented approach and to move beyond simple knowledge recall.
Activities emphasized the higher levels of Bloom's Taxonomy, particularly applying, analyzing, evaluating, and creating.
Learners applied strategies to authentic academic tasks, analyzed information and course expectations, evaluated their own approaches, and produced work demonstrating their developing skills.
Assessment therefore served two purposes: measuring learning within the program and providing practice with the kinds of thinking and performance students would encounter in their credit courses.
Implementation
Implementation
The program was implemented as a year-long learning experience, with approximately 100 three-hour workshops delivered across three modules and three academic trimesters.
The scale of the program required careful attention to consistency, workshop sequencing, learning outcomes, instructional materials, and instructor usability.
PowerPoint was an institutional requirement for workshop delivery. From an LXD perspective, I would have preferred a more interactive digital authoring environment, such as Articulate Rise, where appropriate. A digital format could have provided greater opportunities for learner interaction, practice, feedback, and learner choice while maintaining consistency across the program.
Evaluation
Evaluation
Following launch, we analyzed learner feedback and outcomes to evaluate whether the program was achieving its intended purpose.
The evaluation provided evidence of positive learner perceptions of the program's effectiveness. Students indicated that they felt the program was meeting its learning objectives and reported increased confidence that the program was preparing them for their credit courses.
This feedback was particularly important because the program's ultimate purpose was not simply language development, but helping students feel prepared to perform successfully in their undergraduate academic environment.
Reflection & ID/LXD Takeaways
Reflection & ID/LXD Takeaways
This project reinforced the importance of designing from the learner's real-world performance context.
One of the strongest elements of the process was analyzing credit-course syllabi before finalizing the learning experience. This helped us move from asking “What should we teach?” to asking “What do learners need to be able to do in order to succeed?” That shift informed the learning outcomes, program architecture, workshop topics, and assessment approach.
The project also demonstrated the importance of modular learning architecture when learner entry points cannot be controlled. Designing the three modules as independent experiences allowed the program to accommodate different student entry points without sacrificing coherence.
Finally, the scale of the project reinforced the importance of consistency, reusable design structures, and alignment. Developing approximately 100 three-hour workshops required a strong underlying architecture so that individual learning experiences could remain purposeful while contributing to a coherent overall program.
If I were redesigning the experience today, I would explore a more interactive digital delivery model. The institutional requirement to use PowerPoint provided consistency and ease of implementation, but a tool such as Articulate Rise could support richer interaction, practice, feedback, and learner choice.
Overall, the project demonstrates my ability to apply instructional design and learning experience design principles across the full design cycle—from needs and performance analysis through learning outcomes, program architecture, learning experience development, assessment, implementation, and evaluation—while working within real institutional constraints.
Project #3: AI-Powered Professional Communication
Project #3: AI-Powered Professional Communication
Role
Role
Learning Experience Designer — needs analysis, learning design, AI interaction design, prototyping, and development
AI-powered, scenario-based conversational practice experience
The project applies instructional design and learning experience design principles to an AI-powered practice environment. I led the needs analysis, definition of the performance problem, learning objectives, interaction design, feedback design, prototyping, and development of the experience.
The development process incorporated an iterative, rapid-prototyping approach, drawing on principles associated with both ADDIE and SAM: defining the performance need and objectives, developing an initial solution, testing the experience, identifying design issues, and iterating.
Challenge
Challenge
The starting point for the needs analysis was a performance need rather than a content gap.
Many working professionals understand the importance of workplace relationships but lack confidence navigating informal professional conversations, particularly small talk. Through needs analysis, I identified that uncertainty about what to say, how to respond, and how much to share can make professional interactions difficult to navigate.
The performance gap was not simply a lack of knowledge about "good small talk." Learners needed opportunities to make communication decisions in context and understand the potential impact of those decisions.
This led to a key design question: How might an AI-powered practice experience help professionals develop the judgment and confidence to navigate everyday workplace conversations?
Rather than designing a traditional instructional module explaining communication principles, I chose a practice-first approach that allows learners to experience the interaction, make decisions, and receive feedback.
Audience
Audience
Working professionals who want to develop greater confidence and skill in professional small talk and relationship-building conversations.
The audience may understand professional communication expectations conceptually but need additional practice, contextual guidance, and feedback to apply those skills in authentic situations.
Objectives
Objectives
The objectives focus on observable performance, rather than knowledge recall.
By using the experience, learners should be able to:
Select communication strategies appropriate to different professional relationships and settings.
Respond appropriately to common workplace and networking conversations.
Recognize when a response may be too formal, too personal, or otherwise mismatched to the context.
Identify opportunities to build rapport and strengthen a professional interaction.
Recognize missed opportunities and consider alternative communication choices.
Apply feedback to subsequent interactions.
Build confidence through repeated, low-risk practice.
The objectives informed the design of the scenarios, AI feedback criteria, and embedded assessment.
Approach
Approach
I designed the experience using contextualized, performance-based practice rather than content delivery alone.
The design follows an iterative learning experience model:
Define the need → establish objectives → prototype the interaction → test → refine → repeat
This reflects the structured analysis and design orientation of ADDIE, combined with the rapid prototyping and iterative refinement associated with SAM.
Professional small talk is highly dependent on context. A response that is appropriate when speaking with a close colleague may not be appropriate with a senior leader, client, or new networking contact.
For this reason, context became a core instructional variable.
Before beginning a dialogue, learners select:
Professional relationship
Setting
The AI then uses those variables to establish the conversational context.
Rather than asking learners to identify the "correct" response from predetermined options, the experience allows them to generate their own responses. This creates a more authentic practice environment and allows the learner's actual communication choices to become the basis for feedback. Feedback was designed to go beyond right/wrong judgments.
The AI coach identifies:
Effective communication choices
Potentially inappropriate or ineffective choices
Why a response may not fit the context
Alternative approaches the learner could consider
Missed opportunities to build rapport or advance the interaction
This supports formative assessment and feedback for learning, allowing learners to use the feedback to improve subsequent performance.
Design
Design
The experience uses a contextualized, iterative practice model designed to keep learners focused on the communication task while minimizing unnecessary cognitive and technical complexity.
Context → Practice → Feedback → Reflection → Reapplication
Learners select a professional relationship and setting, then engage in an AI-generated conversation. The coach evaluates their responses for appropriateness, tone, relationship dynamics, and conversational opportunities, providing immediate feedback on both effective choices and missed opportunities.
Learners can then apply that feedback to subsequent interactions, creating a cycle of practice, formative feedback, reflection, and adjustment.
This is probably the right level for the portfolio: it shows contextualization, cognitive load considerations, authentic practice, formative assessment, and iterative learning without getting bogged down in describing the mechanics.
The application was coded using Claude Code and self-hosted. Development followed an iterative prototyping process in which the interaction, AI behaviour, and feedback were refined as the experience was tested.
Assessment
Assessment
Assessment is embedded in the learning experience rather than separated into a traditional quiz.
Because the learning objectives focus on communication performance, the learner demonstrates the target skill by actually participating in simulated conversations.
The AI evaluates responses against the contextual expectations established by the selected relationship and setting.
The assessment therefore considers:
Appropriateness: Does the response fit the professional context?
Effectiveness: Does it support the purpose of the interaction?
Context sensitivity: Does the learner adapt their communication to the relationship and setting?
Opportunity recognition: Does the learner recognize opportunities to build rapport or strengthen the relationship?
The feedback functions as formative assessment, giving learners information they can immediately apply to another interaction.
A future iteration could introduce a more explicit performance rubric and longitudinal tracking so learners could see patterns across multiple conversations and monitor development over time.
Reflection
Reflection
The most successful design decision was making context a central part of the learning experience. Professional communication cannot always be reduced to universal rules; the appropriate response depends on the relationship, setting, and purpose of the interaction.
The decision to use open-ended conversational responses also increased the authenticity of the practice. Instead of recognizing a preferred answer, learners must generate a response themselves, making the experience closer to the performance they ultimately need to carry out in the workplace.
The missed-opportunity feedback was another important design decision. It expands the learning objective beyond avoiding inappropriate communication and helps learners recognize opportunities to actively build professional relationships.
The iterative development process also highlighted an important consideration in AI-powered learning design: the quality of the learning experience depends not only on the interface but on the quality and consistency of the AI's feedback. Continued development would therefore focus on refining evaluation criteria, improving feedback consistency, expanding the scenario library, and introducing a structured performance rubric.
Future iterations could also incorporate progressive difficulty, beginning with lower-stakes interactions and gradually introducing more complex relationship dynamics, networking situations, and higher-stakes professional conversations.
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