A.2: Course Project : Mid-term Pecha Kucha Presentation

📅 Submit by: 2026.03.18 ⏰ 00:00 (Midnight before class)

📤 Upload your slides here:
CCAI9012 Pecha Kucha Submission Form

Slides must be submitted in PowerPoint format so we can combine all presentations into a single deck before class. Late submissions may delay the setup of the session.

Format

The midterm presentation follows a Pecha Kucha format.

• 20 slides
• 20 seconds per slide (auto-advance)
• Total duration: approximately 6 minutes 40 seconds

Slides should be primarily visual, with minimal text.
Each presentation will be followed by a short discussion and peer feedback session.
The goal is to communicate ideas clearly and efficiently through images, diagrams, and structured visual storytelling.

A PowerPoint template is available for teams who would like a starting point:
Template download: CCAI9012 Pecha Kucha Template.
Please use the title slide provided in the template.
The remaining slides can be organised and formatted freely to best communicate your project.

⚠️ Please arrive on time and be ready when your team is called.
The review session will run through 7 teams consecutively.

To keep the session on schedule:

• presentations must not exceed the Pecha Kucha duration
• each team will receive approximately 5 minutes of discussion

Staying within the time limit allows every team to receive fair feedback.

What Your Presentation Should Communicate

Teams should use the presentation to communicate the current state of the project.

• Problem or Opportunity

    – What issue, question, or design opportunity is the project addressing?
    – Why is this problem meaningful or worth exploring?

• Proposed AI-Assisted Approach

    – What type of system, workflow, or AI-assisted process are you proposing?
    – How does AI contribute to the design or investigation?

• Preliminary Thinking

    – Early ideas about data, model behaviour, or responsibility considerations.

• Early Results and Design Decisions

    – Experiments, tests, or design explorations completed so far.
    – Decisions that are currently guiding the project direction.

• Open Questions and Challenges

    – Uncertainties that remain unresolved.
    – Technical, conceptual, or ethical risks.

Expectations

The emphasis is on clarity and structure, not completeness.

Your presentation should:

    • what the project is attempting
    • why the project matters
    • where feedback is most needed

Discussion and Feedback

Each presentation will be followed by a short discussion and peer feedback session.

Teams are expected to:

The midterm review is intended to help strengthen the direction of your project before the final submission.

Grading Criteria

In a nutshell

We are not grading:

We are grading:

Criterion What It Means
Problem Framing Is the problem or opportunity clearly defined, bounded, and situated in context?
System Concept Is the proposed AI-assisted approach understandable, coherent, and plausibly aligned with the problem?
Process Thinking Do you demonstrate structured thinking about workflow, methods, and experimentation (i.e., how you will build, test, and iterate)?
Integration Do you reason critically about how mechanisms, datasets, and responsibility interact in the creation and use of the system?
Communication Are ideas communicated clearly through visuals and a coherent spoken narrative?

Rubric

Criterion Excellent Adequate Insufficient
Problem Framing Clear, specific, well-motivated problem with appropriate scope and constraints Problem identifiable but somewhat broad, vague, or under-scoped Problem unclear, overly broad, or poorly motivated
System Concept System/workflow clearly articulated with logical structure and clear role of AI Approach described but with gaps in structure, feasibility, or AI role clarity Approach confusing, inconsistent, or not clearly AI-assisted
Process Thinking Clear plan for methods and experimentation; shows iterative logic (what will be tested, how, and why) Some plan or early experiments shown, but methodology is underdeveloped Little evidence of planned or executed experimentation; process is ad hoc
Integration Thoughtful early synthesis of mechanisms + datasets + responsibility, with clear implications for design decisions Mentions these dimensions but connections are shallow or unclear Treats dimensions separately or ignores one or more; no critical reasoning
Communication Strong visual storytelling; minimal text; clear pacing; narrative makes feedback needs explicit Understandable but uneven; some text-heavy slides or unclear transitions Hard to follow; too dense; visuals do not support the narrative