Rice Cooker Task Analysis
In Methods for Human Factors Engineers (ENP 64) class, we were instructed to perform a cognitive and behavioral task analysis on an "expert" and a "novice" on a task.
Why a Rice Cooker?
As someone who considers themselves an expert on rice cooking, I’ve always found joy in the process. The Muji rice cooker, with its minimalist design, simple interface, and cube shape, has become a product I deeply love and use regularly. My connection with cooking rice started in childhood, learning from my mom how to wash and prepare rice—a task that still brings me satisfaction. Given my passion for the product and the nostalgic joy it evokes, I decided to analyze the task of using a rice cooker, specifically the Muji model
Why Task Analysis is Important
Task analysis breaks down complex processes into smaller, more manageable steps, allowing us to understand the differences in accuracy, efficiency, and cognitive load at varying experience levels. By uncovering the actions and decisions made by both experts and novices, task analysis can inform product design, improving the overall user experience. This project provided insights into the specific challenges faced by different users when interacting with the same product.
The Process
I conducted dynamic interviews, observing the behaviors of two participants: an expert and a novice, while simultaneously asking questions to uncover the rationale behind their actions. This dual approach allowed me to analyze how their levels of familiarity influenced their interaction with the rice cooker.
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I used Figma to visually display these different flows as shown below.
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Interviewees + Analysis
The Expert: A 20-year-old who uses a rice cooker several times a week. Confident and familiar with the process, she intuitively measured rice and water, operated the cooker, and anticipated when the rice would be ready, showing a deeper engagement with each step.
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The Novice: A 20-year-old who rarely uses a rice cooker and typically cooks rice on the stove. She relied heavily on external instructions and faced uncertainty with the water-to-rice ratio and whether the process had started, demonstrating a need for clearer feedback from the cooker.
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Through observing the expert's confidence and the novice's uncertainty, I gained insight into how user experience varies based on familiarity. The expert engaged deeply and navigated the process smoothly, while the novice relied on external instructions and struggled with steps like the water-to-rice ratio and confirming the cooker had started.
Reflections
It’s important to note that my findings apply only to the Muji rice cooker I used for this study, and not all rice cookers follow the same process. For instance, some rice cookers use a 1:1 water-to-rice ratio, which would align with the novice’s assumption in this case. Additionally, many rice cookers—like the one I grew up with—play a song to signal the start of the cooking process. This feature could have reduced the confusion the novice experienced with the Muji model, which only displays a countdown timer 13 minutes before the rice is ready. These observations highlight how subtle design variations can significantly impact the user experience.
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​If I were to conduct a more comprehensive study, I would include a larger pool of participants with varying levels of expertise and potentially use a more common rice cooker model. Expanding the study would offer broader insights and help identify key design improvements that could benefit a wider range of users.
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