Progressively disclose analytical depth: start beginners with streamlined visual interfaces, then introduce richer analytical tools as expertise grows¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The article recommends that educational simulations match support to learner expertise. To avoid overwhelming beginner-level users, "the system should initially offer a streamlined, visual interface that minimizes information density and fosters motivation." As users gain expertise, richer analytical tools and data granularity are introduced, creating "a scaffold that guides all users from initial engagement toward deeper analytical understanding." This follows from the observed split between beginners relying on visual cues and advanced users thriving in the Analysis Console.

Design Implications¶

Context¶

Requirements¶

• The system must offer both lightweight visual status cues and deeper analytical dashboards that can be introduced as learner expertise develops.

Constraints¶

• Grounded in a small qualitative case study of user-study participants; the authors attribute the preference divergence to prior domain knowledge and cognitive load.

Target Learners¶

• beginner-to-advanced university students in simulation-based courses

Target Learning Goals¶

• sustained engagement and progression toward analytical mastery

Related Strategies¶

Examples¶

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Key Sources¶

• Yanjia Li, Kelcy Kexin Han, Tianrui Hu, Yi-Fan Cao, Huamin Qu, Sicheng Song. (2026). SupplyNet: Supporting Visual Exploratory Learning in Supply Chain via Contextual Multi-Agent Simulation. https://arxiv.org/abs/2606.24694