1. Infоrmаtiоn Prоcessing Model, Neuroimаging, аnd Perception Scenario:A team of human-factors engineers is designing a heads-up display (HUD) for emergency responders. During testing, they notice that new trainees consistently miss critical icons when scenes become visually complex. Some participants report that the display “felt instant,” while others say the information “arrived too quickly to process.” The team wants to understand which stages of information processing are overloaded and what neuroimaging tools would best reveal where the bottleneck occurs. Question:Using the information-processing model, explain where perceptual breakdowns are most likely occurring and why. Then describe which neuroimaging technique(s) (e.g., fMRI, EEG, ERP, PET) would be most appropriate for diagnosing the perceptual or attentional bottleneck, and justify your choice. Finally, propose one design change to the HUD that would reduce perceptual errors and explain why it would help. 2. Attention Types, Working Memory, Memory Systems, Encoding/Retrieval Scenario:A software company is developing an adaptive learning platform for medical students studying diagnostic skills. As students progress through a case simulation, the system tracks their eye movements, response times, study behaviors, and memory performance. Data show that students make more diagnostic errors when the simulation requires them to divide attention across multiple symptoms, especially when the interface displays text, audio, and images simultaneously. Some students with strong working memory compensate well, while others struggle unless they use deliberate encoding strategies. The company wants to redesign the system to improve long-term retention and accurate retrieval during high-stress decision-making. Question:Identify the types of attention involved in this scenario (selective, sustained, divided, executive) and explain how they contribute to the observed performance differences. Discuss how working memory capacity and the distinction between short-term and long-term memory influence diagnostic accuracy. Then describe two effective encoding or retrieval strategies the students could use to improve learning, and explain how the platform could integrate these methods into its design. 3. Problem Solving, Biases, and Thinking Traps Scenario:A public-health analyst is assigned to troubleshoot a sudden drop in vaccination rates in a mid-sized city. After reviewing the first week of data, they confidently conclude that the decline must be caused by misinformation on social media. Without exploring demographic trends, clinic access, seasonal effects, or logistical issues, they prepare a full report and propose a costly media-countermeasure campaign. Later, it becomes clear that the major cause was a recent change in clinic hours that made weekday appointments inaccessible for night-shift workers. The analyst is surprised they “missed something so obvious.” Question:Identify the problem-solving errors, cognitive biases, and thinking traps demonstrated in this scenario. Explain how each one affected the analyst's reasoning process and ultimate conclusions. Then describe how using a more systematic problem-solving approach (e.g., hypothesis testing, root-cause analysis, or decision trees) could have prevented the error. Finally, propose one concrete strategy the analyst could adopt to avoid falling into these traps in future investigations. 4. Knowledge Structures, Language, and Communication Scenario:A multinational engineering firm is struggling with miscommunication during collaborative design meetings. Teams report that they consistently leave meetings believing they “agreed,” only to discover later that each group interpreted the plan differently. The project manager notices that engineers rely heavily on jargon and assume shared background knowledge, while newer team members interpret terms using everyday meanings. Cultural differences in indirect vs. direct communication styles also lead to misunderstandings, especially when conveying uncertainty or constraints. Question:Explain how differences in knowledge structures (schemas, semantic networks, expertise levels) contribute to the communication failures in this scenario. Describe how language’s core properties (referential, meaningful, structured, creative, communicative) relate to the misinterpretations occurring between teams. Then discuss how communication processes—including pragmatics, implied meaning, and audience design—shape what is actually understood versus what was intended. Finally, propose two interventions that would help the teams communicate more effectively and reduce ambiguity during collaborative work.