Science Task Prescreen

Task Title: Optimizing the Haber Process: Designing for Maximum Ammonia Yield Grade: 11th Grade (High School) Date: March 2024 SEP: Constructing Explanations and Designing Solutions DCI: PS1.B: Chemical Reactions; ETS1.C: Optimizing the Design Solution CCC: Stability and Change Task Purpose: To evaluate students’ ability to apply Le Chatelier’s Principle to optimize a chemical system (the Haber Process) and balance equilibrium concepts with real-world engineering constraints.

Instructions

Before you begin, review the full task description and any accompanying materials. Then complete the prescreen checklist below.

Prescreen Questionnaire

Question Yes No
1. Is there a phenomenon or problem driving the task? [x] [ ] 🚩
2. Can the majority of the task be answered without using information provided by the task scenario? [ ] 🚩 [x]
3. Can significant portions of the task be answered successfully by using rote knowledge (e.g., definitions, prescriptive or memorized procedure)? [ ] 🚩 [x]
4. Does the majority of the task require students to use reasoning to successfully complete the task? [x] [ ] 🚩
5. Does the task require students to use some understanding of disciplinary core ideas to successfully complete the task? [x] [ ] 🚩
6. Do students have to use at least one science and engineering practice to successfully complete the task? [x] [ ] 🚩
7. Are the dimensions assessed separately in the majority of the task? [ ] 🚩 [x]
8. Is the task coherent and comprehensible from the student perspective? [x] [ ] 🚩

Recommendation

Summary

Summarize your evidence and reasoning: The task is grounded in a real-world problem (industrial fertilizer production via the Haber Process). Students cannot simply recall the definition of Le Chatelier’s Principle; they must actively apply it using data from the simulation (reasoning) to explain shifts in equilibrium (DCI: Chemical Reactions). Furthermore, the final part requires them to refine an engineering solution by balancing theoretical thermodynamic optimal conditions with practical kinetic and economic constraints (SEP: Designing Solutions, DCI: Optimizing the Design Solution). The dimensions are integrated throughout the analysis and recommendation phases. No red flags are present.