Science Task Screener

Task Title: Greenhouse Effect: Modeling Earth’s Energy Budget

Grade: High School

Date: 2024-05-20

Instructions

• Before you begin: Complete the task as a student would. Then, consider any support materials provided to teachers or students, such as contextual information about the task and answer keys/scoring guidance.
• Using the Task Screener: Use this tool to evaluate tasks designed for three-dimensional standards. For each criterion, record your evidence for the presence or absence of the associated indicators. After you have decided to what degree the indicators are present within the task, revisit the purpose of your task and decide whether the evidence supports using it.

Criterion A. Tasks are driven by high-quality scenarios that are grounded in phenomena or problems.

i. Making sense of a phenomenon or addressing a problem is necessary to accomplish the task.

What was in the task, where was it, and why is this evidence?

1. Is a phenomenon and/or problem present?

Yes. The task opens with a striking comparison: Venus and Earth are nearly the same size and distance from the Sun, yet Venus’s surface temperature is 462°C while Earth’s is 15°C. The key difference identified is atmospheric CO₂ concentration (Venus: 96,500 ppm vs. Earth: ~420 ppm). This is an authentic, puzzling planetary science phenomenon that students must make sense of through the task. The phenomenon is presented in Part 1 (Engage) and referenced throughout Parts 3 and 4 as the driving question.

1. Is information from the scenario necessary to respond successfully to the task?

Yes, students must use the Greenhouse Effect simulation to collect their own quantitative data across five investigations (GHG concentration, albedo, solar intensity, cloud cover, and baseline) to analyze how each variable affects Earth’s energy budget. The specific numerical values for temperature and energy flows at each setting are required to construct the visual model and CER argument in Part 4. The Venus-Earth comparison cannot be explained without the simulation-generated data on how GHG concentration affects temperature, including the observed logarithmic scaling relationship.

ii. The task scenario is engaging, relevant, and accessible to a wide range of students.

Features of engaging, relevant, and accessible tasks:

Suggestions for improvement of the task for Criterion A:

Consider including a visual comparison graphic (Earth vs. Venus size, distance, atmospheric composition, temperature) to enhance the multimodal presentation of the anchoring phenomenon. A brief historical note about how Venus’s extreme temperature was discovered (via Soviet Venera probes in the 1970s) could add scientific authenticity and intrigue.

Criterion B. Tasks require sense-making using the three dimensions.

i. Completing the task requires students to use reasoning to sense-make about phenomena or problems.

Consider in what ways the task requires students to use reasoning to engage in sense-making and/or problem solving.

Students must reason from their quantitative simulation data across five investigations to: (1) identify the shape and magnitude of the relationship between each variable (GHG, albedo, solar, clouds) and temperature, (2) categorize factors as affecting energy input, output, or storage/redistribution, (3) determine whether each relationship is causal or correlational, (4) explain the mechanistic basis of the greenhouse effect using the Microscopic View observations (how greenhouse gas molecules interact with infrared vs. visible photons), (5) evaluate the net effect of competing factors (e.g., clouds both reflect solar input and trap infrared output), and (6) apply all of this to explain the Venus-Earth temperature contrast. This goes well beyond recall — it requires genuine causal reasoning about a complex Earth system.

ii. The task requires students to demonstrate grade-appropriate dimensions:

Evidence of SEPs (which element[s], and how does the task require students to demonstrate this element in use?)

Students develop and use a model of Earth’s energy budget that includes components (solar radiation, reflected radiation, absorbed surface energy, infrared radiation, greenhouse gas molecules, clouds, atmospheric layers, surface), relationships (how GHG concentration, albedo, solar intensity, and cloud cover affect energy flows), and connections (mechanistic account of energy flow → climate change, evaluating net effects of competing factors). The model is informed by and validated against students’ own simulation data (Developing and Using Models, elements 2 and 4).

Evidence of CCCs (which element[s], and how does the task require students to demonstrate this element in use?)

Students identify causal relationships between specific variables (GHG concentration, albedo, solar intensity, cloud cover) and climate outcomes (temperature change, energy imbalance). They describe the mechanism by which increased CO₂ causes reduced outgoing longwave radiation, causing an energy imbalance, causing the planet to warm to a new equilibrium. They evaluate the net effect of competing factors (e.g., increased solar vs. increased albedo; cloud warming vs. cloud cooling) — a key example of Cause and Effect analysis (CCC: Cause and Effect).

Evidence of DCIs (which element[s], and how does the task require students to demonstrate this element in use?)

Students apply understanding that Earth’s atmospheric composition (specifically greenhouse gas concentration) alters the flow of energy through the climate system by selectively absorbing and re-emitting infrared radiation. They recognize that changes in greenhouse gases affect outgoing longwave radiation while leaving incoming shortwave solar radiation largely unchanged (DCI: ESS2.A Earth Materials and Systems; ESS2.D Weather and Climate). The Venus-Earth comparison leverages ESS1.B (Earth and the Solar System — secondary) by comparing planetary atmospheres across the solar system.

iii. The task requires students to integrate multiple dimensions in service of sense-making and/or problem-solving.

Consider in what ways the task requires students to use multiple dimensions together.

The Part 4 visual model prompt explicitly asks students to construct a model that includes: components (DCI — greenhouse gases, energy flows, Earth system components), relationships from simulation data (SEP — quantitative relationships between variables and temperature), and connections tracing cause-effect mechanisms (CCC — causal pathways from atmospheric composition → energy imbalance → temperature change → climate feedbacks). The CER component forces triple integration: students cite simulation-derived quantitative evidence (SEP) to support claims about how atmospheric composition affects climate (DCI), while reasoning through the causal mechanisms and competing effects that explain both the Venus-Earth contrast and sensitivity of Earth’s climate (CCC).

iv. The task requires students to make their thinking visible.

Consider in what ways the task explicitly prompts students to make their thinking visible (surfaces current understanding, abilities, gaps, problematic ideas).

Students make their thinking visible through: (1) completing structured data tables across five investigations showing temperature, incoming/outgoing energy, and observations for 21 different experimental conditions, (2) writing analysis responses in Part 3 about energy budget dynamics and photon interactions from the Microscopic View, (3) constructing a visual model of Earth’s energy budget with explicit component, relationship, and connection elements, and (4) writing a comprehensive CER argument with claim, evidence, and reasoning sections connecting simulation data to the Venus-Earth phenomenon.

Suggestions for improvement of the task for Criterion B:

Consider asking students to explicitly draw and label energy flow arrows with energy flux values (W/m²) on their visual model to make the quantitative nature of the energy budget more visible. A class discussion protocol where students share and critique each other’s models before finalizing their CER would deepen the sensemaking.

Criterion C. Tasks are fair and equitable.

i. The task provides ways for students to make connections of local, global, or universal relevance.

Consider specific features of the task that enable students to make local, global, or universal connections to the phenomenon/problem and task at hand. Note: This criterion emphasizes ways for students to find meaning in the task; this does not mean “interest.” Consider whether the task is a meaningful, valuable endeavor that has real-world relevance–that some stakeholder group locally, globally, or universally would be invested in.

Understanding Earth’s energy budget and the greenhouse effect is directly relevant to global climate change — the most significant environmental challenge of the 21st century. Students can connect this to local observations (changing weather patterns, sea-level rise, heat waves), national policy debates (carbon pricing, renewable energy transitions, international climate agreements), and universal human concerns (food security, habitability of the planet, intergenerational equity). The Venus comparison provides a powerful example of what happens when the greenhouse effect runs unchecked — a lesson of direct relevance to current CO₂ concentration trends (~420 ppm and rising).

ii. The task includes multiple modes for students to respond to the task.

Describe what modes (written, oral, video, simulation, direct observation, peer discussion, etc.) are expected/possible.

Students respond through: (1) manipulating an interactive simulation with sliders and visual views (kinesthetic/visual), (2) recording quantitative data in structured data tables (written), (3) written analysis questions requiring explanation and sense-making, (4) constructing a visual model (diagrammatic — concept map, flow chart, or annotated diagram), and (5) a comprehensive CER argument (extended written response). The CSV export feature enables additional analysis in spreadsheet software for students who benefit from digital data manipulation.

iii. The task is accessible, appropriate, and cognitively demanding for all learners (including English learners or students working below/above grade level).

iv. The task cultivates students’ interest in and confidence with science and engineering.

Consider how the task cultivates students interest in and confidence with science and engineering, including opportunities for students to reflect their own ideas as a meaningful part of the task; make decisions about how to approach a task; engage in peer/self-reflection; and engage with tasks that matter to students.

By empowering students to act as climate scientists investigating how four different variables affect Earth’s energy budget through an interactive simulation, the task fosters authentic engagement with experimental design, data analysis, and scientific modeling. The Venus-Earth comparison is inherently surprising and generates genuine curiosity. Students make their own decisions about experimental conditions, and the CER and model-building phases allow them to take ownership of their scientific explanations.

v. The task focuses on performances for which students’ learning experiences have prepared them (opportunity to learn considerations).

Consider the ways in which provided information about students’ prior learning (e.g., instructional materials, storylines, assumed instructional experiences) enables or prevents students’ engagement with the task and educator interpretation of student responses.

The task assumes basic familiarity with the concepts of energy, temperature, and the atmosphere, but scaffolds all specific content knowledge (the greenhouse effect, energy budget, albedo, the role of different variables) directly within the activity. The five investigations proceed from establishing a baseline to testing individual variables systematically, building understanding progressively. Students do not need prior knowledge of the Stefan-Boltzmann law or radiative forcing — the simulation handles the physics, allowing students to focus on the qualitative and quantitative relationships.

vi. The task presents information that is scientifically accurate.

Describe evidence of scientific inaccuracies explicitly or implicitly promoted by the task.

All temperature responses to GHG concentration, albedo, solar intensity, and cloud cover in the simulation are consistent with established climate science principles: GHG forcing follows a logarithmic relationship with concentration (consistent with radiative transfer theory), albedo changes have a linear effect on absorbed solar energy (consistent with surface energy balance), clouds have competing shortwave and longwave effects, and the system tends toward a new equilibrium temperature when perturbed. The Venus (96,500 ppm CO₂, 462°C) vs. Earth (~420 ppm CO₂, 15°C) comparison is scientifically accurate and well-documented in planetary science.

Suggestions for improvement of the task for Criterion C:

Consider providing a simplified data table with partially completed entries for students who need additional scaffolding, and sentence starters for the CER argument. A glossary of key terms (albedo, longwave radiation, shortwave radiation, energy budget, equilibrium) would support English learners and students with varied background knowledge.

Criterion D. Tasks support their intended targets and purpose.

Before you begin:

1. Describe what is being assessed. Include any targets provided, such as dimensions, elements, or PEs:

The task assesses students’ ability to develop and use a model to describe how variations in the flow of energy into and out of Earth’s systems result in changes in climate, aligned to HS-ESS2-4. Specifically, it assesses students’ capacity to identify factors affecting energy input/output/storage (components), organize these into causal categories (relationships), and construct a mechanistic account linking energy flow changes to climate outcomes (connections), while evaluating the net effect of competing factors.

1. What is the purpose of the assessment? (check all that apply)
   • [x] Formative (including peer and self-reflection)
   • [ ] Summative
   • [x] Determining whether students learned what they just experienced
   • [ ] Determining whether students can apply what they have learned to a similar but new context
   • [ ] Determining whether students can generalize their learning to a different context
   • [ ] Other (please specify): N/A

i. The task assesses what it is intended to assess and supports the purpose for which it is intended.

Consider the following:

1. Is the assessment target necessary to successfully complete the task?

Yes, understanding that variations in greenhouse gas concentration, albedo, solar intensity, and cloud cover affect Earth’s energy budget by altering the balance between incoming and outgoing energy, and that this causes temperature change, is essential to correctly constructing the visual model and CER argument explaining the Venus-Earth temperature contrast.

1. Are any ideas, practices, or experiences not targeted by the assessment necessary to respond to the task? Consider the impact this has on students’ ability to complete the task and interpretation of student responses.

Basic data recording and graph interpretation skills are required but are at the high school level. The CSV export feature requires basic spreadsheet familiarity. None of these are substantial barriers for the target grade level.

1. Do the student responses elicited support the purpose of the task (e.g., if a task is intended to help teachers determine if students understand the distinction between cause and correlation, does the task support this inference)?

Yes. The visual model with explicit component, relationship, and connection elements, combined with the CER argument, directly supports assessing whether students understand the energy budget as a system of causal relationships — not just a memorized fact about the greenhouse effect. The requirement to categorize factors as affecting input/output/storage and as causal or correlational provides specific diagnostic information.

ii. The task elicits artifacts from students as direct, observable evidence of how well students can use the targeted dimensions together to make sense of phenomena and design solutions to problems.

Consider what student artifacts are produced and how these provide students the opportunity to make visible their 1) sense-making processes, 2) thinking across all three dimensions, and 3) ability to use multiple dimensions together [note: these artifacts should connect back to the evidence described for Criterion B].

The completed data tables (21 data points across 5 investigations) provide evidence of systematic data collection (SEP). The Part 3 analysis responses show students’ ability to identify patterns and reason about mechanisms. The visual model artifact explicitly demonstrates integration of components (DCI), relationships from data (SEP), and causal connections (CCC). The CER argument provides a culminating artifact that requires students to marshal quantitative evidence (SEP) in service of explaining the Venus-Earth phenomenon (DCI) through causal reasoning (CCC).

iii. Supporting materials include clear answer keys, rubrics, and/or scoring guidelines that are connected to the three-dimensional target. They provide the necessary and sufficient guidance for interpreting student responses relative to the purpose of the assessment, all targeted dimensions, and the three-dimensional target.

Consider how well the materials support teachers and students in making sense of student responses and planning for follow up (grading, instructional moves), consistent with the purpose of and targets for the assessment. Consider in what ways rubrics include:

1. Guidance for interpreting student thinking using an integrated approach, considering all three dimensions together as well as calling out specific supports for individual dimensions, if appropriate:

The Teacher Notes and NGSS Alignment section at the bottom of the task clearly maps each part of the task to the three dimensions (SEP: Developing and Using Models, CCC: Cause and Effect, DCI: ESS2.A/ESS2.D/ESS1.B) and the three evidence statements for HS-ESS2-4 (components, relationships, connections).

1. Support for interpreting a range of student responses, including those that might reflect partial scientific understanding or mask/misrepresent students’ actual science understanding (e.g., because of language barriers, lack of prompting or disconnect between the intent and student interpretation of the task, variety in communication approaches):

Multiple response modalities (quantitative data tables, written analysis, visual model, CER argument) allow teachers to triangulate student understanding. A student who struggles with writing may still demonstrate strong understanding through their visual model and data tables, and vice versa.

1. Ways to connect student responses to prior experiences and future planned instruction by teachers and participation by students:

The task connects to prior learning about energy transfer and atmospheric science, and prepares students for future work on climate feedbacks (ice-albedo feedback, cloud feedback, CO₂ feedback), the carbon cycle, and human impacts on climate systems (HS-ESS2-2, HS-ESS3-5, HS-ESS3-6).

iv. The task’s prompts and directions provide sufficient guidance for the teacher to administer it effectively and for the students to complete it successfully while maintaining high levels of students’ analytical thinking as appropriate.

Consider any confusing prompts or directions, and evidence for too much or too little scaffolding/supports for students (relative to the target of the assessment—e.g., a task is intended to elicit student understanding of a DCI, but their response is so heavily scripted that it prevents students from actually showing their ability to apply the DCI).

The 5E layout with clear headings, numbered investigations, and structured data tables guides students through the task without providing answers. The data table with 21 rows across 5 investigations is systematic but requires students to actively engage with each experimental condition. The analysis questions in Part 3 prompt explanation without leading. The visual model and CER instructions provide a framework while leaving substantial room for student creativity and individual reasoning. The cognitive demand is maintained at a high level throughout.

Suggestions for improvement of the task for Criterion D:

Provide a sample assessment rubric that weights the visual model and CER components according to the three evidence statements. Consider adding a peer-review component where students use the component/relationship/connection framework to evaluate each other’s models.

Overall Summary

Consider the task purpose and the evidence you gathered for each criterion. Carefully consider the purpose and intended use of the task, your evidence, reasoning, and ratings to make a summary recommendation about using this task. While general guidance is provided below, it is important to remember that the intended use of the task plays a big role in determining whether the task is worth students’ and teachers’ time.

The “Greenhouse Effect: Modeling Earth’s Energy Budget” task is highly aligned with HS-ESS2-4 and NGSS three-dimensional learning. It effectively engages students with a compelling anchoring phenomenon (the Venus-Earth temperature paradox) and guides them through an authentic, multi-variable investigation using the Greenhouse Effect simulation. Students develop a visual model (SEP: Developing and Using Models) that identifies causal cause-effect relationships (CCC: Cause and Effect) between atmospheric composition and climate (DCI: ESS2.A, ESS2.D, ESS1.B) to construct evidence-based explanations of energy flow and climate change. The task earns “extensive” ratings across all four criteria due to its rigorous integration of the three dimensions, its well-structured 5E progression, its accessibility for diverse learners, and its direct alignment with the targeted performance expectation and evidence statements.

Final recommendation (choose one):

• [x] Use this task (all criteria had at least an “adequate” rating)
• [ ] Modify and use this task
• [ ] Do not use this task