few_shots: 
Example:
Concept/skill: 
Explain equivalence of fractions in special cases, and compare fractions by reasoning about their size.
 Grade 3 expectations in this domain are limited to fractions with denominators 2, 3, 4, 6, and 8.

Problem/activity:
Task
 Arrange the fractions in order from least to greatest. Explain your answer with a picture.
 $\frac{1}{5}, \frac{1}{7}, \frac{1}{3} $
 $\frac{2}{5}, \frac{2}{7}, \frac{2}{3} $
 $\frac{5}{6}, \frac{3}{6}, \frac{1}{6} $
 $\frac{5}{12}, \frac{8}{12}, \frac{4}{12} $

Answer: 
Yes. By arranging the fractions in this problem, students learn to compare fractions by reasoning about their size.

Now, assess whether the following problem or activity is 'aligned' with the given Common Core standard in Mathematics.

shot_info: im_task_000157_pos_0

3
standard_description: Understand solving an equation or inequality as a process of answering a question: which values from a specified set, if any, make the equation or inequality true? Use substitution to determine whether a given number in a specified set makes an equation or inequality true.
problem_activity: Task
Below is a table showing the approximate boiling point of water at different elevations:
{"table": [{"_attributes": {"class": ["regular"]}, "tbody": [{"tr": [{"th": [{"_value": "Elevation (meters above sea level)"}, {"_value": "Boiling Point (degrees Celsius)"}]}, {"td": [{"_value": "0"}, {"_value": "100"}]}, {"td": [{"_value": "500"}, {"_value": "98.2"}]}, {"td": [{"_value": "1000"}, {"_value": "96.5"}]}, {"td": [{"_value": "1500"}, {"_value": "94.7"}]}, {"td": [{"_value": "2000"}, {"_value": "93.1"}]}, {"td": [{"_value": "2500"}, {"_value": "91.3"}]}]}]}]}
Based on the table,
if we were to model the relationship between the elevation and the boiling point of water, would a linear function be appropriate? Explain why or why not.
Below are some additional values for the boiling point of water at higher elevations:
{"table": [{"_attributes": {"class": ["regular"]}, "tbody": [{"tr": [{"th": [{"_value": "Elevation (meters above sea level)"}, {"_value": "Boiling Point (degrees Celsius)"}]}, {"td": [{"_value": "5,000"}, {"_value": "83.2"}]}, {"td": [{"_value": "6,000"}, {"_value": "80.3"}]}, {"td": [{"_value": "7,000"}, {"_value": "77.2"}]}, {"td": [{"_value": "8,000"}, {"_value": "74.3"}]}, {"td": [{"_value": "9,000"}, {"_value": "71.5"}]}]}]}]}
Based on the table,
if we were to model the relationship between the elevation and the boiling point of water, would a linear function be appropriate? Explain why or why not.
When the information from both tables is combined, would a linear function be appropriate to model this data?  What kind of function would you use to model the data?  Why?


aligns: no