Seasonal variation within your region; using computational tools to compile and analyze Precipitation data<\/h4>\n
Purpose<\/strong> [\/et_pb_text][et_pb_text _builder_version=”4.21.0″ _module_preset=”default” text_line_height=”1.6em” global_colors_info=”{}”]<\/p>\n Demonstrate how to access historical county-level data in CoCoRaHS using <\/span>CoCoRaHS Rainy Day reports<\/span><\/a>. Group students into teams (ideally four students per team, as each student will be assigned a season: winter through fall of the previous year) and give each team a different county in the region of the state where your school is located. Each team will use <\/span>CoCoRaHS Rainy Day reports<\/span><\/a> to access the most recent four seasons\u2019 worth of precipitation data for their assigned county.\u00a0\u00a0<\/span><\/p>\n Emphasize the large number of data points students are working with when looking at seasonal totals, and ask students about potential challenges<\/span>\u00a0of adding approximately 90 data points (e.g., takes a long time, easy to make mistakes or lose track). Ask students if they know of any digital tools that scientists use to analyze data. Introduce students to Google Sheets, describing how computational tools like this can help<\/span> Each team then uses Google Sheets to create a graph displaying the seasonal totals for their assigned county. Students compare data from their assigned counties to look for patterns. Students make sense of similarities and what accounts for seasonal differences and any differences they observe across counties.<\/p>\n <\/p>\n [\/et_pb_text][et_pb_button button_url=”@ET-DC@eyJkeW5hbWljIjp0cnVlLCJjb250ZW50IjoicG9zdF9saW5rX3VybF9wYWdlIiwic2V0dGluZ3MiOnsicG9zdF9pZCI6IjYzNSJ9fQ==@” button_text=”Previous: 5: January” button_alignment=”left” _builder_version=”4.16″ _dynamic_attributes=”button_url” _module_preset=”default” custom_button=”on” button_text_size=”14px” button_border_width=”0px” button_icon=”#||divi||400″ button_icon_placement=”left” button_on_hover=”off” custom_padding=”|20px|||false|false” global_colors_info=”{}”][\/et_pb_button][et_pb_button button_url=”@ET-DC@eyJkeW5hbWljIjp0cnVlLCJjb250ZW50IjoicG9zdF9saW5rX3VybF9wYWdlIiwic2V0dGluZ3MiOnsicG9zdF9pZCI6IjYzOSJ9fQ==@” button_text=”Next: 7: March” button_alignment=”right” _builder_version=”4.16″ _dynamic_attributes=”button_url” _module_preset=”default” custom_button=”on” button_text_size=”14px” button_border_width=”0px” button_icon=”$||divi||400″ button_on_hover=”off” custom_padding=”|||20px|false|false” custom_css_main_element=”text-align:right !important;” global_colors_info=”{}”][\/et_pb_button][\/et_pb_column][et_pb_column type=”1_3″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ _module_preset=”default” text_font_size=”14px” text_line_height=”1.3em” header_font=”EB Garamond||||||||” header_font_size=”56px” header_line_height=”1.3em” header_2_font=”|700|||||||” header_2_font_size=”30px” header_3_font=”|600|||||||” header_3_font_size=”26px” header_3_line_height=”1.4em” header_4_font=”|700||on|||||” header_4_text_color=”#89CEA4″ header_4_font_size=”16px” header_4_letter_spacing=”1px” header_4_line_height=”1.8em” custom_margin=”||2px|||” header_font_size_tablet=”50px” header_font_size_phone=”32px” header_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.16″ _module_preset=”default” text_font_size=”14px” text_line_height=”1.3em” header_font=”EB Garamond||||||||” header_font_size=”56px” header_line_height=”1.3em” header_2_font=”|700|||||||” header_2_font_size=”30px” header_3_font=”|600|||||||” header_3_font_size=”26px” header_3_line_height=”1.4em” header_4_font=”|700||on|||||” header_4_text_color=”#89CEA4″ header_4_font_size=”16px” header_4_letter_spacing=”1px” header_4_line_height=”1.8em” min_height=”109.8px” custom_margin=”||2px|||” header_font_size_tablet=”50px” header_font_size_phone=”32px” header_font_size_last_edited=”on|phone” global_colors_info=”{}”] Science Standards: <\/strong><\/p>\n ESS.5.1.1 <\/strong>Analyze and interpret data to compare daily and seasonal changes in weather conditions and patterns<\/p>\n ESS.5.1.2 <\/strong>Analyze and interpret weather data to explain current and upcoming weather conditions in a given location.<\/p>\n ESS.5.1.3 <\/strong>Construct an explanation to summarize the ocean\u2019s influences on weather and climate in North Carolina<\/p>\n ESS.5.1.4 <\/strong>Use models to explain how the sun\u2019s energy drives the processes of the water cycle<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.21.0″ _module_preset=”default” text_font=”||||||||” text_font_size=”13px” text_line_height=”1.4em” custom_margin=”||12px||false|false” hover_enabled=”0″ global_colors_info=”{}” sticky_enabled=”0″]<\/p>\n Science Practices<\/strong> [\/et_pb_text][et_pb_text _builder_version=”4.21.0″ _module_preset=”default” text_font=”||||||||” text_font_size=”13px” text_line_height=”1.4em” custom_margin=”||12px||false|false” hover_enabled=”0″ global_colors_info=”{}” sticky_enabled=”0″]<\/p>\n Math Standards:<\/strong><\/p>\n NC.5.MD.2 <\/strong>Represent and interpret data: Collect data by asking a question that yields data that changes over time.<\/p>\n NC.5.NBT.3 <\/strong>Read, write, and compare decimals to thousandths.<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.16″ _module_preset=”default” text_font=”||||||||” text_font_size=”13px” text_line_height=”1.4em” custom_margin=”||32px||false|false” global_colors_info=”{}”]<\/p>\n Math Practices<\/strong> [\/et_pb_text][et_pb_text _builder_version=”4.16″ _module_preset=”default” text_font_size=”14px” text_line_height=”1.3em” header_font=”EB Garamond||||||||” header_font_size=”56px” header_line_height=”1.3em” header_2_font=”|700|||||||” header_2_font_size=”30px” header_3_font=”|600|||||||” header_3_font_size=”26px” header_3_line_height=”1.4em” header_4_font=”|700||on|||||” header_4_text_color=”#89CEA4″ header_4_font_size=”16px” header_4_letter_spacing=”1px” header_4_line_height=”1.8em” custom_margin=”||2px|||” header_font_size_tablet=”50px” header_font_size_phone=”32px” header_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][et_pb_blurb image=”https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/02\/Asset-20.png” icon_placement=”left” image_icon_width=”100%” _builder_version=”4.21.0″ _module_preset=”default” body_line_height=”1.4em” custom_margin=”||10px||false|false” global_colors_info=”{}”]<\/p>\n Meteorological Seasons<\/a>; Seasonal Weather Patterns<\/a><\/p>\n [\/et_pb_blurb][et_pb_blurb image=”https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/02\/Asset-18.png” icon_placement=”left” image_icon_width=”100%” _builder_version=”4.16″ _module_preset=”default” body_line_height=”1.4em” custom_margin=”||10px||false|false” global_colors_info=”{}”]<\/p>\n Ms. Clark\u2019s Class Uses Computational Tools to Examine Seasonal Patterns<\/a><\/p>\n [\/et_pb_blurb][et_pb_blurb image=”https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/02\/Asset-22.png” icon_placement=”left” image_icon_width=”100%” _builder_version=”4.16″ _module_preset=”default” body_line_height=”1.4em” custom_margin=”||10px||false|false” global_colors_info=”{}”]<\/p>\n Scaffolding Students\u2019 Use of Computational Tools<\/a><\/p>\n [\/et_pb_blurb][et_pb_blurb image=”https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/02\/Asset-17.png” icon_placement=”left” image_icon_width=”100%” _builder_version=”4.21.0″ _module_preset=”default” body_line_height=”1.4em” custom_margin=”||10px||false|false” global_colors_info=”{}”]<\/p>\n Accessing Historical Data in CoCoRaHS<\/a><\/p>\n [\/et_pb_blurb][et_pb_blurb image=”https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/02\/Asset-29.png” icon_placement=”left” image_icon_width=”100%” _builder_version=”4.21.0″ _module_preset=”default” body_line_height=”1.4em” custom_margin=”||10px||false|false” global_colors_info=”{}”]<\/p>\n Digital Literacy Skills<\/a><\/p>\n [\/et_pb_blurb][et_pb_blurb image=”https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/02\/Asset-23.png” icon_placement=”left” image_icon_width=”100%” _builder_version=”4.21.0″ _module_preset=”default” body_line_height=”1.4em” custom_margin=”||10px||false|false” global_colors_info=”{}”]<\/p>\n Finding New Answers<\/a><\/p>\n [\/et_pb_blurb][et_pb_blurb image=”https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/02\/Asset-19.png” icon_placement=”left” image_icon_width=”100%” _builder_version=”4.21.0″ _module_preset=”default” body_line_height=”1.4em” custom_margin=”||10px||false|false” global_colors_info=”{}”]<\/p>\n Connecting the Water Cycle to Seasonal Precipitation<\/a><\/p>\n [\/et_pb_blurb][et_pb_blurb image=”https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/02\/Asset-28.png” icon_placement=”left” image_icon_width=”100%” _builder_version=”4.16″ _module_preset=”default” body_line_height=”1.4em” global_colors_info=”{}”]<\/p>\n March Preview<\/a><\/p>\n [\/et_pb_blurb][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ admin_label=”Objectives” module_id=”narrative” _builder_version=”4.16″ background_enable_color=”off” custom_padding=”35px|||||” border_width_top=”8px” border_color_top=”#89CEA4″ global_colors_info=”{}”][et_pb_row column_structure=”1_4,3_4″ use_custom_gutter=”on” gutter_width=”1″ make_equal=”on” admin_label=”Module Heading with Icon” _builder_version=”4.16″ custom_padding=”||1px|||” locked=”off” global_colors_info=”{}”][et_pb_column type=”1_4″ _builder_version=”4.16″ custom_padding=”|||” custom_css_main_element=”width: 18%!important;” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_image src=”https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/02\/Asset-20.png” title_text=”Asset 20″ show_bottom_space=”off” align=”center” _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][et_pb_column type=”3_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ _module_preset=”default” header_font=”EB Garamond||||||||” header_text_align=”left” header_text_color=”#454545″ header_font_size=”42px” header_line_height=”2.2em” header_3_font=”|700|||||||” header_3_text_color=”#454545″ header_3_font_size=”26px” header_line_height_tablet=”1.2em” header_line_height_phone=”1.2em” header_line_height_last_edited=”on|tablet” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.21.0″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n Remember, students will be working with data for meteorological seasons in the same way as meteorologists and climatologists.\u00a0<\/span><\/p>\n Refer back to the <\/span>Extensions Support<\/a> in December for more information regarding meteorological seasons.<\/span><\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ admin_label=”Objectives” module_id=”graphingtips” _builder_version=”4.16″ background_enable_color=”off” custom_padding=”35px|||||” border_width_top=”8px” border_color_top=”#89CEA4″ global_colors_info=”{}”][et_pb_row column_structure=”1_4,3_4″ use_custom_gutter=”on” gutter_width=”1″ make_equal=”on” admin_label=”Module Heading with Icon” _builder_version=”4.16″ custom_padding=”||1px|||” locked=”off” global_colors_info=”{}”][et_pb_column type=”1_4″ _builder_version=”4.16″ custom_padding=”|||” custom_css_main_element=”width: 10%!important;” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_image src=”https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/02\/Asset-18.png” title_text=”Asset 18″ show_bottom_space=”off” align=”center” _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][et_pb_column type=”3_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ _module_preset=”default” header_font=”EB Garamond||||||||” header_text_align=”left” header_text_color=”#454545″ header_font_size=”42px” header_line_height=”2.2em” header_3_font=”|700|||||||” header_3_text_color=”#454545″ header_3_font_size=”26px” header_line_height_tablet=”1.2em” header_line_height_phone=”1.2em” header_line_height_last_edited=”on|tablet” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.21.0″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n Ms. Clark recognizes that although CoCoRaHS makes a lot of data available to students, they might be discouraged by the number of calculations they would have to do to make sense of the data. Ms. Clark wants to demonstrate the affordances of using computational tools to organize, represent, and analyze large amounts of data. She decides to begin instruction as though students will be manually working with large data sets. When students begin to raise questions about the challenges of managing such a large number of values (i.e., a season\u2019s worth of daily precipitation records), Ms. Clark introduces Google Sheets as a tool for students\u2019 use.\u00a0<\/span><\/p>\n After grouping students into teams of 4, Ms. Clark assigns each team to a different county in the region. Within each county-specific team, the students assign the four seasons among themselves. Ms. Clark demonstrates how to access a season\u2019s worth of data for a particular county using the <\/span>CoCoRaHS Rainy Day report<\/span><\/a>, explaining to the class, \u201cFor example, if you wanted to look at precipitation data for summer (June, July, August) in Wake County, you would put in 6\/1\/2020 and 8\/31\/2020, and select Wake.\u201d Then, to find the total average precipitation across all stations in Wake County, you would add the values in this first column. One student exclaims, \u201cWe have to add ALL of those?!\u201d Another chimes in, \u201cThat\u2019s going to take forever!\u201d Ms.Clark then says, \u201cActually, we are going to use a tool to help us,\u201d to which one student replies, \u201cOh, right, we can use calculators.\u201d The student from earlier reiterates, \u201cThat\u2019s still going to take forever!\u201d Ms. Clark assures students that this tool will help in the same way that a calculator does but that they will also be able to keep track of what values are being added.\u00a0<\/span><\/p>\n Ms Clark wants her students to understand what is happening behind the scenes in the <\/span>Google Sheet Template<\/span><\/a> template, so before having students use the template to sum 90+ values, she models using three values she knows they can add in their head. Once they see how they can use Google Sheets to add a column of numbers, Ms. Clark gauges that they’re ready to move on to the data analysis for the CoCoRaHS data. <\/span>Ms. Clark demonstrates how to use the <\/span>Google Sheet Template<\/span><\/a> to calculate totals by copying and pasting the data from CoCoRaHS. Ms. Clark has created a copy of the template for each team to enter the data that they find on the <\/span>CoCoRaHS Rainy Day report<\/span><\/a>. <\/span><\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ admin_label=”Objectives” module_id=”takingnotes” _builder_version=”4.16″ background_enable_color=”off” custom_padding=”35px|||||” border_width_top=”8px” border_color_top=”#89CEA4″ global_colors_info=”{}”][et_pb_row column_structure=”1_4,3_4″ use_custom_gutter=”on” gutter_width=”1″ make_equal=”on” admin_label=”Module Heading with Icon” _builder_version=”4.16″ custom_padding=”||1px|||” locked=”off” global_colors_info=”{}”][et_pb_column type=”1_4″ _builder_version=”4.16″ custom_padding=”|||” custom_css_main_element=”width: 10%!important;” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_image src=”https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/02\/Asset-22.png” title_text=”Asset 22″ show_bottom_space=”off” align=”center” _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][et_pb_column type=”3_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ _module_preset=”default” header_font=”EB Garamond||||||||” header_text_align=”left” header_text_color=”#454545″ header_font_size=”42px” header_line_height=”2.2em” header_3_font=”|700|||||||” header_3_text_color=”#454545″ header_3_font_size=”26px” header_line_height_tablet=”1.2em” header_line_height_phone=”1.2em” header_line_height_last_edited=”on|tablet” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n If this is students\u2019 first experience using a spreadsheet, providing a template that already includes a formula that sums the values will support their early work with computational tools. To build their understanding, it is important to show the formula and discuss how it communicates which values to add. <\/span><\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=”2_5,3_5″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”2_5″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_image src=”https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/03\/Picture1-2.png” title_text=”Picture1″ _builder_version=”4.16″ _module_preset=”default” width=”80.6%” min_height=”579px” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][et_pb_column type=”3_5″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.21.0″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n Discussing the Template With Students<\/b><\/p>\n 1. Click on the cell that displays \u201c0\u201d for Total Average Precipitation.<\/span><\/p>\n 2. Show students where =SUM(B2:B94) appears.\u00a0<\/span><\/p>\n 3. Explain how that formula tells the computer what to do. Demonstrate how the template will automatically calculate the sum.<\/span><\/p>\n 4. Demonstrate how the template will only add values in the designated cells by typing values in columns other than B.\u00a0<\/span><\/p>\n 5. Then, use the <\/span>CoCoRaHS Rainy Day report<\/span><\/a> to demonstrate how to create a seasonal report and copy the values into the spreadsheet, pointing out to students that the template has one sheet per season and one for the graph. <\/span><\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=”3_5,2_5″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”3_5″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.16″ _module_preset=”default” width=”100%” global_colors_info=”{}”]<\/p>\n Copying the Template<\/b><\/p>\n When making copies, consider renaming each copy to include the names of the assigned counties. <\/span><\/p>\n [\/et_pb_text][\/et_pb_column][et_pb_column type=”2_5″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_image src=”https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/03\/Picture2-2.png” title_text=”Picture2″ _builder_version=”4.16″ _module_preset=”default” min_height=”89px” height=”466px” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ admin_label=”Objectives” module_id=”decimals” _builder_version=”4.16″ background_enable_color=”off” custom_padding=”35px|||||” border_width_top=”8px” border_color_top=”#89CEA4″ global_colors_info=”{}”][et_pb_row column_structure=”1_4,3_4″ use_custom_gutter=”on” gutter_width=”1″ make_equal=”on” admin_label=”Module Heading with Icon” _builder_version=”4.16″ custom_padding=”||1px|||” locked=”off” global_colors_info=”{}”][et_pb_column type=”1_4″ _builder_version=”4.16″ custom_padding=”|||” custom_css_main_element=”width: 10%!important;” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_image src=”https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/02\/Asset-17.png” title_text=”Asset 17″ show_bottom_space=”off” align=”center” _builder_version=”4.21.0″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][et_pb_column type=”3_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ _module_preset=”default” header_font=”EB Garamond||||||||” header_text_align=”left” header_text_color=”#454545″ header_font_size=”42px” header_line_height=”2.2em” header_3_font=”|700|||||||” header_3_text_color=”#454545″ header_3_font_size=”26px” header_line_height_tablet=”1.2em” header_line_height_phone=”1.2em” header_line_height_last_edited=”on|tablet” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.21.0″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n Daily county-level averages are available through the <\/span>Rainy Days Report<\/a>.\u00a0<\/span><\/p>\n Students should select the county they\u2019re focused on from the \u201cALL COUNTIES\u201d drop-down menu.\u00a0<\/span><\/p>\n <\/span>Then, students should change the dates accordingly to obtain data for each season (e.g., 6\/1\/21-8\/31\/21 for meteorological summer).<\/span><\/p>\n Copying these values and pasting them into a spreadsheet will allow students to calculate each seasonal total by combining the daily county averages and generate a graph to compare the four seasonal totals.<\/span><\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=”1_2,1_2″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”1_2″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.21.0″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n Google Sheet Templates<\/b><\/p>\n Blank Seasonal Total Precipitation, including auto-generated graph<\/span><\/a><\/p>\n Sample Seasonal Total Precipitation, including auto-generated graph<\/span><\/a><\/p>\n [\/et_pb_text][\/et_pb_column][et_pb_column type=”1_2″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.21.0″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n Student Reference Sheet<\/span><\/a><\/p>\n [\/et_pb_text][et_pb_image src=”https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/03\/Picture1-3.png” title_text=”Picture1″ _builder_version=”4.16″ _module_preset=”default” min_height=”303px” custom_padding=”||0px|||” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ admin_label=”Objectives” module_id=”commonmistakes” _builder_version=”4.16″ background_enable_color=”off” custom_padding=”35px|||||” border_width_top=”8px” border_color_top=”#89CEA4″ global_colors_info=”{}”][et_pb_row column_structure=”1_4,3_4″ use_custom_gutter=”on” gutter_width=”1″ make_equal=”on” admin_label=”Module Heading with Icon” _builder_version=”4.16″ custom_padding=”||1px|||” locked=”off” global_colors_info=”{}”][et_pb_column type=”1_4″ _builder_version=”4.16″ custom_padding=”|||” custom_css_main_element=”width: 10%!important;” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_image src=”https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/02\/Asset-29.png” title_text=”Asset 29″ show_bottom_space=”off” align=”center” _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][et_pb_column type=”3_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ _module_preset=”default” header_font=”EB Garamond||||||||” header_text_align=”left” header_text_color=”#454545″ header_font_size=”42px” header_line_height=”2.2em” header_3_font=”|700|||||||” header_3_text_color=”#454545″ header_3_font_size=”26px” header_line_height_tablet=”1.2em” header_line_height_phone=”1.2em” header_line_height_last_edited=”on|tablet” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.16″ _module_preset=”default” custom_padding=”||17px|||” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.21.0″ _module_preset=”default” ul_line_height=”2em” header_font=”EB Garamond||||||||” header_font_size=”56px” header_line_height=”1.3em” header_2_font=”|700|||||||” header_2_font_size=”30px” header_3_font=”|600|||||||” header_3_font_size=”26px” header_3_line_height=”1.4em” header_4_font=”|700||on|||||” header_4_text_color=”#89CEA4″ header_4_font_size=”16px” header_4_letter_spacing=”1px” header_4_line_height=”1.8em” custom_padding=”0px||||false|false” header_font_size_tablet=”50px” header_font_size_phone=”32px” header_font_size_last_edited=”on|phone” global_colors_info=”{}”]As students analyze data gathered in a digital spreadsheet ( Excel or Google Sheets), digital literacy skills can help enhance student understanding. Below is a list of some digital literacy skills that can help students as they analyze, understand, and communicate their ideas. Students will develop many of these skills as they work with CoCoRaHS data.\u00a0<\/span><\/p>\n Loewus, L. (2016, November 8). What Is Digital Literacy? <\/span>Education Week<\/span><\/i>. https:\/\/www.edweek.org\/teaching-learning\/what-is-digital-literacy\/2016\/11<\/a>\u00a0<\/span><\/span><\/p>\n <\/span><\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ admin_label=”Objectives” module_id=”meteorologist” _builder_version=”4.16″ background_enable_color=”off” custom_padding=”35px|||||” border_width_top=”8px” border_color_top=”#89CEA4″ global_colors_info=”{}”][et_pb_row column_structure=”1_4,3_4″ use_custom_gutter=”on” gutter_width=”1″ make_equal=”on” admin_label=”Module Heading with Icon” _builder_version=”4.16″ custom_padding=”||1px|||” locked=”off” global_colors_info=”{}”][et_pb_column type=”1_4″ _builder_version=”4.16″ custom_padding=”|||” custom_css_main_element=”width: 10%!important;” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_image src=”https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/02\/Asset-20.png” title_text=”Asset 20″ show_bottom_space=”off” align=”center” _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][et_pb_column type=”3_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ _module_preset=”default” header_font=”EB Garamond||||||||” header_text_align=”left” header_text_color=”#454545″ header_font_size=”42px” header_line_height=”2.2em” header_3_font=”|700|||||||” header_3_text_color=”#454545″ header_3_font_size=”26px” header_line_height_tablet=”1.2em” header_line_height_phone=”1.2em” header_line_height_last_edited=”on|tablet” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.21.0″ _module_preset=”default” header_4_font=”|700||on|||||” header_4_text_color=”#89CEA4″ header_4_font_size=”16px” header_4_letter_spacing=”1px” header_4_line_height=”1.4em” global_colors_info=”{}”]<\/p>\n The fifth grade NC weather standard states that students will understand weather patterns and phenomena, making connections to weather in a particular place and time and compare seasonal changes in weather conditions. As students begin to find patterns in seasonal data within their region, it would be helpful to compare their findings to their understanding of seasonal patterns found in different locations. Ask students to consider: <\/span>What seasonal patterns are you finding in our data? Is our fall data different from our winter data thus far? Why might this be? How does location affect the seasonal weather patterns we are finding in our data? Does our location within the Northern Hemisphere account for seasonal differences in our data? How do you know?<\/span><\/i>\u00a0<\/span><\/p>\n This activity represents a good opportunity to review the difference between weather and climate. <\/span>As students review patterns in seasonal data, help students realize that they are looking at seasonal data for one instance of that particular season making their data seasonal weather data, not climate data. Refer back to the August\/September Science <\/a><\/span>support<\/a> on weather and climate to review as necessary. <\/span><\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ admin_label=”Objectives” module_id=”writingprompts” _builder_version=”4.16″ background_enable_color=”off” custom_padding=”35px|||||” border_width_top=”8px” border_color_top=”#89CEA4″ global_colors_info=”{}”][et_pb_row column_structure=”1_4,3_4″ use_custom_gutter=”on” gutter_width=”1″ make_equal=”on” admin_label=”Module Heading with Icon” _builder_version=”4.16″ custom_padding=”||1px|||” locked=”off” global_colors_info=”{}”][et_pb_column type=”1_4″ _builder_version=”4.16″ custom_padding=”|||” custom_css_main_element=”width: 18%!important;” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_image src=”https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/02\/Asset-23.png” title_text=”Asset 23″ show_bottom_space=”off” align=”center” _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][et_pb_column type=”3_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ _module_preset=”default” header_font=”EB Garamond||||||||” header_text_align=”left” header_text_color=”#454545″ header_font_size=”42px” header_line_height=”2.2em” header_3_font=”|700|||||||” header_3_text_color=”#454545″ header_3_font_size=”26px” header_line_height_tablet=”1.2em” header_line_height_phone=”1.2em” header_line_height_last_edited=”on|tablet” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.16″ _module_preset=”default” header_4_font=”|700||on|||||” header_4_text_color=”#89CEA4″ header_4_font_size=”16px” header_4_letter_spacing=”1px” header_4_line_height=”1.4em” global_colors_info=”{}”]<\/p>\n In citizen science projects, the outcomes are unknown, because scientists are using participant data to answer questions. Participating in these projects enables students to authentically contribute to scientific research. When students encounter data points and weather events that are unexpected, acknowledging that change and finding new answers are foundational to real science! <\/span><\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ admin_label=”Objectives” module_id=”assessment” _builder_version=”4.16″ background_enable_color=”off” custom_padding=”35px|||||” border_width_top=”8px” border_color_top=”#89CEA4″ global_colors_info=”{}”][et_pb_row column_structure=”1_4,3_4″ use_custom_gutter=”on” gutter_width=”1″ make_equal=”on” admin_label=”Module Heading with Icon” _builder_version=”4.16″ custom_padding=”||1px|||” locked=”off” global_colors_info=”{}”][et_pb_column type=”1_4″ _builder_version=”4.16″ custom_padding=”|||” custom_css_main_element=”width: 18%!important;” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_image src=”https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/02\/Asset-19.png” title_text=”Asset 19″ show_bottom_space=”off” align=”center” _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][et_pb_column type=”3_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ _module_preset=”default” header_font=”EB Garamond||||||||” header_text_align=”left” header_text_color=”#454545″ header_font_size=”42px” header_line_height=”2.2em” header_3_font=”|700|||||||” header_3_text_color=”#454545″ header_3_font_size=”26px” header_line_height_tablet=”1.2em” header_line_height_phone=”1.2em” header_line_height_last_edited=”on|tablet” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.21.0″ _module_preset=”default” header_4_font=”|700||on|||||” header_4_text_color=”#89CEA4″ header_4_font_size=”16px” header_4_letter_spacing=”1px” header_4_line_height=”1.4em” global_colors_info=”{}”]<\/p>\n Below is a sample of how students may respond to questions around the science content standard ESS.5.1.4. <\/span><\/p>\n ESS.5.1<\/b> How might the water cycle be connected to seasonal precipitation amounts?\u00a0<\/span><\/p>\n \u00a0I know that the sun makes the water cycle happen. In the summer, there is more sunlight than in other seasons. This makes me think that the reason the summer precipitation amounts are higher for the mountain and piedmont regions than other seasons is because more sunlight means more evaporation which leads to more precipitation. I\u2019m not sure why that wouldn\u2019t be the same in the coastal region because the coastal region also has more hours of sunlight in the summer compared to other seasons. <\/span><\/i><\/span><\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ module_id=”looking-ahead” _builder_version=”4.16″ _module_preset=”default” custom_padding=”33px|||||” global_colors_info=”{}”][et_pb_row _builder_version=”4.16″ _module_preset=”default” width=”100%” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_cta _builder_version=”4.16″ _module_preset=”default” header_text_align=”left” background_color=”#ebebeb” text_orientation=”left” background_layout=”light” global_colors_info=”{}”]<\/p>\n [\/et_pb_cta][et_pb_button button_url=”@ET-DC@eyJkeW5hbWljIjp0cnVlLCJjb250ZW50IjoicG9zdF9saW5rX3VybF9wYWdlIiwic2V0dGluZ3MiOnsicG9zdF9pZCI6IjYzOSJ9fQ==@” button_text=”Next: 7: March” button_alignment=”right” _builder_version=”4.16″ _dynamic_attributes=”button_url” _module_preset=”default” custom_button=”on” button_text_size=”14px” button_border_width=”0px” button_icon=”$||divi||400″ button_on_hover=”off” custom_padding=”|||20px|false|false” custom_css_main_element=”text-align:right !important;” global_colors_info=”{}”][\/et_pb_button][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":" 6: February
Last month students considered geographic features in their sense-making activities. This month, students will make sense of seasonal variation in their region by examining historical county-level precipitation data across the most recent four seasons (winter through fall of the previous year). As they work with these data, students will begin to recognize the power of computational tools by using Google Sheets to compile and analyze county precipitation data from the CoCoRaHS website. <\/span><\/p>\n![\"\"](\"https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/02\/Asset-27.png\")
<\/p>\n![\"\"](\"https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/03\/Picture2-1-300x186.png\")
\u00a0students work with large amounts of data. Show students how the provided <\/span>Google Sheet Template<\/span><\/a> works to calculate sums.<\/span><\/p>\nStandards + Practices<\/h4>\n
![\"\"](\"https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/02\/Asset-17.png\")
[\/et_pb_text][et_pb_text _builder_version=”4.21.0″ _module_preset=”default” text_font=”||||||||” text_font_size=”13px” text_line_height=”1.4em” custom_margin=”||12px||false|false” hover_enabled=”0″ global_colors_info=”{}” sticky_enabled=”0″]<\/p>\n
SP2: Developing and using models
SP5: Using mathematics and computational thinking<\/p>\n
MP5: Use appropriate tools strategically<\/p>\nResources + Supports<\/h4>\n
Meteorological Seasons<\/b><\/h3>\n
\n
Ms. Clark\u2019s Class Uses Computational Tools to Examine Seasonal Patterns<\/b><\/h3>\n
Scaffolding Students\u2019 Use of Computational Tools<\/b><\/h3>\n
\n
\n
\u00a0<\/span>Accessing Historical Data in CoCoRaHS<\/b><\/h3>\n
Digital Literacy Skills<\/h3>\n
\n
\n
\n
\n
\n
Seasonal Weather Patterns<\/h3>\n
Finding New Answers<\/h3>\n
Connecting the Water Cycle to Seasonal Precipitation<\/h3>\n
![\"\"](\"https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/02\/Asset-28.png\")
Now that students have examined data patterns across seasons, next month students will make sense of regional precipitation by comparing precipitation totals for one season across regions. Students may overgeneralize when looking at their county\u2019s data and will benefit from understanding how representative their county is of an entire region. Consider where your station is in your county and other stations that represent various other locations within your county (refer back to<\/span> November <\/span>to review how representativeness is addressed, averaging multiple stations in a county).<\/span><\/p>\n