{"id":604,"date":"2022-02-16T11:07:34","date_gmt":"2022-02-16T16:07:34","guid":{"rendered":"https:\/\/dev4.legawebdesign.com\/?page_id=604"},"modified":"2024-09-12T15:15:31","modified_gmt":"2024-09-12T19:15:31","slug":"llp-feb","status":"publish","type":"page","link":"https:\/\/horizon-research.com\/tl4cs\/lostladybug\/llp-feb\/","title":{"rendered":"LLP, 6: February"},"content":{"rendered":"\n[et_pb_section fb_built=”1″ custom_padding_last_edited=”on|phone” admin_label=”Header” _builder_version=”4.16″ background_enable_image=”off” background_size=”contain” background_position=”top_right” custom_padding=”40px||||false|false” custom_padding_tablet=”40px|0px|50px|0px|false|false” custom_padding_phone=”30px||||false|false” global_colors_info=”{}”][et_pb_row column_structure=”2_3,1_3″ _builder_version=”4.16″ max_width=”1280px” use_custom_width=”on” custom_width_px=”1280px” global_colors_info=”{}”][et_pb_column type=”2_3″ module_class=”engage-inline-button” _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ text_font=”||||||||” text_line_height=”1.6em” 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=”#cc232f” header_4_font_size=”16px” header_4_letter_spacing=”1px” header_4_line_height=”1.8em” max_width=”900px” custom_margin=”||14px|||” text_font_size_tablet=”” text_font_size_phone=”15px” text_font_size_last_edited=”on|desktop” text_line_height_tablet=”” text_line_height_phone=”1.6em” text_line_height_last_edited=”on|phone” header_font_size_tablet=”50px” header_font_size_phone=”32px” header_font_size_last_edited=”on|phone” global_colors_info=”{}”]

6: February<\/h2>[\/et_pb_text][et_pb_code _builder_version=”4.16″ _module_preset=”default” max_width=”40px” module_alignment=”right” custom_margin=”-54px||10px||false|false” global_colors_info=”{}”]
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Examining ladybug data with variation in habitat and weather conditions<\/h4>\n

Purpose:<\/strong> During this month, as students continue to look for ladybugs outside, their analysis of previous months\u2019 data help them make sense of patterns in ladybug sightings. Students will examine habitat and weather conditions and compare with another location in their state as they explore each location\u2019s features (e.g., weather, geographic location, vegetation). As students consider the relationships of both locations\u2019 ladybug data, they are more prepared for spring ladybug searches ahead.<\/span><\/p>[\/et_pb_text][et_pb_text _builder_version=”4.16″ _module_preset=”default” text_line_height=”1.6em” global_colors_info=”{}”]

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Allow students time to review the schoolyard map, the data collection record sheet, and class data uploaded to the LLP website thus far to look for patterns in the data. Consider the prevalence of native\/non-native species on your school grounds, weather<\/span>\u00a0conditions, and locations where ladybugs have been found. Guide students to consider where ladybugs have been found and\/or why they have not been found in relation to location and weather on your school grounds.\"\"<\/p>\n

Share findings with students from another location in your state. Begin by showing students the location on a map, then use satellite imagery of the location to discuss the features that differ from your schoolyard. Divide students into groups, assigning each a different factor that might influence the other location\u2019s findings. Consider your school location\u2019s features that may impact temperature and other types of weather such as latitude as students consider how far north or south it is in the state compared to the other location. Students can also explore theirs and the other location\u2019s elevation. Additional considerations such as vegetation and time spent looking can also impact their data, so you can ask the groups to review the data to look for patterns. Discuss as a class what they discover and how it is similar to or different from your class ladybug data, and what features of the area might influence the ladybug data. <\/span><\/p>[\/et_pb_text][et_pb_text _builder_version=”4.21.0″ _module_preset=”default” background_color=”#338BC8″ custom_margin=”10px|10px|10px|10px|true|true” custom_padding=”10px|10px|10px|10px|true|true” border_radii=”on|5px|5px|5px|5px” global_colors_info=”{}”]

Not finding ladybugs?<\/b><\/span> Remember, the more you search, the better chance you have of finding ladybugs. Even taking your students out for just a few minutes each day, at various times of day, might be more fruitful than searches thus far. Refer to the Citizen Science Support<\/a><\/span> regarding the benefits of repeated searches. <\/span><\/span><\/p>[\/et_pb_text][et_pb_button button_url=”@ET-DC@eyJkeW5hbWljIjp0cnVlLCJjb250ZW50IjoicG9zdF9saW5rX3VybF9wYWdlIiwic2V0dGluZ3MiOnsicG9zdF9pZCI6IjYwMiJ9fQ==@” 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@eyJkeW5hbWljIjp0cnVlLCJjb250ZW50IjoicG9zdF9saW5rX3VybF9wYWdlIiwic2V0dGluZ3MiOnsicG9zdF9pZCI6IjYxOSJ9fQ==@” 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=”#cc232f” 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=”{}”]

Standards + Practices<\/h4>[\/et_pb_text][et_pb_text _builder_version=”4.16″ _module_preset=”default” text_font=”||||||||” text_font_size=”13px” text_line_height=”1.3em” custom_margin=”||12px||false|false” locked=”off” global_colors_info=”{}”]

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Science Standards: <\/strong><\/p>\n

\u00a0LS.5.2.1<\/b> Compare the characteristics of several common ecosystems ( including estuaries and salt marshes, oceans, lakes and ponds, forests, and grasslands) in terms of their ability to support a variety of populations.<\/span><\/strong><\/p>\n

LS.5.2.3 <\/b><\/span><\/strong>Use models to infer the effects that may result from the interconnected <\/span>relationships of plants and animals to their ecosystem.<\/span><\/p>[\/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=”{}”]

Science Practices<\/strong>
SP4: Analyzing and interpreting data
SP8: Obtaining, evaluating, and communicating information<\/p>[\/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=”#cc232f” 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=”{}”]

Resources + Supports<\/h4>[\/et_pb_text][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” background_layout=”dark” custom_margin=”||10px||false|false” custom_padding=”0px||||false|false” global_colors_info=”{}”]

Continuing to Search<\/a><\/p>[\/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=”{}”]

Mr. Jones Prepares Data File for Class Use<\/a><\/p>[\/et_pb_blurb][et_pb_blurb image=”https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/02\/Asset-25.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=”{}”]

Practice Overview: Analyzing and Interpreting Data<\/a><\/p>[\/et_pb_blurb][et_pb_blurb image=”https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/02\/Asset-16.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=”{}”]

Differences in Data Collection<\/a><\/p>[\/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=”4.16″ _module_preset=”default” body_line_height=”1.4em” custom_margin=”||10px||false|false” global_colors_info=”{}”]

Writing Prompt<\/a><\/p>[\/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=”{}”]

March Preview<\/a><\/p>[\/et_pb_blurb][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ admin_label=”Objectives” module_id=”citscience” _builder_version=”4.16″ background_enable_color=”off” custom_padding=”35px|||||” border_width_top=”8px” border_color_top=”#cc232f” 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: 15%!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=”4.21.0″ _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=”{}”]

Continuing to Search<\/h3>[\/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=”{}”]

Repeated searches, even when nothing is found, are important for data collection in Citizen science projects. Searching during the same or different weather, locations, and vegetation provides the opportunity for students to not only collect valuable data, but to also gain a deeper understanding of their schoolyards and patterns in their data. This is valuable information not only for the Lost Ladybug Project, but for comparing with a another location\u2019s data as well.<\/p>\n

Which species have your students found so far? Are the patterns you see at your school similar or different than the ladybugs found at other locations? This month, you\u2019ll start to look at how your school\u2019s findings relate to other locations, which helps address the second overarching scientific question. Now that students are beginning to make sense of data from other locations in the state, revisit their predictions related to the question about geographic variance.<\/span><\/p>[\/et_pb_text][\/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=”#cc232f” 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: 15%!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=”{}”]

Mr. Jones Prepares Data File for Class Use<\/h3>[\/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=”4.16″ _module_preset=”default” global_colors_info=”{}”]

Mr. Jones entered his email address on the data export<\/a> page on the LLP website to generate a data file for students\u2019 use. He repeated the process using the state feature to identify other locations with data collection in his state.<\/span><\/p>[\/et_pb_text][et_pb_image src=”https:\/\/horizon-research.com\/tl4cs\/wp-content\/uploads\/2022\/02\/6-February-2022-1.jpg” title_text=”6 February 2022″ _builder_version=”4.16″ _module_preset=”default” custom_padding=”||0px|||” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][et_pb_column type=”1_2″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”]

Looking at the file, he is concerned that the export as-is may be challenging for students to interpret. Before sharing the file with students, he decides to modify it in the following ways to make the file more student-friendly.<\/p>\n