Scheduling
06-24-2021
06-25-2021
8:30 am
3:30 pm
Course Information
Non Data System
Learning Acceleration: Success Criteria for Reading and Writing
OSSE in partnership with Corwin Learning invites English Language Arts (ELA) grades K-8 general and special education teachers and instructional coaches to register for a professional learning series focused on accelerating student learning in reading and writing by focusing on teacher clarity in instruction which will deepen practice and instruction in academic vocabulary, authentic writing and reading proficiency and engagement. Participants will: 
    Explore learning experiences that promote academic language learning,
    Explore teacher clarity practices that engage students in a variety of 
settings as metacognitive skills in reading and writing, 
    Support teachers in creating clear outcomes for literacy instruction, and 
    Understand how to use data to inform instructional decisions to support 
the needs of all learners

Planning for instruction using student data in order to drive teacher clarity and the implementation of evidence-based practices will support the reciprocal process of language, reading, and writing; therefore, participants will be required to participate in two sessions that will include opportunities to engage with research, your student data, discuss and plan for implementation and leave with a plan to begin learning acceleration. Participants will be offered 9 professional learning units (PLUs) for full-participation in this training.
Web Seminar Course
Trainer Information
Ashleigh Tillman Ashleigh.Tillman@dc.gov
Lauren Allen
Facility Information
Webinar
Online
200
50
http://Zoom Link is forthcoming
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8:30 am-3:30 pm
Tillman, Ashleigh
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  519 OSSE in partnership with Corwin Learning invites English Language Arts (ELA) grades K-8 general and special education teachers and instructional coaches to register for a professional learning series focused on accelerating student learning in reading and writing by focusing on teacher clarity in instruction which will deepen practice and instruction in academic vocabulary, authentic writing and reading proficiency and engagement. Participants will: 
    Explore learning experiences that promote academic language learning,
    Explore teacher clarity practices that engage students in a variety of 
settings as metacognitive skills in reading and writing, 
    Support teachers in creating clear outcomes for literacy instruction, and 
    Understand how to use data to inform instructional decisions to support 
the needs of all learners

Planning for instruction using student data in order to drive teacher clarity and the implementation of evidence-based practices will support the reciprocal process of language, reading, and writing; therefore, participants will be required to participate in two sessions that will include opportunities to engage with research, your student data, discuss and plan for implementation and leave with a plan to begin learning acceleration. Participants will be offered 9 professional learning units (PLUs) for full-participation in this training.
Created on April 28, 2021 at 11:07 AM (EDT). Owned by Tillman, Ashleigh.
Ashleigh Tillman
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When you bring additional fields into a conversion, Quickbase often finds inconsistencies. For example, say you're converting your Companies column into its own table. One company, Acme Corporation, has offices in New York, Dallas and Portland. So, when you add the City column to the conversion, Quickbase finds three different locations for Acme. A single value in the column you're converting can only match one value in any additional field. Quickbase needs you to clean up the extra cities before it can create your new table. To do so, you have one of two choices:

  • If you want to create three separate Acme records (Acme-New York, Acme-Dallas and Acme-Portland) click the Conform link at the top of the column.
  • If the dissimilar entries are mistakes (say Acme only has one office in New York and the other locations are data-entry errors) go back into your table and correct the inconsistencies—in this case, changing all locations to New York. Then try the conversion again.

Read more about converting a column into a table.

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