Online: Tech Quick Learn - Enhancing Data Analysis for Classroom Teachers

.00 Points
  • Wed, Nov 12, 2025 - Wed, Nov 12, 2025

  • Online Training

  • Online Training

40

SEATS AVAILABLE

NON-MEMBERS

$0

MEMBERS

$0

REGISTER NOW

Contact Information

Details

Course No.

#126912

Category

District: Professional Learning (9431)

Classroom Hours

.00

Non-Classroom
Hours

0

Component Numbers

3.003.006 Technology and Learning

Course Description URL

-

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STARTS IN

66

days

Start Date

Wed, Nov 12, 2025

End Date

Wed, Nov 12, 2025
Session Dates and Times

Registration Deadline

Mon, Nov 10, 2025

Withdrawal Deadline

Mon, Nov 10, 2025

Course Description
 More Details

The Technology Quick Learn sessions explore new methods of using technology, including AI, in teacher's instructional work. In this session, participants will discover how to enhance data analysis for K-12 classroom teachers. Learn how to use AI tools to collect, interpret, and apply data insights to inform your teaching practices and improve student outcomes. Participants must attend the 60-minute virtual training and complete a corresponding assignment to be eligible for Inservice credit.
 
Important: Participants must complete a minimum of three, but no more than six, virtual sessions and corresponding assignments to receive Inservice credit. Credit will be awarded in a separate PDS course upon successful completion of all course requirements.

Schedule

START DATE

START TIME

End TIME

11-12-2025

02:30PM

03:30PM

Additional Information


Substitute Provided No
Stipend Provided (Charter teachers) No
Stipend Provided (HCPS teachers) No
Stipend Provided (Private teachers) No
Does this training contribute to a teacher's meeting the criteria for Highly Qualified status? No
Evaluation Method - Students F-Other performance assessment
Evaluation Method - Staff A-Changes in classroom practice
Delivery Methods B-Electronic, Interactive
Follow-Up Methods P-Participant Product related to training (may include lesson plans, written reflection, audio/videotape, case study, samples of student work)