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Data Driven Teaching: Advice Using Data to Inform Teaching. Practical Tips and Examples from Faculty and Grads of The University of Texas of Arlington. Hosted by: Peggy Semingson, Ph.D. Nely Tinajero, Master’s Candidate and Teacher Ali Capasso, Master’s Candidate and Teacher University of Texas at ARLINGTON Dept. of Curriculum and Instruction New teacher WEBINAR: Fall 2015 Recordings will be available of webinars. No names will be visible in the recordings. The recording will be available on our YouTube channel: http://www.youtube.com/utanewteachers SATURDAY, SEPTEMBER 12, 2015 1:00-1:45 PM, CST

Data Driven Teaching: Using Data to Inform Teaching

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Data Driven Teaching: AdviceUsing Data to Inform Teaching. Practical Tips and Examples from Faculty and Grads of The University of Texas of Arlington.

Hosted by:

Peggy Semingson, Ph.D.Nely Tinajero, Master’s Candidate and Teacher Ali Capasso, Master’s Candidate and Teacher

University of Texas at ARLINGTONDept. of Curriculum and InstructionNew teacher WEBINAR: Fall 2015

Recordings will be available of webinars. No names will be visible in the recordings.

The recording will be available on our YouTube channel: http://www.youtube.com/utanewteachers

SATURDAY, SEPTEMBER 12, 2015 1:00-1:45 PM, CST

These are our opinions and suggestions!

The opinions of each the presenters in the series are their own individual viewpoints and do not necessarily reflect the views of UT Arlington.

Our goal is for you to hear a variety of viewpoints to help support you in your first years of teaching! We have been down the road you are going!

– Support– Respect– Dialogue– Sharing

• Ask questions and post comments along the way.

• Main Q/A at the end.• Make a list of “Things to Google”

later.• Use chat window often. • We will check the chat window

throughout the session and respond in “real time” as we can.

Tips for your own learning

RecordingsArchive

Social Media:

YouTube [video]: http://www.youtube.com/utanewteachers Slideshare [PowerPoints]http://www.slideshare.net/utanewteachers Facebook Page [interaction/updates]: https://www.facebook.com/UTANewTeacherProject

Upcoming Webinar Events

• October 10, Webinar• Topic: Teaching with

EdModo in K-12 Settings

• Guest speaker: Dr. Harrison McCoy (UTA Alumni)

• Thanks for joining us! Please use the marker/pen tool to mark a small x below where you are at. You can also type it in the chat window.

WHERE WE ARE NOW:Use the pen tool to mark your location

Poll question: • Where are you in your teaching career?

• Select A-E ptional! We will display the results!• The drop down polling area is in the participants window next to the “hand”

tool.

I am currently a: A. Pre-service teacherB. 1st-3rd year teacher & UTA graduateC. 1st-3rd year teacher & non-UTA graduateD. 4th year+ teacherE. Faculty or none of the above

Prior Knowledge: Understanding “Data Driven Teaching”Overview of the text tool: type about what comes to mind when you hear the term “Data Driven Teaching” in the box below using the text tool. (Or, use the

chat window.)

Hello! I amDr. Peggy Semingson, Associate Professor at The University of Texas at Arlington, Dept. of Curriculum and Instruction (2008-Present)

• Former bilingual/ESL teacher and reading specialist (8 years, elementary, public schools)

• Ph.D. in Language and Literacy from UT Austin

• Seven years as professor at UT Arlington

• Associate Professor of Literacy Studies in the Department of Curriculum and Instruction

Key ideas:Do not “teach to the test”!

Involve students in the process

• Collecting Data

• Analyzing Data

• Action!

Collecting Data: Terminology and Types of Data• Baseline data-initial data collection “starting point”• Formative (ongoing data)• Summative (cumulative at end of unit)• Informal-classroom-based data collection• Formal-standardized tests are an example• Screening-check for students who might face challenges• Progress Monitoring -systematic data collection (informal)• Digital assessment, e.g., iStation http://www.istation.com/ Schoolology

https://www.schoology.com/home.php Google Classroom https://classroom.google.com/ineligible

Analyzing Data

• Spreadsheets! Learn how to use Excel! • Include multiple measures-not just one data source• Involve students in the analysis and help them to set learning

goals.• Help students chart progress, e.g., reading fluency chart. • Decide action steps and interventions based on data.

Example from Hello Literacy(Used with Creative Commons License CC-BY)

http://www.helloliteracy.com/2012/06/progress-monitoring-vs-progress.html

Action Steps

• Determine who needs intervention and on what skills.• Keep intervention flexible.• Grade-wide discussion of data helps.• School-wide planning/coordination of intervention is ideal.• Student Self-assessment– Checklists for students– Student written reflection

Obtaining Baseline Data

By: Nely Tinajero SantoyoMasters in Curriculum and Instruction

with Literacy Studies Emphasis

About Me• UTA alumni and current

graduate student.• 5 years in early childhood• Has worked with youth

and adults for 11 years.• I love to teach and

empower others.

The Importance of Baseline Data

Gives you a starting point and let’s you know how much you need to help each student grow

It shows what a student can do without interventions Baseline data collected is formative Common assessments or school district assessments

can be used

Common Assessments• Having consistency is key across your grade level

when developing teacher made assessments.• Meeting with your vertical teams can help in

deciding what concepts to introduce early on.• After giving a common assessment, meet with your

PLC’s (Professional Learning Communities) and discuss trends and areas of concern.

Progress Monitoring• Develop measurable objectives to meet the students

areas of concern.• Tier students according to their growing abilities. • Continue to assess students throughout the year and

document their progress.• The data and work samples that are collected can be

useful when referring students for additional academic support.

In conclusion, baseline data is……..

Baseline

datacommon assessme

ntsReview

the data

Tier studen

ts

Progress

monitor

Keep record

of progre

ss

Thanks for watching!

If you have more questions feel free to e-mail me at

[email protected]

“This is OUR classroom.”How to involve students in data analysis and

instructional planning.Alison Capasso,

1st and 2nd grade teacher

Why involve your students in the planning process?

o Students gain a sense of ownership and understanding of their own learning.

o Students trust that you truly value their input about your instructional practices.

o These practices build community in the classroom.

o Analyzing data together builds metacognition and encourages the growth mindset.

How Do I Start? Start each week by displaying a weekly

objective using your curriculum and the TEKS/Other standards. This should be something which can be measured using data from an assessment.

Inform the students of what strategy/strategies will be used to learn about this material.

Over the week, remind the students of the learning goal each day.

Assess mastery in some way (ideally several ways) toward the end the week.

Discuss results as soon as possible after assessment and compare with your learning plan.

The power is in the discussion. Students will be made

aware of their individual proficiency with the skill.

The class can decide together how to proceed with the learning.

The class can analyze what aspects of the skill confuse them.

Opportunities can be given for input into instructional strategies.

Give them the opportunity to

make an individual

growth plan.

Remember-Rome wasn’t

built in a day! The more you

discuss performance,

the deeper you can go.

Data Types, Graphing and Describing Them*Dr. Mohan Pant, UT Arlington• Data can be textual (qualitative) or numerical (quantitative)• Quantitative data can be classified as ordinal, interval, or ratio scale

• Store data in an Excel file using columns for variable names and rows for participants• Graphing data may involve drawing a Bar graph, Pie Chart, Line Graph,

Scatterplot, which can be done Excel.• Describing data may involve both graphical and numerical summaries

(e.g., measures of central tendency and measures of dispersion).• Excel can be used for computing basic descriptive statistics such as

mean, standard deviation, and correlation. • If you have any questions, write email at [email protected].

Demo of Data Types• See the link to see a spreadsheet with ways to display and visualize

data: https://uta.box.com/s/nhib5rcynhofrfyiamjc9shnyue033ic

What do you think?type in the chat window!

• What information stood out to you from The presentation?

• What questions do you have?

• “I hope to explore.…”• “I learned….”• “ I want to try….”• “I want to know….”

UT Arlington Master’s in Mind, Brain, and Education

Our work at the SW Center for Mind, Brain and Education seeks to advance the quality of teaching based upon insights gained from the cognitive and neural sciences as well as contribute to research in this new and evolving field.

We build collaborative research relationships with schools, develop research trajectories that profit from the strengths of our faculty and students and maintain a working and teaching laboratory for researchers and graduate students.

1. Courses include: Neuroscience of typical and atypical language development Neuroscience of typical and atypical mathematical reasoning Complex dynamic systems Research design EEG research methodology

2. Individual work: Research-based capstone project encouraged - Conference presentations encouraged - Publishing in peer-reviewed journals

For more information on the Mind, Brain, and Education Master’s degree, please contact Dr. Marc [email protected]