Data Driven Teaching: Advice on Using Data to Inform Teaching
Data Driven Teaching: Advice
Using Data to Inform Teaching. Practical Tips and Examples from Faculty and Grads of The University of Texas of Arlington.
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.
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The recording will be available on our
SATURDAY, SEPTEMBER 12, 2015
1:00-1:45 PM, CST
These are our opinions and
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!
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along the way.
• Main Q/A at the end.
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your own learning
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• October 10, Webinar
• Topic: Teaching with
EdModo in K-12 Settings
• Guest speaker: Dr.
Harrison McCoy (UTA
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I am currently a:
A. Pre-service teacher
B. 1st-3rd year teacher & UTA graduate
C. 1st-3rd year teacher & non-UTA graduate
D. 4th year+ teacher
E. 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
Hello! I am
Dr. 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
• Six years as professor at UT Arlington
• Associate Professor of Literacy
Studies in the Department of
Curriculum and Instruction
Do not “teach to the test”!
Involve students in the process
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
• 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
• 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)
• 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 Santoyo
Masters in Curriculum and Instruction
with Literacy Studies Emphasis
• UTA alumni and current
• 5 years in early childhood
• Has worked with youth and
adults for 11 years.
• I love to teach and empower
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
• 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
• 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
• The data and work samples that are collected can be useful when
referring students for additional academic support.
In conclusion, baseline data is……..
Thanks for watching!
If you have more questions feel free to e-
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“This is OUR classroom.”
How to involve students in data analysis and
1st and 2nd grade teacher
Why involve your students in the
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
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
The power is in the discussion.
Students will be made aware of
their individual proficiency with
The class can decide together
how to proceed with the
The class can analyze what
aspects of the skill confuse
Opportunities can be given for
input into instructional
Give them the
built in a day!
The more you
deeper you can
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
• 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 firstname.lastname@example.org.
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Graduate Program in Literacy Studies
• Email Dr. Kathleen Tice about Literacy Studies: email@example.com
• Our other Master’s programs in Curriculum and Instruction:
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
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 Schwartz