Thinking With Data:Teaching Data Literacy Skills across the Curriculum

Mark van ‘t Hooft, Annette Kratcoski, Karen Swan, Phil Vahey, & Dale CookKent State University

Research Center for Educational Technology

E-Tech Ohio Conference, Columbus, OHFebruary 2010

• Why Data Literacy?

• Project Goals and Objectives

• Unit Background: Thinking with Data

• Digital Tools and Thinking with Data

• Sample Activity

• Some Research Findings

Overview

This material is based upon work supported by the National Science Foundation under Grant No. ESI-0628122.

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Why Data Literacy?

“We use data every day—to choose medications or health practices, to decide on a place to live, or to make judgments about education policy and practice. The newspapers and TV news are full of data about nutrition, side effects of popular drugs, and polls for current elections. Surely there is valuable information here, but how do you judge the reliability of what you read, see, or hear? This is no trivial skill—and we are not preparing students to make these critical and subtle distinctions.”

-- Andee Rubin

Develop a modular, interdisciplinary middle school unit, consisting of a series of four subject area modules that:

support deep student understanding of standards-based content and processes in four disciplines: Social Studies, Mathematics, Science, and English Language Arts.

use real-world data across the disciplines, allowing students to engage in key aspects of data literacy both within and across the disciplines.

are based on recent and robust findings in cognition and instruction, and specifically address the notion of transfer across the curriculum (PFL).

Integrate digital tools to support learning across modules.

Create a set of assessments that measure student growth in data literacy as well as unique disciplinary approaches to it.

Goals & Objectives

Standards-Based Content

Data literacy requirement

MS standards– SS (NCSS)

MS standards– math (NCTM)

MS standards– science (NSES)

MS standards– ELA (NCTE)

Formulate and answer data-

based questions

“Formulate historical questions, obtain data, question &identify gaps in data & construct sound interpretations”

“Formulate questions, design studies & collect data about characteristics shared by 2 populations, or different characteristics within 1 population”

“Identify questions that can be answered through scientific investigations; develop the ability to refine & refocus broad & ill-defined questions”

“Conduct research on issues & interests by generating ideas & questions & posing problems”

Use appropriate data, tools, &

representations

“Use appropriate geographical tools such as atlases, database systems, charts, graphs & maps to generate, manipulate & interpret information”

“Select, create & use appropriate graphical representations of data; discuss & understand the correspondence between data sets & their representations”

“Use appropriate tools & techniques to gather, analyze & interpret data, guided by the question asked & the investigations designed”

“Gather, evaluate & synthesize data from a variety of sources to communicate discoveries in ways that suit their purpose & audience”

Develop and evaluate data-

based inferences & explanations

“Encourage increasingly abstract thought as learners use data & apply skills in analyzing human behavior in relation to physical & cultural environments.”

“Use observations about differences between 2 or more samples to make conjectures about populations, formulate new questions, & studies to answer them”

“Formulate questions, design & execute investigations, interpret data, use evidence to generate explanations; propose alternatives & critique explanations & procedures”

“Use spoken, written & visual language to accomplish purposes (eg. learning, enjoyment, persuasion & exchange of information)”

Unit Context: World Water Issues

Water Use in the Tigris-Euphrates Basin(SS, Math, Science)

and in the United States (ELA)

"The Earth, with its diverse and abundant life forms, including over six billion humans, is facing a serious water crisis. All the signs suggest that it is getting worse and will continue to do so, unless corrective action is taken. The crisis is one of governance, essentially caused by the ways in which humans have mismanaged water.”

-- World Water Development Report (United Nations, 2000)

Real-World Data

Water Access and Use

75.42

213.60

26.2637.53

19.95

42.70

0.00

50.00

100.00

150.00

200.00

250.00

Iraq Syria Turkey

country

cub

ic k

m

1. Total w ater access (incubic km)

1. Total w ater use (in cubickm)

Pedagogical Approach: PFL

preparing students to learn in one curricular context (SS),

with formal learning occurring in another (Math), &

extending the PFL approach to include application (Science) &

communication activities (ELA).

Preparation for Future Learning

English Language

Arts

Social Studies

ScienceMathematics

preparation application communicationtelling

Technology and Data Literacy

Knowing how to use digital and connected technology has become an ever-increasing part of being literate, as technology has become the “pen and paper of our time, … the lens through which we experience much of our world”

-- Warlick, 2006

Large generalizations about ‘digital kids’ and their affinity for new styles of learning have a pernicious consequence – they can blind us to the actual literacy gaps that exist in children’s use of digital media. If using digital tools well actually places cognitive demands on children that they need help with, we’d better attend to and address them…. We are beginning to recognize that the literacy demands of common media tools vary according to the purpose to which they are put.

--Tally, 2007

Use of Digital Technology in the Modules

What we could/should use vs

What the reality of school imposes

How do we deal most effectively with this tension, without shortchanging learners?

How much choice can/should we provide as part of the basic unit? Or should this just be a consideration for module extensions?

What are the literacy demands that the use of digital technologies for learning puts on students?

Use of Digital Technology in the Modules

Emphasis on simple tools (for a variety of reasons, including access and scalability)

•Internet-based materials (including all lesson plans and related materials such as data sets, videos, flash animations, digital maps, reference materials…)•Word processor•PowerPoint for content delivery•Spreadsheets

Fostering Data Literacy Across the Curriculum

Requires:•input from across the disciplines, allowing each teacher to remain a content expert•but not imposing responsibility for teaching a new discipline (data literacy) on teachers

Our approach:•Investigate a complex, engaging, real-world problem•Social Studies sets the context•Math is used for quantitative analysis (proportional reasoning)•Science investigates the context from a scientific perspective, building upon analyses conducted in math•ELA has students explore issues emerging from the data and communicate positions regarding these

Data Literacy KSAs

Formulate and answer data-based questions

1.1 Students understand how data does (or does not) fairly describe a situation/context (e.g. what is missing, what is there)

1.2 Students understand what questions can or cannot be fairly answered by a data set or data sets.

1.3 Students recognize that data may be transformed to create a fairer measure to be used in answering a question.

1.4 Students understand when one can or cannot make fair/accurate predictions.

1.5 Students can formulate relevant and answerable questions based on the context and data.

Use appropriate data, tools, and representations

2.1 Students can evaluate data for credibility and relevance.

2.2 Students can distinguish between fair and unfair representations of data for answering a question.

2.3 Students can use fair representations for understanding a situation.

2.4 Students understand there are instances when data should be aggregated, summarized, etc.

2.5 Students understand there are instances in which proportional measures can be used to create a fairer comparison.

2.6 When asked to make a fair comparison, students can identify key variables, develop required proportional measures, and/or create accurate and meaningful representations of the comparison.

Develop and evaluate data-based arguments, inferences, and explanations

3.1 Students can accurately interpret data representations to answer questions about a data set and make comparisons between data sets.

3.2 Students can accurately analyze and interpret data to answer questions about a data set and make fair comparisons between data sets.

3.3 Students can develop and interpret information from data by comparing, contrasting, and synthesizing across data sets, to understand how different data sets can shed light on an issue.

3.4 Students can develop data-based arguments and use data in proposing solutions to problems or use data as evidence in supporting or opposing a position.

3.5 Students can accurately evaluate and compare data-based inferences and arguments.

An Example

http://www.rcet.org/twd/index.html

Sample Activities

• Social Studies: 2. Water in the Middle East

• Math: 4. What is Fair?

• Science: Science Challenges 1 and 2

• (ELA: 1.1 Data)

Science Challenge How does irrigation affect the soil?

 

amount of agricultural

land(km2 )

amountof agricultural

land that is irrigated

(km2 )

amount of irrigated land

w/salty soil

(km2 )

percent of salty soil

w/ severe salinity

problem

Iraq 60,190 33,050 24,457 4%

Syria 54,210 12,670 5,320 19%

Turkey 260,130 41,860 15,000 0%

Challenge Questions:

1. Which country depends the most on irrigation?2. Put the countries in rank order based on the percentage of irrigated

land with salty soil.3. Which country has the most salty soil with a severe salinity problem?4. What do you think the relation is among rainfall, irrigation, and salty soil

problems?

Science Challenge #2: What leads to salt runoff in the rivers?

0

1

2

3

4

5

6

Tigris River atSamarra

Tigris River atQurne

Euphrates Riverat Al Kaim

Diyala River atDiyala Weir

(Dam)

Tigris River atMosul M

as

s o

f s

alt

ion

s in

wa

ter

(mill

ieq

uiv

ale

nts

)

Na (sodium)

Cl (chloride)

IRRIGATED LAND

RAINFED AGRICULTURE

FLOOD PLAINS

DESERT LAND - SYRIA

DESERT LAND - IRAQ

Challenge Questions:

1. Where is it most/least salty?2. What types of land are near the most and least salty parts of the river?3. What do you think is causing these problems?

Some Research Findings

Are teachers able to effectively implement the TWD modules?

Yes, as long as there is sufficient administrative support and associated professional development.

Some Research Findings

Do students who engage in the TWD modules increase their understanding of data literacy?Yes; students exposed to the TWD curriculum had a pre/post test gain score that was 3 points higher (~ 20%) than comparable students in the same school who did not engage with the TWD materials.

When considering questions individually, student scores improved the most on items that required higher order thinking skills such as data interpretation across multiple tables and calculation of proportional data.

Some Research Findings

Do students who engage in the TWD modules also increase their understanding of Math and Science?

Yes; pre/post testing in Math and Science showed statistically significant gains in learning disciplinary content (but not as much as in data literacy gains).

Some Research Findings

Can we expect, based on teacher and principal input, that this program can be scalable to a wide number of schools?

Yes; with the exception of Social Studies, teachers felt that the TWD unit fit into the 7th grade curriculum.

There were concerns about tensions created due to using PFL, especially at the end of the Social Studies module (lack of closure).

A few teachers thought that some of the materials were too advanced for their students.

Teachers expressed the importance of staff development, working as a team of teachers so each knew what the other three were doing in their modules, and alignment with content standards.

Conclusions (Lessons Learned So Far)

• Data literacy is a part of all aspects of our lives, including education. It is important to teach, but not easy to do.

• Teaching it across the curriculum may help in this matter.

• Integrating digital tools creates opportunities for rich experiences for data literacy (variety of resources; data manipulation in multiple formats; media creation).

• Integrating digital tools creates challenges (students’ and teachers’ technology literacy levels; access).

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