>Tuva Tools Editions



This document gives an overview of the four different Tuva Tools editions Tuva Jr., Elem-middle, Middle, and High. The Tuva Authoring Environment enables both Tuva and its partners to customize tools for their audience. Creators can choose between pre-compiled editions of the tool via the authoring environment. Each edition focuses on data concepts and skills relevant to the concerned grade band. Currently, there are four available presets: Tuva Jr., Elem-middle, Middle, and High. These presets adjust the toolbar to display features suited for the respective school levels. Notably, Tuva Jr transforms the entire data environment to fit the needs of elementary school kids.


How to Use

The four editions are described in more detail below.  Scroll down to learn about the distinctions between each edition.  Use the chart at the bottom to compare the editions side by side.


Elem-Middle Preset

The Tuva Jr. edition is activated using a radio button under Presets


The default view for Tuva Jr, is the PLAY VIEW. This view leverages the metaphor of a card game that involves dragging and dropping cards into the Play Area and sorting attributes. 


Thus, Tuva Jr. defines a marked pedagogical shift in design based on research that indicates several aspects of the Middle School edition of the Tuva Tools that could potentially pose challenges for very young children such as the initial random state of cases, the CASE Card view, and the toolbar. 


Elements in the Play Area appear step-by-step. After placing a Card, the bottom data action bar appears. Sorting cards by attributes triggers the top toolbar. This gradual introduction approach reduces cognitive load and streamlines options, preventing overwhelming choices for young learners.



The environment is uncluttered for ease of use.


Similarly, the Plot View in Tuva Jr. has fewer, bigger icons with larger fonts.  All the icons used  are visually meaningful to children.



Thus, Tuva Jr. learners progress from the engaging PLAY view to the more intricate plot view. 


Elem-Middle Preset

This mode is meant to cater to students transitioning from elementary school to middle school. Most toolbar menu items are hidden; the idea is to reduce the complexity of the graphing environment so that students can focus on concepts essential to their level. Further, each submenu in the toolbar has fewer options. For example, the Model Data menu only offers the Movable line. The Least Squares Line and the f(x) functionality have been removed.



Middle Preset

This mode is meant to cater to students in middle school. Most toolbar menu items are available, and the submenus have more options as compared to the Elem-Middle edition.



High Preset

The toolbar menu shows all options, and this mode is meant to cater to students in high school.



Side-by-side Comparison

Here’s a quick snapshot of how the four editions compare in terms of concepts and skills:

Tuva Jr. Elem-middle Mode Middle Mode High Mode

Ask simple questions of data (about individuals in a group or a single attribute)

Read and describe an individual card of interest

Compare two case cards (by comparing one or more attributes) 

Understand that each card/icon represents a single individual or event

Differentiate between categorical and quantitative attributes

Estimate number of cards in a category by stacking and subitizing

Compare categories using the count function

Express the count of a given category as a part of the whole, that is, as a fraction

Compare attributes with fractional or decimal values

Find the minimum and maximum values for the attribute chosen to order the cards

Informally describe the range of values for the attribute

Identify the value that has the highest frequency

Begin thinking about what is typical of a group

Describe rudimentary associations between two quantitative attributes

Read and interpret ordered pairs in a scatter plot

Display Numerical Data in Elementary Dot Plots & Bar Charts of Values to explore min/max values, extreme values, and range of data

Display and Read Data in Scatter Plots & Line Graphs to explore trends and associations informally

Display and Read Aggregated Data in Bar Charts of Frequencies, Pie Graphs & Stretched Bar Charts

Build familiarity with Axis Scale & Create Scaled Intervals


Manipulate data by filtering and dragging categorical attributes

Display data in Maps to Build Familiarity with Spatial Distributions

Elem-middle Mode+

Create and interpret distributions of data using dot plots, box plots & histograms

Compare Groups using parallel dot plots, parallel box plots, & parallel histograms

Describe and interpret associations between Categorical attributes using Dot Plots & Two-way Tables

Describe Distributions using Mean, Median, MAD and IQR

Describe the direction and strength of linear relationships using informal tools

Use multiple line graphs to represent ordered data and to compare localized and overall trends across locations or categories

Model and interpret trends & linear relationships using the Movable line 

Manipulate Slider Parameters to Fit Linear data 

Use rates & proportions to compare groups of unequal sizes 

Create and interpret Bar Charts of Sums and Bar Charts of Means

Choose between frequency, relative percentage and relative proportion scales in data displays

Generate random samples from populations

Generate multiple samples to explore sampling variability

Study the effects of sample size on representativeness of the sample

Middle Mode+

Interpret variability using Standard Deviation (SD) as a measure of spread

Establish bimodality using SD

Compare groups using standard deviation

Use Two-way  Tables/Contingency Tables to study conditional probabilities and to establish associations

Describe the strength and direction of a linear relationship using the Coefficient of Correlation

Use the Least Squares Line for Linear regression analysis

Judge the fit of a Linear Model using the Show Squares feature

Use the f(x) functionality to model and interpret linear  & nonlinear relationships

Manipulate slider parameters to fit nonlinear data (quadratic, exponential, cubic, etc.)

Use Standard Error as a metric to find the difference from the true mean

Visualize and interpret the Distribution of Sample Statistics

Explore the Central Limit Theorem

Compute z-scores to standardize a distribution

Assess the Normality of a Distribution using multiple SDs and z-scores



Was this article helpful?
0 out of 0 found this helpful