iv2012_tracerpresentation_phdwork

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COMPARISON OF EMERGING INFORMATION

VISUALIZATION TOOLS FOR HIGHER

EDUCATIONMarta Pinto | Rui Raposo | Fernando

Ramos

Information Visualization Application | 13 July 2012

Montpellier, France

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Information Visualization (IV) is being used in many fields, including Education.

In a society driven by knowledge economy, information is relevant for all the

stakeholders of any field, and Higher Education is one the many fields which

are gradually grasping the advantage of the adoption of IV solutions in

activities linked to:.

• Decision making

• Sharing data and information of interest to institutions, decision makers at a

political or financial level, and to a wide range of public [Anderson,2008;

Powell, 2004].

• Accessing and manipulating massive data-sets, to benefit research, help to

visualize more complex systems and strengthen international

communication and collaboration in research [OECD, 2012].

Marta Pinto| [email protected] Raposo| [email protected] Ramos| [email protected]

Comparison of Emerging IV Tools for Higher Education

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The evolution of IV is enabling its massive use worldwide by recognized governmental and non-

governmental organizations, institutions, services, entities, which have realized the power of this

type of communication and understanding of data and information on a large scale.



http://www.oecdbetterlifeindex.org/

http://atlas.media.mit.edu/explore/tree_map/export/usa/all/show/2009/

http://chronicle.com/article/Adults-With-College-Degrees-in/125995/

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Over the last few years IV has also gone beyond its focus on individual singled out objects with their

own sets of variables, to increasing the number of tasks of comparison of complex data. Complex

networks represented in IV [Lima, 2011]:



http://www.visualcomplexity.com/vc/

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Interest in researching IV for HIGHER EDUCATION?

European Higher Education Area



Diversity

transparent,

details about

institutions

• Benchmarking exercises.

• Classifying and ranking HEI study programs.

• Creating quality profiles.

• Comparable information.

https://www.facebook.com/ProjetoTracer

https://www.facebook.com/ProjetoTracer

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HIGHER EDUCATION: the vast majority of data and deriving information is not available from open

databases, this means that it will need to be collected directly from institutions, a time consuming

task for whomever collects data and for institutions who may be see it as a burden [van Vught,

2012].

Data regarding HE is valuable to decision makers, and its visibility on the web may give institutions

prestige, helping them attract students, scholars and financial investment [Ortega, et al, 2008;

Butler, 2012].



DATASETS

Open and public use Use for

research and

knowledge transfer

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Search results in 4 IV tools for European Higher Education, with data regarding the Higher Education

Intitutions, propose to map diversity of HE and characterize HEI according to their autonomy, mobility,

ranking and classification.

1*. U-MAP TOOL: a classification tool

of European HE intitutions, with a

description of the profiles through 6

comparable dimensions. Decision

makers, general public.

(ongoing, demo stage, final report)



METHODOLOGY | TOOL SELECTION

http://www.u-map.eu/

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3*. UNIVERSITY AUTONOMY IN

EUROPE TOOL: lets the user

compare 28 HE systems regarding

their academic, organizational,

financial and staffing autonomy.

Decision makers. (finalized)

4. MAUNIMO TOOL: aiming to draw attention to various forms

and types of academic mobility.

(ongoing)



2*. U-MULTIRANK TOOL: derives from U-map. A global multi-ranking tool,

aiming to allow users to select HEIs performance indicators according to

their own preferences and priorities, and define the institutional profile of

their interest. Decision makers, general public. (ongoing, final report)

http://www.maunimo.eu/

http://www.university-autonomy.eu/

http://www.u-multirank.eu/

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METHODOLOGY | COMPARISON of TOOLS

Focusing on the design and interaction patterns of the tools, sustained on the

work of the three authors, we propose 3 tables to establish a comparison:

Heer and Shneiderman (2012) : taxonomy of tools that support the fluent and flexible use of

visualizations.

Gleicher, et al. (2008): visual comparison for IV, by. Both the work of these authors focus in a

more broad analysis of IV and its design.

Behrens (2008): comparison at a deeper level of the patterns in the IV tools, according to the

compiling of visualization methods.

* U-Multirank tool is not active online, analysis according to the information in the final report.

* U-Map tool , analysis according to the online available demonstration mode and final report.



3 tools compared

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COMPARISON 1: Heer, Shneiderman (2012) - Taxonomy of Tools that Support the Fluent and Flexible Use of Visualizations

PROCESS & PROVENANCE VIEW MANIPULATION DATA & VIEW SPECIFICATION

Record analysis histories for revisitation, review and sharing

Annotate patterns to document findings

Share views and annotations to enable collaboration

Guide users through analysis tasks or stories.

Select items to highlight, filter, or manipulate them

Navigate to examine high-level patterns and low-level detail

Coordinate views for linked, multi-dimensional

Organize multiple windows and workspaces

Visualize data by choosing visual encodings

Filter out data to focus on relevant items

Sort items to expose patterns

Derive

U-Map

University Autonomy in Europe

U-Multirank



Tools

Taxonomy

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Tools

Juxtaposition SuperpositionExplicit representation of relations

U-Map

University Autonomy in Europe

U-Multirank *

COMPARISON 2: Gleicher, et al (2011) - VISUAL COMPARISON FOR INFORMATION VISUALIZATION



visual comparison

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Tools

Visualzation MethodsU-Map

University autonomy in

Europe

U-Multirank

Display PatternsDiscrete quantities (Simple Bar Charts, Multiset Bar Charts and Stacked Bar Charts).

Behaviour Patterns

Filtering (Layering, Active Objects, Boundary Filters, Facet Browsing and Dynamic Query).

Arrangement (Selective Arrangement, Sortable Columns, Custom Dimensions and Isolated Comparisons).

Exploration ("Details on Demand" and DataTips).

Interaction Patterns include:

Boolean selection (usually done with interface elements such as radio buttons, checkboxes, and dropdown menus)

Spatial navigation (Drag and Drop and SelectionMasks). no data

Interaction patterns most common in use arethe selection of elements by interacting with the checkboxesor dropdown menus of the interface.



COMPARISON 3: Behrens (2008) - VISUALIZATION METHODS

U-Map and U-Multirank tools, allow the users to have behavior patterns such as filtering the information to access and arranging it facilitate understanding andcomparison tasks, and allowing for a deeper exploration ofdata and information by giving details on demand as well asdata tips.

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All tools have adopted the visual presentation of data in a sunburst layout, and only offer one

type of visualization method, what makes this set of tools limited in what it concerns the

exploration of visual displays and interface interactions design.

Each sunburst line represents a unique indicator, made up by its length, or a multitude of squares.

In University Autonomy in Europe the more squares are filled, the more autonomous the HE

system.

DISCUSSION & CONCLUSIONS



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Comparison by having visual

representation of 2 or more

instituions, according to specific

variables of interest to the user.

University Autonomy tool,

comparison is not allowed by

putting the sunburst graphs side by

side, visualization is not dynamic.



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U-Multirank enables the creation of the user-selected groups of sufficiently comparable institutions.

This two-step approach is completely new in international and national rankings.

3 set of tools are very similar in the visualization , and have non hierarchical data presentation.

2 set of tools are very similar in the interactions provided.

In such a strong social web context, it is noted that none of the IV tools allow the user to collaborate, annotate or share visualizations.

There would be advantages to allow the user to save the result of his interaction patterns, and to be able to export the visualization, or share it with others on the social web.



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THANK YOU!

This research is financed by FEDER grants under Programa Operacional Factores de Competitividade – COMPETE and by National Funds under FCT – Fundação para a Ciência e Tecnologia PTDC/CPECED/113368/2009COMPETE:FCOMP-01-0124-FEDER-014394

Information Visualization Application | 13 July 2012

COMPARISON OF EMERGING IV TOOLS FOR HIGHER EDUCATIONMarta Pinto| [email protected] Raposo| [email protected] Ramos| [email protected]

iv2012_tracerpresentation_phdwork

Education

visualization iv

higher educationmarta

evolution of iv

years iv

european higher education

comparison of complex

higher educationintitutions

comparison of toolsfocusing