Martina Rau

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CONTACTING US

Main Office

Educational Psychology
School of Education
UW-Madison
859 Education Sciences
1025 W. Johnson Street
MadisonWI  53706-1796

Tel: 608/262-3432
Fax: 608/262-0843

Email: edpsych@education.wisc.edu
or by contact form
 

Martina A. Rau

Profile Photo

Martina A. Rau

Assisant Professor
Educational Psychology (EdPsych)

1086 Educational Sciences  binoculars icon
1025 West Johnson Street
Madison, WI 53706
Office: 608/262-0833
Fax: 608/262-0843

marau@wisc.edu
Website: Learning, Representations, & Technology Lab
Recent research video
Curriculum Vitae

Personal Biography

Martina Rau is an Assistant Professor in the Department of Educational Psychology in the area of Learning Sciences and is affiliated with the Department of Computer Sciences. She received her Ph.D. in Human-Computer Interaction from Carnegie Mellon University, and a BA/MA in Psychology from the University of Freiburg (Germany). Her research focuses on learning with multiple external representations in educational technologies. She uses a multi-methods approach to integrate learning outcome measures and process-level measures.


Education

Ph D, Human-Computer Interaction Institute
Carnegie Mellon University
Pittsburgh, PA

MS, Human-Computer Interaction
Carnegie Mellon University
Pittsburgh, PA

MA, Psychology
University of Freiburg
Germany

BA, Psychology
University of Freiburg
Germany


 

 

Research Interests

My research focuses on learning with multiple graphical representations. Learning materials in most STEM domains use graphical representations to emphasize conceptual aspects of the learning content. When and how do multiple graphical representations help students' conceptual learning? In one line of my research, I investigate how best to provide instructional support for students to benefit from graphical representations. My research shows that students need to be supported to engage in sense-making processes to conceptually understand how different graphical representations depict information, and in fluency-building processes to acquire perceptual expertise in using representations and in finding correspondences between them. Another line of my research focuses on making use of the novel opportunities that educational technologies offer for learning with graphical representations: students can interact with graphical representations and receive immediate feedback on these interactions. As part of my research, I develop intelligent tutoring systems that include interactive graphical representations. In investigating these questions, I employ a variety of methods, including classroom experimentation, educational data mining of log data obtained from intelligent tutoring systems, eye-tracking research, and think-aloud studies.

Grants and Sponsorships

  • 2015-2020 - Amount: $2,999,737.00, "Lucid: A Project-Focused Cross-Disciplinary Graduate Training Program For Data-Enabled Research In Human And Machine Learning And Teaching," Awarded By: National Science Foundation / NRT Data-Enabled Science and Engineering, Sponsor Type: Federal, Martina A. Rau, Co-Principal; Tim Rogers, Principal; Zhu Jerry, Co-Principal; Alibali Martha, Co-Principal; Nowak Rob, Co-Principal; Matthews Percival, Supporting; Willett Rebecca, Supporting; Kaplan David, Supporting; .
  • 8/31/2019 - Amount: $549,392.00, "Exp: Modeling Perceptual Fluency With Visual Representations In An Intelligent Tutoring System For Undergraduate Chemistry," Awarded By: National Science Foundation, Martina A. Rau, Principal; Jerry Zhu, Co-Principal; Rob Nowak, Co-Principal.
  • 8/31/2019 - Amount: $599,829.00, "Supporting Chemistry Learning With Adaptive Support For Connection Making Between Graphical Representations In A Cognitive Tutoring System," Awarded By: National Science Foundation, Martina A. Rau, Principal; Judith Burstyn, Co-Principal.
  • 2016-2017 - Amount: $45,227.00, "Adaptive Support For Connection Making Among Multiple Visual Representations In Chemistry," Awarded By: Wisconsin Alumni Research Fund, Sponsor Type: University of Wisconsin-Madison, Martina A. Rau; .
  • 6/30/2016 - Amount: $42,073.00, "Intelligent Representations: How To Integrate Physical And Virtual Representations By Adapting To The Individual Student’s Needs In Real Time," Awarded By: Wisconsin Alumni Research Fund, Sponsor Type: University of Wisconsin-Madison, Martina A. Rau.
  • 2015-2016 - Amount: $6,000.00, "Intelligently Combining Physical And Virtual Representations In Educational Technologies," Awarded By: Wisconsin Center for Education Research (WCER) Faculty Research Support Award, Sponsor Type: University of Wisconsin-Madison, Martina A. Rau; .
  • 6/30/2015 - Amount: $53,642.00, "Learning With Multiple, Interactive Graphical Representations In Organic Chemistry," Awarded By: Wisconsin Alumni Research Fund, Sponsor Type: University of Wisconsin-Madison, Martina A. Rau.
  • 5/31/2015 - Amount: $20,000.00, "Cap: Student Travel Support For The 7th International Conference On Educational Data Mining (edm 2014)," Martina A. Rau.

Publications

  • Rau, M.A., & Pardos, Z. (2016). Adding eye-tracking AOI data to models of representation skills does not improve prediction accuracy. In T. Barnes, M. Chi & M. Feng (Eds.), Proceedings of the 9th International Conference on Educational Data Mining, (pp. 622-623). Raleigh, NC: International Educational Data Mining Society.
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  • Rau, M.A. (2016). Association rules uncover social triggers of conceptual learning with physical and virtual representation. In T. Barnes, M. Chi & M. Feng (Eds.), Proceedings of the 9th International Conference on Educational Data Mining, (pp. 478-483). Raleigh, NC: International Educational Data Mining Society.
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  • Rau, M.A. (2016). Conditions for the effectiveness of multiple visual representations in enhancing STEM learning. Educational Psychology Review, pp. 1-45.
    Online Publication/Abstract
  • Rau, M.A., Mason, B., & Nowak, R. (2016). How to model implicit knowledge? Use of metric learning to assess student perceptions of visual representations. In T. Barnes, M. Chi & M. Feng (Eds.), Proceedings of the 9th International Conference on Educational Data Mining, (pp. 199-206). Raleigh, NC: International Educational Data Mining Society.
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  • Rau, M.A., Wu, S., & Schuberth, J. (2016). Sequencing physical representations with human tutors and virtual representations with a computer tutor in chemistry. In C.-K. Looi, J. Polman, U. Cress & P. Reimann (Eds.), Proceedings of the International Conference of the Learning Sciences 2016, (pp. 1173-1174). Singapore: ISLS.
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  • Rau, M.A. (2016). Social, perceptual, and conceptual factors of learning with multiple external representations in educational technologies. Proceedings of the International Conference of the Learning Sciences 2016, (pp. 1378-1379). Singapore: ISLS.
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  • Rau, M.A., Aleven, V., & Rummel, N. (2016). Supporting students in making sense of connections and in becoming perceptually fluent in making connections among multiple graphical representations. Journal of Educational Psychology.
  • Rau, M.A., Michaelis, J.E., & Natalie, F. (2015). Connection Making between Multiple Graphical Representations: A Multi-Methods Approach for Domain-Specific Grounding of an Intelligent Tutoring System for Chemistry. Computers and Education. 82, 460-485.
  • Rau, M.A. (2015). Enhancing Undergraduate Chemistry Learning by Helping Students Make Connections among Multiple Graphical Representations. Chemistry Education Research and Practice.
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  • Rau, M.A., & Wu, S.P. (2015). ITS Support for Conceptual and Perceptual Processes in Learning with Multiple Graphical Representations. In H. C. Lane, K. Yacef, J. Mostow & P. Pavlik (Eds.), Artificial Intelligence in Education, (pp. 762-765). Berlin / Heidelberg: Springer.
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  • Rau, M.A., Aleven, V., & Rummel, N. (2015). Successful Learning With Multiple Graphical Representations and Self-Explanation Prompts. Journal of Educational Psychology, (pp. 30-46).
  • Peterson, J., Pardos, Z., Rau, M.A., Swigart, A., Gerber, C., & McKinsey, J. (in press). Understanding Student Success in Chemistry using Gaze Tracking & Pupillometry. Artificial Intelligence in Education.
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  • Rau, M.A. (in press). Why Do the Rich Get Richer? A Structural Equation Model to Test How Spatial Skills Affect Learning with Representations. Proceedings of the 7th International Conference on Educational Data Mining (EDM 2015).
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  • Rau, M.A., Aleven, V., Rummel, N., & Pardos, Z. (2014). How Should Intelligent Tutoring Systems Sequence Multiple Graphical Representations of Fractions? A Multi-Methods Study. International Journal of Artificial Intelligence in Education. 24(2), 125-161.
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  • Rau, M.A., & Evenstone, A. (2014). Multi-Methods Approach for Domain-Specific Grounding: An ITS for Connection Making in Chemistry. In S. Trausan-Matu et al. (Eds.), Proceedings of the 12th International Conference on Intelligent Tutoring Systems, (pp. 426-435).
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  • Rau, M.A. (2014). Sequencing Sense-Making and Fluency-Building Support for Connection Making between Multiple Graphical Representations. In J. L. Polman, E. A. Kyza, D. K. O’Neill, I. Tabak, W. R. Penuel, A. S. Jurow, K. O’Connor, T. Lee & L. D’Amico (Eds.), Learning and Becoming in Practice: The International Conference of the Learning Sciences (ICLS) 2014, (pp. 977-981). Boulder, CO: International Society of the Learning Sciences.
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  • Rau, M.A., Aleven, V., & Rummel, N. (2013). Complementary effects of sense-making and fluency-building support for connection making: A matter of sequence? Artificial Intelligence in Education, Berlin Heidelberg: Springer.
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  • Rau, M.A. (2013). Conceptual Learning with Multiple Graphical Representations: Intelligent Tutoring Systems Support for Sense-making and Fluency-building Processes.
  • Rau, M.A., Scheines, R., Aleven, V., & Rummel, N. (2013). Does Conceptual Understanding Enhance Acquisition of Fluency – Or Vice Versa? Searching for Models to Investigate Mediators. Proceedings of the 6th International Conference on Educational Data Mining (EDM 2013).
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  • Rau, M.A., Aleven, V., & Rummel, N. (2013). How to use multiple graphical reprsentations to support conceptual learning? Research-based principles in the Fractions Tutor. Artificial Intelligence in Education, Berlin Heidelberg: Springer.
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  • Rau, M.A., Aleven, V., & Rummel, N. (2013). Interleaved practice in multi-dimensional learning tasks: which dimension should we interleave? Learning and Instruction. 23, 98-114.
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  • Carlson, R., Genin, K., Rau, M.A., & Scheines, R. (2013). Student Profiling from Tutoring System Log Data: When do Multiple Graphical Representations Matter?
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  • Rau, M.A., Aleven, V., Rummel, N., & Rohrbach, S. (2013). Why Interactive Learning Environments can have it all: Resolving design conflicts between competing stakeholder goals. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems.
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  • Rau, M.A., Aleven, V., Rummel, N., Pacilio, L., & Tunc-Pekkan, Z. (2012). How to schedule multiple graphical representations? A classroom experiment with an intelligent tutoring system for fractions. The future of learning: Proceedings of the 10th international conference of the learning sciences (ICLS 2012), Sydney, Australia: ISLS.
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  • Rau, M.A., & Pardos, Z. (2012). Investigating Practice Schedules of Multiple Fraction Representations Using Knowledge Tracing Based Learning Analysis Techniques. Proceedings of the 5th International Conference on Educational Data Mining.
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  • Matlen, B., Atit, K., Goksun, T., Rau, M.A., & Ptouchkina, M. (2012). Representing Space: Exploring the Relationship between Gesturing and Geoscience Understanding in Children. Spatial Cognition VIII, Berlin / Heidelberg: Springer.
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  • Rau, M.A., & Scheines, R. (2012). Searching for Variables and Models to Investigate Mediators of Learning from Multiple Representation. Proceedings of the 5th International Conference on Educational Data Mining, Berlin / Heidelberg: Springer.
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  • Rau, M.A., Aleven, V., Rummel, N., & Rohrbach, S. (2012). Sense Making Alone Doesn’t Do It: Fluency Matters Too! ITS Support for Robust Learning with Multiple Representations. Intelligent Tutoring Systems, Berlin / Heidelberg: Springer.
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  • Hayashi, E., Rau, M.A., Neo, Z., Tan, N., Ramasubramanian, S., & Paulos, E. (2012). Time Blocks: “Mom, Can I Have Another Block of Time?”. Proceedings of the 2012 ACM Conference on Human Factors in Computing Systems (CHI 2012).
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  • Feenstra, L., Aleven, V., Rummel, N., Rau, M.A., & Taatgen, N. (2011). Thinking with Your Hands: Interactive Graphical Representations in a Tutor for Fractions Learning. Lecture Notes in Computer Science, (pp. 453-455).
  • Rau, M.A., Aleven, V., & Rummel, N. (2010). Blocked versus Interleaved Practice With Multiple Representations in an Intelligent Tutoring System for Fractions. Proceedings of the 10th International Conference of Intelligent Tutoring Systems, Berlin / Heidelberg: Springer.
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  • Rau, M.A., Aleven, V., & Rummel, N. (2009). Intelligent Tutoring Systems with Multiple Representations and Self-Explanation Prompts Support Learning of Fractions. In V. Dimitrova, R. Mizoguchi, & B. du Boulay (Eds.), Proceedings of the 14th International Conference on Artificial Intelligence in Education, (pp. 441-448). Amsterdam, the Netherlands: IOS Press.
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Presentations

  • Rau, M.A., Author Only, Rummel, N., Presenter & Author, & Aleven, V., Author Only Selbsterklärungs-Prompts helfen Schülern beim Lernen mit multiplen graphischen Repräsentationen von Brüchen, 12. Fachtagung Pädagogische Psychologie der DGPs, Saarbrücken, Germany.
  • Rau, M.A., Author Only, Aleven, V., Presenter & Author, & Rummel, N., Author Only Self-explanations prompts enable students to benefit from learning with multiple graphical re-presentations of fractions, 13th Biennial EARLI Conference for Research on Learning and Instruction, Amsterdam, Netherlands.
  • Rau, M.A., Presenter & Author, Tunk-Pekkan, Z., Author Only, Pacilio, L., Author Only, Aleven, V., Author Only, & Rummel, N., Author Only Facilitating the Representational Fluency and Flexibility through Sequencing Multiple Graphical Representations, 14th Biennial EARLI Conference for Research on Learning and Instruction, Exeter, UK.
  • Rau, M.A., Presenter & Author, Aleven, V., Author Only, & Rummel, N., Author Only Resolving design conflicts between competing goals in educational technologies, 15th Biennial EARLI Conference for Research on Learning and Instruction, Munich, Germany.
  • Rau, M.A., Presenter & Author, Aleven, V., Author Only, & Rummel, N., Author Only Support for sense making and fluency in learning with multiple representations, 15th Biennial EARLI Conference for Research on Learning and Instruction, Munich, Germany.
  • Rau, M.A., Presenter & Author Sense-making support alone doesn’t do it: fluency matters too! Support for learning with multiple representations, inter-Science of Learning Center Conference, Philadelphia, PA.
  • Rau, M.A., Presenter & Author, Aleven, V., Author Only, & Rummel, N., Author Only Supporting Learning with Multiple Graphical Representations with Intelligent Tutoring Technology, International EARLI Special Interest Group on Instructional Design and Learning with Computers, Ulm, Germany.
  • Rau, M.A., Presenter & Author, Aleven, V., Author Only, & Rummel, N., Author Only Blocked versus Interleaved Practice with Multiple Graphical Representations of Fractions, International EARLI Special Interest Group on Text and Graphics Comprehension, Tübingen, Germany.
  • Rau, M.A., Presenter & Author, Aleven, V., Author Only, & Rummel, N., Author Only How to schedule multiple graphical representations? A classroom experiment with an intelligent tutoring system for fractions, Society for Research on Educational Effectiveness Fall 2011 Conference, Washington, DC.

Departmental Service

  • Education Graduate Research Scholars Advisory Committee
    Dates of Membership: 2015 - Pres.

  • Global Education Committee
    Dates of Membership: 2015 - Pres.

  • University Senate
    Dates of Membership: 2015 - Pres.

  • Research Awards / Fellowship Awards Committee
    Dates of Membership: 2014 - Pres.

  • Faculty/Staff Honors Committee
    Dates of Membership: Aug. 2013 - July 2014

School Service

  • Wisconsin Ideas in Education Series
    Dates of Membership: 2014 - Pres.

Awards and Honors

  • Best Paper Award at the 6th International Conference on Educational Data Mining (EDM 2013)
    Organization: International Educational Data Mining Society
    Scope: International
    Description: Rau, M. A., Scheines, R., Aleven, V., & Rummel, N. (2013). Does Representational Understanding Enhance Fluency Or Vice Versa? Searching for Mediation Models. In S. K. D’Mello, R. A. Calvo & A. Olney (Eds.), Proceedings of the 6th International Conference on Educational Data Mining (EDM 2013) (pp. 161-169): International Educational Data Mining Society.
    Date(s): July 2013
  • Siebel Scholar, Class of 2013
    Organization: Siebel Foundation
    Purpose: Scholarship/Research
    Scope: International
    Description: This scholarship is awarded annually for academic excellence and demonstrated leadership to 85 top students from the world’s leading graduate schools
    Date(s): August 2012
  • Best Student Paper Award at the 14th International Conference on Artificial Intelligence in Education
    Organization: International Artificial Intelligence in Education Society
    Scope: International
    Description: Rau, M. A., Aleven, V., & Rummel, N. (2009). Intelligent Tutoring Systems with Multiple Representations and Self-Explanation Prompts Support Learning of Fractions. In V. Dimitrova, R. Mizoguchi, & B. du Boulay (Eds.), Proceedings of the 14th International Conference on Artificial Intelligence in Education (pp. 441-448). Amsterdam, the Netherlands: IOS Press.
    Date(s): July 2009

Memberships

  • Department of Computer Sciences
    Position Held: Affiliate, Scope of Organization: UW Madison, Member Since: September 2014

The following is a representative sample of media contributions.

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