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Martina A. Rau, Ph.D. - Publications

Affiliations: 
2013 Human-Computer Interaction Carnegie Mellon University, Pittsburgh, PA 
Area:
Computer Science, Tests and Measurements Education, Educational Psychology Education
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32 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2020 Rau MA, Keesler W, Zhang Y, Wu S. Design Tradeoffs of Interactive Visualization Tools for Educational Technologies Ieee Transactions On Learning Technologies. 13: 326-339. DOI: 10.1109/Tlt.2019.2902546  0.483
2020 Rau MA. Comparing Multiple Theories about Learning with Physical and Virtual Representations: Conflicting or Complementary Effects?. Educational Psychology Review. 32: 297-325. DOI: 10.1007/S10648-020-09517-1  0.436
2019 Mason B, Rau MA, Nowak R. Cognitive Task Analysis for Implicit Knowledge About Visual Representations With Similarity Learning Methods. Cognitive Science. 43: e12744. PMID 31529528 DOI: 10.1111/Cogs.12744  0.611
2019 Wu SPW, Corr J, Rau MA. How instructors frame students' interactions with educational technologies can enhance or reduce learning with multiple representations Computers in Education. 128: 199-213. DOI: 10.1016/J.Compedu.2018.09.012  0.617
2019 Wu SPW, Rau MA. How Students Learn Content in Science, Technology, Engineering, and Mathematics (STEM) through Drawing Activities. Educational Psychology Review. 31: 87-120. DOI: 10.1007/S10648-019-09467-3  0.671
2018 Rau MA, Wu SPW. Combining Instructional Activities for Sense-Making Processes and Perceptual-Induction Processes Involved in Connection-Making Among Multiple Visual Representations Cognition and Instruction. 36: 361-395. DOI: 10.1080/07370008.2018.1494179  0.616
2018 Rau MA. Making connections among multiple visual representations: how do sense-making skills and perceptual fluency relate to learning of chemistry knowledge? Instructional Science. 46: 209-243. DOI: 10.1007/S11251-017-9431-3  0.715
2017 Rau MA. How do Students Learn to See Concepts in Visualizations? Social Learning Mechanisms with Physical and Virtual Representations Journal of Learning Analytics. 4: 240-263. DOI: 10.18608/Jla.2017.42.16  0.633
2017 Rau MA. A Framework for Educational Technologies that Support Representational Competencies Ieee Transactions On Learning Technologies. 10: 290-305. DOI: 10.1109/Tlt.2016.2623303  0.532
2017 Rau MA. Sequencing support for sense making and perceptual induction of connections among multiple visual representations Journal of Educational Psychology. 110: 811-833. DOI: 10.1037/Edu0000229  0.637
2017 Rau MA, Aleven V, Rummel N. Supporting Students in Making Sense of Connections and in Becoming Perceptually Fluent in Making Connections among Multiple Graphical Representations. Journal of Educational Psychology. 109: 355-373. DOI: 10.1037/Edu0000145  0.77
2017 Rau MA, Kennedy K, Oxtoby L, Bollom M, Moore JW. Unpacking “Active Learning”: A Combination of Flipped Classroom and Collaboration Support Is More Effective but Collaboration Support Alone Is Not Journal of Chemical Education. 94: 1406-1414. DOI: 10.1021/Acs.Jchemed.7B00240  0.673
2017 Wu SPW, Rau MA. Effectiveness and efficiency of adding drawing prompts to an interactive educational technology when learning with visual representations Learning and Instruction. 55: 93-104. DOI: 10.1016/J.Learninstruc.2017.09.010  0.595
2017 Rau MA, Bowman HE, Moore JW. An adaptive collaboration script for learning with multiple visual representations in chemistry Computers & Education. 109: 38-55. DOI: 10.1016/J.Compedu.2017.02.006  0.665
2017 Rau MA, Matthews PG. How to make ‘more’ better? Principles for effective use of multiple representations to enhance students’ learning about fractions Zdm. 49: 531-544. DOI: 10.1007/S11858-017-0846-8  0.756
2017 Rau MA, Aleven V, Rummel N. Making connections among multiple graphical representations of fractions: sense-making competencies enhance perceptual fluency, but not vice versa Instructional Science. 45: 331-357. DOI: 10.1007/S11251-017-9403-7  0.783
2016 Rau MA. Conditions for the Effectiveness of Multiple Visual Representations in Enhancing STEM Learning Educational Psychology Review. 1-45. DOI: 10.1007/S10648-016-9365-3  0.623
2015 Rau MA. Enhancing undergraduate chemistry learning by helping students make connections among multiple graphical representations Chemistry Education Research and Practice. 16: 654-669. DOI: 10.1039/C5Rp00065C  0.739
2015 Rau MA, Aleven V, Rummel N. Successful learning with multiple graphical representations and self-explanation prompts Journal of Educational Psychology. 107: 30-46. DOI: 10.1037/A0037211  0.796
2015 Rau MA, Michaelis JE, Fay N. 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. DOI: 10.1016/J.Compedu.2014.12.009  0.665
2015 Rau MA, Wu SPW. ITS support for conceptual and perceptual connection making between multiple graphical representations Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 9112: 398-407. DOI: 10.1007/978-3-319-19773-9_40  0.665
2014 Rau MA, Aleven V, Rummel N, Pardos Z. How should intelligent tutoring systems sequence multiple graphical representations of fractions? A multi-methods study International Journal of Artificial Intelligence in Education. 24: 125-161. DOI: 10.1007/s40593-013-0011-7  0.751
2014 Rau MA, Evenstone AL. Multi-methods approach for domain-specific grounding: An ITS for connection making in chemistry Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8474: 426-435. DOI: 10.1007/978-3-319-07221-0_53  0.561
2014 Rau MA, Aleven V, Rummel N. Sequencing sense-making and fluency-building support for connection making between multiple graphical representations Proceedings of International Conference of the Learning Sciences, Icls. 2: 977-981.  0.755
2013 Rau MA, Aleven V, Rummel N, Rohrbach S. Why interactive learning environments can have it all: Resolving design conflicts between competing goals Conference On Human Factors in Computing Systems - Proceedings. 109-118. DOI: 10.1145/2470654.2470670  0.595
2013 Rau MA, Aleven V, Rummel N. Interleaved practice in multi-dimensional learning tasks: Which dimension should we interleave? Learning and Instruction. 23: 98-114. DOI: 10.1016/J.Learninstruc.2012.07.003  0.707
2013 Rau MA, Aleven V, Rummel N. Complementary effects of sense-making and fluency-building support for connection making: A matter of sequence? Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7926: 329-338. DOI: 10.1007/978-3-642-39112-5-34  0.775
2013 Rau MA, Aleven V, Rummel N. How to use multiple graphical representations to support conceptual learning? research-based principles in the fractions tutor Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7926: 762-765. DOI: 10.1007/978-3-642-39112-5-107  0.773
2012 Rau MA, Aleven V, Rummel N, Rohrbach S. Sense making alone doesn't do it: Fluency matters too! ITS support for robust learning with multiple representations Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7315: 174-184. DOI: 10.1007/978-3-642-30950-2_23  0.797
2012 Rau MA, Rummel N, Aleven V, Pacilio L, Tunc-Pekkan Z. How to schedule multiple graphical representations? A classroom experiment with an intelligent tutoring system for fractions 10th International Conference of the Learning Sciences: the Future of Learning, Icls 2012 - Proceedings. 1: 64-71.  0.765
2010 Rau MA, Aleven V, Rummel N. Blocked versus interleaved practice with multiple representations in an intelligent tutoring system for fractions Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6094: 413-422. DOI: 10.1007/978-3-642-13388-6_45  0.774
2009 Rau MA, Aleven V, Rummel N. Intelligent tutoring systems with multiple representations and self-explanation prompts support learning of fractions Frontiers in Artificial Intelligence and Applications. 200: 441-448. DOI: 10.3233/978-1-60750-028-5-441  0.765
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