Making connections among multiple graphical representations of fractions: sense-making competencies enhance perceptual fluency, but not vice versa
暂无分享,去创建一个
[1] Richard Lowe,et al. Constructing a mental representation from an abstract technical diagram , 1993 .
[2] S. Ainsworth. DeFT: A Conceptual Framework for Considering Learning with Multiple Representations. , 2006 .
[3] Vincent Aleven,et al. A New Paradigm for Intelligent Tutoring Systems: Example-Tracing Tutors , 2009, Int. J. Artif. Intell. Educ..
[4] D. Gentner,et al. Learning and Transfer: A General Role for Analogical Encoding , 2003 .
[5] Vincent Aleven,et al. Why interactive learning environments can have it all: resolving design conflicts between competing goals , 2013, CHI.
[6] Kathleen A. Cramer. Using concrete models to build middle‐grade students understanding of functions , 2001 .
[7] Keith S. Taber,et al. Revisiting the chemistry triplet: drawing upon the nature of chemical knowledge and the psychology of learning to inform chemistry education , 2013 .
[8] Ton de Jong,et al. The effects of directive self-explanation prompts to support active processing of multiple representations in a simulation-based learning environment , 2011, J. Comput. Assist. Learn..
[9] A. Su,et al. The National Council of Teachers of Mathematics , 1932, The Mathematical Gazette.
[10] R. Atkinson,et al. Transitioning From Studying Examples to Solving Problems: Effects of Self-Explanation Prompts and Fading Worked-Out Steps. , 2003 .
[11] David H. Uttal,et al. Comprehending and Learning from ‘Visualizations’: A Developmental Perspective , 2008 .
[12] Shaaron Ainsworth,et al. The effects of self‐explaining when learning with text or diagrams , 2003 .
[13] John R. Anderson,et al. Cognitive Tutors: Lessons Learned , 1995 .
[14] Hermann G. Ebner,et al. Improving cross-content transfer in text processing by means of active graphical representation , 2003 .
[15] Hans Spada,et al. The Active Integration of Information during Learning with Dynamic and Interactive Visualisations , 2004 .
[16] Mitchell J. Nathan,et al. Representational disfluency in algebra: evidence from student gestures and speech , 2009 .
[17] Ji Y. Son,et al. Perceptual Learning Modules in Mathematics: Enhancing Students' Pattern Recognition, Structure Extraction, and Fluency , 2010, Top. Cogn. Sci..
[18] T. Jong,et al. Supporting students' learning with multiple representations in a dynamic simulation-based learning environment , 2006 .
[19] Robert L. Goldstone,et al. Reuniting perception and conception , 1998, Cognition.
[20] Martha W. Alibali,et al. Actions speak louder with words: The roles of action and pedagogical language for grounding mathematical proof , 2014 .
[21] Vincent Aleven,et al. Successful learning with multiple graphical representations and self-explanation prompts. , 2015 .
[22] P. Kellman,et al. Perceptual Learning, Cognition, and Expertise , 2013 .
[23] Yash Patel,et al. Using Multiple Representations to Build Conceptual Understanding in Science and Mathematics , 2014 .
[24] Vincent Aleven,et al. An effective metacognitive strategy: learning by doing and explaining with a computer-based Cognitive Tutor , 2002, Cogn. Sci..
[25] John R. Anderson. The Architecture of Cognition , 1983 .
[26] Richard Lowe,et al. Selectivity in diagrams: reading beyond the lines , 1994 .
[27] Alexander Renkl,et al. The Cambridge Handbook of Multimedia Learning: The Worked-Out Examples Principle in Multimedia Learning , 2005 .
[28] T. Mueller. Learning to Think Spatially , 2006 .
[29] Vincent Aleven,et al. Rule-Based Cognitive Modeling for Intelligent Tutoring Systems , 2010, Advances in Intelligent Tutoring Systems.
[30] Erol Özçelik,et al. An eye-tracking study of how color coding affects multimedia learning , 2009, Comput. Educ..
[31] Percival G. Matthews,et al. Fractions as percepts? Exploring cross-format distance effects for fractional magnitudes , 2015, Cognitive Psychology.
[32] John K. Gilbert,et al. Visualization: An Emergent Field of Practice and Enquiry in Science Education , 2008 .
[33] D. Kahneman. A perspective on judgment and choice: mapping bounded rationality. , 2003, The American psychologist.
[34] John Airey,et al. A disciplinary discourse perspective on university science learning: Achieving fluency in a critical constellation of modes , 2009 .
[35] Alexander Renkl,et al. Assisting self-explanation prompts are more effective than open prompts when learning with multiple representations , 2009 .
[36] Loretta L. Jones,et al. Molecular visualization in chemistry education: The role of multidisciplinary collaboration , 2005 .
[37] Stephen J. Pape,et al. The Role of Representation(s) in Developing Mathematical Understanding , 2001 .
[38] Martina A. Rau,et al. Conditions for the Effectiveness of Multiple Visual Representations in Enhancing STEM Learning , 2017 .
[39] Robb Lindgren,et al. Generating a learning stance through perspective-taking in a virtual environment , 2012, Comput. Hum. Behav..
[40] Robert B. Kozma,et al. Students Becoming Chemists: Developing Representationl Competence , 2005 .
[41] Stellan Ohlsson,et al. Computational Models of Skill Acquisition , 2008 .
[42] Rolf Ploetzner,et al. Supporting learning with interactive multimedia through active integration of representations , 2005 .
[43] A. Glenberg,et al. The illusion of knowing: Failure in the self-assessment of comprehension , 1982 .
[44] Billie Eilam,et al. Teaching, Learning, and Visual Literacy: The Dual Role of Visual Representation , 2012 .
[45] Shaaron Ainsworth. How Should We Evaluate Multimedia Learning Environments , 2008 .
[46] E. Gibson. Principles of Perceptual Learning and Development , 1969 .
[47] Charalambos Y. Charalambous,et al. Drawing on a Theoretical Model to Study Students’ Understandings of Fractions , 2007 .
[48] P. Spirtes,et al. Causation, prediction, and search , 1993 .
[49] Tina Seufert. Supporting Coherence Formation in Learning from Multiple Representations , 2003 .
[50] Philip J. Kellman,et al. Perceptual Learning and the Technology of Expertise: Studies in Fraction Learning and Algebra. , 2008 .
[51] David Maxwell Chickering,et al. Optimal Structure Identification With Greedy Search , 2002, J. Mach. Learn. Res..
[52] S. Asli Özgün-Koca,et al. Ninth Grade Students Studying the Movement of Fish to Learn about Linear Relationships: The Use of Video-Based Analysis Software in Mathematics Classrooms , 2008 .
[53] John K. Gilbert,et al. Visualization: A Metacognitive Skill in Science and Science Education , 2005 .
[54] A. Dreher,et al. Teachers Facing the Dilemma of Multiple Representations Being Aid and Obstacle for Learning: Evaluations of Tasks and Theme-Specific Noticing , 2015 .
[55] K. Anders Ericsson. Perceptual and Memory Processes in the Acquisition of Expert Performance: The EPAM Model , 2014 .
[56] P. Shah,et al. Exploring visuospatial thinking in chemistry learning , 2004 .
[57] Zachary A. Pardos,et al. How Should Intelligent Tutoring Systems Sequence Multiple Graphical Representations of Fractions? A Multi-Methods Study , 2013, International Journal of Artificial Intelligence in Education.
[58] Shaaron Ainsworth,et al. Examining the Effects of Different Multiple Representational Systems in Learning Primary Mathematics , 2002 .
[59] Wolfgang Schnotz,et al. The Cambridge Handbook of Multimedia Learning: An Integrated Model of Text and Picture Comprehension , 2005 .
[60] Thomas E. Kieren,et al. Rational and fractional numbers: From quotient fields to recursive understanding , 1993 .
[61] K. VanLehn. The Relative Effectiveness of Human Tutoring, Intelligent Tutoring Systems, and Other Tutoring Systems , 2011 .
[62] Barbara Y. White,et al. Making Their Own Connections: Students' Understanding of Multiple Models in Basic Electricity , 1999 .
[63] Xiaojin Zhu,et al. Humans Learn Using Manifolds, Reluctantly , 2010, NIPS.
[64] J. Deloache. Dual representation and young children's use of scale models. , 2000, Child development.
[65] Sibel Kazak,et al. Saying More than You Know in Instructional Settings , 2011 .
[66] Kenneth R. Koedinger,et al. A Data Repository for the EDM Community: The PSLC DataShop , 2010 .
[67] A. Renkl,et al. Instructional Aids to Support a Conceptual Understanding of Multiple Representations. , 2009 .
[68] E. Gibson. Perceptual Learning in Development: Some Basic Concepts , 2000 .
[69] J. R. Landis,et al. The measurement of observer agreement for categorical data. , 1977, Biometrics.
[70] Cheryl I. Johnson,et al. Applying the self-explanation principle to multimedia learning in a computer-based game-like environment , 2010, Comput. Hum. Behav..
[71] D. Gentner. Structure‐Mapping: A Theoretical Framework for Analogy* , 1983 .
[72] Vincent Aleven,et al. Supporting Students in Making Sense of Connections and in Becoming Perceptually Fluent in Making Connections Among Multiple Graphical Representations , 2017 .
[73] Albert T. Corbett,et al. The Knowledge-Learning-Instruction Framework: Bridging the Science-Practice Chasm to Enhance Robust Student Learning , 2012, Cogn. Sci..
[74] Vincent Aleven,et al. Example-Tracing Tutors: Intelligent Tutor Development for Non-programmers , 2016, International Journal of Artificial Intelligence in Education.
[75] F. Paas,et al. Uncovering the problem-solving process: cued retrospective reporting versus concurrent and retrospective reporting. , 2005, Journal of experimental psychology. Applied.
[76] Timothy J. Nokes-Malach,et al. Effectiveness of holistic mental model confrontation in driving conceptual change , 2012 .
[77] Hans Spada,et al. Acquiring knowledge in science and mathematics : the use of multiple representations in technology based learning environments , 1998 .
[78] Tina Seufert,et al. Cognitive load and the format of instructional aids for coherence formation , 2006 .
[79] Jennifer L. Chiu,et al. Evidence for effective uses of dynamic visualisations in science curriculum materials , 2015 .
[80] Daniel Bodemer,et al. External and mental referencing of multiple representations , 2006, Comput. Hum. Behav..