Instructional Aids to Support a Conceptual Understanding of Multiple Representations.
By Kirsten Berthold, Alexander Renkl. 2009
263 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Education, Experimental and Cognitive Psychology
View Paper: https://www.semanticscholar.org/paper/039271e18dc7f3a03839d66196463c092a264a2b
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Fred Paas
- Roxana Moreno
- Tamara van Gog
- Richard E. Mayer
- J. V. van Merriënboer
- John Sweller
- Alexander Renkl
- Emily R. Fyfe
In Education
- Fred Paas
- Tamara van Gog
- J. V. van Merriënboer
- Richard E. Mayer
- Roxana Moreno
- Bethany Rittle-Johnson
- Alexander Renkl
- Patricia A. Alexander
In Experimental and Cognitive Psychology
- Fred Paas
- J. V. van Merriënboer
- Tamara van Gog
- Richard E. Mayer
- John Sweller
- Roxana Moreno
- Alexander Renkl
- Patricia A. Alexander
Citations in the corpus
- Pedagogical Agent Signaling of Multiple Visual Engineering Representations: The Case of the Young Female Agent (2013, background): “However, few studies have examined the impact of visual signaling in instruction combining text with equations and diagrams (these include Berthold & Renkl, 2009; Moreno et al., 2010; Ozogul et al., 2011).”
- Concreteness Fading in Mathematics and Science Instruction: a Systematic Review (2014, background): “Thus, learners need support in relating or integrating the different representations (e.g., Berthold and Renkl 2009; Schwonke et al. 2009).”
- Handbook of Research on Learning and Instruction (2011, background): “Results showed that learners’ expectations for success in skill acquisition were divided along gender-appropriate lines.”
- Developing Conceptual and Procedural Knowledge of Mathematics (2015, background): “…2009; Vamvakoussi & Vosniadou, 2004) (Izsák, 2005) b. Explain why procedures work Explain why ok to borrow when subtract (Fuson & Kwon, 1992) (Berthold & Renkl, 2009; Jacobs, Franke, Carpenter, Levi, & Battey, 2007; Reimer & Moyer, 2005; Stock, Desoete, & Roeyers, 2007) c. Draw concept…”
- Development of an instrument for measuring different types of cognitive load (2013, background): “…IL is optimal and EL is low, learners can engage in knowledge elaboration processes (Kalyuga, 2009) like selfexplanation (Atkinson, Renkl, & Merrill, 2003; Berthold & Renkl, 2009) and argumentation (Fischer, 2002; Knipfer, Mayr, Zahn, Schwan, & Hesse, 2009) that impose GL and facilitate learning.”
- Toward an Instructionally Oriented Theory of Example-Based Learning (2014, methodology): “, using the same color or simultaneous flashing of corresponding elements ; Berthold & Renkl , 2009 ) .”
- Cognitive activities in complex science text and diagrams (2010, background): “…research on students’ reasoning with representations has used simplified images, typically with only one (arrows; Butcher, 2006; naming labels; Berthold & Renkl, 2009; Grosse & Renkl, 2006; Schnotz & Bannert, 2003; numbering; Bodemer & Faust, 2006) or two (arrows and words; Löhner, van…”
- Comparing Four Instructional Techniques for Promoting Robust Knowledge (2015, background): “Even if students are engaged in studying worked examples, evidence suggests that the act of generation can be a valuable learning process because it activates prior knowledge and brings it in direct relation to the problem at hand (Berthold and Renkl 2009; Chi 2000).”
- How to make ‘more’ better? Principles for effective use of multiple representations to enhance students’ learning about fractions (2017, background): “For example, prompting students to such selfexplain mappings has been shown to enhance learning of domain knowledge (Berthold and Renkl 2009; van der Meij and de Jong 2011).”
- How Effective are Instructional Explanations in Example-Based Learning? A Meta-Analytic Review (2010, background): “Berthold and Renkl (2009) , for example, found that the acquisition of procedurals skills was impaired when learners produced faulty self-explanations during example processing.”