Shaaron E. Ainsworth

Developmental and Educational Psychology · 2002–2011

A researcher in the Science corpus: 7 papers; trusts 24 researchers and is trusted by 68 researchers here, as inferred from the citation graph.

Subfields

• Developmental and Educational Psychology — 31 citations into it; #194 of 8,223 by trust here, #917 by citations
• Education — 24 citations into it; #251 of 11,309 by trust here, #920 by citations
• Experimental and Cognitive Psychology — 20 citations into it; #206 of 9,731 by trust here, #875 by citations
• Artificial Intelligence — 9 citations into it; #14,581 of 35,345 by trust here, #17,110 by citations
• Automotive Engineering — 7 citations into it
• Computer Vision and Pattern Recognition — 5 citations into it
• Statistics and Probability — 5 citations into it; #5,054 of 12,932 by trust here, #8,740 by citations

Whom Shaaron E. Ainsworth trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Wolfgang Schnotz
2. Michelene T. H. Chi
3. Richard E. Mayer
4. Tina Seufert
5. Peggy N. Van Meter
6. Richard K. Lowe
7. Andrew Elby
8. Robert B. Kozma
9. Andrea A. diSessa
10. Peter A. Bibby

Who trusts Shaaron E. Ainsworth overall

1. Christine D. Tippett
2. Kirsten Berthold
3. Russell Tytler
4. Alexander Renkl
5. Vaughan Prain
6. Martina A. Rau
7. Narayankripa Sundararajan
8. Rolf Schwonke
9. Matthew Inglis
10. Fabien Lotte

Papers from Shaaron E. Ainsworth's perspective

Ordered by how strongly the researchers Shaaron E. Ainsworth trusts endorse each paper. Same corpus, a different order for every researcher.

1. Categorization and Representation of Physics Problems by Experts and Novices
2. Eliciting Self-Explanations Improves Understanding
3. Worked-out examples: instructional explanations support learning by self- explanations
4. Learning from human tutoring (Cognitive Sciences)
5. Multimedia Learning: The Promise of Multimedia Learning
6. Toward Computer-Based Support of Meta-Cognitive Skills: a Computational Framework to Coach Self-Explanation
7. Inventing to Prepare for Future Learning: The Hidden Efficiency of Encouraging Original Student Production in Statistics Instruction
8. SERT: Self-Explanation Reading Training
9. The Roles of Representations and Tools in the Chemistry Laboratory and Their Implications for Chemistry Learning
10. Aids to computer-based multimedia learning

Their papers

• The Educational Value of Multiple-representations when Learning Complex Scientific Concepts (2008) — 370 citations
• Drawing to Learn in Science (2011) — 704 citations
• The impact of text coherence on learning by self-explanation (2007) — 119 citations
• DeFT: A Conceptual Framework for Considering Learning with Multiple Representations. (2006) — 1,724 citations
• Multiple Forms of Dynamic Representation. (2004) — 298 citations
• Erratum to “The effects of self‐explaining when learning with text or diagrams” (2003) — 312 citations
• Examining the Effects of Different Multiple Representational Systems in Learning Primary Mathematics (2002) — 311 citations