A further study of productive failure in mathematical problem solving: unpacking the design components

By Manu Kapur. 2011

188 citations recorded by the source corpus.

Subfields: Developmental and Educational Psychology, Education, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/06e86c28eeb1b5ee737d5ff3d12f56e7ae5e1f37

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Developmental and Educational Psychology

1. Manu Kapur
2. Nikol Rummel
3. Katharina Loibl
4. Ido Roll
5. Katerine Bielaczyc
6. Bert Jonsson
7. Johan Lithner
8. Yvonne Liljekvist

In Education

1. Manu Kapur
2. Nikol Rummel
3. Katharina Loibl
4. Ido Roll
5. Katerine Bielaczyc
6. Bert Jonsson
7. Yvonne Liljekvist
8. Mathias Norqvist

In Statistics and Probability

1. Manu Kapur
2. Nikol Rummel
3. Katerine Bielaczyc
4. Katharina Loibl
5. Bert Jonsson
6. Yvonne Liljekvist
7. Mathias Norqvist
8. Ido Roll

Citations in the corpus

• Learning mathematics through algorithmic and creative reasoning (2014, background): “Well-defined tasks possess fewer parameters that can vary and, therefore, enhance participants’ confidence in completing the task (for a full explanation see, Kapur, 2008, 2011).”
• Learning from productive failure (2015, methodology): “In Kapur (2011), this question was addressed.”
• Designing for Productive Failure (2012, background): “Taken together, these findings emphasize the need to design and understand conditions under which delaying structure in learning and problem-solving activities can enhance learning (Kapur, 2008, 2009, 2010).”
• Examining Productive Failure, Productive Success, Unproductive Failure, and Unproductive Success in Learning (2016, background): “Both studies (Kapur, 2011; Loibl & Rummel, 2013) suggest that although guidance in the initial problem solving may well lead to problem-solving success or better quality of solutions, this better performance does not translate to better learning from the subsequent instruction.”
• Comparing Learning From Productive Failure and Vicarious Failure (2014, background): “Over a series of studies, I have demonstrated the efficacy of the PF learning design over a direct instruction design in terms of significantly better conceptual and transfer gains without a compromise in procedural fluency (Kapur, 2010, 2011a, 2012; Kapur & Bielaczyc, 2012).”
• Towards a Theory of When and How Problem Solving Followed by Instruction Supports Learning (2017, background): “In other studies (e.g., Kapur 2010, 2011, 2012; Loibl and Rummel 2014b; Roll et al. 2011), instruction includes an additional component in that the teacher builds on typical student-generated solutions before explaining the structurally relevant components of the canonical solution.”