Manu Kapur
Education University of Hong Kong, Psychological Studies, Faculty Member
- I am currently a Professor of Psychological Studies at the Hong Kong Institute of Education (HKIED). Prior to joining... moreI am currently a Professor of Psychological Studies at the Hong Kong Institute of Education (HKIED). Prior to joining the HKIED, I was the Head of the Curriculum, Teaching and Learning Department, as well as the Head of the Learning Sciences Lab (LSL) at the National Institute of Education (NIE) of Singapore. For more information, visit www.manukapur.com.edit
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Productive failure has shown positive effects on conceptual and transfer measures, but no clear effects on procedural measures. It is therefore an open question whether, and to what extent, productive failure methods may be used to... more
Productive failure has shown positive effects on conceptual and transfer measures, but no clear effects on procedural measures. It is therefore an open question whether, and to what extent, productive failure methods may be used to enhance the learning of procedural skills. A typical productive failure study focuses on a single, complex concept; in contrast, procedural knowledge generally consists of a series of less-complex procedural steps. In this study, failure occasions were adapted to specifically fit procedural knowledge by introducing procedural problems prior to the formal instruction of relevant principles. These procedural problems offered brief but multiple occasions for failure, which we call micro productive failure. A total of 85 sixth-graders were introduced to algebraic expression simplification by providing problem-solving prior to instruction (PS-I condition), compared to providing problem-solving after instruction (I-PS condition). Findings reveal a stable effect...
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Unscaffolded problem-solving before receiving instruction can give students opportunities to entertain their exploratory hypotheses at the expense of experiencing initial failures. Prior literature has argued for the efficacy of such... more
Unscaffolded problem-solving before receiving instruction can give students opportunities to entertain their exploratory hypotheses at the expense of experiencing initial failures. Prior literature has argued for the efficacy of such preparatory activities in preparing students to learn from instruction. Despite growing understanding of the underlying cognitive mechanisms, the pedagogical value of success or failure in initial problem-solving attempts is still unclear. We do not know yet whether some ways of succeeding or failing are more efficacious than others. We report empirical evidence from a classroom intervention (N = 221), where we designed scaffolds to explicitly push student problem-solving toward success via structuring, but also toward failure via problematizing. Our rationale for explicit failure scaffolding was rooted in facilitating problem-space exploration. We subsequently compared the differential preparatory effects of success-driven and failure-driven problem-solving on learning from follow-up instruction. Results suggested that failure-driven scaffolding (nudging students to generate suboptimal solutions) and success-driven scaffolding (nudging students to generate optimal solutions by giving them heuristics with low specificity) had similar outcomes on posttest assessments of conceptual understanding. Students exposed to failure-driven scaffolding, however, demonstrated higher quality of constructive reasoning. These trends were more salient for the learning concept with greater difficulty
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When teaching a novel mathematical concept, should we present learners with abstract or concrete examples? In this experiment, we conduct a critical replication and extension of a well-known study that argued for the general advantage of... more
When teaching a novel mathematical concept, should we present learners with abstract or concrete examples? In this experiment, we conduct a critical replication and extension of a well-known study that argued for the general advantage of abstract examples (Kaminski, Sloutsky, & Heckler, 2008a). We demonstrate that theoretically motivated yet minor modifications of the learning design put this argument in question. A key finding from this study is that participants who trained with improved concrete examples performed as well as, or better than, participants who trained with abstract examples. We argue that the previously reported "advantage of abstract examples" manifested not because abstract examples are advantageous in general, but because the concrete condition employed suboptimal examples.
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Mathematical Problem Solving in Singapore Schools Using Innovation Techniques to Generate NewA" Problems, Mathematical Problems for the Secondary Classroom Mathematical Problem Posing in Singapore Primary Schools Integrating... more
Mathematical Problem Solving in Singapore Schools Using Innovation Techniques to Generate NewA" Problems, Mathematical Problems for the Secondary Classroom Mathematical Problem Posing in Singapore Primary Schools Integrating Open-Ended Problems in the Lower Secondary Mathematics Lesson Arousing Students' Curiosity and Mathematical Problem Solving Learning Through Productive Failure in Mathematical Problem Solving Tasks and Pedagogies that Facilitate Mathematical Problem Solving Note Taking as Deliberative Pedagogy: Scaffolding Problem Solving Learning Solving Mathematical Problems by Investigation Mathematical Modeling and Real Life Problem Solving Generative Activities in Singapore (GenSing): Pedagogy and Practice, What's Next?.
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" Community " has become a commonplace term in the learning sciences. Alongside this popularization comes the view that communities are, in general, something to strive towards. We draw on contemporary trends to problematize this... more
" Community " has become a commonplace term in the learning sciences. Alongside this popularization comes the view that communities are, in general, something to strive towards. We draw on contemporary trends to problematize this assumption and motivate a discussion for the productivity of dissent.
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Learning and performance are not always commensurable. Conditions that maximize performance in the initial learning may not maximize learning in the longer term. I exploit this incommensurability to theoretically and empirically... more
Learning and performance are not always commensurable. Conditions that maximize performance in the initial learning may not maximize learning in the longer term. I exploit this incommensurability to theoretically and empirically interrogate four possibilities for design: productive success, productive failure, unproductive success, and unproductive failure. Instead of only looking at extreme comparisons between discovery learning and direct instruction, an analysis of the four design possibilities suggests a vast design space in between the two extremes that may be more productive for learning than the extremes. I show that even though direct instruction can be conceived as a productive success compared to discovery learning, theoretical and empirical analyses suggests that it may well be an unproductive success compared with examples of productive failure and productive success. Implications for theory and the design of instruction are discussed.
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A previously hypothesized formula for calculating components of adaptive expertise (AE= 0.10F + 0.40C + 0.50T, where F = Factual knowledge, C= Conceptual knowledge, and T = Transfer) was tested and the weighting adjusted based on analysis... more
A previously hypothesized formula for calculating components of adaptive expertise (AE= 0.10F + 0.40C + 0.50T, where F = Factual knowledge, C= Conceptual knowledge, and T = Transfer) was tested and the weighting adjusted based on analysis undertaken usin g 2-group MANOVA with the original study data. This data included measures of change along three facets of adaptive expertise: factual knowledge, conceptual knowledge and transfer. Analysis of the univariate effects reveals a significant difference in the transfer gain ( F=10.573, p= .004) but no significant difference on gains in conceptual knowledge ( F= .920, p= .349) or factual knowledge ( F= 3.104, p= .094). The linear combination that maximally separated the two groups was: 0.14F - 0.36C + 1.27T. The relative magnitudes of the weights share the same ordinal trend (F < C < T) as the original formula. The formula has theoretical underpinnings in How People Learn and attempts to describe points along the trajectory of novic...
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A large body of research has been concerned with learners' difficulties to detect and avoid misconceptions and to construct relations between multiple representations for building coherent mental representations of STEM topics.... more
A large body of research has been concerned with learners' difficulties to detect and avoid misconceptions and to construct relations between multiple representations for building coherent mental representations of STEM topics. Moreover, much research has been invested in the questions of how to choose the optimal representation of knowledge to optimize cognitive load and how to design multiple representations for learning purposes. MUPEMURE builds on this work and takes it further by asking how learners can be facilitated to actively create and modify multiple representations and acquire multiple perspectives on science topics through specific, collaborative knowledge building activities. This new perspective on representations is addressing current online scenarios of knowledge construction, e.g., in social networking sites, where learners can create, upload, and discuss pictures and videos.
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We advance a complexity− grounded, quantitative method for uncovering temporal patterns in CSCL discussions. We focus on convergence because understanding how complex group discussions converge presents a major challenge in CSCL research.... more
We advance a complexity− grounded, quantitative method for uncovering temporal patterns in CSCL discussions. We focus on convergence because understanding how complex group discussions converge presents a major challenge in CSCL research. From a complex systems perspective, convergence in group discussions is an emergent behavior arising from the transactional interactions between group members. Leveraging the concepts of emergent simplicity and emergent complexity (Bar-Yam 2003), a set of theoretically-sound ...
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... Paper 2: Delaying Structure: Productive Failure in Learning the Physics of Electricity using Agent-based models Authors: Michael J. Jacobson(a), Suneeta A. Pathak(b), Beaumie Kim(b), and BaoHui Zhang(b) (a)Centre for Research on... more
... Paper 2: Delaying Structure: Productive Failure in Learning the Physics of Electricity using Agent-based models Authors: Michael J. Jacobson(a), Suneeta A. Pathak(b), Beaumie Kim(b), and BaoHui Zhang(b) (a)Centre for Research on Computer Supported Collaborative ...
ABSTRACT This paper provides a &quot;theoretical case study&quot; of how perspectives from complexity research might provide insights into debates of theory in the learning sciences. The debate we examine concerns the... more
ABSTRACT This paper provides a &quot;theoretical case study&quot; of how perspectives from complexity research might provide insights into debates of theory in the learning sciences. The debate we examine concerns the &quot;fault line&quot; in the field related to the &quot;knowledge-in-pieces&quot; versus &quot;coherent knowledge&quot; about conceptual change (diSessa, 2006), which extends back to the seminal monograph in Cognition and Instruction in which diSessa (1993) articulated his theory of phenomenological primitives (p-prims) and of &quot;knowledge-in-pieces.&quot;
&amp;amp;quot;The goal of communities of learners (CoL) models is to foster deep disciplinary understanding -- -- an understanding of both subject matter and the ways the disciplinary community works with knowledge in a domain.... more
&amp;amp;quot;The goal of communities of learners (CoL) models is to foster deep disciplinary understanding -- -- an understanding of both subject matter and the ways the disciplinary community works with knowledge in a domain. Through working collectively to carry out investigations, learners develop the agency and social capacities necessary for creatively working with knowledge. Such models require teachers and students to engage in new modes of inquiry that tend to be very different from the ways in which learning and teaching occur in more traditional classrooms. In fact, we have previously described this type of educational model as a “radical reconceptualization of educational practice” (Bielaczyc &amp;amp;amp; Collins, 1999). Similarly, Bereiter (2002) claims “Students need to be socialized into the world of work with knowledge, and that is an even more radical cultural change than becoming ‘digital’” (p. 220). Thus, we believe that one of the greatest challenges facing the implementation of CoL models concerns how to support the change processes that teachers and their students must move through. The intention of this chapter is to collect together what has been learned in the educational community and in our own work with teachers concerning how to cultivate a community of learners. We discuss both key theoretical underpinnings (design principles, epistemology and an understanding of how students learn) along with five key changes in the classroom that we believe provide the most transformational leverage in bringing CoL’s to life in K-12 classrooms.&amp;amp;quot;
Throughout most of history, teaching and learning have been based on apprenticeship. Children learned how to speak, grow crops, construct furniture, and make clothes. But they didn’t go to school to learn these things; instead, adults in... more
Throughout most of history, teaching and learning have been based on apprenticeship. Children learned how to speak, grow crops, construct furniture, and make clothes. But they didn’t go to school to learn these things; instead, adults in their family and in their communities showed them how, and helped them do it. Even in modern societies, we learn some important things through apprenticeship: we learn our first language from our families, employees learn critical skills on the job, and scientists learn how to conduct world-class research by working side-by-side with senior scientists as part of their doctoral training. But for most other kinds of knowledge, schooling has replaced apprenticeship. Apprenticeship requires a very small teacher-to-learner ratio and this is not realistic in the large educational systems of modern industrial economies.
If there were some way to tap into the power of apprenticeship, without incurring the large costs associated with hiring a teacher for every two or three students, it could be a powerful way to improve schools. In the 1970s and 1980s, researchers at the intersection of education and new computer technology were studying how this new technology could help to transform schooling. In a series of articles we explored how to provide students with apprenticeship-like experiences, providing the type of close attention and immediate response that has always been associated with apprenticeship.
If there were some way to tap into the power of apprenticeship, without incurring the large costs associated with hiring a teacher for every two or three students, it could be a powerful way to improve schools. In the 1970s and 1980s, researchers at the intersection of education and new computer technology were studying how this new technology could help to transform schooling. In a series of articles we explored how to provide students with apprenticeship-like experiences, providing the type of close attention and immediate response that has always been associated with apprenticeship.
Research Interests:
Article usage statistics combine cumulative total PDF downloads and full-text HTML views from publication date (but no earlier than 25 Jun 2011, launch date of this website) to 10 Feb 2013. Article views are only counted from this site.... more
Article usage statistics combine cumulative total PDF downloads and full-text HTML views from publication date (but no earlier than 25 Jun 2011, launch date of this website) to 10 Feb 2013. Article views are only counted from this site. Although these data are updated every 24 hours, there may be a 48-hour delay before the most recent numbers are available.
Page 1. Productive failure in CSCL groups Manu Kapur &amp; Charles K. Kinzer Received: 7 February 2008 /Accepted: 21 November 2008 / Published online: 10 December 2008 © International Society of the Learning Sciences, Inc.; Springer... more
Page 1. Productive failure in CSCL groups Manu Kapur &amp; Charles K. Kinzer Received: 7 February 2008 /Accepted: 21 November 2008 / Published online: 10 December 2008 © International Society of the Learning Sciences, Inc.; Springer Science + Business Media, LLC 2008 ...
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... by explanations and critique could be independent of each other whereas for the second group, they could be co-evolving and dependent. ... Therefore, methods that take temporality into account stand to not only add to the... more
... by explanations and critique could be independent of each other whereas for the second group, they could be co-evolving and dependent. ... Therefore, methods that take temporality into account stand to not only add to the methodological toolkit of the researcher but also help in ...
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When learning a new math concept, should learners be first taught the concept and its associated procedures and then solve problems, or solve problems first even if it leads to failure and then be taught the concept and the procedures?... more
When learning a new math concept, should learners be first taught the concept and its associated procedures and then solve problems, or solve problems first even if it leads to failure and then be taught the concept and the procedures? Two randomized-controlled studies found that both methods lead to high levels of procedural knowledge. However, students who engaged in problem solving before being taught demonstrated significantly greater conceptual understanding and ability to transfer to novel problems than those who were taught first. The second study further showed that when given an opportunity to learn from the failed problem-solving attempts of their peers, students outperformed those who were taught first, but not those who engaged in problem solving first. Process findings showed that the number of student-generated solutions significantly predicted learning outcomes. These results challenge the conventional practice of direct instruction to teach new math concepts and procedures, and propose the possibility of learning from one&amp;amp;amp;amp;#39;s own failed problem-solving attempts or those of others before receiving instruction as alternatives for better math learning.
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This study demonstrates an existence proof for productive failure: engaging students in solving complex, ill-structured problems without the provision of support structures can be a productive exercise in failure. In a computer-supported... more
This study demonstrates an existence proof for productive failure: engaging students in solving complex, ill-structured problems without the provision of support structures can be a productive exercise in failure. In a computer-supported collaborative learning setting, ...