Reasoning and Problem Solving

Leighton, Jacqueline P.; Sternberg, Robert J.

doi:10.1002/9781118133880.hop204023

Cited by 5 publications

(3 citation statements)

References 141 publications

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“…Mental model of learning environment alongside information processing of instructional lesson (knowledge and skills) observe and hear in their classroom environments (Leighton & Sternberg, 2012). As illustrated in the middle box of Figure 3 above, mental models include two parts -a cognitive part related to the knowledge and skills learned in the instructional environment, and an affective part related to their sense of wellbeing within that environment (Leighton & Sternberg, 2012).…”

Section: Mental Models Of Learningmentioning

confidence: 99%

“…As illustrated in the middle box of Figure 3 above, mental models include two parts -a cognitive part related to the knowledge and skills learned in the instructional environment, and an affective part related to their sense of wellbeing within that environment (Leighton & Sternberg, 2012). For example, on the cognitive front, a student who observes a teacher repeatedly assign math homework may add to his or her mental model the idea that math requires practicing skills.…”

Section: Mental Models Of Learningmentioning

confidence: 99%

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Operationalizing the role of trust for student wellbeing, learning and achievement

Leighton

Seitz

Chu

et al. 2016

Intnl. J. Wellbeing

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This paper provides an argument regarding the importance of relational trust between students and teachers during the learning process. Establishing this trust is expected to foster student wellbeing and lead to openness to learn and increased innovativeness. However, there is a relative dearth of theoretical and empirical literature on behaviors to establish relational trust (Bryk & Schneider, 2002;Tschannen-Moran & Hoy, 1997), and how these behaviors can be expected to lead to wellbeing and academic achievement. The Learning Errors and Formative Feedback (LEAFF) model is proposed to organize key aspects of the theoretical literature as they might relate to measurable ways in which trust can be promoted with specific words and actions in the classroom to enhance learning. Based on the LEAFF model, a framework is designed to operationalize facets of trust to help teachers develop trusting relationships with their students. However, the potential effects of these facets need to be empirically tested in future studies to secure optimal learning outcomes.

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Section: Mental Models Of Learningmentioning

confidence: 99%

Section: Mental Models Of Learningmentioning

confidence: 99%

Operationalizing the role of trust for student wellbeing, learning and achievement

Leighton

Seitz

Chu

et al. 2016

Intnl. J. Wellbeing

Self Cite

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“…Here we followGiardino (2017) and others in not making a clear-cut distinction between problem solving and reasoning when it comes to mathematics. However, we are aware that these two types of processes are distinguished in cognitive psychology(Galotti 1989;Leighton and Sternberg 2012).…”

mentioning

confidence: 99%

A fresh look at research strategies in computational cognitive science: The case of enculturated mathematical problem solving

Fabry

Pantsar

2019

Synthese

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Marr's seminal distinction between computational, algorithmic, and implementational levels of analysis has inspired research in cognitive science for more than 30 years. According to a widely-used paradigm, the modelling of cognitive processes should mainly operate on the computational level and be targeted at the idealised competence, rather than the actual performance of cognisers in a specific domain. In this paper, we explore how this paradigm can be adopted and revised to understand mathematical problem solving. The computational-level approach applies methods from computational complexity theory and focuses on optimal strategies for completing cognitive tasks. However, human cognitive capacities in mathematical problem solving are essentially characterised by processes that are computationally sub-optimal, because they initially add to the computational complexity of the solutions. Yet, these solutions can be optimal for human cognisers given the acquisition and enactment of mathematical practices. Here we present diagrams and the spatial manipulation of symbols as two examples of problem solving strategies that can be computationally sub-optimal but humanly optimal. These aspects need to be taken into account when analysing competence in mathematical problem solving. Empirically informed considerations on enculturation can help identify, explore, and model the cognitive processes involved in problem solving tasks. The enculturation account of mathematical problem solving strongly suggests that computational-level analyses need to be complemented by considerations on the algorithmic and implementational levels. The emerging research strategy can help develop algorithms that model what we call enculturated cognitive optimality in an empirically plausible and ecologically valid way.

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A pedagogical alliance for trust, wellbeing and the identification of errors for learning and formative assessment

Leighton

Gómez²

2017

Educational Psychology

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Reasoning and Problem Solving

Cited by 5 publications

References 141 publications

Operationalizing the role of trust for student wellbeing, learning and achievement

Operationalizing the role of trust for student wellbeing, learning and achievement

A fresh look at research strategies in computational cognitive science: The case of enculturated mathematical problem solving

A pedagogical alliance for trust, wellbeing and the identification of errors for learning and formative assessment

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