Fostering complex problem solving for diverse learners: engaging an ethos of intentionality toward equitable access

Complex problem solving is an effective means to engage students in disciplinary content while also furnishing critical non-cognitive and life skills. Despite increased adoption of complex problem-solving methods in K-12 classrooms today (e.g., case-, project-, or problem-based learning), we know little about how to make these approaches accessible to linguistically and culturally diverse (LCD) students. In this paper, we promote a conceptual framework, based on an ethos of intentionality, that supports culturally responsive teaching (CRT). We provide specific questions to guide teachers’ implementation of an ethos of intentionality, through critical reflection and meaningful action, and discuss a framework for culturally relevant practice that operationalizes key central tenets (e.g., high expectations, cultural competence, and critical consciousness). Finally, we include strategies that can help teachers and designers translate the principles of the CRT framework into action with a specific focus on complex problem solving in classrooms.

     

浅谈如何在阅读教学中实施问题教学

在阅读教学中实施问题教学,对于激发学生阅读的认知动力,强化阅读的认知操作活动,提高阅读活动效能,培养学生独立阅读的能力以及评价反馈阅读教学效果,都有极为重要的意义.本文从三方面探讨了如何在阅读教学中实施问题教学创设问题情境、培养学生的问题意识;教给学生质疑方法,启发学生提出问题;教给学生解疑方法,培养他们解决问题的能力.     

Learning Relative Motion Concepts in Immersive and Non-immersive Virtual Environments

The focus of the current study is to understand which unique features of an immersive virtual reality environment have the potential to improve learning relative motion concepts. Thirty-seven undergraduate students learned relative motion concepts using computer simulation either in immersive virtual environment (IVE) or non-immersive desktop virtual environment (DVE) conditions. Our results show that after the simulation activities, both IVE and DVE groups exhibited a significant shift toward a scientific understanding in their conceptual models and epistemological beliefs about the nature of relative motion, and also a significant improvement on relative motion problem-solving tests. In addition, we analyzed students’ performance on one-dimensional and two-dimensional questions in the relative motion problem-solving test separately and found that after training in the simulation, the IVE group performed significantly better than the DVE group on solving two-dimensional relative motion problems. We suggest that egocentric encoding of the scene in IVE (where the learner constitutes a part of a scene they are immersed in), as compared to allocentric encoding on a computer screen in DVE (where the learner is looking at the scene from “outside”), is more beneficial than DVE for studying more complex (two-dimensional) relative motion problems. Overall, our findings suggest that such aspects of virtual realities as immersivity, first-hand experience, and the possibility of changing different frames of reference can facilitate understanding abstract scientific phenomena and help in displacing intuitive misconceptions with more accurate mental models.     

A causal framework for analysing alternative conceptions

A model for the analysis of subjects’ causal reasoning is proposed, drawing on de Kleer and Brown's ‘mechanistic mental models’. The purpose of the model is to provide a framework for understanding the possible causal structure of children's and adults’ spontaneous reasoning about the physical world. The model is used to analyse data on students’ understanding of aspects of forces and motion; to reanalyse a protocol of Driver's; and to compare and criticize the models of Andersson and of Rozier. We show how the model can provide a language for describing common‐sense causal thinking.     

Teacher interactions and effects on group triple problem solving space

ABSTRACT

Research shows that collaborative work promotes student learning and improves social skills, but teachers are still exploring how to best support problem-solving in a small group context, particularly in the science classroom. This study builds on prior research to characterise teacher interactions with small groups in secondary science and analyses how those interactions affect a collectively constructed space – the triple problem solving space (TPSS) – in which group members collectively understand a task (content/cognitive dimension), manage social interactions (social/relational dimension), and co-construct the emotional life of the group (affective dimension). Results of two biology teachers’ interactions with students in small groups working on inquiry and engineering design activities show that most interactions were administrative and had little influence on the group’s TPSS. Teacher interactions that engaged students in monitoring their problem-solving process, however, did have the capacity to increase cognitive work of the group, which subsequently impacted the students’ group affect and social dimension. These findings suggest that interactions focused on cognitive processes have the potential to support all aspects of a group’s TPSS. Though this research is only a first step in understanding the impact of teacher interactions on small group work, implications for teaching practices are discussed.     

Fluid reasoning,working memory and planning ability in assessment of risk for mathematical difficulties

ABSTRACT

The demands on mathematical problem-solving have increased in almost all school systems internationally and may constitute a barrier for children with special educational needs (SEN). This study explored the role of fluid reasoning (FR), working memory (WM) and complex executive function of planning (EF) in children (N = 62) referred for assessment of SEN, and specifically of risk for mathematical difficulties (MD). Performances on FR, WM and complex EF of planning were used to predict risk for MD. Results showed that planning ability predicted children at risk for MD, beyond FR or WM ability, when comparing with children not at risk for MD. It was concluded that assessing the complex EF of planning in addition to FR and WM ability is crucial in identifying children at risk for MD. The importance of understanding how planning ability affects children’s mathematical problem-solving is discussed, in relation to assessment and teaching practices.     

Learning problem-solving through making games at the game design and learning summer program

Today’s complex and fast-evolving world necessitates young students to possess design and problem-solving skills more than ever. One alternative method of teaching children problem-solving or thinking skills has been using computer programming, and more recently, game-design tasks. In this pre-experimental study, a group of middle school students (n = 18) with an age average of 12.6 attended a game-design summer program for 10 days. Students were assessed in their problem-solving skills, specifically in system analysis and design, decision-making, and troubleshooting domains, at the beginning and end of the program. The results indicated that there were significant improvements in students’ problem-solving skills after attending the summer program, Wilks’ Λ = .258, F (3, 15) = 14.397, p < .001, η ² = .742. For system analysis and design, and decision-making follow-up t-tests pointed to large and medium effect sizes, while for troubleshooting the gains were not significant. This study is a contributes to the growing body of literature investigating the benefits of designing games for young children by adding that game-design activities can be suitable venues for young children to learn and practice problem-solving skills.     

Designing effective supports for causal reasoning

Causal reasoning represents one of the most basic and important cognitive processes that underpin all higher-order activities, such as conceptual understanding and problem solving. Hume called causality the “cement of the universe” [Hume (1739/2000). Causal reasoning is required for making predictions, drawing implications and inferences, and explaining phenomena. Causal relations are usually more complex than learners understand. In order to be able to understand and apply causal relationships, learners must be able to articulate numerous covariational attributes of causal relationships, including direction, valency, probability, duration, responsiveness, as well as mechanistic attributes, including process, conjunctions/disjunctions, and necessity/sufficiency. We describe different methods for supporting causal learning, including influence diagrams, simulations, questions, and different causal modeling tools, including expert systems, systems dynamics tools, and causal modeling tools. Extensive research is needed to validate and contrast these methods for supporting causal reasoning.     

Questioning Our Questions: Assessing Question Asking Practices to Evaluate a yPAR Program

The purpose of this research was to examine question asking practices in a youth participatory action research (yPAR) after school program housed at an elementary school. The research question was: In which ways did the adult question asking practices in a yPAR setting challenge and/or reproduce conventional models of power in educational settings? We aligned Fink’s taxonomy (Creating significant learning experiences: an integrated approach to designing college courses. Jossey-Bass, San Francisco, 2003) to Freire’s (The pedagogy of the oppressed. Continuum, New York, 1970/2000) banking concept and problem-posing educational models. All adult questions were categorized from twelve randomly selected yPAR sessions over 2 years. The program served 4th and 5th grade students. Of the 500+ questions adults asked, 17 % were foundational (aligned with Freire’s banking concept). All other questions were aligned with Freire’s problem-posing model. Specifically, 34 % were application, 3 % were integration, 15 % were caring, 11 % were human dimension, and 8 % were learning how to learn questions. By studying question asking patterns and practices, we gained a better understanding of how students and adults navigated this particular after school space, which, at its core, sought to disrupt conventional notions of power and status.     

Problem Solving and Teaching How to Solve Problems in Technology-Rich Contexts

ABSTRACT

Problem solving is perhaps the key characteristic that makes us human. Given the kinds of problems that we face in a competitive economy and society, the new generation of learners is ever more required to have problem-solving abilities. By drawing from the literature on technological pedagogical content knowledge, design thinking, general and specific methods of problem solving, and role of technologies for solving problems, this article highlights the importance of problem solving for future teachers and discusses strategies that can help them become good problem solvers and understand the requirements of teaching their students problem solving in technology-rich contexts. This article consists of two main parts. Part 1 focuses on strategies required to help preservice teachers to be better problem solvers, and Part 2 summarizes approaches to introduce preservice teachers to the methods of teaching problem solving. The strategies reviewed provide a tangible guidance for teacher education programs regarding how to promote future teachers’ problem-solving skills.     

Written feedback provided by first-year engineering students,undergraduate teaching assistants,and educators on design project work

ABSTRACT

Feedback is an important part of design education. To better understand how feedback is provided to students on their engineering design work, we characterised and compared first-year engineering students’, undergraduate teaching assistants’, and educators’ written feedback on sample student design work. We created a coding scheme including two domains: Substance and Focus of feedback. Educators made more and longer comments than undergraduate teaching assistants, and undergraduate teaching assistants made more and longer comments than first-year students. The first-year students focused on giving specific directions in their feedback while educators and undergraduate teaching assistants asked thought-provoking questions. Students tended to make more comments about the ways that their peers had communicated their design work while educators and undergraduate teaching assistants made more comments about the design ideas presented in the sample work. This study offers implications for practice for supporting educators, undergraduate teaching assistants, and first-year engineering students to be able to provide feedback on design work.     

Model-Based Knowing: How Do Students Ground Their Understanding About Climate Systems in Agent-Based Computer Models?

This paper gives a grounded cognition account of model-based learning of complex scientific knowledge related to socio-scientific issues, such as climate change. It draws on the results from a study of high school students learning about the carbon cycle through computational agent-based models and investigates two questions: First, how do students ground their understanding about the phenomenon when they learn and solve problems with computer models? Second, what are common sources of mistakes in students’ reasoning with computer models? Results show that students ground their understanding in computer models in five ways: direct observation, straight abstraction, generalisation, conceptualisation, and extension. Students also incorporate into their reasoning their knowledge and experiences that extend beyond phenomena represented in the models, such as attitudes about unsustainable carbon emission rates, human agency, external events, and the nature of computational models. The most common difficulties of the students relate to seeing the modelled scientific phenomenon and connecting results from the observations with other experiences and understandings about the phenomenon in the outside world. An important contribution of this study is the constructed coding scheme for establishing different ways of grounding, which helps to understand some challenges that students encounter when they learn about complex phenomena with agent-based computer models.

     

EFFECT OF CULTURE ON HIGH-SCHOOL STUDENTS’ QUESTION-ASKING ABILITY RESULTING FROM AN INQUIRY-ORIENTED CHEMISTRY LABORATORY

In order to cope with complex issues in the science–technology–environment–society context, one must develop students’ high-order learning skills, such as question-asking ability (QAA), critical thinking, evaluative thinking, decision-making, and problem-solving capabilities within science education. In this study, we are concerned with evaluating the effect of student–teacher interaction—which is regulated by culture and traditions—on the QAA in science classroom in general and, specifically in our case, in chemistry laboratory classroom. We take Arab and Jewish sectors that are according to the literature different in their culture and tradition, as a model for our investigation. Specially developed and validated tools, including a novel practical test and an adapted article followed by a questionnaire for evaluating QAA, were administered to the research student population, and the responses were analyzed quantitatively. Observations were conducted in order to better understand the quantitative results that we got. Our findings indicate that there was a difference in the QAA between the 2 sectors. According to our findings, we assume that cultures, tradition, norms, social structure, modes of living, and related factors play a significant role as far as the development of students’ QAA and apparently any intended attempt targeting the QAA paradigm shift must take into consideration the multicultural context within which it is to be implemented.     

Teacher characteristics for success in the classroom: Chinese principals’ perceptions for hiring decisions

Two research questions guided this study of teacher selection: (a) What characteristics do Chinese principals look for when hiring teachers? And (b) what is the effect of participants’ gender, experience, or school location on perceived characteristics of effective teacher candidates in hiring? Both interviews and a questionnaire survey were used to collect data from a southwest city of Shandong Province, China. In this mixed design study, quantitative results were consistent with the qualitative results. Additionally, the study results are intended to help readers better understand school principals’ perceived characteristics of effective teachers in a Chinese context and provides a framework for future comparative research between China and the USA.

     

Moral disengagement: A new lens with which to examine children’s justifications for lying

ABSTRACT

The development of children’s lie-telling abilities is considered to be a social and cognitive milestone. While occasional lying is developmentally appropriate, the use of frequent, antisocial lies as a maladaptive problem-solving mechanism can indicate behaviour problems. Since lying is often considered a moral transgression, researchers should examine lying from the perspective of moral theory to understand children’s reasons for lying, which may help to understand how chronic lying develops. A theoretical framework, namely the social cognitive process of moral disengagement (MD) could not only provide new insight into children’s justifications for telling common lies, but also atypical, antisocial lies. This paper aims to describe how MD may be applied to explain children’s justifications for lying, especially antisocial lies, and how adults can address MD by modelling the positive consequences of truth-telling, to promote honesty in children.     

Using causal models to bridge the divide between big data and educational theory

An extraordinary amount of data is becoming available in educational settings, collected from a wide range of Educational Technology tools and services. This creates opportunities for using methods from Artificial Intelligence and Learning Analytics (LA) to improve learning and the environments in which it occurs. And yet, analytics results produced using these methods often fail to link to theoretical concepts from the learning sciences, making them difficult for educators to trust, interpret and act upon. At the same time, many of our educational theories are difficult to formalise into testable models that link to educational data. New methodologies are required to formalise the bridge between big data and educational theory. This paper demonstrates how causal modelling can help to close this gap. It introduces the apparatus of causal modelling, and shows how it can be applied to well-known problems in LA to yield new insights. We conclude with a consideration of what causal modelling adds to the theory-versus-data debate in education, and extend an invitation to other investigators to join this exciting programme of research.

Practitioner notes

What is already known about this topic

• ‘Correlation does not equal causation’ is a familiar claim in many fields of research but increasingly we see the need for a causal understanding of our educational systems.
• Big data bring many opportunities for analysis in education, but also a risk that results will fail to replicate in new contexts.
• Causal inference is a well-developed approach for extracting causal relationships from data, but is yet to become widely used in the learning sciences.

What this paper adds

• An overview of causal modelling to support educational data scientists interested in adopting this promising approach.
• A demonstration of how constructing causal models forces us to more explicitly specify the claims of educational theories.
• An understanding of how we can link educational datasets to theoretical constructs represented as causal models so formulating empirical tests of the educational theories that they represent.

Implications for practice and/or policy

• Causal models can help us to explicitly specify educational theories in a testable format.
• It is sometimes possible to make causal inferences from educational data if we understand our system well enough to construct a sufficiently explicit theoretical model.
• Learning Analysts should work to specify more causal models and test their predictions, as this would advance our theoretical understanding of many educational systems.

     

The use of adjunct displays to facilitate comprehension of causal relationships in expository text

We examined whether making cause and effect relationships explicit with an adjunct display improves different facets of text comprehension compared to a text only condition. In two experiments, participants read a text and then either studied a causal diagram, studied a list, or reread the text. In both experiments, readers who studied the adjunct displays better recalled the steps in the causal sequences, answered more problem-solving transfer items correctly, and answered more questions about transitive relationships between causes and effects correctly than those who reread the text. These findings supported the causal explication hypothesis, which states that adjunct displays improve comprehension of causal relationships by explicitly representing a text’s causal structure, which helps the reader better comprehend causal relationships.     

How to ask better questions? Dewey's theory of ecological psychology in encouraging practice of action learning

This paper provides an overview of John Dewey's ecological psychology and his basic concepts: experience, inquiry, and habit. The concept of habit, which is particularly relevant in understanding problem-solving strategies, is further explicated on the basis of Gross’s (2009. “A Pragmatist Theory of Social Mechanisms.” American Sociological Review 74: 358–379) conceptions of habits by way of an analysis of an action learning case study. It is argued that a deeper understanding of Dewey's ecological psychology, and the application of his concepts, may assist action learning practitioners to better understand why problems arise and how people solve them habitually, and thereby enable us to ask questions that can foster double loop learning.     

Reflecting critically on the critical disposition within Internationalisation of the Curriculum (IoC): the developmental journey of a curriculum design team

ABSTRACT

Internationalisation of curriculum (IoC) practices promote students developing knowledge of other cultures, attitudes, values and ethics. This conceptual article argues that embedding critical reflection in the IoC program – through integrating insights from both IoC thinkers and critical reflection literature – may allow educators and students to not only gain understanding and/or competency in other cultures but better address questions of privilege, power and colonisation and thereby interrogate their own normative cultural understandings. Borrowing from debates within IoC pedagogy, as well as from Ahmed’s work on critical reflection, this article also argues that cross/intercultural understanding should be understood (and taught) not as a competency but a disposition towards thinking, analysing and understanding the world which is based on critiquing the ‘self’ and its relationship with the ‘other’.