自动化专业系列实验教学中的认知心理引导

在系列实验教学过程中进行认知心理引导,是落实以学习者为中心教学理念的重要环节。针对自动化专业本科生,基于认知心理学,结合系列课程系列实验案例讨论了基于问题解决的知识建构过程的引导、系统的学科视角的引导、科学分析方法论的引导、以及实践创新意识的引导。     

Metacognition as a Basis for Learning Support Software

In order to understand the task of instructional designers who produce learning support software, this paper reviews the influence of learning theory on instructional design, recent developments in computer technology, and the evolving role of the instructor as a facilitator of higher-order thinking. Constructivist principles of learning and an appreciation for the fact that the learner must become more independent and skilled in metacognitive self-assessment and self-management are fundamental to this changing role. Two cognitive tools that provide learner/user support for personal construction of knowledge systems are “MindMap” and “Learning FourMat Processor.” These tools are examined in the light of current learning theory and a recent study comparing the work of novice and expert writers using different forms of performance support. Recommendations are made for the development of a more complete set of cognitive tools that enables users to construct their own multimedia knowledge systems based on higher-order thinking and problem solving.     

Activity theory as a framework for designing constructivist learning environments

The epistemic assumptions of constructive learning are different from those of traditional instruction, so classical methods of needs and task analysis are inappropriate for designing constructivist learning environments (CLEs). This paper argues that activity theory provides an appropriate framework for analyzing needs, tasks, and outcomes for designing CLEs. Activity theory is a socio-cultural, socio-historical lens through which designers can analyze human activity systems. It focuses on the interaction of human activity and consciousness within its relevant environmental context. Since conscious learning emerges from activity (performance), not as a precursor to it, CLEs should attempt to replicate the activity structures, tools and sign systems, socio-cultural rules, and community expectations that performers must accommodate while acting on some object of learning. After explicating assumptions of activity theory and briefly describing the components of CLEs, this paper describes a process for using activity theory as a framework for describing the components of an activity system that can be modeled in CLEs.His current research focuses on designing constructivist learning environments, cognitive tools for learning, knowledge representation methods, problem solving, computer-supported collaborative argumentation, cognitive task analysis, and individual differences and learning.His current research focuses on designing constructivist learning environments, cognitive tools for learning, knowledge representation methods, problem solving, computer-supported collaborative argumentation, cognitive task analysis, and individual differences and learning.Her research interests include activity theory and structural knowledge.     

案例知识与复杂问题解决

人们在日常生活中需要不断地解决各种问题,正如波普尔所说"全部的生活就是问题解决"。问题解决,尤其是复杂问题的解决,已成为认知科学和学习研究中关注的焦点。复杂问题的解决是一个动态的复杂过程,需要综合运用多种认知和非认知成分。先前的研究已经提出了解决复杂问题的多种模型,给人们解决复杂问题提供了可依靠的支架。而案例知识作为一种典型性、叙事性、情境性、实践性、个人性、整体性的经验知识在问题解决中得到了广泛应用,已成为支持复杂问题解决的有效形式,具体表现为:支持问题境脉的阐释、支持问题的多视角认识、支持解决方案的生成、支持解决方案的确定以及支持对问题解决结果的评价。它正作为一种支持人们解决问题的资源,在现实中发挥越来越大的作用。     

Team-based complex problem solving: a collective cognition perspective

Today, much problem solving is performed by teams, rather than individuals. The complexity of these problems has exceeded the cognitive capacity of any individual and requires a team of members to solve them. The success of solving these complex problems not only relies on individual team members who possess different but complementary expertise, but more importantly, their collective problem solving ability. To better conceptualize large scale complex problem solving, an understanding of collective cognitive components and processes during team-based complex problem solving is necessary. This paper offers a conceptual discussion about complex problem solving from a collective cognition perspective. The types of cognitive processing and cognitive components of team-based problem solving (TBPS) as well as the cognitive states of collective emergent cognitive states and the interactive mechanisms will be discussed. Also, implications from the model for assessing TBPS performance and suggestions for future research will be offered.     

PROBLEM FINDING: DISCOVERING AND FORMULATING PROBLEMS

Research and theory on problem finding are scarce. This can be ascribed to difficulties in the operationalisation of the concept and to neglect of the importance of this essential link in the problem solving cycle. A similar lacuna, however, is not found in early research in the field of problem solving. In problem solving four components can be distinguished: cognitive (sensitivity to problems and formulating the problem), motivational (effectance motivation and curiosity), emotional (wonder and surprise) and, finally, personality components (tolerance for ambiguity, stimulus reduction and self‐confidence). Selective encoding, combining and comparing can be regarded as essential elements of the cognitive component. With respect to the developmental aspects of problem finding, emphasis is laid on the importance of competence motivation and the quality of attachment as determinants. The educational implications are unequivocal: problem solving and problem finding must have equal positions in curricula. For the time being this means that education will have to pay more attention to problem finding.     

Measuring and Validating Cognitive Modifiability as an Ability: A Study in the Spatial Domain

Measuring cognitive modifiability from the responsiveness of an individual's performance to intervention has long been viewed (e.g., Dearborne, 1921) as an alternative to traditional (static) ability measurement. Currently, dynamic testing, in which cues or instruction are presented with ability test items, is a popular method for assessing cognitive modifiability. Despite the long-standing interest, however, little data exists to support the validity of cognitive modifiability measures in any ability domain. Several special methodological difficulties have limited validity studies, including psychometric problems in measuring modifiability (i.e., as change), lack of appropriate validation criteria, and difficulty in linking modifiability to cognitive theory. In this article, relatively new developments for solving the validation problems are applied to measuring and validating spatial modifiability. Criterion-related validity for predicting learning in an applied knowledge domain, as well as construct validity, is supported.     

The Rationality Debate: Application of Cognitive Psychology to Mathematics Education

Research in mathematics education usually attempts to look into students’ learning and other mental processes. It could therefore be expected to build on knowledge acquired within the academic discipline of cognitive psychology. Our aim in this paper is to show how some recent developments in cognitive psychology can help interpret empirical results from mathematics education. In particular, we will be looking into the heuristics-and-biases research by Kahneman and Tversky, the alternative views by Gigerenzer et al., and the more recent dual-process theory that has come to play a central role in interpreting this research. We first introduce the relevant background from cognitive psychology and survey its connections to previous work in mathematics education; then we apply this theoretical framework for re-interpreting previously-published empirical data from mathematics education research. We conclude with a discussion of potential theoretical and practical benefits of such synthesis.     

论符号加工取向的认知研究

符号加工认知论是现代认知心理学的一种重要的研究取向。符号加工认知论强调知识对行为和认知活动的决定作用,强调对认知过程的整体性研究,并把"心理活动像计算机"作为其隐喻基础,采用计算机模拟的方法,对知觉、注意、记忆以及问题解决等认知问题进行了大量的模拟研究,在揭示人的认知本质和机制等方面取得了重要的进展,但由于隐喻本身的局限性,也使这种研究存在着严重的不足。     

Using and Selecting Graphic Techniques to Acquire Structural Knowledge

Structural knowledge, the knowledge of relationships between concepts in a content area, is essential for comprehension and problem solving. Learning structural knowledge can be facilitated through learner-generated two-dimensional diagrams of conceptual relationships. These diagrams include networks, concept maps, pattern notes, semantic maps and graphic organizers. In this paper, we describe the characteristics of graphic techniques and the cognitive processes that learners use to construct the diagrams. We then propose a model that can be used to choose between different graphic techniques based upon the cognitive processes elicited by the techniques and the learning outcomes derived from their use.     

问题解决策略的认知和元认知研究

介绍了国内外学者近年来对问题解决策略的认知和元认知研究的最新成果:Alessandro Antonietti和梁宁建等人所做的大学生对一般问题解决策略的元认知的调查,Daniela Lueangeli等人所做的算术应用题解决中的认知和元认知能力的研究.     

Empowering educationally disadvantaged mathematics students through a strategies-based problem solving approach

A major impediment to problem solving in mathematics in the great majority of South African schools is that disadvantaged students from seriously impoverished learning environments are lacking in the necessary informal mathematical knowledge to develop their own strategies for solving non-routine problems. A randomized pretest–posttest control group design was used to empirically investigate the effectiveness of a strategies-based problem solving approach on the problem solving performance of 9th grade disadvantaged students. In this approach students receive explicit instruction on a wide repertoire of problem solving strategies. The results reported in this study show a significant improvement in problem solving performance when a strategies-based approach to problem solving was being implemented. Quantitative and qualitative analyses of the responses to the items showed how the treatment group students had internalized as part of their problem solving repertoire the strategies on which they had been explicitly instructed on. The findings of this study make a case for the adoption of this approach so that the gap between the student’s existing problem solving competence, and the cognitive demands of a problem solving task can be bridged.     

Some implications of cognitive theory for instructional design

This article examines some of the implications of recent developments in cognitive theory for instructional design. It is argued that behavioral theory is inadequate to prescribe instructional strategies that teach for understanding. Examples of how instructional designers have adopted relevant aspects of cognitive theory are described. However, it is argued that such adoption is only a first step. The growing body of evidence for the indeterminism of human cognition requires even further changes in how instructional designers think and act. A number of bodies of scholarly research and opinion are cited in support of this claim. Three implications of cognitive theory for design are offered: instructional strategies need to be developed to counter the reductionism implicit in task analysis; design needs to be integrated into the implementation of instruction; designers should work from a thorough knowledge of theory not just from design procedures.     

“Accepting Emotional Complexity”: A Socio-Constructivist Perspective on the Role of Emotions in the Mathematics Classroom

A socio-constructivist account of learning and emotions stresses the situatedness of every learning activity and points to the close interactions between cognitive, conative and affective factors in students’ learning and problem solving. Emotions are perceived as being constituted by the dynamic interplay of cognitive, physiological, and motivational processes in a specific context. Understanding the role of emotions in the mathematics classroom then implies understanding the nature of these situated processes and the way they relate to students’ problem-solving behaviour. We will present data from a multiple-case study of 16 students out of 4 different junior high classes that aimed to investigate students’ emotional processes when solving a mathematical problem in their classrooms. After identifying the different emotions and analyzing their relations to motivational and cognitive processes, the relation with students’ mathematics-related beliefs will be examined. We will specifically use Frank’s case to illustrate how the use of a thoughtful combination of a variety of different research instruments enabled us to gather insightful data on the role of emotions in mathematical problem solving.     

数学解题的有意义学习

解决数学问题的学习是寻求解决数学问题方法的一种心理活动，是一种高级形式的学习活动，数学解题学习是有意义发现学习的数学解题认识观，数学的解题认知结构由解题知识结构，思维结构和解题元认知结构组成，“理解题意和解题回顾”是数学解题有意义学习的最重要环节。     

Predictors of well‐structured and ill‐structured problem solving in an astronomy simulation

This study compared the problem‐solving skills required for solving well‐structured problems and ill‐structured problems in the context of an open‐ended, multimedia problem‐solving environment in astronomy. Two sets of open‐ended questions assessed students' abilities for solving well‐structured and ill‐structured problems. Generalized, rubric scoring systems were developed for assessing problem‐solving skills. Instruments were also developed and administered to assess cognitive and affective predictors of problem‐solving performance. By regressing the scores on the cognitive and affective predictors onto students' scores on the well‐structured and ill‐structured problems, we concluded that solving well‐structured and ill‐structured problems require different component skills. Domain knowledge and justification skills were significant predictors of well‐structured problem‐solving scores, whereas ill‐structured problem‐solving scores were significantly predicted by domain knowledge, justification skills, science attitudes, and regulation of cognition. Implications for problem solving in science education are presented. © 2003 Wiley Periodicals, Inc. J Res Sci Teach 40: 6–33, 2003     

Solving complex problems: A convergent approach to cognitive load measurement

The study challenged the current practices in cognitive load measurement involving complex problem solving by manipulating the presence of pictures in multiple rule‐based problem‐solving situations and examining the cognitive load resulting from both off‐line and online measures associated with complex problem solving. Forty‐eight participants were recruited from a subject pool in the Educational Psychology department in a large research university in western USA. Results showed that the presence of pictures had no effect on learners' complex problem solving as measured by the response time and accuracy. However, the online measure (eg, pupillometric measures) revealed a change in cognitive load associated with the presence of pictures in complex problem solving. The authors concluded that different measures of cognitive load may actually be measuring separate aspects of cognitive load. Discussions were made on how research on multimedia learning and cognitive load could be advanced by carefully considering multiple aspects of cognitive load and by including the use of convergent measurement techniques to capture the variations of cognitive load involved in learning.     

基于数学问题解决的模式识别研究述评

数学问题解决中的模式识别的研究视角,可以分为基于数学解题认知过程与解题策略角度、基于"归类"的视角、基于数学问题解决中模式识别与其他因素的关系的视角等,具体研究领域涉及几何解题中的视觉模式识别、几何问题解决中的模式识别、解代数应用题的认知模式、数学建模中的模式识别等.由于在知觉领域与问题解决领域"模式识别"的表述存在一定的混乱性,将基于数学问题解决的模式识别界定为:当主体接触到数学问题后,与自己认知结构中的某数学问题图式相匹配的思维与认知过程.并进一步通过其与"归类"的区别与联系、与"化归"的区别与联系使"基于数学问题解决的模式识别"的概念得以澄清.在范围上,把问题解决中的模式识别界定为一种思维过程的阶段或者思维策略,认为它是解题的重要组成部分,但并不是解题的全部.对于未来的展望,期望系统的理论研究、期望对学生问题解决中模式识别的认知过程与机理的实质性的研究以及对学生问题解决中模式识别的教学实验研究.     

2 Perspectives in pedagogy

The paper discusses the dominant place of expository verbal teaching in most teaching institutions, and argues that it is deleterious to pupil learning. It goes on to propose that greater attention to pedagogy is essential to break out of current transmission modes of teaching. In particular, it is crucial to develop teaching for conceptual learning and for problem solving, and it is suggested that there is information from learning psychology that can be fruitfully related to practical teaching to achieve these developments. However, it is not suggested that teachers merely applylearning theory, but that they explore its relevance and mode of application to real teaching situations. In teacher education there is a serious problem of lack of pedagogical understanding in supervisory staff of student teachers. This is a vital deficiency that will need to be repaired before advances in teacher preparation can be realistically expected.