中学生问题解决中操作要求对资源分配的影响

Schema acquisition is one of the mechanisms of learning. How to design reasonable teaching material to promote schema acquisition is an important question that psychological researchers and educators both interested. Cognitive Load Theory indicates that: The cognitive resource of Human is limited, the organization and presentation of the learning material should avoid demanding the learner consume resource in actions that have nothing to do with schema acquisition. How can we do that? Sweller. J. et think: Increasing the operation cost of the learning material would make the students put more resource into the implementation of the operation, this kind of resource consuming has nothing to do with schema acquisition. So, in order to make the students put more resource into actions which relating to schema acquisition, we should decrease the operation cost of the learning material. But, the research results of O'Hara et indicate: In problem-solving of knowledge lean field, increasing the operation cost would make the college students invent more resource to plan and understanding actions. So, Increasing the operation cost would facilitate the schema acquisition. How operation cost will effect the Middle-School Students' (MSS) schema acquisition and resource distribution when they solve problems of knowledge lean/rich field? This is the main question this research want to make inquiry. IN this research, we use three experiments indicate: Increasing the operation cost of actions, the implementing action would be less and the planning action would be more. So, increasing the operation cost can promote the schema acquisition. We use "cost-benefit analysis" strategy to explain this result. This strategy means that: Human is rational, before doing one action, he will weigh the cost and the coming benefit of this action, if the coming benefit is higher than the cost, he will implement this action; if the cost is higher than the coming benefit, this action will be contained. On the one hand, this research further affirms the core opinion of the Cognitive Load Theory: Human's cognitive resource is limited, we should put the limited resource into actions which is related to the schema acquisition; On the other hand, for the learning material designing principle which is advanced by the Cognitive Load Theory, we raise our questions. Besides, the question we raised holds some identical views with the constructive learning opinion: Learning is not passive information absorption, but positively constructing the meaning of the information, besides, this kind of construction can't done by others. The result of this research can provide some theory guidance and experimental basis for the designing of the MSS's science teaching material from a complete new angle.

中小学生欺负行为及其主要影响因素研究

The present paper studied the school bullying and the primary impact factors, for understanding the nature of bullying, and providing measures and references to the elimination and controlling of school bullying. Primarily with methods of questionnaires and psychometrics, combined with case study and interviews, the following findings were found: in Chinese culture, bullying is a behavior intentionally causing harm to the weaker or weakers. There were 5 types of bullying-physical, social exclusion, threat, breakage and verbal. In Chinese schools the occurrence of bullying had regular patterns. The factor that impact children's bullying behavior was personality traits, interpersonal techniques, family atmosphere, education and upbringing styles. In personality traits, bullies tended to be more extroversive, impulsive, obstinate, obdurate and lack of sympathy. Victims tended to be more introversive, self-restrained, lack of confidence, lonely, anxious and depressive. Both of them expressed more mental problem tendencies than normal children did. When confronted with interpersonal conflicts, they used little problem solving strategies. Bullies had more extroverted emotional responses, and victims had more social support strategies. In the light of family influence, bullies were relatively superior in family's social economic conditions. But their parents had little time and energy spent on them. They tended to be punitive, and had indulgent, reject or despotic upbringing styles. The role of victim might be related to the disadvantage of family's social economic status. Their parents had the tendency of spoiling and overindulgence. The research concluded that in different cultures the connotation of bullying was not homogenous. The occurrence of school bullying had regular patterns. Bullying behavior was primarily influenced by the personality traits of both bullies and victims, the coping strategies of interpersonal conflicts, family's social economic status, parents' basic emotional attitudes, ways of educating, punitive tendencies and school atmosphere. The occurrence of bullying behavior was the result of the combined process of past experience, behavior habits, personality traits, cognitive evaluation, certain evocative clues and the environment conditions. It reminded that quality education and mental health education in schools was essential. Strengthening basic social skill training in school, creating positive family atmosphere, having more communications between schools and families and implementing strict regulations against bullying was essential to interfere and eliminate the school bullying.

不同学习策略对改变学生物理要领错误的影响

In the field of misconceptions research, previous research was focused mainly on the effect of naive concepts on the learning of scientific concept. In this study, from the viewpoint of declarative and procedural knowledge, conceptual errors on Newtonian mechanics were studied comparatively between high-performance and low-performance students. Furthermore, the effects of self-explain learning strategies and reflective learning on the change of subjects' conceptual errors were explored. The result of experiments indicated: 1. There was significant difference in the number of conceptual errors of declarative and procedural knowledge between high-performance students and low-performance students. And Low-performance students made more conceptual errors of procedural knowledge than that of declarative knowledge. For high-performance students, there was no distinct difference between these two kinds of errors. 2. In the distribution of conceptual errors, most errors of declarative knowledge were mainly focused on the understanding of concepts of friction and acceleration. The errors of procedure knowledge most errors concentrated on the judgment of vector direction and the conceptual understanding. 3. Compared with high-performance students, the representation of conceptual declarative knowledge of low-performance students is less complex, more concrete and context bound. 4. The comparative analysis of problem-solving strategies showed: high-performance students preferred to apply analytic strategy, solving problems based on physical concepts and principles; low-performance students preferred to use context strategy, solving problem according to the literal meaning of problems, subjective and groundless presumption and wrong concepts and principles. 5. Self-explain strategies can help students correct their conceptual errors effectively. Reflective learning could help students to correct the concept errors in some degree, but the distinct effect was not observed.

对癌症生存者应对资源的研究

A survey study of cancer survivors was conducted to explore the coping resources, which buffers the life of cancer survivors against stressful situation. Participants reported coping strategies, positive affect and negative affect, personality, perceived social support, fighting spirit and helpless/hopeless as well as quality of life through a set of self-assessment questionnaire. The results indicated that the frequency of coping strategies used by cancer survivors from high to low were: growing, problem solving, seeking support,self-controlling, wishful thinking, and distancing. The correlational analysis indicated that among the six sets of coping strategies, growing was positively correlated most strongly with most of the dimensions in quality of life as well as positive affect. Among the five personality, Neuroticism was positively correlated most strongly with helpless/hopeless and negative affect; and was negatively correlated most strongly with fighting spirit and positive affect. Extraversion was positively correlated most strongly with positive affect and negatively correlated most strongly with helpless/hopeless; Agreeableness was negatively correlated most strongly with negative affect; Conscientiousness was positively correlated most strongly with fighting spirit. Subjects with higher score in quality of life reported higher frequency of coping strategies in growing and problem solving and less in wishful thinking. They also reported higher scores in Extraversion, Agreeableness, Conscientiousness as well as lower scores in Neuroticism. The regression analysis displayed that not negative affect but positive affect entered the regression model when all the psychological and social variables in the study were accounted for. Taken together, these data suggested that, growing was the most effective coping strategy among the six sets of strategies for cancer survivors to improve quality of life, to maintain positive affect and to enhance fighting spirit. Neuroticism was vulnerable to resist stressors; Extraversion, Agreeableness, and Conscientiousness were stress-resisted factors. Positive affect may has more adaptational significance than negative affect during chronic stress. These data also implicated that positive affect should be paid more attention to in coping research.

弈棋问题解决启发式的元策略模型

Problem solving is one of the basic processes of human cognition and heuristic strategy is the key to human problem solving, hence, the studies on heuristic strategy is of great importance in cognitive psychology. Current studies on heuristics in problem solving may be summarized as follows: nature and structure of heuristics, problem structure and representation, expert knowledge and expert intuition, nature and role of image, social cognition and social learning. The present study deals with the nature and structure of heuristics. The Solitaire problem was used in our the experiments. Both traditional experimental method and computer simulation were used to study the nature and structure of heuristics. Through a series of experiments, the knowledge of Solitaire problem solving was summed up, its metastrategy is worked out, and then the the metastrategy by computer simulation and experimental verification are tested.

大学生应激应付研究

In this study, we made research on coping with stress in undergraduate students. The whole work included two parts: (a) We developed the Coping Strategies Questionnaire and had it tested. Five kinds of coping strategies were found by factor analysis: Problem Solving, Passive Acceptance, Support Seeking, Emotion Regulation, and Unadaptation. The reliability and validity coefficients of the questionnaire was high. (b) We examined the relations among personality characteristics (Locus of control, Extraversion, Neuroticism), emotion state, cognitive appraisal (psychological pressure, controllability, resource of social support), and the specific coping processes in several specific stressful events. The results indicated that coping have some degree of consistency across different situations which suggested that there is a general coping tendency, and that this general coping tendency, in addition to the above considered variables, have different degree of effects on subjects' choice of specific coping strategies. Finally, theoretical model of the relationship was tested through path analysis.

问题解决及学习中的条件认知水平

Learning to recognize the conditions under which actions should be considered is a crucial component in the acquisition of cognitive skill. This research focus on the way in which conditions are recognized during problem solving, so as to design effective material for learning through problem solving. The results of experiment I indicated that the subjects abstracted contents from different resources as condition at structural level through out the whole process of problem solving. The results of experiment 2 indicated that the efficiency of learning through problem solving could be greatly improved by emphasizing the recognization of conditions at structural level. The implications for both theory and application are discussed.

Meta-Rules: Reasoning About Control

How can we insure that knowledge embedded in a program is applied effectively? Traditionally the answer to this question has been sought in different problem solving paradigms and in different approaches to encoding and indexing knowledge. Each of these is useful with a certain variety of problem, but they all share a common problem: they become ineffective in the face of a sufficiently large knowledge base. How then can we make it possible for a system to continue to function in the face of a very large number of plausibly useful chunks of knowledge? In response to this question we propose a framework for viewing issues of knowledge indexing and retrieval, a framework that includes what appears to be a useful perspective on the concept of a strategy. We view strategies as a means of controlling invocation in situations where traditional selection mechanisms become ineffective. We examine ways to effect such control, and describe meta-rules, a means of specifying strategies which offers a number of advantages. We consider at some length how and when it is useful to reason about control, and explore the advantages meta-rules offer for doing this.

Combining Associational and Causal Reasoning to Solve Interpretation and Planning Problems

This report describes a paradigm for combining associational and causal reasoning to achieve efficient and robust problem-solving behavior. The Generate, Test and Debug (GTD) paradigm generates initial hypotheses using associational (heuristic) rules. The tester verifies hypotheses, supplying the debugger with causal explanations for bugs found if the test fails. The debugger uses domain-independent causal reasoning techniques to repair hypotheses, analyzing domain models and the causal explanations produced by the tester to determine how to replace faulty assumptions made by the generator. We analyze the strengths and weaknesses of associational and causal reasoning techniques, and present a theory of debugging plans and interpretations. The GTD paradigm has been implemented and tested in the domains of geologic interpretation, the blocks world, and Tower of Hanoi problems.

Computation and Pre-Parametric Design

My work is broadly concerned with the question "How can designs bessynthesized computationally?" The project deals primarily with mechanical devices and focuses on pre-parametric design: design at the level of detail of a blackboard sketch rather than at the level of detail of an engineering drawing. I explore the project ideas in the domain of single-input single-output dynamic systems, like pressure gauges, accelerometers, and pneumatic cylinders. The problem solution consists of two steps: 1) generate a schematic description of the device in terms of idealized functional elements, and then 2) from the schematic description generate a physical description.

ARLO: Another Representation Language Offer

This paper describes ARLO, a representation language loosely modelled after Greiner and Lenant's RLL-1. ARLO is a structure-based representation language for describing structure-based representation languages, including itself. A given representation language is specified in ARLO by a collection of structures describing how its descriptions are interpreted, defaulted, and verified. This high level description is compiles into lisp code and ARLO structures whose interpretation fulfills the specified semantics of the representation. In addition, ARLO itself- as a representation language for expressing and compiling partial and complete language specifications- is described and interpreted in the same manner as the language it describes and implements. This self-description can be extended of modified to expand or alter the expressive power of ARLO's initial configuration. Languages which describe themselves like ARLO- provide powerful mediums for systems which perform automatic self-modification, optimization, debugging, or documentation. AI systems implemented in such a self-descriptive language can reflect on their own capabilities and limitations, applying general learning and problem solving strategies to enlarge or alleviate them.

Coherent Behavior from Incoherent Knowledge Sources in the Automatic Synthesis of Numerical Computer Programs

A fundamental problem in artificial intelligence is obtaining coherent behavior in rule-based problem solving systems. A good quantitative measure of coherence is time behavior; a system that never, in retrospect, applied a rule needlessly is certainly coherent; a system suffering from combinatorial blowup is certainly behaving incoherently. This report describes a rule-based problem solving system for automatically writing and improving numerical computer programs from specifications. The specifications are in terms of "constraints" among inputs and outputs. The system has solved program synthesis problems involving systems of equations, determining that methods of successive approximation converge, transforming recursion to iteration, and manipulating power series (using differing organizations, control structures, and argument-passing techniques).

Qualitative Process Theory

Objects move, collide, flow, bend, heat up, cool down, stretch, compress and boil. These and other things that cause changes in objects over time are intuitively characterized as processes. To understand common sense physical reasoning and make programs that interact with the physical world as well as people do we must understand qualitative reasoning about processes, when they will occur, their effects, and when they will stop. Qualitative Process theory defines a simple notion of physical process that appears useful as a language in which to write dynamical theories. Reasoning about processes also motivates a new qualitative representation for quantity in terms of inequalities, called quantity space. This report describes the basic concepts of Qualitative Process theory, several different kinds of reasoning that can be performed with them, and discusses its impact on other issues in common sense reasoning about the physical world, such as causal reasoning and measurement interpretation. Several extended examples illustrate the utility of the theory, including figuring out that a boiler can blow up, that an oscillator with friction will eventually stop, and how to say that you can pull with a string but not push with it. This report also describes GIZMO, an implemented computer program which uses Qualitative Process theory to make predictions and interpret simple measurements. The represnetations and algorithms used in GIZMO are described in detail, and illustrated using several examples.

A Computational Model of Skill Acquisition

This thesis confronts the nature of the process of learning an intellectual skill, the ability to solve problems efficiently in a particular domain of discourse. The investigation is synthetic; a computational performance model, HACKER, is displayed. Hacker is a computer problem-solving system whose performance improves with practice. HACKER maintains performance knowledge as a library of procedures indexed by descriptions of the problem types for which the procedures are appropriate. When applied to a problem, HACKER tries to use a procedure from this "Answer Library". If no procedure is found to be applicable, HACKER writes one using more general knowledge of the problem domain and of programming techniques. This new program may be generalized and added to the Answer Library.

Description and Theoretical Analysis (Using Schemata) of Planner: A Language for Proving Theorems and Manipulating Models in a Robot

Planner is a formalism for proving theorems and manipulating models in a robot. The formalism is built out of a number of problem-solving primitives together with a hierarchical multiprocess backtrack control structure. Statements can be asserted and perhaps later withdrawn as the state of the world changes. Under BACKTRACK control structure, the hierarchy of activations of functions previously executed is maintained so that it is possible to revert to any previous state. Thus programs can easily manipulate elaborate hypothetical tentative states. In addition PLANNER uses multiprocessing so that there can be multiple loci of changes in state. Goals can be established and dismissed when they are satisfied. The deductive system of PLANNER is subordinate to the hierarchical control structure in order to maintain the desired degree of control. The use of a general-purpose matching language as the basis of the deductive system increases the flexibility of the system. Instead of explicitly naming procedures in calls, procedures can be invoked implicitly by patterns of what the procedure is supposed to accomplish. The language is being applied to solve problems faced by a robot, to write special purpose routines from goal oriented language, to express and prove properties of procedures, to abstract procedures from protocols of their actions, and as a semantic base for English.