The Theories Of Neo Classical Economics - 1608 Words

4.1 Positive outcomes Based on the theories of neo-classical economics, Greener (2008) proposed two main types of benefits of the promotion of markets in welfare service delivery: 1) empowering purchasing power of service users; 2) improve competition and efficiency of providers. These benefits of marketization represent in the field of care for older people. First, the market provision empowers service users to ‘exercise consumer sovereignty’ (Greener, 2008) through greater opportunities of choices (Daly and Lewis, 2000; Drakeford, 2007). In respect of this, the market could improve quality of services and push the older care move from producer-driven to consumer-driven provision. Second, market mechanism emphasizes the improvement of quality and reduction of costs through competition among providers, which inherently promotes efficiency (Brennan et al., 2012). Yet, there is no agreement of all these benefits has been taken place in practice or not. For example, Lewis and West (2014) argue t hat changes in ‘greater choice’, ‘flexibility’, and ‘responsiveness’ is very little, but the cost has been saved indeed. The benefits of ideal market have certain conditions: enough information to both buyers and sellers; duly influence on price per unit; and no sunk costs for entering and exiting the market (Greener, 2008). In the field of social care, it’s difficult to reach these conditions (Land and Himmelweit, 2010). As Brennan and his colleagues (2012) argued, an ideal care marketShow MoreRelatedThe United States Of Inequality Essay1153 Words   |  5 Pagesrealities we face in our country today, with regards to income inequality. Income inequality in the United States is at a rise. And the sobering factor is that so little is being done to address this issue. According to a new study by researchers at the Economic Policy Institute, forces of rising inequality are operating at an all-time high throughout the United States. 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With this introduction to the Jewish worldview of economics we as readers are able to transitionRead MoreAccounting Essay1593 Words   |  7 Pagesresponsibility and should be blame. Audit in agency theory Agency theory and audit’s role â€Å"Agency theory is part of the positivist group of theories which derives from the financial economics literature† (Michael, 1994). It requires the companies or organizations establish a contract between the real owners of economic entity and managers, the principals and agent, and let managers represent them to control and use their economic resource (Michael, 1994). Currently, more and more companies

Developmental Skills Childhood And Social Emotional...

Developmental Skills Domain in Early Childhood Social-Emotional Behavior. Social-emotional development includes the child’s experience, expression, and management of emotions and the ability to establish positive and rewarding relationships with others (Cohen and others 2005). It encompasses both intra- and interpersonal processes. The core features of emotional development include the ability to identify and understand one’s own feelings, to accurately read and comprehend emotional states in others, to manage strong emotions and their expression in a constructive manner, to regulate one’s own behavior, to develop empathy for others, and to establish and maintain relationships. (National Scientific Council on the Developing Child 2004, 2) In addition to identifying and labeling basic emotions, preschool age children are beginning to understand mental states and differentiate between their own and others’ preferences (Bronson, 2000). Dramatic role- play activities contribute to the development and understanding of others’ perspectives; children are able to act out various scenarios and learn through trial and error what peers may want and expect. Preschool age children can identify ways to comfort people and alleviate their distress, and their desire to work toward positive interactions increases sharing and helping behaviors (Bronson, 2000). 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Metacognitive Skills Free Essays

Metacognition refers to learners’ automatic awareness of their own knowledge and their ability to understand, control, and manipulate their own cognitive processes. 2 Metacognitive skills are important not only in school, but throughout life. For example, Mumford (1986) says that it is essential that an effective manager be a person who has learned to learn. We will write a custom essay sample on Metacognitive Skills or any similar topic only for you Order Now He describes this person as one who knows the stages in the process of learning and understands his or her own preferred approaches to it – a person who can identify and overcome blocks to learning and can bring learning from off-the-job learning to on-the-job situations. As you read this section, do not worry about distinguishing between metacognitive skills and some of the other terms in this chapter. Metacognition overlaps heavily with some of these other terms. The terminology simply supplies an additional useful way to look at thought processes. Metacognition is a relatively new field, and theorists have not yet settled on conventional terminology. However, most metacognitive research falls within the following categories: 1. Metamemory. This refers to the learners’ awareness of and knowledge about their own memory systems and strategies for using their memories effectively. Metamemory includes (a) awareness of different memory strategies, (b) knowledge of which strategy to use for a particular memory task, and (c) knowledge of how to use a given memory strategy most effectively. 2. Metacomprehension. This term refers to the learners’ ability to monitor the degree to which they understand information being communicated to them, to recognize failures to comprehend, and to employ repair strategies when failures are identified. Learners with poor metacomprehension skills often finish reading passages without even knowing that they have not understood them. On the other hand, learners who are more adept at metacomprehension will check for confusion or inconsistency, and undertake a corrective strategy, such as rereading, relating different parts of the passage to one another, looking for topic sentences or summary paragraphs, or relating the current information to prior knowledge. (See Harris et al. , 1988; – add more) 3. Self-Regulation. This term refers to the learners’ ability to make adjustments in their own learning processes in response to their perception of feedback regarding their current status of learning. The concept of self-regulation overlaps heavily with the preceding two terms; its focus is on the ability of the learners themselves to monitor their own learning (without external stimuli or persuasion) and to maintain the attitudes necessary to invoke and employ these strategies on their own. To learn most effectively, students should not only understand what strategies are available and the purposes these strategies will serve, but also become capable of adequately selecting, employing, monitoring, and evaluating their use of these strategies. (See Hallahan et al. , 1979; Graham Harris, 1992; Reid Harris, 1989, 1993. In addition to its obvious cognitive components, metacognition often has important affective or personality components. For example, an important part of comprehension is approaching a reading task with the attitude that the topic is important and worth comprehending. Being aware of the importance of a positive attitude and deliberately fostering such an attitude is an example of a metacognitive skill. In the preceding paragraph, metacognition has been described as a conscious awareness of one’s own knowledge and the conscious ability to understand, control, and manipulate one’s own cognitive processes. This is not quite accurate; but it’s difficult to define metacognition more accurately. (It’s easier to point out examples of metacognitive activity than to define what it is. ) It would be more accurate to say that metacognitive strategies are almost always potentially conscious and potentially controllable (Pressley, Borkowski, Schneider, 1987). For example, good readers automatically (unconsciously) employ metacognitive strategies to focus their attention, to derive meaning, and to make adjustments when something goes wrong. They do not think about or label these skills while performing them; but if we ask them what they were doing that was successful, they can usually describe their metacognitive processes accurately. In addition, when serious problems arise – as when there is a distraction, when they encounter extremely difficult or contradictory text, or when they have to advise someone else regarding the same skill – they slow down and become consciously aware of their metacognitive activity. While it is occasionally useful to consciously reflect on one’s metacognitive processes and while it useful to make learners aware of these processes while they are trying to acquire them, these skills become most effective when they become overlearned and automatic. If these skills were not automatic and unconscious, they would occupy some of the effort of the working memory; and this would have the result of making reading, listening, and other cognitive activities less efficient. Therefore, like any other skill that becomes automatic and requires minimal activity in the working memory, metacognitive skills work best when they are overlearned and can operate unconsciously. Learners with good metacognitive skills are able to monitor and direct their own learning processes. Like many other processes, metacognitive skills are learned by applying principles from almost every other chapter in this book. When learning a metacognitive skill, learners typically go through the following steps (Pressley, Borkowski, Schneider, 1987): 1. They establish a motivation to learn a metacognitive process. This occurs when either they themselves or someone else points gives them reason to believe that there would be some benefit to knowing how to apply the process. (Motivation is discussed in chapter 5). 2. They focus their attention on what it is that they or someone else does that is metacognitively useful. This proper focusing of attention puts the necessary information into working memory (Chapter 6). Sometimes this focusing of attention can occur through modeling (Chapter 12), and sometimes it occurs during personal experience. 3. They talk to themselves about the metacognitive process. This talk can arise during their interactions with others, but it is their talk to themselves that is essential. This self talk serves several purposes: oIt enables them to understand and encode the process (Chapter 6). oIt enables them to practice the process (Chapter 3). oIt enables them to obtain feedback and to make adjustments regarding their effective use of the process (Chapters 3 and 12). oIt enables them to transfer the process to new situations beyond those in which it has already been used (Chapters 3 and 6). 4. Eventually, they begin to use the process without even being aware that they are doing so. This process usually represents a high-level implementation of the phases of learning and instruction described by Gagne and discussed in Chapter 3 of this book. When teachers intervene to help students develop a metacognitive process, they often use the scaffolded instruction strategies described in chapter 12. In addition, the techniques of cooperative learning and peer tutoring (discussed in Chapter 15) often provide opportunities for students to talk to others about their thought processes; and it is often the process of formulating thoughts in order to express them to others that leads to metacognitive development (Piaget, 1964). Finally, it is interesting to note an important relationship between the higher order skills of metacognition and the basic or factual skills that may be a part of a specific unit of instruction. Students typically learn metacognitive skills while they are involved in learning something else. If they are to do this successfully, it is extremely important that the learners have overlearned the prerequisite content knowledge for the subject matter topic being studied. If that prerequisite knowledge has not been mastered to a sufficient level of automaticity, then the working memory of the learner will be overwhelmed by the subject matter; and the result will be no time for metacognitive reflection. For example, when children who have largely mastered the prerequisite skills try to solve a word problem in arithmetic, they can afford to talk to themselves about what they are doing, because their working memory is not totally occupied with other demands. That is, well prepared children will have time for metacognitive practice. On the other hand, when children who are missing some of these prerequisite skills try to solve the same problem, their working memory is likely to be totally occupied with a frantic need to find the basic skills and facts needed to solve the problem. If this is the case, they not only have solved the problem less effectively; but they also have little or no time for practicing or developing metacognitive skills. When teachers and parents try to help students, it is important not to do too much thinking for them. By doing their thinking for the children they wish to help, adults or knowledgeable peers may make them experts at seeking help, rather than expert thinkers. On the other hand, by setting tasks at an appropriate level and prompting children to think about what they are doing as they successfully complete these tasks, adults can help children become independent and successful thinkers (Biemiller Meichenbaum, 1992). In other words, it is often better to say, What should you do next? † and then to prompt the children as necessary, instead of simply telling them what to do. The preceding paragraph describes how the intellectual rich get richer and the poor get poorer. Knowledge of factual information and basic skills provides a foundation for developing metacognitive skills; and metacognitive skills enable students to master information and solve problems more easily. If teachers hope to help low-performing students break out of their intellectual imprisonment, they must find a way to help them develop both an automatic grasp of basic skills and effective metacognitive skills to enable self-directed learning. Misconceptions with regard to specific subject matter were discussed in Chapters 4 and 6. Wittrock (1991) notes that learners’ misconceptions about learning-to-learn skills and about metacognitive strategies are also a critical source of learning problems. For example, a student who adheres to a belief that the best way to learn scientific concepts is to repeat the definitions ten times each night before going to bed is not as likely to come to an understanding of these concepts as a person who has a more effective conception of how to master these concepts. Finally, note that a major purpose of this book is to help you develop your metacognitive skills. In chapter 1 I suggested that you apply various strategies while reading this book. If you have done so, there is a good chance that by now you understand the rationale of many of these principles and can see how they contribute to your own learning. By becoming consciously aware of these strategies and how they work, you will not only be able to use these principles to teach others more effectively, you’ll also be able to use them to monitor and improve your own thought processes. That’s metacognition! How to cite Metacognitive Skills, Papers

Principles of Business Analytics

Question: What is the meaning of decision making. Answer: Introduction The decision making is one of the most basic cognitive procedures of human behaviors. The decision making process is a vital process in personal life as well as vital for professional purpose (Tamir et al. 2015). The decision making component is an important principle of the business analytics. There are widely used decision theories that are widely implemented in the business scenario. In a business scenario, there is a need to perform routine decision making tasks. There is a need to adopt cognitive decision making policies to achieve business success. This report describes the role of human cognition in the decision making process. The second part of the report describes the role of analytics in decision making process. It also discusses the influence of data in the process of decision making. Task 1 Meaning of decision making The process of the selection of a preferred course of action among a set of alternatives or options is known as decision making. The layered model of brain comprises of the fundamental cognitive procedures of decision making (Glscher et al. 2012). There are specific characteristics of the decision making processes such as decision maker, decision situation, and the decision process. The core cognitive features of the human brain are known to share similar characteristics. The three important features of the decision making process include a set of alternatives or choices, decision goals and a list of selection strategies (Glscher et al. 2012). If there is a fulfillment of these three criteria, then the decision making process can be easily carried out by a human being. The consequences of the decision making processes can be estimated from the strategies of decision making used by the decision maker (Elwyn et al. 2012). The different strategies of decision making require a combination of decision selection criteria. It is also important to perform rational decision making for the success of business entities. There is a need to adopt different decision strategies as per the values of the decision makers, attitudes towards risk and the prediction of future outcomes. Human cognition in decision making The intellectual capabilities of the human beings have made it possible for themselves to gain a superior status among all animal species (Seligman and Csikszentmihalyi 2014). The presence of intellectual capabilities has allowed the human beings to adapt to a specific environment, and there have been evolving patterns of decision making capabilities. There has been a transformation in the intellectual capabilities of human beings. The intellectual capabilities of human beings have transformed into sophisticated and more specialized skills (Seligman and Csikszentmihalyi 2014). The specialized skills include planning, observation, problem solving and coordination. The decision making process works in close collaboration with the problem solving process (Seligman and Csikszentmihalyi 2014). The decision making process consists of the analysis, synthesis and the evaluation of the job tasks. The analysis of the job tasks is the first step of the decision making process. Process of decision making The cognitive process of the decision making begins with the detailed analysis of the decision making problem (Croskerry 2013). The objective of the decision making process should be identified, and an initial framework needs to be created. The alternatives should be assessed for the purpose of the formulation of strategies. The alternatives are thoroughly evaluated and the human intellectual capabilities give an idea regarding the best alternative (Croskerry 2013). The best alternatives out of the given choices are selected. The selected best alternative should be evaluated well and checked if it meets the predetermined goals or standards (Croskerry 2013). The decision maker would make sure that the decision meets the current scenario and the personal judgment. If there is a mismatch between the expected outcome and the current outcome, then the decision making process needs to be repeated (Croskerry 2013). The decision making process should be done until a satisfied decision arrive s. Task 2 The phenomenon of human decision making is influenced by rational behavior and does not always follow a fixed course (Seligman and Csikszentmihalyi 2014). There are individual differences in the cognitive process, which aids in the decision making process. The role of analytics is immense in the decision making process. The business analytics consists of the study of various patterns of data through operations and statistical analysis and the application of these to customers and the business (Croskerry 2013). The business analytics deals with the technologies, skills and practices for the continuous investigation of the past performances of business so that insights to the business can be gained. The business insights help in the business planning, which in turn helps in the decision making process. Role of Business analytics in business The business analytics play an important role in the business scenario (Holsapple Lee-Post and Pakath 2014). The cognitive analytics is a powerful tool to bridge any gaps between the data structure and the reality of decision making, which is an everyday function of the managers. The data and information is a vital part of the decision making process. The cognitive analytics is an additional part of cognitive computing (Holsapple Lee-Post and Pakath 2014). The cognitive computing comprises of machine learning, language processing, and the related infrastructure. There is a need to massive data processing and the ability to analyze various sources of data. The analysis of data can be essential for gaining business insights and various crucial parameters about the organization. The cognitive analysis depends on the information technology tools to generate the required hypothesis (Holsapple Lee-Post and Pakath 2014). The hypothesis is drawn after the consultation with connecting informa tion sources, which are relevant. Decision making process and the Probability theory The analytical decisions are driven by the organizational data (Power Sharda and Burstein 2015). The use of direct observations, figures, charts, facts are the basis for successful decision making. The decisions cannot be taken on whims and fancies. It should be directly related to the statistical figures and the current situation of the business. The decision makers use surveys, questionnaires and other means for the purpose of data collection (Power Sharda and Burstein 2015). The collected data is tabulated and put into appropriate software, which is suitable for the specific types of data. The tabulated data is then analyzed thoroughly. The decision maker should consider all the pre-determined parameters, before beginning the process of data analysis. The probability theory is an important component in the decision making process (Berger 2013). The managers need to take decisions, which are related to uncertainty. The decisions need to be made on appropriate assumptions. This theo ry helps the manager to deal with investment issues, introduction of a new product, stock decisions, individual investor and others. Techniques of analytics The descriptive and inferential techniques of analytics are important for business (Devore 2015). The descriptive techniques involve the description and summarizing the collected data in a meaningful manner. This technique helps the decision maker to understand the explicit details of the data in a clear manner. The purpose of the descriptive techniques is to present the decision maker with a visual picture of the implications of the data. In the absence of the descriptive techniques, the decision maker would face difficulty in the analysis of the raw, unstructured data. The inferential techniques make use of a limited segment of the data and not the entire data (Kern 2014). The purpose of the inferential techniques allows the decision maker to make generalizations regarding the sample population. The sample should represent the population accurately. The inferential techniques deal with the estimation of parameters and the testing of relevant hypothesis. Conclusion The decision making is a vital part of the human beings. It applies to both the personal as well as professional life. The decision making is not an independent function; rather it is interconnected to other variables like data, information, analytics and others. The efficient decision making would ensure individual success as well as organizational success. References Berger, J.O., 2013.Statistical decision theory and Bayesian analysis. Springer Science Business Media. Croskerry, P., 2013. From mindless to mindful practicecognitive bias and clinical decision making.N Engl J Med,368(26), pp.2445-2448. Devore, J., 2015.Probability and Statistics for Engineering and the Sciences. Cengage Learning. Elwyn, G., Frosch, D., Thomson, R., Joseph-Williams, N., Lloyd, A., Kinnersley, P., Cording, E., Tomson, D., Dodd, C., Rollnick, S. and Edwards, A., 2012. Shared decision making: a model for clinical practice.Journal of general internal medicine,27(10), pp.1361-1367. Glscher, J., Adolphs, R., Damasio, H., Bechara, A., Rudrauf, D., Calamia, M., Paul, L.K. and Tranel, D., 2012. Lesion mapping of cognitive control and value-based decision making in the prefrontal cortex.Proceedings of the National Academy of Sciences,109(36), pp.14681-14686. Holsapple, C., Lee-Post, A. and Pakath, R., 2014. A unified foundation for business analytics.Decision Support Systems,64, pp.130-141. Kern, S.E., 2014. Inferential statistics, power estimates, and study design formalities continue to suppress biomedical innovation.arXiv preprint arXiv:1411.0919. Power, D.J., Sharda, R. and Burstein, F., 2015.Decision support systems. John Wiley Sons, Ltd. Seligman, M.E. and Csikszentmihalyi, M., 2014.Positive psychology: An introduction(pp. 279-298). Springer Netherlands. Tamir, M., Bigman, Y.E., Rhodes, E., Salerno, J. and Schreier, J., 2015. An expectancy-value model of emotion regulation: Implications for motivation, emotional experience, and decision making.Emotion,15(1), p.90.