The relationship between employees job satisfaction and customer satisfaction in service business

Abstract This study is conducted within the bank of America and is aimed at showing the relationship between employee satisfaction and customer satisfaction in the banking industry.Advertising We will write a custom proposal sample on The relationship between employees’ job satisfaction and customer satisfaction in service business specifically for you for only $16.05 $11/page Learn More The study is necessitated by the realization that customer satisfaction is determined by the perceptions the customers have on the nature and the quality of services offered. Since the study focuses on the correlation between employee satisfaction and customer satisfaction at a specific point in time, a cross sectional study design is chosen. 104 participants will be targeted for this study, 53 of which will be employees of the bank of America. Data will be mostly collected through written interviews. However provision for oral interview will be available especial ly for corporate clients who may be too busy to fill in written interviews. Seven aspects of job satisfaction will be measured and correlated with five categories of customer satisfaction. The study concludes that customer satisfaction is directly influenced by employee satisfaction. A number of factors interplay in this relationship. These include job security, work load, motivation, and employee empowerment, among others. Introduction Management experts believe that business success is attained through offering quality service to customers. However, not many of these experts link quality service with the level of employees’ satisfaction. Suffice to state that the service industry is seen as one of the key sectors of growth in any economy. As such, proper management of the service industry is needed to ensure that the value of service offered does not compromise customer expectations. This is because, negative customer perceptions about the nature and the quality of service offered is detrimental to business growth. This suggests that customers’ perceptions about service quality are directly proportional to the business success achievable.Advertising Looking for proposal on business economics? Let's see if we can help you! Get your first paper with 15% OFF Learn More There a number of characteristics unique to the service industry. Employees in the service industry put in more hours while serving numerous customers, most of whom have complicated needs. This usually makes the job of customer service providers very cumbersome. As a result, Yagil (2006) explains that service providers are most likely to be fatigued and burned out. Such burn out has a direct influence on the quality of service offered. In a survey conducted by Burke, Graham and Smith (2005), it is found out that customer service is a psychological intercreative human experience. This implies that service provision is relational, face to face, and has got nothing to do with the products that the service provider offers. A good intercreative environment thus improves the perception of the customer on the quality of service offered. As such, two major conclusions can be made from the assertion above: perception plays a vital role in determining the nature of service quality; customer service provision is a psycho social activity. Burke et al. (2005) conclude that service provision has to be offered appropriately; otherwise the customer is dissatisfied. This leads to loss of business. This assertion is confirmed in a study conducted within the Indian mobile phone industry by Sathish, Santhosh, Naveen and Jeevanantham (2011). In this study, it is evident that one of the major reasons why consumers of Indian mobile phone services switch providers is poor quality of service offered. Therefore, customer satisfaction is directly connected to nature of service offered. The level of employees’ satisfaction varies and can be attributed to a number of factors. These include poor salaries, employee attrition, work load issues as well as employee empowerment (Bull 2005; Yagil 2006). Yagil (2006) and Burke et al. (2005) add that the perception of the customer on the quality of service is directly connected to employees’ satisfaction. These factors, coupled with employee burn out determine the kind of behavior exhibited by employees within the customer service industry. As a result, service providers portray loss of enthusiasm and positive regard for their jobs, lack of concern for clients’ needs, both emotional and physical exhaustion among other behaviors (Yagil 2006).Advertising We will write a custom proposal sample on The relationship between employees’ job satisfaction and customer satisfaction in service business specifically for you for only $16.05 $11/page Learn More During the cause of service provision, if employees portray negative attitudes and behaviors towards the cus tomer, the customers’ level of satisfaction with service quality decreases. This assertion can be attributed to the fact that social behavior is determined by the perceptions about the underlying motives and the prevailing environment, within which service is offered (Yagil 2006). As such, the perception of the customer regarding the quality of service offered is influenced by the behavior and attitude portrayed by employees. The studies above suggest a complex relationship between customer satisfaction, employee behavior and the quality of service offered. Customer satisfaction determined by customers’ perception on the quality of service offered. Employees’ conduct is determined by how the customers perceive value of service offered. The perception of the customer is influenced by the level of job satisfaction. As mentioned above, previous studies reveal that employee satisfaction is directly related to customer’s perception on service quality. As such, it is imperative to conclude that there is relationship between employees’ job satisfaction and customer perception of service quality which affects the overall satisfaction in the service business. While previous studies focused on hotel, teaching and telephone industries, there does not exist any study that focuses on the relationship between employee satisfaction and customer satisfaction within the banking sector. As such this study seems relevant. The purpose of this study is to test hypothesis that the there is a relationship between employee satisfaction and customer satisfaction and perceived service quality. As such, the following questions seem relevant for this study: Do customers report higher satisfaction with service quality when employees indicate higher levels of work satisfactions? What aspects of job satisfaction that directly effect employees’ morale and behavior and how it effects customer satisfaction? To supply answers to this questions, the cr oss sectional study design has been chosen. Data for this study will be collected, separately, from employees and customers of Bank of America New York branch.Advertising Looking for proposal on business economics? Let's see if we can help you! Get your first paper with 15% OFF Learn More Since previous studies show that customer satisfaction is dependent on perceptions about employees’ job satisfaction, for the purpose of this study, employee satisfaction is the independent variable and customer’s satisfaction is the depended variable. The bank of America was chosen because of the high number of customers served by the bank as well as high number of employee within the bank. As such, the banks employees and customers will provide sufficient sources of data for this study. Methodology This study targets both the employees and customers at the bank of America’s New York branch. The branch is chosen due to its central location as well as due to the fact that its serves a large clientele base. The study targets both individual and corporate customers, who will be observed at a particular point in time. A total number of 104 customers will be targeted. The number 104 has been chosen not because it has any special meaning in relation to the study but since it is manageable, and will also allow the researcher to collect as much data as possible. The target population will be divided into 53 employees and 51 customers. Out of the 51 customers, 17 corporate will be targeted. All the employees targeted for this study will be from departments that deal directly with the customers. As such, employees from the customer relations desk, tellers, loan clerks, information officers among other will be provide valid data for this study. As explained above, the numbers chosen for this study have no special meaning in relation to the topic of the study. However, odd numbers are chosen for the sake of tallying. Since the researcher targets all types of clients and employees at a particular point ion time, a cross sectional study design seems relevant for this study. According to Rose and Barker (1997), a cross sectional study targets a subset of the entire population with the aim of providing data that can be used to formulate generalized assum ptions regarding the entire population. It is also imperative to mention that the study is based on observations made, whose results are related to the employee satisfaction (independent variable for this study) and customer satisfaction (dependent variable for this study). As Rose and Barker (1997) further explain, studies which evaluate the relationships between variables and seek to establish pattern are descriptive in nature. As such, this study is descriptive. Participants As explained previously, the study targets 104 participants. The participant will be selected from both the employees and customers of the bank of America. In total 53 employees and 51 customers (both corporate and individual) will be targeted. Since the researcher aims at targeting all types of clients, 17 out of the 53 customers will be corporate. Employees targeted will vary in terms of age, race, job description and gender. To ensure that equity is achieved, the study will identify employees for participa tion as follows. 25 women and 28 men will be identified from all departments especially those that deal with customers directly. The researcher will also identify at least 2 employees from each of the major races, namely Hispanics, Caucasians, blacks and Asians. It is imperative to get the perception of job satisfaction form employees in different age groups. As such, the age criterion for participant has been identified as follows. 25 years and below 26 to 35 years 36 to 45 years 46 to 55 years 55 years and above 51 customers are targeted for this study. Due to the complex nature of the customers, written and oral interviews have been identified as the suitable methods of data collection. Alternatively phone interviews will be used for corporate clients who may not be available during the time of the interview. Procedure Due to time, convenience and logistic constraints, it will be impossible contact each of the employees physically for a face to face interview. As such, written questionnaires are the preferred research tools for employees. As such each of the employees targeted will be requested to fill in a questionnaire separately. Emphasis will be made on providing responses to all questions. Data from employees will be correlated with data derived from the customers. Data which will be used to determine the level of job satisfaction will be derived from employees. To determine the level of job satisfaction, several aspects will be measured. These aspects are: job security, career future, financial rewards, work load, work appeal, leadership and direction. To address each of these issues, the questionnaire includes a table which employees will fill in their perceptions about each of the aspects The purpose of targeting customers is to measure the level customer satisfaction. As such customer satisfaction will be measured using a survey consisting of 22 questions based on the SERVQUAL scale that cover the 5 categories of service quality: reliability, res ponsiveness, assurance, empathy and tangibility. According to Yeck, Morales, Ladhari and Pons (2002) SERVQUAL is the only method which can accurately measure customer service by comparing the expectations of the customer about customer service and the real customer service experience. Therefore, based on Yeck et al.’s (2002) assertions, it is justifiable to use SERVQUAL to analyze findings on customer service in this study The procedure implies that there are two sets of data to be collected for this study. After collection of the two sets of data, an analysis will be done. The criterion for analysis is to compare the live of employee satisfaction and the correlating customer satisfaction. Hypothetical results It is expected that the study will reveal that customer service is determined by customers’ perception about the quality of service offered. It is expected that the study will correlate financial rewards (salaries and other financial benefits) with job satisfacti on aspects. Furthermore, the work load as well as work schedule are expected to portray a significant influence in the employee satisfaction and the overall effect on the customers’ perceptions. Furthermore, employee attrition, work load and labor issues will show a direct influence on employees’ satisfaction. Since, it is assumed that employees of the Bank of America will portray a level of dissatisfaction with their work; the study hopes to find a direct relationship between notable employees’ dissatisfaction with work and the perceptions of customer on the quality of service offered by the bank. The researcher expects to find that employee dissatisfaction directly affects the job morale, and as such the customer perceives low morale with employee dissatisfaction. In this case the researcher hopes that the customer will cite low morale as one of the indicators of job dissatisfaction. Furthermore, the researcher hopes to find data which proves that the customer equates low morale with poor customer service. Within the course of the study, the researcher expects to find a significant level of employees’ satisfaction. This is expected to show correlation with how customer perception on the quality of service rendered to them. As such, the study will find out that in those areas that employee exhibit a high degree of satisfaction, similar degree of employee satisfaction will be noticed. One of the key indicators of employees’ satisfaction with the job is proper remuneration as well as positive perceptions by the customer about the quality of service offered. In this study it is expected that properly paid employees exhibit a high degree of job satisfaction. The study is also expected to expose the fact that positive customer perceptions about the quality of service offered to have a direct relationship with the level of employee satisfaction. As explained earlier, the customers’ perception about the quality of service of fered is founded on the perceptions the customers have about the employee job satisfaction. In this study, it is expected that the researcher expects to identify the speed at which employees offer service, employees’ knowledge about products ad services as well as employees’ willingness to assist customers as having a significant influence on how customers perceive the quality of service. Furthermore, the ability of employees to identify particular needs of each customer, the ability of employees to make the customers feel appreciated as well as confidence portrayed by employees influence customers perception on the quality of service offered. Additionally, both verbal and non verbal communication skills including neatness, dress mode, smiling, use of polite and courteous language, direct eye contacts, among others, as having a directly influence on how customers perceive customer service. Overall, the researcher expects to find out the following correlation between em ployee job satisfaction and the perceptions about the quality of service offered by the bank. In those services which employees exhibited behavior that portrayed them as highly satisfied with their jobs, then customer will be satisfied with services offered in those areas. Conversely, on those areas that employees exhibited behavior that indicated to the customers that they were dissatisfied with their job, customers will equate this as poor customer service. If perception about job satisfaction outweighs perceptions about job dissatisfaction, this leads to increased customer satisfaction, and as such increased rate of customer retention. Discussion The hypothetical results above confirm the hypothesis that employees’ job satisfaction and customer perception of service quality affects the overall satisfaction in the service industry. From the hypothetical results above, it is evident that the quality of customer service is determined by the customer and not the service provid er. As such, this findings support Andreassen and Lindestad’s (1998) assertions that proper management of employees leads to increased employee satisfaction. In relation to this, the hypothetical findings will identify that there several aspects of human resource management, including proper remuneration, affect employee motivation and morale. Additionally, the results above affirm that, as explained by Ahmad, Ahmed, Nawaz and Ahmad (2011) that there are other factors which directly influence employee behavior. These include labor policy issues, work load among others, prolonged contact with customers, among others. These factors are expected to have an influence in the kind of behaviors exhibited by employees and the overall satisfaction with their job. As previously explained, Andreassen and Lindestad’s (1998) assert the need to improve human resource management practices by service industry players. In this regard, Ahmad et al. (2011) stipulates that giving full con trol to employees improves job satisfaction, since employees feel that they are in charge of their work. This corroborates Yagil’s (2006) assertion that empowerment means â€Å"the process of gaining influence over events and outcomes of importance to an individual or group†. In this case, empowering employees significantly enables employees exert influence over customers. This is as a result of the findings that empowering employs directly influence the performance on the job. As such, the more empowered the employee is, the higher the performance on the job. Coupled with other factors mentioned above, such employees are able to meet the demand of the customers and as such this increases customer satisfaction. It can therefore be concluded that how employees behave determine perception on the nature and the quality of service offered by service providers. These conclusions can be validated through the findings explained above, which assert that there are a number of e mployees’ behaviors which are directly related to employee job satisfaction. These behaviors are reflected as follows. The friendliness of employees towards the customers; if employees are friendly the customers perceives such employees as highly satisfied with their jobs. This creates a good relationship with the customers, effectively impressing the employees positively regarding the nature of customer service rendered (Andreassen and Lindestad 1998). Similar effects are realized if employees portray a commendable knowledge of products and services, the willingness of employees to assist the customers as well as the confidence portrayed by employees in handling customer relations issues. Two of the behavior mentioned previously results portray a significance influence on perception of customers regarding customer service. The ability of the employees to identify particular needs of each customer greatly enhances the relationships between the two parties. This creates an imm ediate positive perception about the nature of customer service. Furthermore, good communications skills by the employees are most like to make the customers feel appreciated, thus raising perception about good customer service. Additionally good communication skills are enhanced by non verbal skills such as neatness, smiling, among others. The discussion above shows that customer perception on the nature of customer service based on observable employee behavior. As such, these findings identify an area of interest of which service providers must consider. While human management issues especially those concerning empowerment and provision of tools and facilities to work are vital towards raising employees’ morale, the study also highlights the need to manage employee behavior. This can be attained through motivation and behavioral training. Furthermore, since this study is cross sectional in nature, it only answers the question of employee’s satisfaction and the relati onship it has on customer service, at a particular point in time. This leaves other important questions answered. Such questions include the relationship between employee satisfaction and customer perception on customer service on long term basis. As such, there is need to study this complex relationship over a long period of time. Thus longitudinal studies seem relevant. In addition, this study cannot be used to make valid generalizations, since it is cross sectional in nature. Cross sectional studies are time limited and as such only target a small part of the population (Rose and Barker, 1997). While the data produced is valid, the results cannot used to make generalization about the relationship between customer satisfaction and perception about customer service in the entire service industry, since the target population cannot be used as a fair representation of the entire service industry. Conclusion It is evident that employees’ satisfaction bears heavily on customer p erceptions about customer service and the general satisfaction in the service industry. Despite the fact that there are a number of factors that influence the relationship, the nature customer satisfaction largely depends on the perception the customers have on employee satisfaction. Since customer form their perception based on observable employee behavior, service provider must be keen on the type of behavior exhibited by their employees. As such, other than proving that employees and customer satisfaction are related, the stud provide evidence needed for further action by service providers, especially on the need to train employees on behavior management. Furthermore, the study is cross sectional and as provides opportunities to conduct longitudinal research in future. References List Ahmad, Z., Ahmed, I., Nawaz, M. and Ahmad, Z. (2011). Job Satisfaction of Middle Level Managers in Pharmaceutical Industry of Pakistan Vol. Journal of Management Review, 1(1). Andreassen, T., and Li ndestad, B. (1998), Consumer loyalty and complex services.  International Journal of Service Industry Management, 9 (1). Bull, F. (2005). The relationship between job satisfaction and organizational commitment amongst high school teachers in disadvantaged areas in the Western Cape. Web. Burke R., Graham J and Smith F. (2005). Putting the customer second. TQM Journal, 17(1). Rose, C. and Barker J. (1997). Case-control and cross-sectional studies. London: BMJ. Sathish, M., Santhosh, K., Kumar, K. Naveen, J. and.Jeevanantham, V. (2011). A study on consumer switching behavior in cellular service provider: a study with reference to Chennai. Far East Journal of Psychology and Business, 2(2). Yagil, D. (2006). The relationship of service provider power motivation, empowerment and burnout to customer satisfaction. Journal of Service Management, 17(3). Yeck, S., Morales, M., Ladhari, R., and Pons, F. (2002). 10 years of service quality measurement: reviewing the use of the SERVQUAL instrum ent. Cuadernos de Diffusion, 7(13). This proposal on The relationship between employees’ job satisfaction and customer satisfaction in service business was written and submitted by user Jaxon E. to help you with your own studies. You are free to use it for research and reference purposes in order to write your own paper; however, you must cite it accordingly. You can donate your paper here.

Free Essays on Decriminilization Of Marijuana

Decriminalization of Marijuana Every year our government spends more than nineteen billion dollars to eradicate it’s use in the United States. About seventeen thousand people were arrested last year because of it. We spend twenty thousand dollars a year per inmate to hold these jailbirds captive. Who are these dangerous criminals you ask? Stoners. One argument against the decriminalization of marijuana is why would we want to introduce another intoxicant into our society when alcohol and cigarette smoking is already so damaging? Marijuana is far less harmful to the body than cigarettes. Not to mention while it may be potentially habit forming, it is not addictive. When comparing marijuana to alcohol the differences are obvious. I would much rather be in an argument with guy that has been smoking joints all night than some dude who has spent all night pounding shots of tequila. Alcohol can alter a persons common sense. Despite this, our government trusts us with the burden of drinking responsibly. Over seventeen thousand arrests are made regarding cannabis a year. Almost ninety percent of these arrests are for simple possession, not trafficking or sale. This is an inappropriate use of valuable law enforcement resources that should be focused on more serious and violent crimes. I don’t know about you, but I would rather have a midnight toker for a neighbor than a midnight stalker. The spending of government money needs to be reevaluated. Our government needs to take a step back and admit they were mistaken to think they could successfully discontinue the use of marijuana. â€Å"You cannot have illegal what a significant segment of the population in any society is committed to doing. You simply cannot arrest, prosecute, and punish such a large number of people, particularly in a democracy† (Incardi 285). Ultimately it is not the role of the government to tell it’s adult citizens what risks to take. Bicycles ... Free Essays on Decriminilization Of Marijuana Free Essays on Decriminilization Of Marijuana Decriminalization of Marijuana Every year our government spends more than nineteen billion dollars to eradicate it’s use in the United States. About seventeen thousand people were arrested last year because of it. We spend twenty thousand dollars a year per inmate to hold these jailbirds captive. Who are these dangerous criminals you ask? Stoners. One argument against the decriminalization of marijuana is why would we want to introduce another intoxicant into our society when alcohol and cigarette smoking is already so damaging? Marijuana is far less harmful to the body than cigarettes. Not to mention while it may be potentially habit forming, it is not addictive. When comparing marijuana to alcohol the differences are obvious. I would much rather be in an argument with guy that has been smoking joints all night than some dude who has spent all night pounding shots of tequila. Alcohol can alter a persons common sense. Despite this, our government trusts us with the burden of drinking responsibly. Over seventeen thousand arrests are made regarding cannabis a year. Almost ninety percent of these arrests are for simple possession, not trafficking or sale. This is an inappropriate use of valuable law enforcement resources that should be focused on more serious and violent crimes. I don’t know about you, but I would rather have a midnight toker for a neighbor than a midnight stalker. The spending of government money needs to be reevaluated. Our government needs to take a step back and admit they were mistaken to think they could successfully discontinue the use of marijuana. â€Å"You cannot have illegal what a significant segment of the population in any society is committed to doing. You simply cannot arrest, prosecute, and punish such a large number of people, particularly in a democracy† (Incardi 285). Ultimately it is not the role of the government to tell it’s adult citizens what risks to take. Bicycles ...

Understanding the Visible Learning Theory

Understanding the Visible Learning Theory Educators struggle with a number of questions regarding teaching methods, including: What educational policies have the greatest impact on students?What influences students to achieve?What are best practices for teachers yield the best results? Roughly 78 billion is the estimated dollar amount invested in education by the United States according to market analysts (2014). So, understanding how well this enormous investment in education is working requires a new kind of calculation in order to answer these questions. Developing that new kind of calculation is where Australian educator and researcher John Hattie has focused his research. In his inaugural lecture at the University of Auckland as far back as 1999, Hattie  announced the three principles that would guide his research: We need to make relative statements about what impacts on student work;We need estimates of magnitude as well as statistical significance – it is not good enough to say that this works because lots of people use it etc., but that this works because of the magnitude of impact;We need to be building a model based on these relative magnitudes of effects. The model he proposed in that lecture has grown to become a ranking system of influencers and their effects in education using meta-analyses, or groups of studies, in education. The meta-analyses he used came from all over the globe, and his method in developing the ranking system was first explained with the publication of his book Visible Learning in 2009. Hattie noted that the title of his book was selected to help teachers become evaluators of their own teaching† with the objective of giving teachers a better understanding of the positive or negative effects on student learning: Visible Teaching and Learning occurs when teachers see learning through the eyes of students and help them become their own teachers. The Method Hattie used the data from multiple meta-analyses in order to get a pooled estimate or measure of an effect on student learning. For example, he used sets of meta-analyses on the effect of vocabulary programs on student learning as well as  sets of meta-analyses on the effect of preterm birth weight on student learning. Hatties system of gathering data from multiple educational studies and reducing that data into pooled estimates allowed him to rate the different influences on student learning according to their effects in the same manner, whether they show negative  effects or positive effects. For example, Hattie ranked studies that showed the effects of classroom discussions, problem-solving, and acceleration as well as studies that showed the impact of retention, television, and summer vacation on student learning. In order to categorize these effects  by  groups, Hattie organized the influences into six areas: The studentThe homeThe schoolThe curriculaThe teacherTeaching and learning approaches Aggregating the data that was generated from these meta-analyses, Hattie determined the size of the effect each influence had on student learning. The size effect could be numerically converted for purposes of comparison, for example, an influencer’s effect size of 0 shows that the influence has no effect on student achievement. The greater the size of the effect, the greater the influence. In the 2009 edition of Visible Learning,  Hattie suggested that an effect size of 0,2 could be relatively small, while an effect size of 0,6 could be large. It was the effect size of 0,4, a numerical conversion that Hattie termed as his â€Å"hinge point,† that became the effect size average. In the 2015  Ã‚  Visible Learning,  Hattie rated influence effects by increasing the number of meta-analyses from 800 to 1200. He repeated the method of ranking influencers using the â€Å"hinge point† measurement which allowed him to rank the effects of 195 influences on a scale. T he Visible Learning website has several interactive graphics to illustrate these influences. Top Influencers The number one influencer at the top of the 2015 study is an effect labeled â€Å"teacher estimates of achievement. This category, new to the ranking list, has been given a ranking value of 1,62, calculated at four times the effect of the average influencer. This rating reflects the accuracy of an individual teachers knowledge of students in his or her classes and how that knowledge determines the kinds of classroom activities and materials as well as the difficulty of the tasks assigned. A teacher’s estimates of achievement can also influence  the questioning strategies and the student groupings used in class as well as the teaching strategies selected. It is, however, the number two influencer, collective teacher efficacy, that holds an even greater promise for improving student achievement.  This influencer means harnessing the power of the group to bring out the full potential of students and educators in schools.   It should be noted that Hattie is not the first to point out the importance of collective teacher efficacy. He is the one who rated it as having an effect ranking of 1.57, almost four times the average influence. Back in 2000, educational researchers Goddard, Hoy, and Hoy advanced this idea, stating that â€Å"collective teacher efficacy shapes the normative environment of schools† and that the â€Å"perceptions of teachers in a school that the efforts of the faculty as a whole will have a positive effect on students.† In short, they found that â€Å"teachers in[ this] school can get through to the most difficult students.† Rather than rely on the individual teacher, collective teacher efficacy is a factor that can be manipulated at a whole school level. Researcher Michael Fullen and Andy Hargreaves in their article Leaning Forward: Bringing the Profession Back In  note several factors that must be present including: Teacher autonomy to take on the specific leadership roles with opportunities to participate in making decisions on school-wide issuesTeachers are allowed to collaboratively develop and communicate mutual goals that are clear and specificTeachers are committed to the goalsTeachers work as a team transparently without judgmentTeachers work as a team to collect specific evidence to determine growthLeadership acts responsively to all stakeholders and show concern and respect for their staff. When these factors are present, one of the outcomes is that collective teacher efficacy helps all teachers understand their significant impact on student results. There is also the benefit of stopping teachers from using other factors (e.g. home life, socio-economic status, motivation) as an excuse for low achievement. Way at the other end of the Hattie ranking spectrum, the bottom, the influencer of depression is given an effect score of -,42. Sharing space at the bottom of the  Visible Learning  Ladder are the influencers mobility (-,34) home corporal punishment (-,33), television (-,18), and retention (-,17). Summer vacation, a much-beloved institution, is also negatively ranked at -,02. Conclusion In concluding his inaugural address almost twenty years ago, Hattie pledged to use the best statistical modeling, as well as to conduct meta-analyses to achieve integration, perspective, and magnitude of effects. For teachers, he pledged to provide evidence that determined the differences between experienced and expert teachers as well as to assess the teaching methods that increase the probability of impact on student learning. Two editions of Visible Learning are the product of the pledges Hattie made in determining what works in education. His research can help teachers see better how their students learn best. His work is also a guide for how to best invest in education; a review of 195 influencers that can be better targeted by  statistical significance  for billions in investment...78 billion to start.

Understanding the Visible Learning Theory

Understanding the Visible Learning Theory Educators struggle with a number of questions regarding teaching methods, including: What educational policies have the greatest impact on students?What influences students to achieve?What are best practices for teachers yield the best results? Roughly 78 billion is the estimated dollar amount invested in education by the United States according to market analysts (2014). So, understanding how well this enormous investment in education is working requires a new kind of calculation in order to answer these questions. Developing that new kind of calculation is where Australian educator and researcher John Hattie has focused his research. In his inaugural lecture at the University of Auckland as far back as 1999, Hattie  announced the three principles that would guide his research: We need to make relative statements about what impacts on student work;We need estimates of magnitude as well as statistical significance – it is not good enough to say that this works because lots of people use it etc., but that this works because of the magnitude of impact;We need to be building a model based on these relative magnitudes of effects. The model he proposed in that lecture has grown to become a ranking system of influencers and their effects in education using meta-analyses, or groups of studies, in education. The meta-analyses he used came from all over the globe, and his method in developing the ranking system was first explained with the publication of his book Visible Learning in 2009. Hattie noted that the title of his book was selected to help teachers become evaluators of their own teaching† with the objective of giving teachers a better understanding of the positive or negative effects on student learning: Visible Teaching and Learning occurs when teachers see learning through the eyes of students and help them become their own teachers. The Method Hattie used the data from multiple meta-analyses in order to get a pooled estimate or measure of an effect on student learning. For example, he used sets of meta-analyses on the effect of vocabulary programs on student learning as well as  sets of meta-analyses on the effect of preterm birth weight on student learning. Hatties system of gathering data from multiple educational studies and reducing that data into pooled estimates allowed him to rate the different influences on student learning according to their effects in the same manner, whether they show negative  effects or positive effects. For example, Hattie ranked studies that showed the effects of classroom discussions, problem-solving, and acceleration as well as studies that showed the impact of retention, television, and summer vacation on student learning. In order to categorize these effects  by  groups, Hattie organized the influences into six areas: The studentThe homeThe schoolThe curriculaThe teacherTeaching and learning approaches Aggregating the data that was generated from these meta-analyses, Hattie determined the size of the effect each influence had on student learning. The size effect could be numerically converted for purposes of comparison, for example, an influencer’s effect size of 0 shows that the influence has no effect on student achievement. The greater the size of the effect, the greater the influence. In the 2009 edition of Visible Learning,  Hattie suggested that an effect size of 0,2 could be relatively small, while an effect size of 0,6 could be large. It was the effect size of 0,4, a numerical conversion that Hattie termed as his â€Å"hinge point,† that became the effect size average. In the 2015  Ã‚  Visible Learning,  Hattie rated influence effects by increasing the number of meta-analyses from 800 to 1200. He repeated the method of ranking influencers using the â€Å"hinge point† measurement which allowed him to rank the effects of 195 influences on a scale. T he Visible Learning website has several interactive graphics to illustrate these influences. Top Influencers The number one influencer at the top of the 2015 study is an effect labeled â€Å"teacher estimates of achievement. This category, new to the ranking list, has been given a ranking value of 1,62, calculated at four times the effect of the average influencer. This rating reflects the accuracy of an individual teachers knowledge of students in his or her classes and how that knowledge determines the kinds of classroom activities and materials as well as the difficulty of the tasks assigned. A teacher’s estimates of achievement can also influence  the questioning strategies and the student groupings used in class as well as the teaching strategies selected. It is, however, the number two influencer, collective teacher efficacy, that holds an even greater promise for improving student achievement.  This influencer means harnessing the power of the group to bring out the full potential of students and educators in schools.   It should be noted that Hattie is not the first to point out the importance of collective teacher efficacy. He is the one who rated it as having an effect ranking of 1.57, almost four times the average influence. Back in 2000, educational researchers Goddard, Hoy, and Hoy advanced this idea, stating that â€Å"collective teacher efficacy shapes the normative environment of schools† and that the â€Å"perceptions of teachers in a school that the efforts of the faculty as a whole will have a positive effect on students.† In short, they found that â€Å"teachers in[ this] school can get through to the most difficult students.† Rather than rely on the individual teacher, collective teacher efficacy is a factor that can be manipulated at a whole school level. Researcher Michael Fullen and Andy Hargreaves in their article Leaning Forward: Bringing the Profession Back In  note several factors that must be present including: Teacher autonomy to take on the specific leadership roles with opportunities to participate in making decisions on school-wide issuesTeachers are allowed to collaboratively develop and communicate mutual goals that are clear and specificTeachers are committed to the goalsTeachers work as a team transparently without judgmentTeachers work as a team to collect specific evidence to determine growthLeadership acts responsively to all stakeholders and show concern and respect for their staff. When these factors are present, one of the outcomes is that collective teacher efficacy helps all teachers understand their significant impact on student results. There is also the benefit of stopping teachers from using other factors (e.g. home life, socio-economic status, motivation) as an excuse for low achievement. Way at the other end of the Hattie ranking spectrum, the bottom, the influencer of depression is given an effect score of -,42. Sharing space at the bottom of the  Visible Learning  Ladder are the influencers mobility (-,34) home corporal punishment (-,33), television (-,18), and retention (-,17). Summer vacation, a much-beloved institution, is also negatively ranked at -,02. Conclusion In concluding his inaugural address almost twenty years ago, Hattie pledged to use the best statistical modeling, as well as to conduct meta-analyses to achieve integration, perspective, and magnitude of effects. For teachers, he pledged to provide evidence that determined the differences between experienced and expert teachers as well as to assess the teaching methods that increase the probability of impact on student learning. Two editions of Visible Learning are the product of the pledges Hattie made in determining what works in education. His research can help teachers see better how their students learn best. His work is also a guide for how to best invest in education; a review of 195 influencers that can be better targeted by  statistical significance  for billions in investment...78 billion to start.

Understanding the Visible Learning Theory

Understanding the Visible Learning Theory Educators struggle with a number of questions regarding teaching methods, including: What educational policies have the greatest impact on students?What influences students to achieve?What are best practices for teachers yield the best results? Roughly 78 billion is the estimated dollar amount invested in education by the United States according to market analysts (2014). So, understanding how well this enormous investment in education is working requires a new kind of calculation in order to answer these questions. Developing that new kind of calculation is where Australian educator and researcher John Hattie has focused his research. In his inaugural lecture at the University of Auckland as far back as 1999, Hattie  announced the three principles that would guide his research: We need to make relative statements about what impacts on student work;We need estimates of magnitude as well as statistical significance – it is not good enough to say that this works because lots of people use it etc., but that this works because of the magnitude of impact;We need to be building a model based on these relative magnitudes of effects. The model he proposed in that lecture has grown to become a ranking system of influencers and their effects in education using meta-analyses, or groups of studies, in education. The meta-analyses he used came from all over the globe, and his method in developing the ranking system was first explained with the publication of his book Visible Learning in 2009. Hattie noted that the title of his book was selected to help teachers become evaluators of their own teaching† with the objective of giving teachers a better understanding of the positive or negative effects on student learning: Visible Teaching and Learning occurs when teachers see learning through the eyes of students and help them become their own teachers. The Method Hattie used the data from multiple meta-analyses in order to get a pooled estimate or measure of an effect on student learning. For example, he used sets of meta-analyses on the effect of vocabulary programs on student learning as well as  sets of meta-analyses on the effect of preterm birth weight on student learning. Hatties system of gathering data from multiple educational studies and reducing that data into pooled estimates allowed him to rate the different influences on student learning according to their effects in the same manner, whether they show negative  effects or positive effects. For example, Hattie ranked studies that showed the effects of classroom discussions, problem-solving, and acceleration as well as studies that showed the impact of retention, television, and summer vacation on student learning. In order to categorize these effects  by  groups, Hattie organized the influences into six areas: The studentThe homeThe schoolThe curriculaThe teacherTeaching and learning approaches Aggregating the data that was generated from these meta-analyses, Hattie determined the size of the effect each influence had on student learning. The size effect could be numerically converted for purposes of comparison, for example, an influencer’s effect size of 0 shows that the influence has no effect on student achievement. The greater the size of the effect, the greater the influence. In the 2009 edition of Visible Learning,  Hattie suggested that an effect size of 0,2 could be relatively small, while an effect size of 0,6 could be large. It was the effect size of 0,4, a numerical conversion that Hattie termed as his â€Å"hinge point,† that became the effect size average. In the 2015  Ã‚  Visible Learning,  Hattie rated influence effects by increasing the number of meta-analyses from 800 to 1200. He repeated the method of ranking influencers using the â€Å"hinge point† measurement which allowed him to rank the effects of 195 influences on a scale. T he Visible Learning website has several interactive graphics to illustrate these influences. Top Influencers The number one influencer at the top of the 2015 study is an effect labeled â€Å"teacher estimates of achievement. This category, new to the ranking list, has been given a ranking value of 1,62, calculated at four times the effect of the average influencer. This rating reflects the accuracy of an individual teachers knowledge of students in his or her classes and how that knowledge determines the kinds of classroom activities and materials as well as the difficulty of the tasks assigned. A teacher’s estimates of achievement can also influence  the questioning strategies and the student groupings used in class as well as the teaching strategies selected. It is, however, the number two influencer, collective teacher efficacy, that holds an even greater promise for improving student achievement.  This influencer means harnessing the power of the group to bring out the full potential of students and educators in schools.   It should be noted that Hattie is not the first to point out the importance of collective teacher efficacy. He is the one who rated it as having an effect ranking of 1.57, almost four times the average influence. Back in 2000, educational researchers Goddard, Hoy, and Hoy advanced this idea, stating that â€Å"collective teacher efficacy shapes the normative environment of schools† and that the â€Å"perceptions of teachers in a school that the efforts of the faculty as a whole will have a positive effect on students.† In short, they found that â€Å"teachers in[ this] school can get through to the most difficult students.† Rather than rely on the individual teacher, collective teacher efficacy is a factor that can be manipulated at a whole school level. Researcher Michael Fullen and Andy Hargreaves in their article Leaning Forward: Bringing the Profession Back In  note several factors that must be present including: Teacher autonomy to take on the specific leadership roles with opportunities to participate in making decisions on school-wide issuesTeachers are allowed to collaboratively develop and communicate mutual goals that are clear and specificTeachers are committed to the goalsTeachers work as a team transparently without judgmentTeachers work as a team to collect specific evidence to determine growthLeadership acts responsively to all stakeholders and show concern and respect for their staff. When these factors are present, one of the outcomes is that collective teacher efficacy helps all teachers understand their significant impact on student results. There is also the benefit of stopping teachers from using other factors (e.g. home life, socio-economic status, motivation) as an excuse for low achievement. Way at the other end of the Hattie ranking spectrum, the bottom, the influencer of depression is given an effect score of -,42. Sharing space at the bottom of the  Visible Learning  Ladder are the influencers mobility (-,34) home corporal punishment (-,33), television (-,18), and retention (-,17). Summer vacation, a much-beloved institution, is also negatively ranked at -,02. Conclusion In concluding his inaugural address almost twenty years ago, Hattie pledged to use the best statistical modeling, as well as to conduct meta-analyses to achieve integration, perspective, and magnitude of effects. For teachers, he pledged to provide evidence that determined the differences between experienced and expert teachers as well as to assess the teaching methods that increase the probability of impact on student learning. Two editions of Visible Learning are the product of the pledges Hattie made in determining what works in education. His research can help teachers see better how their students learn best. His work is also a guide for how to best invest in education; a review of 195 influencers that can be better targeted by  statistical significance  for billions in investment...78 billion to start.

Leftside bias and Holistic effect in face recognition Lab Report

Leftside bias and Holistic effect in face recognition - Lab Report Example One hundred twenty trials were done for each orientation (Upright: Left or Right and Inverted: Left or Right), that is 120 upright images (60 adult and 60 baby images) and 120 inverted images (60 adult and 60 baby images) were shown to the participants. Group data was analyzed using T - test. Results showed a significant difference (p Participant's T-test (two tailed, independent sample) was performed to compare the mean probability of the study group with the null hypothesis (i.e. probability of the participants holding the left-left face as the original face whether the image is upright or inverted is 0.5). In this study, 120 trials were done. Therefore to analyze the group data N = 60 was considered and to analyze individual data N = 120 was considered. For statistical calculations probability of null hypothesis was taken as 0.05. To find out if there was any significant difference between the two groups in terms of chimeric face chosen (left-left or right-right) with respect to how the images are positioned (upright or inverted), an Independent T - test was done. Table 2 and 3 shows the results of the T - tests (also the Descriptive Analysis is shown). Table 2 Descriptive Analysis The Descriptive Analysis showed that greater than 50 percent of the participants chose a left-left chimeric face. This result is in resemblance of the 'left-side bias' observed by Hsiao and Cottrell (2009). Table 3 T-test Results The t-test results revealed a significant difference of participants choosing a left-left chimeric face on both upright and inverted images. Discussion This study was carried out to identify whether the orientation of images upon presentation has a significant effect on the decisions made participants of the facial likeness task. One hundred twenty trials were done for each orientation (Upright: Left or Right and Inverted: Left or Right), that is 120 upright images (60 adult and 60 baby images) and 120 inverted images (60 adult and 60 baby images) were shown to the participants. Group data was analyzed using T - test. To find out if there was

Case study analysis and continuous professional development Essay

Case study analysis and continuous professional development - Essay Example Organizational contextual factors Sonoco Products Company is a global packaging company that was developed in 1899 in Hartsville, South Carolina. Major James Coker established the company and his main target was to make paper cone used to hold yarn in the textile industry. The company kept on making paper cones till it became a leading paper cone industry, experiencing competition from other cone producing companies. This led to its expansion and it started manufacturing packages till it became the largest packing industry in the world (Thomas, Groysberg, and Reavis, 2008). The company proposed a new organizational restructuring that would suit the function cost by at least 20%, this is for the reason that, the company had been highly taxed due to the high cost it was experiencing, so the company managed to increase the sales by 14% by reducing expenses with the increase in shareholders. The organization established a new organizational model; this was to improve the top growth in im proving the company’s sales to compete with companies around the world. The consumer packaging department was to check the packaging style to meet the demands of the customers around the world. This strategy was a rethinking strategy of certain company structures like the human resources. Under the HR every manager managed talents within each of her or his division (Kotelnikov, 2006). The managing director developed policies for performance, management, compensation, development and successful management. These polices advocated for the HR to increase general manager accountability for talent management, to distribute HR talent management and to distribute more, to optimize HR talent ability to give customized ability to the customers. These strategies are only effective if implemented by serious working staff members within the organization (Fort and Salin, 2001). The Sonoco Company established in 1889 in California was a textual industry and gradually developed into a consu mer packaging consumer industry. This growth occurred manly through acquisition in 1990 where the company made 60% acquisition around the world. The company occupied two segments the packaging segments and the consumer packaging. The industrial segment which served as the textile industry paper industry and film industry employed around 11000 employees and made 55% revenue to the company. The consumer packaging had a range of 6000 employees and made high revenue to the company with its products. Some of the company’s products are Gillette, Krafts, Nestle and Procter as well as Gamble. The cultural background of the company is friendly, collaborative, and ethical and team oriented. Most of these employees have been in the organization for over twenty years and enjoyed working with the members of the community. During the late 1990s there was a fall in the stock and change was a required in the structure of the organization to solve the problem (Mission statement - Sonoco, 2009 ). In the early 1990, the packaging companies generated around 40 billion and the consumer industry represented about 70% countrywide distribution. Paper industry accounted for 30% and film industry accounte