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|STUDENT FEEDBACK FORM|
Institute of Sport and Exercise Science
|MODULE: MSPO4001||ASSIGNMENT NUMBER: 02 Data Handling|
|STUDENT NUMBER:||This assignment is part of a moderated sample YES|
|Your feedback comes in two parts. Section 1 (diagnostic comments) is designed to help you identify the strengths of the assignment and to give you guidance about how you can improve the overall quality of future assignments. The second section (marking matrix) explains how your final grade was determined. This feedback will help clarify those things that you did not understand. Please see your tutor for further clarification or click http://www.worcester.ac.uk/studyskills/documents/Using_feedback_to_improve_your_work_2011.pdffor more advice.|
|Diagnostic commentsWhat you did well:|
· Provided a basic overview of 5 relevant research articles
· Demonstrated a basic appreciation of some of the fundamentals of data handling; particularly with regards to the use of quantitative methods
· Offered some cogent observations and critiques of key data handling approaches in some areas.
In order to improve
| Use of LiteratureIn some places ok, however a far greater breadth and depth needed in order to demonstrate engagement with research methodology and an engagement with relevant approaches in the chosen field of study.|
|ReferencingOk, though with some errors and inconsistencies throughout.|
If problems have been identified with your referencing of material, it is advised that you go to http://www.worcester.ac.uk/studyskills/documents/Plagiarism_Referencing_2011.pdf or contact firstname.lastname@example.org
|First Marker Name: Date: mark:|
|Second Marker Name: Date: mark:|
|AGREED FINAL MARK:||E (FAIL)|
Your grade is based on assessment of the following information (these do not carry equal weighting and are for guidance only) –
|Article selection||At least 5 research articles with full text available as either hyperlink or appendix|
|Validity, reliability, credibility, transferability||Validity & reliability or credibility & transferability, of the method, instruments, tools or tests used to collect the data have been critically evaluated through comparison with both research methods texts and research article use to reach a coherent fully justified conclusion||Validity & reliability or credibility & transferability, of the method, instruments, tools or tests used to collect the data have been evaluated through comparison with both research methods texts and research article use to reach a coherent justified conclusion||Validity & reliability or credibility & transferability, of the method, instruments, tools or tests used to collect the data have been described predominantly with some reference to research methods texts and /or research articles to reach a conclusion.|
|Data preparation||Data preparation methods employed have been critically evaluated through comparison with both research methods texts and research article use to reach a coherent fully justified conclusion||Data preparation methods employed have been evaluated through comparison with both research methods texts and research article use to reach a coherent justified conclusion||Data preparation methods employed have been described predominantly with some reference to research methods texts and/or research articles to reach a conclusion||FAIL|
|Data analysis||Identified data analysis has been critically evaluated through comparison with both research methods texts and research article use to reach a coherent fully justified conclusion||Identified data analysis has been evaluated through comparison with both research methods texts and research article use to reach a coherent justified conclusion||Identified data analysis has been predominantly described predominantly in relation to research methods texts and/or research articles to reach a conclusion||FAIL|
|Data interpretation||Interpretation of the data analysis and drawn conclusions have been critically evaluated through comparison with both research methods texts and research article use to reach a coherent fully justified conclusion||Interpretation of the data analysis and drawn conclusions have been evaluated through comparison with both research methods texts and research article use to reach a coherent justified conclusion||Interpretation of the data analysis and drawn conclusions have been predominantly described with reference to research methods texts and/or research articles to reach a conclusion||FAIL|
|Limitations||Strengths &/or limitations in the articles have been clearly identified and are fully supported by critical evaluation in relation to both research methods texts and research article use to reach a coherent fully justified conclusion regarding the academic merit of each article and any combinations of the five chosen.||Strengths &/or limitations in the articles have been identified and are supported by evaluation in relation to both research methods texts and research article use to reach a coherent justified conclusion regarding the academic merit of each article.||Strengths &/or limitations in the articles have been identified and in relation to research methods texts and/or research articles to reach a conclusion regarding the academic merit of each article.|
|Proposed data handling & analysis section for the research proposal***||Proposed data handling and analysis techniques will be fully supported from appreciation of previous research texts, findings and analysis. They will be detailed and where appropriate (quantitative data) proposed statistical tests will be identified in specific relation to their use to answer the aims/question. Handling & analysis of qualitative data will be fully underpinned with both methodological and research supported justification.||Proposed data handling and analysis techniques will be predominantly well justified from previous research texts, findings and analysis. They will be detailed and where appropriate (quantitative data) proposed statistical tests will be identified in relation to the proposed research aims. Handling & analysis of qualitative data will be underpinned with methodological and/or research supported justification.||Proposed data handling and analysis techniques will be justified, and where appropriate (quantitative data) proposed statistical tests will be broadly identified but not in relation to the aims or research questions of the proposal. Handling & analysis of qualitative data will be appropriate with some methodological and/or research supported justification.|
|Reference list||The list will be fully in accordance with the HRS.||The list will be predominantly in accordance with the HRS.||The list will be mostly in accordance with the HRS.|
|Communication||Throughout, the material will be communicated very effectively and will be fully referenced in accordance with the Harvard Referencing system with excellent grammar and spelling throughout.||Throughout, the material will be communicated effectively and will be referenced in accordance with the Harvard Referencing system with very good grammar and spelling throughout.||Throughout, the material will be communicated well and in the appropriate format and will be predominantly referenced in accordance with the Harvard Referencing system with good grammar and spelling throughout.|
***You must write a proposed data handling & analysis section to follow on from your proposal (assessment 1) that should be written in the FUTURE tense and should identify everything you intend to do with your data with the rationale for the chosen method of data collection, handling and subsequent analysis clearly evident (max 500 words).
Assignment 2: Data Handling
Student ID: 13007727
The choice of data handling methodology is influenced by the collection strategy, type of variables under study, accuracy needed, data collection point, and the skills of the researcher (Guenther 2013). Importantly are the links between the variables, their sources, and the practical methods that will be utilised for its collection as they are crucial in the choice of appropriate data handling methodologies.
In qualitative methodology, data collection embraces techniques that are either unstructured or semi-structured. Notably, the methods constitute of focus groups, direct observations, and individual interviews. In the methodology, the chosen sample size is small and respondents are randomly selected. Premised on Landau et al (2013) assertion, qualitative methodologies are crucial in giving insights to problems and further developing a platform of generating ideas and hypotheses for the study.
On the other hand, quantitative methodologies seek to quantify a study problem by sourcing numerical data that is later transformed into figures that can be statistically interpreted. The methodology embraces structured techniques of data collection and handling. Particularly, surveys that can be online-based, paper-based, or mobile-based are utilised for data collection. As data analysis is a process of applying statistical techniques in describing, illustrating and evaluating data (Weathington et al 2012) this study will be premised on appraising data collection, handling, analysis and interpretation in the selected articles. Identifying limitations borne from the employed data collection, handling analysis and interpretation constitutes the scope of this study. This study will also succinctly propose the data handling methodology for the proposal ‘The effects and importance of Team cohesion on Sports performance’ that I will do later.
Reliability of a research methodology refers to how free the method is from measurement errors (
Interactive effects of team cohesion on the perceived efficacy in Semi-Professional Sport
The research design within the article is well described and methods clearly explained and the choice oOverall the buildup and undertaking of the research was well planned and clearly described.
The Multidimensional Sports Cohesion tool (MSCI: Yukelson et al. 1984) that had previously been translated into Spanish by the researchers was utilized in assessing the team’s cohesion. The inventory had 22 items that sought assess to the cohesion aspects that included teamwork, valued roles, unity of purpose, and attraction. The item responses were scaled on a 5-point Likert scale that ranged from “strongly disagree” having a score of 1 to “strongly agree” having a score of 5. In addition, a sociogram was also developed to assess the team’s cohesiveness.
Additionally, a questionnaire premised on Bandura`s (2006) assertions was used to measure efficacy; measuring both the players’ and the coaches’ perceptions towards team member’s levels of efficacy. Similarly, responses were scaled on a 5-point Likert scale.
In order to effectively analyse the data, descriptive, and correlational analysis were utilized in developing the study’s first hypotheses. Secondly, regression analysis was done to facilitate the verification of assertions raised in the hypotheses. Using an SPSS version 15, a statistics program, data was analysed.
This study establishes that the choice of the methodology was relevant to the study. In seeking to determine team cohesion, a method of assessing the cohesion aspects (MSC) was a prerequisite. The data collection methodology is reliable since the obtained value of Cronbach alpha for the self-efficacy instrument was above 0.8. The descriptive statistics that includes mean, standard deviation, and variance were for the analysis of variables that include cohesion, sociogram, and efficacy levels. The correlation of the variables (rxy) was also computed to obtain the coaches’ perceptions regarding athletes’ efficacy and that of the teammates. This study establishes that the approaches to data analysis were appropriate to the type of data collected.
Improving the Performance of a Basketball Team via Development of Cohesion in Sport Group
This article was composed using mixed methods consisting of observation and socio metric Survey methods both of Qualitative nature in order to obtain data from the respondents. The researchers physically observed how the players communicated to each other and determined their level of cohesion and socialization.
The socio-metric survey method in data collection was also utilized in assessing relationships between the players, establishing insight to the relationship, examining and evaluating the structure and social status of the players. Similarly, it measured the acceptance or rejection level among the players. Premised Donley & Grauerholz (2012) observations, the indicators for socio-metric test enable classification of individuals based on acceptance, rejection or isolation level in a group.
The socio-gram constituted of putting the subject that met the highest points (the one having the social status highest index) at the center of the concentric circles and the chart of preference marked unilaterally or mutually. Participants were then required to first write on the paper numbers ranging from 1 to 3 in list A: Listing 3 team-mates in the order of socialization and list B: giving a list of 3 team-mates least associated with.
In data analysis, the statistical indicators that sought to expose the relationship between team’s communication, the level of cohesion and socialization and performance of the basketball team were computed. Particularly, a socio metric analysis that reflected all the rejections and elections tables where constructed. A socio-metric that constituted the initial and final tests where also erected. This study establishes that the choice of methodology (socio-metric survey) was good has it enabled the researchers to collect information from players. Based on Kerzner (2013), surveys enable participants to give candid responses.
The approach to data analysis was appropriate to the type of data collected because it enabled the researchers to assess what they intended to. Notably, the analysis exposed that some team-mates were elected more than others; some rejected while others were found isolated. Additionally, this study establishes that the data collection methodology was reliable since the computed Cronbach alpha for the socio-metric survey instrument was 0.7. However, the observation method utilized in observing how the players communicated to each other in determining their level of cohesion and socialization is subject to bias and as such, the data collection methodology cannot be conclusively relied on in addition to not explaining the nature of their Observation method.
Relationship among the Athlete’s Leadership Behaviors and Team Cohesion in Sports
This article sought to examine the influence athlete leadership behaviors have on team cohesion perceptions. Group Environment Questionnaires (GEQs) (Carron et al, 1985) were administered to the participants whose items sought to determine the scale of cohesion and Leadership in Sports and further assess leadership behaviors of athletes. This method is one of the most widely used methods to assess cohesion in sport and according to Carron et al (1998) provides ample evidence of predictive, consistent inventory of factorial validity.
The GEQs contained an 18-item inventory, which sought to assess the core dimensions of cohesion. Similarly, an Individual Attractions questionnaire that had four items was also utilized in determining the feelings of an individual team player.
All items contained in the GEQs and the Individual Attractions questionnaire were scored and scaled on Likert scale of 9-point (‘strongly disagree =1’ to ‘strongly agree = 9’). In data analysis, alpha coefficients based on the cohesion dimension of the Group Integration were computed. It was concluded that individual perceptions regarding Training and Social Support had a positive correlation with the cohesion dimensions. On the other hand, autocratic behavior was found to have a negative relationship with the dimensions of cohesion.
This study established that the choice of the methodology was good. This is because using the GEQs enabled the participants to elicit responses that facilitated the researchers obtain information that was necessary for determining the core dimensions of cohesion. Similarly, the choice of the Individual Attractions questionnaire was good as it enabled the assessment of feelings of individual team players. It is also established that the approach to data analysis utilized (determination of alpha coefficients) was appropriate to the type of data collected as it enabled the correlation between the cohesion of the dimensions be determined.
However, the GEQs and the Individual Attractions questionnaires did not inclusively cover all the aspects of athlete leadership behaviors. As such, the methodology cannot be conclusively said to have elicited all the perceptions regarding team cohesion.
Experimental Examination of Cohesion Performance Relationships in Interactive Team Sports
This article sought to experimentally examine the relationship between sports team cohesion and performance. This study consisted of a large scale of participants carefully selected and a very small fraction eliminated after the initial first phase due to incomplete team assessment results that would of reflected negatively on the reliability of this research if not eliminated. The methods were clearly explained in addition to a good quantity of suitable participants was used for this research.
Quantitative questionnaires based on cohesion producing and cohesion-reducing manipulation were administered to all participants whose participation enabled them to earn an extra credit in their respective psychology courses. This criterion discouraged undergraduate students who had inadequate knowledge or did not know anything at all regarding playing basketball.
Additionally, the undergraduate student participants were presented with Group Environment Questionnaire (GEQ; Carron et al1985) that sought to determine their age, education level, and ability of playing basketball. Besides, the questionnaire sought to quantify amount of leisure time that is spent in playing basketball. Particularly, the undergraduate male participants were required to respond to the statement, ‘Indicate the number that best estimates your skill in basketball’. A 7-point Likert scale that ranged from ‘Never = 1 to Very Good = 7’ was utilized. Additionally, the participants were required to respond to a statement; ‘Indicate the number estimating how often you participate in basketball.’ A 5-point Likert scale that ranged from ‘Play Once daily = 1 to Never Play = 5’ was employed.
Data analysis done was premised on hypotheses one and two:
Hypothesis 1: Does the increase of task cohesion have an influence on performance?
Analysis of Chi-square was executed to determine the CP and CR. In addition, Multivariate Analysis of Variance (MANOVA) was also computed.
was utilized in analyzing this hypothesis.
The choice of the data methodology was good in accessing information necessary for this study. The methodology was reliable because the computed Cronbach’s alphas for the tools ranged from 0.75 to 0 .79. The approach to data analysis is appropriate to the type of data collected. However, this study establishes that rewarding extra credit to participants in their respective psychology courses compromised the reliability of the data collected.
A protective multilevel examination of the relationship between cohesion and team performance in elite youth sport
Within this article the main object how to examine the bidirectional character of the association between cohesion and performance was clearly demonstrated. The second objective was to translate, develop and test a new translation of the Environment questionnaire (YSEQ). The process of the methods used where of clear context, distinguishing the optimal participants by using two countries with very similar languages and cultures.
The translation of the YSEQ was executed with the well-established parallel back translation method (Brislin, 1970) and a team of qualified interpreters and other professionals to deliver.
The research was divided into 3 stages with time gaps of 4 weeks- 4 months between each stage. In stage one a discrepancy within the two new translated YSEQ questionnaires occurred and had to be rectified and slightly changed the contentent of the questionnaire and therefore invalidated part of the first results which where not included in the overall subscale scores (Eys et al 2007). Never less with a revised translation for stage two and three acceptable reliability coefficients could be obtained.
Confirmatory factor analyses was performed to conduct the gathered data and manifest in descriptive statistics and standardized factor loadings. These where all well explained and demonstrated.
Over the 3 stages participant numbers fluctuated and the lack of competitive sport within 2 stages in addition to the discrepancy within both first translated questionnaires negatively influence the overall results leading to the conclusion that the data is low validity.
Proposal Title: The Effects and Importance of Team Cohesion on Sports Performance
This proposal will employ both qualitative and quantitative approaches in data collections. 150 participants from three soccer teams and three basketball teams will be randomly selected. A Multidimensional Sports Cohesion tool will be utilised for data collection. This is because questionnaires are effective in evoking the respondent’s perceptions and experiencesThe anonymity aspect of the questionnaires gives room to respondents to elicit candid responses in regard the effects and importance of team cohesion on sports performance. In addition, the researcher will observe how players relate and communicate to one another.
An Individual Attractions questionnaire also based on the Likert scale (‘strongly = 1 to strongly agree = 5’) will be employed in order to determine the feelings of individual team players towards team cohesion.
By use of SPSS version 21, data will be analyzed where the correlation, descriptive statistics and correlation coefficients will be anlaysed to determine the effects and importance of team cohesion on Sports performance. Particularly, computation of the alpha coefficients will be appropriate to the type of data collected in determining the correlation between the dimensions of team cohesion and team performance.
In order to ensure reliable data handling methodology, reliability test for both the Multidimensional Sports Cohesion and Individual Attractions tools will be conducted by determining Cronbach coefficient value. A coefficient of 0.7 or greater will be considered desirable to regard the research instruments reliable for data collection. Additionally, test-retest will be done to ensure the reliability of a research instrument, therefore, ensure a reliable data collection methodology.
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This is IMPORTANT!!! The Assignment has to be EDITED and UPDATED with the below but not totally rewritten!!
|Module Code: MSPO4001||Module Title: Research methods.|
|Assignment no: 002||Title: Data handling||Word length:2500|
|Tutor: Dr Julia West|
|Re-assessment question:You must submit a front sheet showing how you engaged with the feedback from your first attempt and detailing the changes you have made in the work as a result of this. These changes should also be highlighted within the work.|
Select a minimum of five of the research articles (not reviews) that you have used to underpin your research proposal that have gathered, analysed and drawn conclusions from their data, preferably using a range of data collection methods and analysis. Make sure that for each, the full article is available in the assessment either as a hyperlink or as a full text in the appendix.
For each article, appraise their data collection, handling, analysis and interpretation and throughout in relation to supporting academic research methods literature and other research articles that may have previously used similar approaches, to include critical evaluation of:
· the validity & reliability or credibility & transferability, of the method, instruments, tools or tests used to collect the data;
· the way in which the collected data has been prepared for analysis;
· the way in which the data has then been analysed;
· the appropriateness of the interpretation of the data analysis presented and the conclusions drawn from this;
· the identified (and unidentified) limitations borne from the employed data collection, handling, analysis and interpretation in order to make judgement regarding the academic merit of each article.
· Developed from this deeper understanding, you must then write a proposed data handling section to follow on from your proposal (assessment 1) that should be written in the FUTURE tense and should identify everything you intend to do with the raw data once you have collected it with the rationale for the chosen method of data handling and subsequent analysis clearly evident.
o In the case of quantitative data, this will revolve around the identification of what you are testing for and why the test you will perform on the data is the most appropriate one to do – you MUST explain this and not just put the test.
o For qualitative data, you should identify the approach you will take to organising, analysing and interpreting your data and the development of themes and theories if applicable.
Assessment Format and Weighting
This is an individual, written assignment & it represents 50% of the marks available for this module.
The marking criteria is the same as on the blackboard page for this module.
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