Goals Outcomes
Leadership Learning objectives
Stages of development Feelings
Cohesiveness Behavioural norms
Group dynamics
The effective team functioning questions focuses on the two domains of internal process and effectiveness criteria with the 11 sub domains of effective teams.
In section C, only biographical information was requested. This section consisted of questions related to:
• Student name; • student number; • group number; • email address; • gender; • population group;
• programme that student was studying; and • work environment.
The data collection process undertaken to implement the selected data collection method which comprised of the following activities:
• The researcher had attended student lectures and had given the students a brief description of the importance of the study and requested the students to complete the electronic questionnaire.
• Students who did not have access to internet were given hard copies of the questionnaires.
• The researcher sent out a reminder via the official NMMU Business School, MBA Unit correspondence email to the students one week prior to the questionnaire due date.
• As the student level of response was not adequate, students were again requested to complete the questionnaire.
• The online questionnaire enabled the data to be captured immediately for analysis.
• Information was collated.
• Collated information was analysed.
• Recommendations were formulated regarding the need for the implementation of effective teamwork in the study groups.
The covering letter accompanying each questionnaire indicated the purpose of the survey and also expressed the support from the NMMU Business School, MBA Unit for the study and emphases the important contribution respondents would make towards developing more effective MBA syndicate groups.
c) Collection of data – secondary data
Secondary research comprised of an extensive investigation of existing material relevant to the topic. A literature study was undertaken to obtain the information required to satisfy the primary research objective stated in Chapter 1 section 1.3.1 to identify literature on EI an effective team functioning of MBA syndicate groups at the NMMU Business School, MBA Unit. Additional sources of secondary data were also consulted in related subject disciplines such as Organisational Psychology and Business Management. International and national data searches included SABINET, Ebscohost, Emerald, Google, Dogpile, Nexes as well as the Internet, also Masters’ treatises and Doctoral theses have been written on EI, groups and MBA studies, were consulted.
d) Analysis of data
The value of a structured approach is that it allows the researcher to standardise the questionnaire to such an extent that a more numerative, statistically based analysis is possible and it also permits the researcher to test hypotheses quantitatively (Jankowicz, 2005: 295).
Greenfield (1996: 122) argues that various stages exist between gathering data and analysing data. These stages include data coding, data editing and data preparation for analysis. These stages must be planned before hand and be part of the documents and procedural designs. Coding refers to the conversion of verbatim answers to categorised data. Data editing involves checking mistakes in the data collected. In order to minimise mistakes and to maximise the validity and quality of data collected through the questionnaire, the researcher obtained professional advice from a qualified statistician during the construction of the questionnaire.
The data was only analysed after it was coded and edited. The data in this study was analysed by a qualified statistician using computer software. Analysis of variance (ANOVA), Cronbach alpha, standard deviation and mean value are examples of some of the tests run. A detailed summary of the data measurement methods are explained in Chapter 5.
e) Credibility of research findings
To measure the credibility of the research, two important concepts must be considered, they are validity and reliability. Both terms are used in connection with measurement. Validity and reliability influence the extent to which one can learn about the phenomenon being studied (Leedy & Ormrod, 2001: 31). A definition of both concepts is given below:
investigated in the real world (Oulton, 1995: 64). Measurements must be valid, reflecting the information presented in the data in an unbiased way. This is often established by seeing whether the information is consistent with other measurement methods, or with what is known and already recorded (Jankowicz, 2005: 111).
Reliability may be affected by, for example, the nature or character of the research worker and the subjects or cases selected to produce the raw data (Oulton, 1995: 64). Reliability is a measure of credibility, data must be reliable, and therefore, the same answer should be obtained on re-measurement with the same measurement methods, assuming the situation has not changed (Jankowicz, 2005: 111).
Validity of the research instrument
In this study, the validity of the research instrument, the analysis of variance (ANOVA) was used for comparing means of three or more variables. This test was used to compare means of three or more samples (Biology sites served by Helios, 2007). The normal acceptable rate for ANOVA is at a level of 0.05 or 5 percent of the Cronbach alpha, in this study, however, the ANOVA test used was at a 10 percent level of significance due to there being no ANOVA that that tested significance at the 5 percent.
Reliability of the research instrument
In this study Cronbach alpha reliability coefficients were used to assess the internal consistency of the entire scale. In each step of this procedure, Cronbach alpha reliability coefficients of the research instruments were computed, so that the individual variables (items) could be removed to improve the reliability of the research instrument, if necessary. The computer programme, STASTISTICA version 7.1 was used. In this reliability test, the Cronbach alpha is used in conjunction with the mean and standard deviation, the Cronbach alpha and inter item correlation are used to test how well a set of
items (or variables) measures a single one-dimensional latent construct. When data has a multidimensional structure, Cronbach alpha will usually be low. Technically speaking, Cronbach alpha is not a statistical test but a coefficient of reliability or consistency (UCLA Academic Technology Service, 2007).
The design of the research instrument is expected to contribute to achieving validity of results. This is accomplished through the use of five point Lickert scale questions. Confidence in the validity of the results is further reinforced through the delimitation of the research and the consistency of the results received across the respondent sample (Oulton, 1995:64). It is anticipated that results would prove reliable that the NMMU Business School, MBA Unit needs to improve MBA syndicate group functioning with EI methods.
4.3 SUMMARY
Table 4.7 summaries Chapter 4. The table shows the research problem, and the methodology used in the study.
Table 4.7: Summary of core research design decisions
Research problem
Is there a relationship between emotional intelligence and effective and efficient teamwork processes and to analyse the overall emotional intelligence profile of the MBA student?
Research methodology
Research paradigm Positivistic Research approach Quantitative Research methodology Survey
Unit of analysis Students and Alumni from the NMMU Business School, MBA Unit
Variable used Quantitative Data: Primary data Secondary data Questionnaire Literature review Reasoning Deductive (Source: Adapted from Brink, 2005: 81)
This chapter has explained the theoretical background of the research methodology of the study. Chapter 5 discusses the analysis and interpretation of the results obtained from the primary research effort.