Introduction.

Taking on a course is a beautiful experience, primarily when an individual fully participates in every aspect of the learning process. Learning is a lifelong activity that begins when a person enrols in a study topic, or an educational course (Bathmaker and Harnett, 2010). Regardless of age, learning is essential in every individual’s life. The lifelong benefit of education not only culminate to entering the workforce, earning certificates, a degree or license, but also leads to motivation, self-improvement, acquisition of more knowledge, career aspirations, and the general wellness (Shanahan, Mortimer & Johnson, 2015). Enrolling and participating in various activities of a course contributes to personal and professional learning. Own learning relates to skills necessary for an individual to excel in multiple aspects of life (Shanahan, Mortimer & Johnson, 2015). Besides, personal education enriches curiosity and interest in improving self. Professional learning, on the other hand, enhances performance, and advancement in the work environment (Shanahan, Mortimer & Johnson, 2015). Becoming a critical scholar requires a set of skills acquired during studying, or taking upon a course. Through reading, writing, researching and time management, an individual develops into a critical scholar (Shanahan, Mortimer & Johnson, 2015). By examining the course, and understanding every concept, it becomes easier to adopt the essential methodologies integral to the field of study, respond to experiences, opinions, new information and events (Briscoe and Khalifa, 2015). Besides, learning contributes to self- knowledge and the achievement of clarity and a better understanding of whatever topic of education. Throughout the course, the research methods relating to identity and power contributed to the development of skills necessary for a critical scholarship. Therefore, this journal discusses in details the benefits of the courses as explained in the PowerPoint presentations, and reflects on critical scholarly aspects.

Learning Outcomes.

During the learning process, different areas were covered that contributes to my knowledge of the field and critical scholarly of the course. To begin with, the use of questionnaires for both qualitative and quantitative research is vital in conducting dependable research in any field of professionalism (Bulmer, 2004). The study helped me understand and apply both self-completing questionnaires and structured interviews while doing research. Besides, I observe the rules for creating and applying questionnaires in the study. Some of the areas requiring attention include low response rate, missing on potential respondents and data, partial answers, and ensuring that the participants understand the questions fully. Through the course, I learnt how to address the questionnaire pitfalls through creating short questionnaires, providing clear instructions, and providing salient questions to the respondents. Based on the four cardinal rules of a well- designed questionnaire, the focus is on keeping the questions and answer together, providing clear instructions to the respondents, making a clear presentation, and ensuring that the questionnaire layout is uncluttered (Bulmer, 2004). In my field of study, and based on the learning outcome, the questionnaire should consider facts, behaviour and attitudes when used in data collection. Closed, open and focus questions all assist in collecting data for both qualitative and quantitative research.

Sampling is another exciting aspect of the learning outcome of the course. Understanding different types of sampling techniques and their importance helps conduct research that would not only contribute to the scholars’ body of knowledge but also help in addressing the general issues requiring attention. While random sampling applies to quantitative research, non- random sampling is best used in qualitative research (Emmel, 2013). According to Emmel, sampling is the process of taking a section of the target population to participate in a research activity. Sampling minimises bias and provides for the representation of the group that should participate in the research (Emmel, 2013). Some of the key terms covered in sampling include sampling error, the sampling frame, the sample, and the population. Sampling error is the difference between the target population and the sample used in the study (Emmel, 2013). The sampling frame is a list of all units from the community from which the sample is drawn. The population is the generalised group from which the sample is drawn, and the sample is the part of the population that participates in the research (Emmel, 2013). The course contributes to the knowledge of achieving an appropriate sample during the study. The more the people sampled to respond to the research question, the small the margin of error, and the lower the discrepancy in the study (Lim and Ting, 2012). I also learnt various factors affecting the sample size, which require redress to avoid biasness and unsupported findings. The factors include time and cost. A large sample would need much time to interview. Similar, preparing data collection instruments such as questionnaires will be costly. The second factor is non- response; thus, the research finds it challenging to make findings. Homogeneity of the population as well hinder the size of the sample with a possibility of influencing a larger sample, especially where the population is more homogenous (Lim and Ting, 2012).

Sampling methods based on the course include random sampling, simple random sampling, stratified random sampling, multi-stage cluster, and cluster sampling, non- probability sampling, convenience sampling, snowball sampling, quota sampling, case studies, theoretical sampling and maximum variation sampling. The maximum variation sampling use units with extreme characteristics considered in the sampling frame. Snowballing is entirely dependent on referrals to get respondents, convenience-sampling picks on readily available participants, and stratified sampling selects on appropriate stratum to participate in the research process.

Univariate analysis in the study contributes to a body of knowledge relating to means and averages, measures of dispersion, different types of variables, graphs and tables, and how aretheir used in a study. Variables are categorised as ordinal, interval, usual and dichotomous (Ho, 2006). Through the course, I learnt that dichotomous variables involve two answers as the case of the male/female, and yes/no. Under standard variables, the order of the answers take any form, for instance, country of origin, type of household pet among others. In the ordinal variable, there is the ordering of answers. However, the distance is the same. While using interval and scale variables, the range provides meaning and is regular. The course as well offers some of the significant roles of univariate variable analysis. The purposes include answering research questions regarding the distribution of variables in the target population involved in the research. Secondly, the analysis helps informs the subsequent stage of composite analysis. Fourth is assisting in the summary of variable values. Finally, it helps in an in-depth understanding of data and checking on errors. The presentation of univariate variables as well-formed part of the course and contributed to my knowledge of the use of frequency tables, diagrams, scales, a measure of central tendency, which involves mode mean and median, and a step of dispersion such as standard deviation, variance, interquartile range and range.

Just like the univariate variables, the course also helped me understand and apply the skills of analysing two variables (Ho, 2006). During the study, the significance of significance, contingency tables, and measures of the association while comparing two variables was evident. Comparing two variables makes it clear to determine whether two aspects involved in research are related. Most importantly is the dependent and the independent variables, which I mastered during the learning process. The independent variable is the cause, whereas the dependent variable is the effect. Understanding the relationship between variables involves bivariate analysis, which explores the relationship, establishes correlations and co-variance, infer the direction of a causal relationship, and the analysis of the contingency tables. The study also highlights the significance of the report using the p-value statistically. Both hypothesis and null hypothesis correlates to the p-value in the study that is observed (Ho, 2006). The course provides the basis for deciding on the level of significance when analysis the variables, and the formulation of the hypothesis. The possible errors as presented in session including rejecting and confirming the null hypothesis. However, the lower the cut- off point for the p-value, the higher the risk of type II error, and the higher the cutoff point, the higher error, which is type I (Ho, 2006). Besides, the course helps to understand the measure of association that deals with phi coefficient for two dichotomous variables, Cramer’s V for nominal and ordinal variables, as well as Spearman’s rho for two ordinal and an interval.

Thematic and content analysis focus on data generation, and thematic analysis of the data (Guest, MacQueen, & Namey, 2011). Based on the study, content analysis is the structuring, ordering and interpreting the mass of data collected. I learnt that data could be generated through podcasts, blogs, interview scripts, newspapers, documents, letters and videos. While making data, there is the use of samples since it is impossible to involve the whole community in the study. Factors considered include generalizability, minimising bias, and representation of the target population. Thematic analysis involves compelling reading and note taking, coding or the categorisation of information, and focusing on repetition, missing data, indigenous categories, and similarities during data analysis (Guest, MacQueen, & Namey, 2011). Through learning, the course helps gain skills for data collection and analysis of the content in a scholarly fashion.

Through the course, I also learnt different types of research interviews and their application in the study in my field. The interviews include focus groups, structured, unstructured and semi-structured interviews (Gillham, 2000). During an interview, there are key points to note, especially with the focus groups. The concerns include controlling the interview session, keeping the participants informed of the interview activities, setting clear objectives for using a specific type of interview, and creating a positive atmosphere for the interview (Gillham, 2000). In data generation, there is need to prepare adequately for the interview, listening more as compared to talking, asking open-ended questions, as well as provoking other topics during the interview if necessary (Gillham, 2000). In the data analysis, practical steps include recording the interview, transcribing, indexing and analysis, which focus on order, structure and supplying meaning to the data collected.

The course as well discussed in details the notion of discourse, which concentrates on the study of language use in the society for conversation or in documents. According to the course, discourse influence generation of knowledge, identity and social relations. Discourse is based on power, and have an impact on meanings (Taylor, 2013). Power is not only entrenched in institutions but also spread throughout society and different social relations. Language promotes and maintains power; therefore discourse analysis influence power and identity (Taylor, 2013). Discourse analysis exists in many forms including ethnomethodological analysis that looks at the structure of communication, the meaning and the rules of language use. (Taylor, 2013).  Foucauldian discourse analysis concentrates on historical practices of power, identities of power wielders, and the use of language as a tool to exclude and marginalise the powerless. Critical discourse analysis on the other hand focus on sociopolitical aspects of beliefs, the texts, and conversations. Critical discourse analysis concentrates on representation, as well as how the representations reproduce hegemony and ideology in society (Taylor, 2013).

Conclusion.

The course covered several topics, which contributed knowledge and skills in my scholarly field. Developing into a critical scholar require an understanding of every aspect of the field of study, especially the steps involved in research. Besides, a critical scholar adopts vital methodologies, and accountable to the established body of knowledge. Hence, the study helped me develop an in-depth understanding of the research processes, types of variables, data collection techniques, analysis and presentation. Furthermore, the study helped me understand that power and identity are not only in the institution but also in the language since it influences the relationship between individuals and within society.

Reference.

Bathmaker, A., and Harnett, P. (2010). Exploring Learning, Identity and Power through Life History and Narrative Research. Routledge.

Briscoe, F. M., and Khalifa, M. A. (2015). Becoming Critical: The Emergence of Social Justice Scholars. SUNY Press.

Bulmer, M. (2004). Questionnaires. SAGE Publications.

Emmel, N. (2013). Sampling and Choosing Cases in Qualitative Research: A Realist Approach. SAGE.

Gillham, B. (2000). Research Interview. A&C Black.

Guest, G, MacQueen, K. M., Namey, E. E. (2011). Applied Thematic Analysis. SAGE.

Ho, R. (2006). Handbook of Univariate and Multivariate Data Analysis and Interpretation with. SPSS. CRC Press.

Lim, W. M., and Ting, D. H. (2012). Research Methodology: A Toolkit of Sampling and Data Analysis Techniques for Quantitative Research. GRIN Verlag

Shanahan, M. J., Mortimer, J. T., & Johnson, M. K. (2015). Handbook of the Life Course, Vol 2. Springer

Taylor, S. (2013). What is Discourse Analysis?. A&C Black.