Research Methodology: Skills Gap in the Workforce in Manufacturing Firms

In the industrial industry, the new population has more free-skill jobs relative to the millions of jobless young people who experience unemployment rates double as high as the national average to occupy those vacancies. To recruit a new generation of jobs, the manufacturing industry must foster the attraction of creativity, advanced technologies, and a strong industrial community, as well as dispel negative beliefs about unsanitary working conditions (Campbell, 2014). If there is a lack of strategies to increase the number of the new generation on the job within the manufacturing industry, there would be the loss of valuable and important opportunity of improving the workplaces and building new ways of thinking and inventions.
Research questions
What are the factors contributing to the widening skill gaps in the manufacturing sector?
What are the perceptions of the youth towards working in the manufacturing industry?
What needs to be done to address the skill gaps in the manufacturing industry?
What role has the education sector played in the skills gap that characterizes the manufacturing sector?
Hypothesis
The skills gap in the manufacturing sector is not significant enough to affect the growth and development of the industry.
Study objectives
General objectives
To determine the skill gaps in the workforce of the manufacturing sector
Specific objectives
Determining the factors that contribute to the skill gap in the manufacturing sector.
Describe the perceptions of the youth towards working in the manufacturing sector.
To establish the strategies that needs to be put in place to address the situation.

To determine the role the education has played in the current situation, as well what the sector should do to address the situation.
Study design
A mixed-methodology will be used to accomplish the objectives of the study. Mixed methodology comprises of quantitative research method and qualitative research methods. Quantitative research is vital in providing data that can be measured using statistical tools. It provides data that can be quantified to establish facts and figures. A cross-sectional study design will be utilized to collect quantitative data from the sampled population. Quantitative data will be collected through the use of structured questionnaires. Qualitative research refers to exploratory research that focuses on gaining an understanding of underlying reasons, motivations, and opinions. It is vital in providing insights into problems and assisting in the development of ideas or hypotheses targeting potential quantitative research. Qualitative research is applied in uncovering trends in thoughts, opinions, and digging deeper into a problem (Creswell, 2013).  In-depth interview and focus group discussion will be used to collect qualitative data. Qualitative data will be collected using open-ended and guided questionnaires. The independent variables include factors such as the courses offered at the learning institution, the perception of students and teachers towards working in the manufacturing industry, the level of innovation in the manufacturing sector, and the strategies that are being implemented by the manufacturing sector to attract a new workforce. Other independent variables include gender, age, and the religion of the participants. The main dependent variable is the skill gaps in the workforce in the manufacturing sector.

Population and sample
The study will be conducted in the learning institution and firms in the manufacturing sector. The study will focus on the tutors and students in educational institutions, as well as the workers in the manufacturing companies. The inclusion criterion states that the study will target mentally competent individuals who are 18 years old and over. Only students and tutors in sampled institution of learning and workers in the manufacturing firms will take part in the study. The exclusion criterion indicates that individuals who are not mentally competent and have not attained the legal age of 18 years and over will not qualify to be part of the study. Individuals who are not students or tutors in learning institutions, as well as those who are not working in the manufacturing companies will not be recruited in the study. Those who fail to consent will not take part in the study. The study will target at least 384 respondents based on Yamane (1967) sampling formula (Yilmaz, 2013).
The study will be conducted after meeting all the ethical requirements. The recruitment of participants will follow all the required ethical procedures. The recruitment of participants to the study will be based on voluntary and free consent. Individuals will not be forced to take part in the study. The privacy and confidentiality of all the participants will be protected. The participants will be fully briefed on the procedures and the implication of taking part in the research study before they become part of the study. The research study will be conducted after it has been approved by the Institutional Review Board.
Data collection methods
Data collection will be done electronically using open source data kits, and voice recording devices. Structured questionnaires will be used to collect quantitative data while guided open-ended questionnaires will be used to collect qualitative data. Confidentiality and privacy of the study participants will be ensured by referring to them using codes. The collected data will also be kept safe and confidential using encryption technique. The quality of data collected will be realized by ensuring that the recorded data is a true reflection of events, response, facts, and observations. The quality of data collection method plays a critical role in influencing the quality of data, and documents how the collected data provides evidence for such quality (Creswell, 2013).  Quality will be ensured through training of the researcher; conducting a pilot study; application of standardized protocols for capturing observations; verifying the consistency of response; routing and customizing questions; confirming the responses against previous answers where applicable and detecting the inadmissible response (Mertens, 2014). 
Data analysis
Quantitative data will be analyzed using descriptive and inferential statistics. Statistical software such as SPSS will be used in analyzing quantitative data to establish the statistical significance of the results. Qualitative data will be analyzed using thematic content analysis. Qualitative Data Analysis (QDA) will be used in the process of transforming qualitative data into some forms of explanation or interpretation of the situations or people under investigation. Interpretative philosophy is the basis of QDA. The data validity and reliability will be ensured by analyzing and evaluating the outcome of the project. The opinion of the experts in the health care sector concerning the outcome of the study will be sought to establish the validity and reliability of data and the result. Analysis of improvement will establish the reliability of the project.










References
Campbell, D. (2014). Millennials and What They Bring to the Manufacturing Table. American Staffing Association. Retrieved on 15 April 2017, from http://hiredynamics.com/wp-content/uploads/2015/01/2-4-14_MFRtech_Millennials-in-manufacturing.pdf.
Creswell, J. W. (2013). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications.
Mertens, D. M. (2014). Research and evaluation in education and psychology: Integrating diversity with quantitative, qualitative, and mixed methods. Sage publications.
Yilmaz, K. (2013). Comparison of quantitative and qualitative research traditions: Epistemological, theoretical, and methodological differences. European Journal of Education, 48(2), 311-325.

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