Critical Analysis of Research Design and Data Collection

In Brief

Research design talks about the overall strategy that you choose to logically integrate the various elements of your research so to make sure that you deal with the research issues efficiently.
Data collection for your research has two parts – P rimary D ata C ollection and S econdary D ata C ollection.
Primary data collection can be done from various sources like workplace, interview, questionnaires, and expert opinion.
Secondary data collection involves literature review, reports etc.

The methodology of research is the path through which researchers are required to conduct their research. It demonstrates the direction along which these researchers formulate their questions and goal and present their result from the data collected during the time of analysis. In this article, we should objectively examine the pieces of the entire cycle of study design and data collection.

Research design

The analysis architecture aims to contain an appropriate structure for a review. The choice you make with respect to the research approach is a crucial decision in the research design process as it says how related data can be available for a study; however, the process of research design engages a number of correlated decisions (Reay et al., 2019).

This report also uses a concise test method to focus on the impact of the workplace protection and risk control program on the fitness, welfare, and property harm of workers for chosen industrial sectors. Descriptive research shows an precise profile of individuals or events. This F ramework G ives R esearcher’s a human, organizational, and industry-oriented viewpoint a profile of defined related aspects of the phenomena of interest. This research design allowed the researchers to grab data from a broad range of respondents on the effect of protection and health on Ethiopian manufacturing industries. And this helped evaluate the feedback gathered on how it impacts the occupational protection and wellbeing of the manufacturing sectors.

Data collection methods

The data collection process is based on the fundamental techniques including collections of secondary and primary data, focused on both qualitative and quantitative data as defined in the previous section. You can take help of the Research D ata C ollection S ervice.

Primary data collection methods

The key origins of primary data are both qualitative and quantitative (Corti et al., 2019). The qualitative sources are field study, questioning, and casual conversations, whereas those of quantitative data sources are sample questionnaires and interview queries. Primary data collection PhD Research is vital to your research.

Workplace site observation data collection

Observation is a significant part of science. It is closely related to data collection, so there are various forms for this: reports, archival documents, interviews, direct findings, group findings. Observational research findings are strong data because the researcher can gather depth of information on a particular behavior (Gregory et al., 2019). The researchers used observation method as a means to gather knowledge and details before the design of the questionnaire and even after work. Workplace data collection is one of the Best Primary data collection. In the sample fields, the researcher made over 20 basic findings of the manufacturing sectors. It found a deeper understanding of the working environment and the various sections within the production system and OSH practices during the observations.

Data collection through interview

In-depth qualitative interview with people deemed to be particularly knowledgeable about the topic of interest. Usually, the semi-structured interview is conducted in a face-to-face setting that lets the researcher to look for new insights, ask questions, and evaluate events from different angles (Baillie, 2019). It allows the researcher know the depth of dominant factors and aftermaths of the present work environment. It has created incentives to optimize attempts to gather data and to analyze complex programs or processes. You can use it when as a researcher; you face limitations of published document or want to triangulate the data obtained from other sources of primary and secondary data.

Interview data collection is one of the most sought after Methodology Primary Data Collection .The benefit of applying interviews as a tool is that it lets respondents raise issues that may not have been expected by the interviewer. The accompanying researcher performed all interviews with staff, managers, and technicians on a face-to-face basis at the workplace.

Data collection through questionnaires

Questionnaires are the key method for collecting primary knowledge in functional testing, provided that the researcher may agree on the questionnaire and the types of questions to be asked.

In this thesis, each respondent is asked to answer an identical list of mixed questions so that bias was avoided. Initially, the questionnaire design was coded and mixed up based on uniform structures from specific topics. The questionnaire, therefore, produced valuable data that was necessary to achieve the goals of the dissertation.

Data obtained from experts’ opinion

You can also get data from the expert’s opinion on the knowledge, management, group effort, and technology use, including their sub-factors, being compared. The resultant data was used for OSH’s prioritization and decision-making, improving factor priorities (Kaverzneva et al., 2019). The variables prioritization was done using Saaty scales and then converted to Fuzzy set values gathered from previous work using a triangular fuzzy range.

Secondary data collection methods

The secondary data relates to data where anyone other than the consumer received (Stobaugh et al., 2019). This source of data gives insights into the current state-of-the-art method research area. It also creates some kind of work void where the researcher wants to fill. Such secondary sources of data may be internal and external sources of knowledge and may span a number of fields.

Literature/desk review and industry papers and reports: The researcher conducted excessive document review and company reports in both online and offline modes to attain the goals of the dissertation. From an analytical point of view, literature reviews should be interpreted as an examination of material, where quantitative and qualitative elements are combined in order to determine both systemic and quality parameters.

A L iterature R eview was carried out using information references such as MEDLINE; Emerald; Taylor and Francis publications; EMBASE ; PsycINFO; Sociological Abstracts; Papers on Injury Prevention; US Labour Statistics, European Safety and Health Information; ABI Inform; Market Source Premier; The search strategy focused on articles or reports measuring one or more of the dimensions within the OSH model framework for research. This quest strategy was focused on a structure and measurement filter strategy established by the community Collection of Health Measurement Instruments (COSMIN) Consensus-based Criteria. Unrelated papers to the study model and priorities were omitted dependent on sampling. Prior to selection, the reviewer (principal investigator) checked a collection of over 2000 papers, blogs, studies, and recommendations to decide if they would be considered for further consideration or dismissal. Discrepancies were thoroughly identified and resolved before more than 300 articles began review of the main group. After deleting the title-based papers, keywords, and summary, the remaining publications were checked in-depth, and the knowledge was collected on the instrument used to determine the study interest aspect. A full list of things was then collated within each target or purpose of the study and checked to find any missed objects.

Conclusion

Both Research design and data collection play crucial roles in research methodology. Our discussion has critically analyzed both the aspects and we hope that it will be of some help to the future researchers.

Reference

Baillie, L. (2019). Exchanging focus groups for individual interviews during qualitative data collection: a discussion. Nurse researcher. [Online]. 27 (2). Available from: http://oro.open.ac.uk/56539/.
Corti, L., Van den Eynden, V., Bishop, L. & Woollard, M. (2019). Managing and sharing research data: a guide to good practice. [Online]. SAGE Publications Limited. Available from: https://books.google.com/books?hl=en&lr=&id=PkSxDwAAQBAJ&oi=fnd&pg=PP1&dq=Corti,+L.,+Van+den+Eynden,+V.,+Bishop,+L.+and+Woollard,+M.,+2019.+Managing+and+sharing+research+data:+a+guide+to+good+practice.+SAGE+Publications+Limited&ots=xZPrhphJ0_&sig=zTj4JTLeKqbLzYuuXH2Pp9FYQII.
Gregory, K., Groth, P., Cousijn, H., Scharnhorst, A. & Wyatt, S. (2019). Searching data: A review of observational data retrieval practices in selected disciplines. Journal of the Association for Information Science and Technology. [Online]. 70 (5). pp. 419–432. Available from: https://asistdl.onlinelibrary.wiley.com/doi/abs/10.1002/asi.24165.
Kaverzneva, T., Rumyantseva, N., Uljanov, A. & Belina, N. (2019). Use of the logical-statistical model as a procedure for assessing occupational risks in the OSH management. In: IOP Conference Series: Materials Science and Engineering. [Online]. 2019, IOP Publishing, pp. 12091. Available from: https://iopscience.iop.org/article/10.1088/1757-899X/666/1/012091/meta.
Reay, J.L., van Schaik, P. & Wilson, C.J. (2019). A systematic review of research investigating the physiological and psychological effects of combining Ginkgo biloba and Panax ginseng into a single treatment in humans: Implications for research design and analysis. Brain and behavior. [Online]. 9 (3). pp. e01217. Available from: https://onlinelibrary.wiley.com/doi/abs/10.1002/brb3.1217.
Stobaugh, H.C., Mayberry, A., McGrath, M., Bahwere, P., Zagre, N.M., Manary, M.J., Black, R. & Lelijveld, N. (2019). Relapse after severe acute malnutrition: A systematic literature review and secondary data analysis. Maternal & child nutrition. [Online]. 15 (2). pp. e12702. Available from: https://onlinelibrary.wiley.com/doi/abs/10.1111/mcn.12702.