Consider a topic in economics and finance such as empirical analysis of Value-at-Risk, back-testing and its significance in financial markets. Extensive discussion of the topic will require identification of the research problem which in this case is that Value-at-Risk model estimates are subject to errors; hence back-testing is essential (Bellini et al., 2017). Literature research on the topic would basically revolve around the origin of VaR, its significance, methods of VaR measurement, back-testing methods, and limitations of the estimate. A suitable hypothesis on the topic would be best described through comparing effectiveness of VaR compared to other methods of measuring investment risk in financial markets, such as shortfall probabilities. Thus, the relevant null hypothesis would be; there is a significant difference in the risk estimates between VaR model and shortfall probability model. The design of the research would then follow this structure: topic identification, problem statement, significance of the research, literature review, data collection, analysis, discussion and conclusion. Use of official data from the London Stock market on three companies would suffice for the research topic. The companies are chosen on convenience. Hypothesis testing will be done using ANOVA because the independent variables are many. Data analysis, discussion, and conclusion of the research will entirely be based on the work covered. Internal validity will be maintained through strict monitoring of variables such that variables selected strictly affect the topic of study. Selection of companies would be based on the market cap size such that three categories exist; large cap size, medium cap size, and small cap size. A quasi experimental design would be the most suitable approach for this study because the study does not necessarily require randomization. Additionally, this research is conducted on data collected over a long period of time, hence making it a longitudinal research: quasi would work best.
Triangular design uses different complementary data on a single topic with the purpose of understanding a research problem better whereas embedded design uses one data set to provide support to a study based on another type of data. On the other hand, explanatory design uses qualitative data to explain quantitative data. Researchers would implement a mixed-methods approach due to advantages that are realized while using the method. Combining both qualitative and quantitative research helps offset weaknesses portrayed in each method while maximizing on the strengths. Additionally, the research problem is better understood and comprehended while using both qualitative and quantitative methods.
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Action research does not need training of a researcher as compared to formal research. The knowledge acquired in action research is usually applied to a specific situation while that gained from formal research is applied generally for most situations. While action research uses secondary sources of data, formal research utilizes primary sources of data. Last, action research deals with current problems while formal research only reviews past research. Researchers choose action research since it is focused on real-time problems and extensively applies results to the targeted problem.
Article Summary
Action Research Design
The purpose of the study was to describe major elements of a National Academy Foundation of Information Technology and the style in which implementation to make students ready for the future after school and their careers is done. The research questions of the study are focused on the primary features of a high-standard IT academy and answering the question, ‘how does a quality academy prepare students to be ready for their careers and the future.’ (Fletcher et al., 2018)
Summation of Research Literature
There has been literature on curriculum integration covered by various authors such as Hernandez-Gantez, Fletcher, and Drake. Hernandez based his study on integration of the curriculum from the lowest integrable parts to the highest integrable parts. Fletcher et al., focused their work on how implementation of curriculum integration would be of greater benefits to career development. Their work insisted that technical education should be separated from core subjects. Drake et al., also focused on the same topic as Hernandez-Gantez in the sense that curriculum integration can be best implemented from the least integrative and the most integrative.
Method for Collecting and Analyzing Data
The research utilized a qualitative case study in finding information on implementation of the career academy model. School personnel were instrumental in providing required information to answer the research questions. A five-day visit to the site enabled data collection through audio-recorded interviews with school administrators, IT teachers, and the board members. Data analysis was conducted by focusing on thematic content analysis to determine factors that influence implementation of curriculum developments in career academy. Repetitive themes in the curricula are then identified. Strategies used in implementation of units spotted were then analyzed, after which synthesis of the themes was done to narrow on the exact perspectives of the interviewees.
Results and Conclusion
The study found out that implementation of STEM is essential in preparing students for their future and careers. The best way of preparation of students for their careers entails shifting of teaching roles such that the students can be exposed to a variety of situations. The study recommended a balanced curriculum whereby the learners also embrace long-term projects which cut across several topics and field in the curriculum. Such type of learning gives learners a wide experience hence preparing them for their future. A culture of collaboration between students and teachers in framing the curriculum is another recommendation that would better learning processes and improve preparation of students for their careers.
References
Bellini, F., Negri, I., & Pyatkova, M. (2017). Backtesting VaR and Expectiles with Realized Scores.
Fletcher, C., Warren, N., and Hernandez-Gantez, V. (2018). Preparing High School Students for a Changing World: College, Career, and Future Ready Learners. Career and Technical Education Research, 43(1), p.77.
