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CONTEXT: Innovation, design, and entrepreneurship are economic drivers promoting competition and growth throughout the world, many of which would not exist without wellestablished continuous improvement and new product development processes. Continuous improvement and new product development processes, such as the lean start-up methodology and design thinking, are well known and thriving in the business world due to the vast amount of empirically-grounded research. Unfortunately, educational institutions and researchers, alike, are lagging when it comes to these processes. Although the quantity of new and transformative degree offerings has increased substantially over the past several decades, limited research has been conducted to document key procedures associated with continuous improvement and the creation of new programs. This problem is only exacerbated when considering the role of innovation during emergency situations. PURPOSE OR GOAL: The purpose of this study is to show one approach (using photovoice) to understand how student voices can be incorporated into the continuous improvement and new program development process, specifically during emergency situations. In contrast to traditional passive data collection methods, such as a survey or focus groups, photovoice is an active data collection method where students engage in the information sharing and interpretation process at a deeper level. Using photovoice, researchers and practitioners, alike, can gain greater insights into the who, what, and how of educational effectiveness. The guiding research question is as follows: What are the factors which can influence the discovery, evaluation, and exploitation of continuous improvement and new program development during emergency situations? APPROACH OR METHODOLOGY/METHODS: This approach uses participatory research, wherein students act as researchers and actively participate in the data collection and analysis process. Under the umbrella of participatory research, the study uses photovoice for collecting qualitative data. The study was implemented in a software engineering course at a university located in the United Kingdom. Students responded to the photovoice prompts by supplying both picture and narrative. The prompts target student perceptions (positive and negative) with respect to blended learning perceptions, technology integration, and career preparedness. The qualitative data was analyzed for themes using NVivo.ACTUAL OR ANTICIPATED OUTCOMES: Analysis of the qualitative data led the researchers to identify three core themes related to the blended learning approach implemented as a result of the COVID-19 pandemic: (1) Institution -macro level, (2) Instruction -mezzo level, and (3) Student -micro level.CONCLUSIONS: The study concludes with recommendations for various higher education benefactors of the user generated data including administration, faculty, marketing, recruitment, advisors, and the students, themselves. It is intended for the overall recommendations to have a direct impact on imp...

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Current reproductive health statistics in Sri Lanka shows a rise in the rate of caesarean delivery rate; consistent with other countries. However, according to the Fortelesa declaration drown by the WHO states that the rate of caesarean deliveries should be kept within a range of 10-15%. Nevertheless, more and more expect ing mothers opt for the caesarean sections looking at the short term benefits it yields. This research aimed to structure the decision making involved and to identify the best method suited for delivery looking at Benefits, Costs and Risks. ANP was used as the methodology for this research, which revealed that Normal Delivery is mo re preferred at a rate of 72%.

Introduction: This paper involves assessing the most suitable insurance company for company X 1 using Multiple Criteria Decision Making (MCDM). This company is one of the biggest financial organizations and problems were identified with the existing process of insurance tender selection. The manual nature of the current process is very tedious and takes almost three months to complete and this increases the probability of error and also leads to employee dissatisfaction. Artifact: To provide a solution to this problem, several MCDM models including Analytical Hierarchy Process (AHP), Analytical Network Process (ANP), and Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) and Fuzzy Sets were researched to determine the best MCDM model for this scenario. After conducting a thorough research it was concluded that the best approach would be to use a hybrid methodology that combines AHP and TOPSIS. By using AHP to calculate the weights and using TOPSIS to determine the best alternative, accurate results can be obtained, as it combines the strengths of the two methodologies. In terms of time and complexity also this hybrid methodology doesn't involve a high level of complexity as in ANP and also with regard to the time factor, although the calculation of weights may require some time, using TOPSIS the best alternative can be determined relatively fast. Methodology: To validate and verify the quality and to ensure that the system worked as intended, several testing strategies such as User Acceptance testing and Accuracy testing was used. The samples used for these testing methods were the staff of the insurance department in company X. * Corresponding author 1 The name of the company cannot be disclosed due to a non-disclosure agreement between the researchers and the organization.