Rish_1_4000_Words_Research_Methods_for_Professional_Practice_JLS (1)

COURSEWORK ASSESSMENT SPECIFICATION Module Title: Research Methods for Professional Practice Module Number: LD7091 Module Tutor Name(s): Rose Fong Academic Year: 2023-24 % Weighting (to overall module): 20% Reflective CPD (continuous professional development) 20% Research Development Log 60% Project Proposal Coursework Title: Professional Practise and Research Project Proposal Table of Content Name LD 7091 1 | P a g e

Part A: Reflective Continuing Professional Development ................................................. 3 Past Achievements ......................................................................................................... 3 Personal SWOT Analysis ............................................................................................... 4 Strengths ..................................................................................................................... 4 Weaknesses ................................................................................................................ 5 Opportunities ............................................................................................................... 5 Threats ........................................................................................................................ 5 Future Development Plan ............................................................................................... 5 Conclusion ...................................................................................................................... 6 Part B: Learning Logs ........................................................................................................ 6 Part C: Research Proposal ................................................................................................ 8 Introduction ........................................................................................................................ 8 Research Overview ........................................................................................................ 8 Research Aim ................................................................................................................. 8 Research Objectives ...................................................................................................... 9 Research Questions ....................................................................................................... 9 Literature Review ............................................................................................................... 9 Chapter Overview ........................................................................................................... 9 Theoretical Background ................................................................................................. 9 Content-Based Recommendation Theory .................................................................. 9 User Engagement Theory ......................................................................................... 10 Preference Modelling and Decision Making Theory ................................................. 10 Empirical Background .................................................................................................. 10 Research Gap .............................................................................................................. 11 Methodology ................................................................................................................. 11 Research Philosophy ................................................................................................... 12 Research Approach ...................................................................................................... 12 Methodological Approach ............................................................................................. 13 Research Strategy ........................................................................................................ 13 Time Horizon ................................................................................................................ 13 Data Collection and Analysis ........................................................................................ 14 Research Gantt Chart .................................................................................................. 14 Conclusion .................................................................................................................... 14 Ethical Considerations .............................................................................................. 14 Name LD 7091 2 | P a g e

Part A: Reflective Continuing Professional Development Past Achievements Throughout my career, I have sharpened my skills in customer service, retail services, and, most importantly, my technical and computer roles. These roles have been instrumental in enabling me to develop the skills and a deeper understanding of the corporate world. In this case, I know how to develop the dissertation. The dissertation is closely intertwined with the skills and knowledge I have gained in my previous career endeavors. First, in June 2023, I worked as a Food and Beverage Assistant at C London, Bond Street in the United Kingdom, where I was tasked with maintaining hygiene and ensuring utter compliance with food handling standards. I was also tasked with facilitating a seamless customer experience and dealing with any customer complaints that could arise. Secondly, between May and July 2021, I worked as a network engineer at Wipro Bangalore, India. This is the job I felt that closely aligned with my career path. I truly enjoyed my work here. In this job, the main task was installing, configuring, and supporting the organization's firewall to strengthen the network security. I was also tasked with ensuring the network performance was viable for the organization's operations. Other tasks included IP address auditing and troubleshooting network problems. These were tasks that I did with zeal and passion. My other career endeavor was a job as a Retail Sales Associate at Walmart in Warangal, India. I worked flexibly at different customer access points, serving the customers. While at this job, I established a performance assessment metric for the sales teams and monitored issues while reporting to supervisors. I also trained new staff on the company's practices and operational techniques. These are the most significant career endeavors I have engaged in, and they have been cumulatively instrumental in shaping my current being. These achievements have also enabled me to develop a deeper interest in my career. The achievements will be vital in shaping the basis for my dissertation. Personal SWOT Analysis SWOT Analysis is a tool used to evaluate an individual’s strengths, weaknesses, Opportunities and Threats aimed at making several adjustments and leverage in their abilities to become a better individual. The figure below is a visualization of SWOT Analysis. Name LD 7091 4 | P a g e

Figure 1: SWOT Analysis Source: (Xmind Ltd. 2020) Strengths I have ample experience as a technical network manager, customer service provider, and retailer. I will leverage the technical network manager's experience in developing the documentary recommender system. The fact that I have engaged in network configuration and troubleshooting places me in a viable position to build the documentary recommender system. Furthermore, my experience as a customer service provider and retailer will be instrumental in enabling me to create a user-friendly documentary recommender system that is conscious of the complexity of different humans. Weaknesses One of my most significant weaknesses is that I have yet to work on developing any system that resembles the one I plan to build. If I had been in a job doing related tasks, I would have established the documentary recommender system easily. Name LD 7091 5 | P a g e

me to realize my various strengths and how I can leverage these strengths to attain my ambitions and life goals. Similarly, the reflection has taught me to work on my weaknesses without fail and watch my productivity scale to greater heights. I have also learned the importance of the future development plan. This action plan is a great tool for avoiding procrastination and laziness; it provides timely recommendations on what activity I should be doing at a particular moment. Part B: Learning Logs Activity of the Learning Log Skills and Knowledge Required Importance of the Learning Log Activity Reflections on the Learning Log Activity Coming up with the project topic Skills on how to come up with appropriate project topic. A project topic is an essential element of enabling researchers to base their research on previous research topics while addressing some changes made to the existing topics and providing a novel project topic. This has enabled me to understand the dynamics of coming up with a project topic, while avoiding the repetition of already existing project topics and fostering originality. Introduction to the Research Clear and precise introduction of the rationale of your project. This will enable the researcher to bring out a clear understanding of the research and prevent unnecessary assumptions. This has enabled me to clarify some vagueness associated with the project and building a sound understanding of the project by others. Establishing the Scope of the Project Understanding the extent to which the research will delve into. Establishing the scope of the study will enable the researcher to make fair estimates of different metrics of the research and make the necessary adjustments and arrangements before the This has enabled me to make logistical arrangements to make the research process seamless while ensuring that all key areas of the research are addressed without fail. Name LD 7091 7 | P a g e

research. Creating the Aims and Objectives of the Research This tests the ability to create SMART objectives for the research. Establishing the aims and objectives prior to the research allows the researcher to assess the existing research and question the validity of existing conclusions. This has enabled me to read widely and understand the flaws that exist with the previous researches. I have also managed to establish timely and proper aims and objectives of the study, by drawing insights from previous researches. Preparation of the Literature Review Skills of analysis and synthesis of information and referencing and citing knowledge are critical when building the literature review. This is important as it will enable the researcher to give proper credit to previous researchers whose work they have used in their own research. The establishment of the literature review allowed me to deepen my understanding of the topic of coding and software development, by drawing insights from the works of different authors. Establishing the Methodology Skills and knowledge of data collection methods is necessary when deciding the suitable and most appropriate methods of collecting data for this particular research. This is necessary to create a viable methodological approach that will ensure that the objectives of the research process are achieved seamlessly. This activity enabled me to choose a methodology that was suitable for me as the researcher and appropriate for the research, ensuring attainment of the objectives of the study. Analysis of Requirements Skills and knowledge on establishing the required resources and dynamics that must be met for the research process and the final system to be This will establish whether the system and the research process are bound to yield the appropriate research objectives and avoid unnecessary This enabled me to assess the rationale of my research method, highlighting the appropriateness of the study methods and made me hopeful to get the Name LD 7091 8 | P a g e

Research Aim The aim of this research is to develop a Documentary Recommender System that uses AI to suggest documentaries for users to watch based on their preferences and interests. Research Objectives 1. To build an algorithm that can be used to recommend documentaries for users based on their preferences and interests. 2. To study user behavior and preferences to establish behavior patterns to assist in building an algorithm that recommends documentaries to users to foster accurate recommendations of documentaries. 3. To develop the established algorithm to an application that users can use to get documentary recommendations. Research Questions 1. What viable algorithm can be used to develop a documentary recommender system for users based on their preferences and interests? 2. What are the behavior patterns that can be linked with users’ preferences that can be used in establishing the documentary recommender system? 3. How can the established algorithm be used to recommend documentaries for users? Literature Review Chapter Overview The researcher will study existing scientific works on developing algorithms for recommender systems. Google Scholar, ACM Digital Library, and IEEE Xplore will be used to gather scholarly sources. It will be done to employ sources that include prior innovations and information on human patterns, emphasizing how they may be used to construct recommender systems. To increase the credibility of the resources, the study will only employ papers and other resources from no later than 2013. This will emphasize advanced ideas and techniques useful in promoting research conduct. Theoretical Background Content-Based Recommendation Theory Content-Based Recommendation Theory focuses on analyzing user preferences to help in establishing patterns in the user’s disposition, and make content suggestions for the user (Javed et al. 2021). The Documentary Recommender system will significantly apply the dynamics of the Content-Based Recommendation Theory to help in establishing user patterns and hence help to establish an algorithm that uses these patterns to give recommendations to users on the documentaries they may watch. The figure below is a visualization of a simple Content-Based Recommendation Theory. Name LD 7091 10 | P a g e

Figure 2: Content Recommender Model Source: (Raghuwanshi and Pateriya 2018) The content recommender gives insights into user engagement and patterns, which will be leveraged to develop the documentary recommender system using a similar but more personalized approach and technique. User Engagement Theory This theory emphasizes the importance of having an understanding of the user’s cognitive disposition while developing patterns of their thinking style and perceptions as they interact with content (Lalmas et al. 2022). In developing the documentary recommender system, the user’s cognitive disposition and emotional pattern are critical in the recommendation process. This is because most documentaries are known to provoke emotions and apt information processing. Therefore, this theory would be necessary for establishing the documentary recommendation system as its main emphasis is the user and their role in the recommendation process. Preference Modelling and Decision Making Theory This theory explores an elaborate understanding of user's preferences and the aspects that define their decision-making process (Chai and Ngai 2020). This theory will expound on user preferences and establish users' various considerations before deciding to watch a certain documentary. This will ultimately make the documentary recommendation system a success as it will dwell on the user's preferences and their process of making decisions and choices. Empirical Background Content-based recommendation systems are only partially novel in the computing and internet space. Major advancements have been made to these systems, making them more user-friendly and personalized, improving their effectiveness in recommending content to users (Batmaz et al. 2019). These recommendation systems interact with the users by prompting them to highlight what they prefer and their interests. The Name LD 7091 11 | P a g e

reasons for the choices made while choosing the research methods. The figure below is a visualization of the research onion. Figure 3: The Research Onion Source: (AESA 2020) Research Philosophy This research will use a positivistic approach to analyze the existing recommendation systems. This will enable the researcher to acknowledge and appreciate the work already done to build recommendation systems. This will further enable the researcher to explore similar recommendation systems and establish how they can be effectively incorporated into the development of the documentary recommendation system. The other philosophical approach that the researcher would use is critical realism. This is because the research requires the use of actual user preferences, metrics that can be measured upon insights from the user. Research Approach An inductive approach is the most suitable endeavor for this research. It is necessary to understand that an inductive approach looks into the existing data and established theories to build up on a new theory. For the documentary recommender system project, the research will involve collection of data from the user engagement Name LD 7091 13 | P a g e

experience and establish patterns in the user interaction with the system. The inductive approach also calls for proper examination and analysis of existing theories in the development of a new theory or system. The inductive approach would also ensure that there is avoidance of mistakes that have previously been conducted in similar research projects. In this sense, the inductive approach is critically essential for use in this research project. Methodological Approach The research will mainly employ the quantitative approach. The quantitative approach allows researchers to measure and analyze different metrics necessary to conduct the research and then arrive at the conclusions (Bauer et al. 2021). The quantitative approach will also enable the researcher to leverage surveys and data on user preferences to establish patterns in user metadata, enabling the development of the appropriate algorithm for the documentary recommender system. The empirical research for this project will require immense insights from data collected from other recommender system projects. In this sense, there will be much quantitative analysis of the data to establish proper connections with other recommender systems and the documentary recommender system. However, qualitative analysis will also be involved, which will involve getting responses from users. There is a need to understand that different users' preferences vary depending on their interests and passions. In this case, the qualitative approach will ensure consideration of each user's passions and interests, allowing the researcher to understand different user preferences and, hence, structuring the algorithm to suit the needs of all users of the documentary recommender system. Furthermore, because the research will involve user interviews and reviews, it is valid to state that there will be an immense application of the qualitative approach. Following that, the research has used both the quantitative and qualitative approaches, which apply to this research project; it is sufficient to state that the research will incorporate mixed approaches to attain its methodological rationale for diverse data collection. Research Strategy The experimental strategy will be the most instrumental in this research project. This is because this project requires a procedural and controlled experiment involving the researcher collecting data to test the efficiency of the developed algorithms by considering the user experience. Additionally, user satisfaction with the recommendation made, which is the main aim of this research, will then be assessed. The correlation between user satisfaction and the recommendations made will then be used to establish a proper algorithm that will be used to make more accurate documentary recommendations for users. Time Horizon This layer of the research onion encompasses the time frame within which the research will be conducted. The layer is categorized into two: Cross-sectional and Longitudinal design. Cross-sectional research involves the researcher collecting data for the research over a very short and specific period and making conclusions from the data after analyzing it. On the other hand, the longitudinal section of the time horizon layer is a long-term research period that involves collecting data several times over a long Name LD 7091 14 | P a g e

Conclusion Ethical Considerations The manipulation of this research will demand considerations of rules and regulations that govern data privacy. It is necessary to understand that during the research, the participants will provide personal information about their preferences and interests, which need to be protected from blackmailers who may use these to extort the user. Therefore, data privacy and protection are top priorities for this research project. The documentary recommendation system, like the preexisting recommendation systems, may make inaccurate user recommendations. In this case, the researcher is supposed to address such possible troubles by offering disclaimers to the users before using the system. Legal Compliance The researcher is also supposed to ensure that the necessary licenses for conducting this research are obtained. This will ensure that the research is done seamlessly and with utter caution to all ethical standards for the entire research process. Social Considerations This system will not offer biases regarding the content that the user would like to watch. Recommendations made will, therefore, foster inclusivity and diversity. Recommender systems are known to enhance diversity by allowing users to access various content recommendations (Silveira et al. 2019). Furthermore, the recommendations will promote self-empowerment by recommending appropriate documentary recommendations and keeping the user informed. Professional Considerations The researcher is to observe all professional standards, creating a professional relationship with the research participants to allow them to give accurate research results. The researchers will also commit themselves to ensuring advancements in the user interface to enhance the system's accuracy. This research will also observe high compliance with academic integrity. Information obtained from other published sources will be cited to credit the original authors of the information. References Raghuwanshi S and Pateriya (2018). Recommendation Systems: techniques, challenges, application, and evaluation. In Advances in intelligent systems and computing (pp. 151–164). https://doi.org/10.1007/978-981-13-1595-4_12 Xmind Ltd. (2020). ‘ Personal SWOT analysis. Knowing where you are, and where to go.’ Xmind. https://xmind.app/blog/personal-swot-analysis-knowing-where-you-are-and- where-to-go/ BloG 132-Research Onion (2020) ‘ A Systematic Approach to Designing Research Methodology | | Welcome to AESA .’ https://www.aesanetwork.org/research-onion-a- systematic-approach-to-designing-research-methodology/ Javed U, Shaukat K, Hameed I, Iqbal F, Alam T and Luo S (2021). ‘A review of content- based and context-based recommendation systems.’ International Journal of Emerging Technologies in Learning (iJET) , 16 (3): pp.274-306. Name LD 7091 16 | P a g e

Lalmas M, O'Brien H and Yom-Tov E (2022). ‘ Measuring user engagement .’ Springer Nature. Chai J and Ngai E (2020). ‘Decision-making techniques in supplier selection: Recent accomplishments and what lies ahead.’ Expert Systems with Applications , 140 : p.112903. Batmaz Z., Yurekli A., Bilge A and Kaleli C (2019). ‘A review on deep learning for recommender systems: challenges and remedies.’ Artificial Intelligence Review , 52 : pp.1-37. Poongodi M, Vijayakumar V, Rawal B, Bhardwaj V, Agarwal T, Jain A, Ramanathan L and Sriram V (2019) ‘Recommendation model based on trust relations & user credibility.’ Journal of Intelligent & Fuzzy Systems , 36 (5): pp.4057-4064. Idrissi N and Zellou A (2020). ‘A systematic literature review of sparsity issues in recommender systems.’ Social Network Analysis and Mining , 10 : pp.1-23. Silveira T, Zhang M, Lin X, Liu Y and Ma S (2019). How good your recommender system is? A survey on evaluations in recommendation. International Journal of Machine Learning and Cybernetics , 10 , pp.813-831. Bauer G, Churchill S, Mahendran M, Walwyn C, Lizotte D and Villa-Rueda A (2021). Intersectionality in quantitative research: A systematic review of its emergence and applications of theory and methods. SSM-population health , 14 , p.100798. Name LD 7091 17 | P a g e