In an exponentially changing world, higher education needs to adapt and evolve to remain competitive, and provide students with a stimulating learning environment that helps them develop the required...

In an exponentially changing world, higher education needs to adapt and evolve to remain competitive, and provide students with a stimulating learning environment that helps them develop the required skills and competencies.
For this reason, you will help the management of the Business School identify ways tosupport students learning experience and, hence, improve their outcome, byinvestigating only oneof the following topics which will act as abasis for your assessment:

1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

Accessibility to academic learning resources. Awareness of career choices.
Blockchain, Metaverse and Web 3.0 technologies. Culture of diversity and inclusivity.

Gamification in learning and education.
Mobile phone Apps.
Modes of learning, e.g. online, onsite, hybrid, etc. Pandemic, i.e. COVID, lockdowns, vaccine, passport.
Social media, e.g. TikTok, Facebook, Twitter, etc.
Student support through Coaching, Mentoring and Tutoring.

1 Assessment Brief Read this assessment brief carefully, it tells you how you are going to be assessed, how to submit your assessment on-time and how (and when) you’ll receive your marks and feedback. Module Code BAE_4_DDM Module Title Data for Decision Making Lecturer Haider Bilal % of Module Mark CW (100%) Distributed 24/01/2022 Submission Method Submit online via this Module’s Moodle site Submission Deadline 16/05/2022 and 5 pm Release of Feedback Feedback will be available online from 06/06/2022 Release of Marks Provisional marks will be available in the Gradebook on Moodle from 06/06/2022 Assessment: This module will be based on one component which will be 100% Coursework assessed. Summative Assessment: In an exponentially changing world, higher education needs to adapt and evolve to remain competitive, and provide students with a stimulating learning environment that helps them develop the required skills and competencies. For this reason, you will help the management of the Business School identify ways to support students learning experience and, hence, improve their outcome, by investigating only one of the following topics which will act as a basis for your assessment: 1. Accessibility to academic learning resources. 2. Awareness of career choices. 3. Blockchain, Metaverse and Web 3.0 technologies. 4. Culture of diversity and inclusivity. 5. Gamification in learning and education. 6. Mobile phone Apps. 7. Modes of learning, e.g. online, onsite, hybrid, etc. 8. Pandemic, i.e. COVID, lockdowns, vaccine, passport. 9. Social media, e.g. TikTok, Facebook, Twitter, etc. 10. Student support through Coaching, Mentoring and Tutoring. 2 Based on your assumptions/claims, you are required to design and conduct a survey to test students’ perception of your chosen topic and how it could impact their learning. The main goal of the assessment is to present the findings of your research to the School’s management to help them make informed decisions about possible changes that that they might need to implement to improve students’ learning experience and hence their outcome. You will need to prepare a portfolio, using MS Word – 1,500 words (+/-10%) plus appendices. The portfolio must address the following 4 objectives:  Conducting a survey and collecting the data.  Analysing the data using Excel.  Visualising and interpreting the data.  Reflecting on the used assumptions and techniques. Requirements Evidenced by research: 1. Aim of the report and the student’s assumptions and/or claims 5 marks 2. Conducting the survey & data collection (Appendix A & B) 15 marks 3. Data analysis using Excel/Python (Appendix C) 15 marks 4. Data representation and Interpretation (Appendix D) 10 marks 5. Communicating results & conclusions to School’s management 10 marks 6. Ethical aspect of using data 5 marks 7. Presentation (Cover page, content table, sections, word count & Images) 5 marks 8. References 5 marks The report must include appendices containing the following: Appendix A – Designed questionnaire and a sample 5 Marks Appendix B - Pre-processing spreadsheet 5 marks Appendix C – Analysed data spreadsheet 10 marks Appendix D – Visualised and interpreted data 10 marks Students will need to apply concepts and technical skills learnt in lectures and workshops and develop analytical and critical skills in the context of data-driven decision making. The report must have references which will need to be listed at the end. If you are not sure how to do this you should check the information about LSBU’s Harvard Referencing available on the Moodle site. To submit the coursework, students must upload their individual report, as a word file, through the Report Submission link before 5 pm of Monday the 16th of May 2022. Important Note: TurnItIn will be enabled and will check for plagiarism. Copying someone else’s work, copying chunks of text directly out of a book or cutting and pasting from web sources is plagiarism and will be treated as an assessment offence by the university. In order to pass this module, students must achieve a minimum mark of 40%. In the event that a student does not achieve the pass mark, another assessment will be required. Formative Assessment: 3 Formative feedback will be given during workshop sessions using real life business cases and practical activities. Feedback to students will be provided as they work during their sessions, to support the development of their formative assessments. This will involve:  In‐class questioning and quizzes during the lectures.  Practical business exercises, discussions and online quizzes during the workshops.  Questions and self‐evaluation during the workshop.  Using a timeline for the portfolio which will include feedback on each of the four outputs: 1. Portfolio Output 1: Questionnaire and raw data – In week 6 2. Portfolio Output 2: Analysing the data using Spreadsheets – In week 8 3. Portfolio Output 3: Business report interpreting the data – In week 10 4. Portfolio Output 4: Reflection on the used assumptions & techniques – In week 1 Assessment Details: Type: Portfolio (MS Word) Resources: Background reading and resources Word Count: 1500 words (+/‐10%) + 4 Appendices Presentation:  Work must be referenced, and a bibliography provided.  Work must be submitted as a Word document (.doc/docx).  Course work must be submitted using Calibri font size 11.  Your student number must appear at the front of the coursework. Your name must not be on your coursework. Referencing: Harvard Referencing should be used, see your Library Subject Guide for guides and tips on referencing. Regulations: Make sure you understand the University Regulations on expected academic practice and academic misconduct. Note in particular:  Your work must be your own. Markers will be attentive to both the plausibility of the sources provided as well as the consistency and approach to writing of the work. Simply, if you do the research and reading, and then write it up on your own, giving the reference to sources, you will approach the work in the appropriate way and will cause not give markers reason to question the authenticity of the work.  All quotations must be credited and properly referenced. Paraphrasing is still regarded as plagiarism if you fail to acknowledge the source for the ideas being expressed. TURNITIN: When you upload your work to the Moodle site it will be checked by anti‐plagiarism software. https://libguides.lsbu.ac.uk/subjects/home http://www.lsbu.ac.uk/__data/assets/pdf_file/0008/84347/academic-regulations.pdf 4 Learning Outcomes This assessment will fully assess the following 5 learning outcomes for this module:  Summarise numerical data in a variety of graphical forms.  Differentiate between the various analytical techniques for solving business problems.  Illustrate the importance of stating assumptions.  Manipulate data using Excel.  Interpret data in order to develop and test claims. Assessment Criteria and Weighting LSBU marking criteria have been developed to help tutors give you clear and helpful feedback on your work. They will be applied to your work to help you understand what you have accomplished, how any mark given was arrived at, and how you can improve your work in future. Criteria Grades Report (1,500 words): 1. Aim of the report and the student’s assumptions and/or claims. 2. Conducting the survey & data collection. 3. Data analysis using Excel/Python. 4. Data representation and Interpretation. 5. Communicating results & conclusions to School’s management. 6. Ethical aspect of using data. /5 /15 /15 /10 /10 /5 Appendices (4 Outputs): Appendix A – Designed questionnaire and a sample. Appendix B - Pre-processing spreadsheet. Appendix C – Analysed data spreadsheet. Appendix D – Visualised and interpreted data. /5 /5 /10 /10 Presentation, Structure & References: 7. Cover page; content table; sections; word count; & images/charts/tables/etc. 8. References & in-text citations. /5 /5 Feedback: Marker: Date: Mark: How to get help We will discuss this Assessment Brief in class. However, if you have related questions, please contact me Haider Bilal ([email protected]) as soon as possible. mailto:[email protected] 5 Resources Core Reading: 1. Evans, J. R. (2021). Business Analytics, Global Edition. United Kingdom: Pearson Higher Education & Professional Group. 2. Priyadarsini, K., Poongodi, B., Latha, A., Jaisankar, S. (2017). Business Statistics: Workbook Using Excel. India: Laxmi Publications. 3. Sharda, R., Delen, D., Turban, E., Liang, T. (2018). Business Intelligence, Analytics, and Data Science: A Managerial Perspective. United Kingdom: Pearson. 4. Szabat, K. A., Stephan, D., Levine, D. M. (2020). Business Statistics: A First Course. United Kingdom: Pearson. 5. Sharpe, N.D., De Veaux, R.D., Velleman, P.F. (2022). Business Statistics. 4th edition, New York: Pearson. Education International. 6. Szabat, K. A., Berenson, M. L., Stephan, D., Levine, D. M. (2019). Basic Business Statistics, Global Edition. United Kingdom: Pearson. Optional Reading: 1. Camm, J. D., Fry, M. J., Cochran, J. J., Ohlmann, J. W. (2021). Business Analytics. United States: Cengage Learning. 2. Favero, L. P., Belfiore, P. (2019). Data Science for Business and Decision Making. United Kingdom: Elsevier Science. 3. Jackson, T. W., Lockwood,