| Week 8: 3:00 pm Friday Week 8, July 21st (AEDT) |
| 30% |
| A written report |
| Maximum word count of 2000, excluding tables, figures, references, and Appendix (detailed requirements are provided in the “Word Limit” Section below) |
| Submission via Turnitin on Moodle course site |
Objective
This team assessment aims to test your ability to conceptualize and solve analytics problems, your skills in R programming, your knowledge of the ethical use of data, and your ability to provide business recommendations based on analytics results. You will form a data analytics team with your peers in this assignment. You are expected to analyze data using descriptive and predictive techniques. The learning content has been covered in the course up until the end of Week 7.
Description
In this team assessment, you must take the business scenario in the individual assessment further to generate actionable insights on improving sales and app satisfaction for ASAL. Recall that:
The online e-store Amazing Sports Australia Ltd (ASAL) sells a variety of branded and non-branded sports products, which have been broadly categorised into (i) Equipment, (ii) Apparel, and (iii) Footwear. The site has recently released a shopping mobile app but is concerned about whether it has effectively boosted sales and promoted its products. The management team seeks to understand customer spending patterns and behaviour with the ultimate objective of optimising app use and enhancing sales.
ASAL has updated the data set and collected additional data on variables. An updated data dictionary has been shared with you in a separate file.
ASAL requires you to:
- Form an analytics team to use descriptive and predictive analytics techniques to generate actionable insights on how to improve user sales and application satisfaction.
- Reflect on the feedback from your project and take it further to help ASAL predict the factors that influence a) user sales and b) application satisfaction.
- Suggest the ethical considerations related to the analysis and the use of data for enhancing sales and application satisfaction.
- Submit your findings as a written report by 3 pm July 21st (Friday) via Turnitin on Moodle.
How to Download Data
Download the team leader’s personalized data, using the link below and change z9999999 to your zID and access it by copying into R Studio
Note that each team will have a personalized data set. Hence, different results and recommendations may emerge across teams even when using the same analytics technique.
Guidance on Data Analysis
- Critically and collaboratively reflect on each team member’s feedback from their project and use them to develop your team project where applicable.
- Use descriptive analytics to identify the key factors that may impact a user’s sales and application satisfaction. Descriptive Analytics refers to statistics and visualization techniques. For example, a box plot and a bar chart are different techniques.
- Use predictive analytics to forecast the factors that influence future user sales and application satisfaction. Predictive Analytics refers to linear regression, logistic regression, and decision tree modelling techniques. For example, linear regression and logistic regression are two different modeling techniques. It would be best if you used the modelling techniques discussed in lectures and workshops (i.e., do not use modelling techniques beyond the scope of this course).
- For each modelling technique (e.g., linear regression, decision tree, etc.) you use, consider trying out several models using different independent variables to predict the outcome variable and present the “best” model in your report. To select a model to be the “best” out of your candidate models, you can assess it based on the model’s goodness of fit and its performance in predicting the outcome variable. You should use methods and criteria learned from this course to test the goodness of fit and its performance (i.e., do not use methods and criteria beyond the scope of this course).
- Develop coherent logic from your business issue identification to your variables and modeling techniques selection and your recommendations to ASAL.
- Explicitly state any key assumptions that impact your data analysis.
Requirements
- Business Issue Identification (10%)
- State business issues that your report seeks to address. Examples of business issues:
- What are the key factors associated with sales? How do these factors influence voluntary sales?
- State business issues that your report seeks to address. Examples of business issues:
- What are the key factors associated with application satisfaction? How do these factors influence users’ satisfaction with the application?
- Data Analysis (40%)
- Use appropriate descriptive analytics techniques and/or a relevant industry context about sales and application satisfaction to identify key variables for predictive analysis.
- Use predictive analytics modelling techniques to forecast how certain variables impact sales and application satisfaction.
- Justify the selection of variables and analytics techniques.
- Interpret analytics results.
- Business Recommendations (20%)
- Provide recommendations based on analytics results.
- Support recommendations based on established industry practices and/or academic references.
- Ethical Consideration and Suggestions (10%)
- Identify ethical issues about data collection, data analysis, and data communication.
- Provide suggestions to avoid and/or mitigate the issues.
- Supplementary reading:
o Consult Danish Design Centre’s Digital Ethics Compass to understand the nuances of data ethics in the context of digital products
- Project Management (10%)
- Follow USNW Guide to Group Work (must read) to participate in the team project.
- Develop and record a project management plan by specifying key milestones and each team member’s responsibilities.
- Nominate a team project lead to facilitate the collaboration.
- Reflect on team project management, for example, the issues impeding effective collaboration; how you would do differently for improvement if you had the time again (150 words maximum).
Note that if any issue emerges from the collaboration and requires the teaching team’s support, a team should report the issues to the teaching team as early as possible by involving all team members.
- Communication and Organization of Report (10%)
- Demonstrate proficiency in writing in English.
- Develop a logical structure to organize the sections of your report.
- Develop an executive summary using jargon-free language.
- Uses figures and/or tables to convey qualitative and quantitative information effectively and accurately.
- Use academic referencing in Harvard style. Refer to UNSW guideline
- Attach the codes of your R programming (not a screenshot) in the Appendix of your report.
Submission Instructions
The team lead or a designated team member needs to submit the written report with all required information via the Turnitin submission link on Moodle. Note that only one report from a group is required.
Your submission must be in a Word or pdf format, accompanied by a cover sheet (to be provided on Moodle). Please note that you need to nominate a team lead on the cover sheet by specifying their name and zID.
The appendix must have all relevant R codes. The codes should take the raw data file provided as the input and must be able to reproduce all analysis that is in the report.
Late Submission
- Late submission will incur a penalty of 5% per day or part thereof (including weekends) from the due date and time. An assessment will only be accepted after five days (120 hours) of the original deadline if special consideration has been approved. An assignment is considered late if the requested format, such as hard copy or electronic copy, has not been submitted on time or where the ‘wrong’ assignment has been submitted.
- No extensions will be granted except for serious illness, misadventure, or bereavement, which must be supported with documentary evidence. Requests for extensions must be made to the Course Convenor by email and be
accompanied by the appropriate documentation by 24 hours before the due date of the assignment. Students must apply for Special Consideration if this is not possible.
- Applications for Special Consideration must be submitted via myUNSW to be valid. Information on when and how to apply for Special Consideration can be found here. If your email asks to confirm receipt of an application, please be aware that we will only reply if we have not received your application.
- The Course Convenor is the only person who can approve a request for an extension. If you request an extension, the Course Convenor will email you the decision. Note: A request for an extension does not guarantee that you will be granted one.
Word Limit
Your report will be evaluated on its quality, and one dimension of the quality is expressing your ideas and analysis concisely. Hence, we suggest a maximum word count of 2000. Note that a penalty will not be applied if your report stays below 2200 words (10% leeway applied), excluding tables, figures, references, and Appendices.
Smarthinking English Support
“… an online writing support platform officially sanctioned by UNSW. Students can submit drafts of their writing to a Smarthinking tutor or connect to a Smarthinking tutor in a real-time session and receive comprehensive feedback on various writing areas”.
Smarthinking is available on the COMM1190 Moodle Site. Using the service, you can:
- Submit your drafts to a Smarthinking tutor for comprehensive feedback on your writing, typically within 24 hours; or
- Connect to a Smarthinking tutor in a live one-on-one session about writing.
- Receive comments on a variety of writing areas, including clarity of your ideas, grammar, organisation, etc.
- Use up to 2 hours on Smarthinking reviews.
UNSW Guide to Group Work
“This page will inform you about the nature of group work, what you should expect, and the expectations teachers have of you in group learning situations.” Furthermore, please refer to Modus Operandi next page.
1. Team formation
The students themselves form the teams. The size of the group is capped at five. Groups of six or above are not allowed under any circumstances. The tutor is responsible for reshuffling the group if there is an unexpected drop-out or for other reasons.
If the team ends up with two or three members, the team will automatically be granted an extension till Monday (i.e., one extra business day).
2. Team bonding
Once the team shall be finalised by the end of week 4, the students shall initiate a first exchange of contacts by email and alternative means of communication (e.g., WhatsApp or mobile phone number). If any team member fails to respond to their teammates within 24 hours, the remaining members can contact their respective tutors.
3. Team Leadership
The role of the team leader is to coordinate that all members are participating and communicating with each other regularly.
4. Team Meeting
All teams must conduct at least two meetings with an adequately set agenda at a mutually agreed time, the first at the beginning to discuss the task allocation and the expected milestones for deliverables, and the second at the end to fine- tune their work and bring them together.
5. Team Contract
A team contract, a.k.a: team charter, can be signed by all team members to ensure a formal agreement of allocated tasks, expected deadlines for task completion, and other relevant matters. The team charter shall be stapled as an appendix to the finalized assignment report as evidence of effective team project management.
6. Check-ins
At the end of every four days, the team leader should proceed with check-ins with the other team members to motivate them to complete the deliverables on time.
7. Logistic management
The teams can create a Gantt chart to plan and monitor the assessment activities. They can opt for any preferred forms of social media or traditional means of communication. Shared writing platforms-namely Google Docs or OneDrive, can foster real-time collaboration and easier tracking of members’ work in one place.
8. Peer review
At the end of each deliverable, each team member is expected to review and provide feedback on each other’s work to enhance the quality of the overall report. The peer assessment review can be reported to the Course convenor in the event of obvious unequal contribution-namely non-participation by a team member. Yet, individual members cannot use the unequal contribution statement to negotiate for more marks beyond the overall effects assigned to the report.
9. Tutor involvement
Your tutor will intervene if there are unresolved contentious issues as a matter of last resort, whereby all communication channels have failed to achieve harmony and civility among team members. Yet, teams should involve tutors as early as possible whenever there are unequal contribution issues or disputes.
Marking Rubric for Team Assessment
| Criteria & Weight | Fail (0% – 49%) | Pass (50% – 64%) | Credit (65%-74%) | Distinction (75%-84%) | High Distinction (85% – 100%) |
| Business Issue Identification (10%) | Does not clearly or correctly identify or define/explain an issue. | Identify and explain some key elements of a business issue(s) but do not cover all relevant aspects. | Identify and explain many key elements of a business issue(s) but misses some relevant aspects. | Identify and accurately explain all relevant, key aspects of a business issue(s). | Identify and accurately explain all relevant, key aspects of a business(s) and address its importance using industry examples. |
| Data Analysis (40%) | No relevant analytical technique was identified.No specific variables were identified.No logic between business issues, analytical techniques, and variable selection.The results of the model are mostly incorrectly interpreted. | Identify one predictive analytical technique for solving the business issue.Identify variables for each technique to be deployed.Attempt to present a logic between business issues, analytical techniques, and variable selection, but the reason is unclear.The results of the analytics model are somewhat correctly | Identify and explain 1 predictive analytical technique for solving the business issue.Use descriptive analytics techniques to identify the variables to be deployed for prediction.Attempt to present a logic between business issues, analytical techniques, and variable selection.The results of the analytics model are mostly correctly | Identify, explain, and justify 1 predictive analytical technique for solving the business issue.Use descriptive analytics techniques to identify, explain, and justify the variables to be deployed for prediction.Explicitly present a logic between business issues, analytical techniques, and variable selection. | Identify, explain, and justify 1 or 2 predictive analytical techniques for solving the business issue.Use descriptive analytics to identify, explain, and justify variables for deploying each technique. Justifications are sound and convincing.Explicitly present a coherent and clear logic between business issues, analytical techniques, and variable selection. |
| Criteria & Weight | Fail (0% – 49%) | Pass (50% – 64%) | Credit (65%-74%) | Distinction (75%-84%) | High Distinction (85% – 100%) |
| No R codes are included. | examined and interpreted. R codes are included and extensive errors are identified. | examined and interpreted. R codes are included, and some errors are identified. | The results of the analytics model performance and findings are mostly correctly examined and interpreted, supported by academic references.R codes are included, and errors are identified occasionally. | The reason is coherent and clear. The results of the analytics model performance and findings are correctly interpreted, critically examined, and supported by academic references. The model is parsimonious.R codes are included without errors. | |
| Business Recommendatio ns (20%) | Inadequate or no recommendati ons are provided. | Develop recommendations, but they may contain many weaknesses or limitations.Recommendations are inconsistently tied to some of the issues discussed. | Develop recommendations, but they may contain some weaknesses.Recommendations are consistently tied to each issue discussed. | Present insightful recommendations, well-supported by analysis.Recommendations are logically and consistently tied to each issue discussed. | Present insightful recommendations, well-supported by analysis, industry practices, and/or human resource management research.Recommendations are logically and consistently tied to each issue discussed, |
| Criteria & Weight | Fail (0% – 49%) | Pass (50% – 64%) | Credit (65%-74%) | Distinction (75%-84%) | High Distinction (85% – 100%) |
| accompanied by critical thinking. | |||||
| Ethical Considerations and Suggestions (10%) | No ethical issues are identified.No suggestions are provided. | two ethical issues are identified.Some issues do not show direct connections with the business context.Suggestions are provided but do not adequately address the issues identified. | two ethical issues are identified.Each ethical issue is connected with the business context using an example.Suggestions are provided but do not adequately address the issues identified. | three ethical issues are identified.Each ethical issue is connected with the business context using an example.Suggestions adequately address each issue identified. | three or more three ethical issues are identified.Each ethical issue is connected with the business context using an example.Suggestions adequately address each issue identified, supported by research or established industry practices. |
| Team Project Management (10%) | No description of how your work is divided.No reflection of your project is provided. | There is a discussion on how the group work went, but the debate is marginal.Reflections/sugges ted improvements are marginal or generic. | There is a discussion of how the group worked together and how the work could be improved.These reflections are of acceptable quality but could be more specific (too generic) or missing important aspects. | There is clear evidence of how your group worked together and how the work could be improved.The reflections are of specific and high quality.A graphic representation (e.g., table, Gannt | There is clear and detailed evidence of how your group worked together and how the work could be improved.The reflections are specific, highly quality, and include well-justified improvement intentions for future group work. |
| Criteria & Weight | Fail (0% – 49%) | Pass (50% – 64%) | Credit (65%-74%) | Distinction (75%-84%) | High Distinction (85% – 100%) |
| Chart) is supplied for group work breakdown. | A graphic representation (e.g., table, Gannt Chart) is supplied for group work breakdown. | ||||
| Communication and Organization of Report (10%) | Your writing is not professional in tone, and has major spelling and grammatical errors.Your written expression does not indicate a logic/flow between each essay section.Poor or unclear structure.Your sources have not been referenced, and/or there are excessive errors in | Some attempt has been made to use a professional tone and presentation in your writing, but there are some spelling and grammatical errors.You have endeavoured to provide logic/flow between each essay section.Attempt to a good structure but lack coherent flow between sections.Some sources are referenced throughout the essay, but there are errors in your referencing of sources. | Your writing is mostly professional in tone and presentation, but occasional spelling and/or grammatical errors exist.Your written expression indicates the logic/flow between each section of the essay.Good structure with organized headings.Most sources are referenced throughout the essay, with only minor errors in referencing.An executive summary is provided and | Your writing is professional in tone and presentation, with a few very minor spellings and/or grammatical errors.Your written expression strongly indicates the logic/flow between each section of the essay.Good structure with organized headings and coherent follow between sections.All sources are referenced throughout the essay with only minor errors in referencing. | Your writing is professional in tone and presented outstandingly with no spelling or grammatical errors.Your written expression provides a strong and coherent indication of the logic/flow between each essay section, enabling key arguments to develop fully.Good structure with organized headings and coherent follow between sections.All sources are referenced throughout the essay, and the |
| Criteria & Weight | Fail (0% – 49%) | Pass (50% – 64%) | Credit (65%-74%) | Distinction (75%-84%) | High Distinction (85% – 100%) |
| referencing in the essay. The word limit has not been adhered to.No executive summary is provided. | An executive summary is provided but missing key aspects of the report. | covers essential aspects of the report. | An executive summary is provided and covers essential aspects of the report using non- jargon language. | seeds are used very well, with no significant errors in referencing. A concise executive summary is provided and covers essential aspects of the report using jargon- free language. |
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