COMM1190 Assessment 2: Team Report
Week 8: 3:00 pm Thursday (AEDT)
30%
A written report
Maximum of 2000 words, excluding references, figures, tables, and appendix.
Via Turnitin on Moodle course site
Objective
In this team assignment, you will play the role of a team of junior consultants for the
firm Insight Bridge Consulting. You have been asked to continue your work on the data
analysis project for the e-commerce website, The Mobile Hub.
Recall that the Mobile Hub is a technology retailer that sells a range of consumer
electronic products, including smartphones, tablets and accessories. The site has
recently launched a new mobile app, but downloads and sales have been lower than
expected. Previously, The Mobile Hub hired Insight Bridge Consulting to help them
analyse a dataset of user behaviour and spending patterns in order to understand user
behaviour to optimise the app and improve sales.
The Mobile Hub has re-engaged Insight Bridge Consulting because the firm is trying
to be bought by E-Electronics Central. E-Electronics Central is a similar online retailer
to The Mobile Hub that sells related products such as audio equipment, cameras, and
gaming devices. E-Electronics also owns an online technology support provider called
Tech Support Central, which specialises in providing remote technical support and
troubleshooting services for a wide range of technology products. E-Electronics
Central wants to purchase The Mobile Hub for two reasons:
1. To expand its technology offerings into smartphones and tablets, which Tech
Support Central currently services; and
2. To gain access to The Mobile Hubs app, since E-Electronics Central currently
makes all sales through their online website.
However, E-Electronics Central is concerned about the Application Satisfaction of The
Mobile Hub.
As a result, The Mobile Hub wants an analysis that features descriptive and predictive
analytics techniques to generate actionable insights on how they can improve user’s
application satisfaction before entering negotiation with E-Electronics Central.
To help with the analysis, the company has provided Insight Bridge Consulting with
some clarification regarding the previous data: They clarified that “rural” in C_Region
refers to regional and that App_E-mailCommunication is about The Mobile Hub
contacting consumers and not the other way around. Moreover, The Mobile Hub has
also provided Insight Bridge Consulting with additional data:
1. C_Number_of_Orders – The number of orders been placed by the customer
using the app.
2. App_SatisfactionRating – A rating out of 100 in terms of satisfaction. The values
L, M, and H were determined by these ratings. Anyone with a rating above 75
was assigned an H by the mobile hubs IT team, anyone with a rating between
50 and 74 provided a rating of M, and anyone with a rating 49 or below was
given a rating of L. As App_SatisfactionRating has more information than the
categories L, M, and H, The Mobile Hub has dictated that the continuous
variable rating measure should be the focus of the app satisfaction analysis.
3. App_SharesWithFriends – Similar to App_SatisfcationRating, The Mobile Hub
also has data on the number of times a customer has shared content from the
app with a friend through a messenger service. They have replaced the
previous variable with numerical data on the number of shares.
4. App_Deleted – Whether or not the customer had previously deleted the app.
5. App_Deleted_Readded – Whether or not the customer had previously deleted
the app and re-added the app to their device.
6. App_ConsumerE-mailFirm – Whether or not the customer has e-mailed the
firm.
Guidance on Data Analysis:
Note: the dataset and the data dictionary will be provided to you separately.
• Critically and collaboratively reflect on the feedback that each team member has
received from their individual 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 app
satisfaction. Descriptive Analytics refers to statistics and visualization techniques.
For example, a box plot and a bar chart are two different techniques.
• Use predictive analytics to diagnose and/or forecast factors that influence users’
app 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. You
should use 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 goodness of fit of a model 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 modelling techniques selection, and your recommendations to The Mobile
Hub.
• Explicitly state any key assumptions that impact your data analysis.
Requirements:
Project Management (10%). Follow USNW Guide to Group Work (must read) to
participate in the team project. Develop a project management plan and record it 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 in 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.
Problem Analysis (60%). Identify business problems, issues, relevant questions. Apply
rigorous analysis, appropriate frameworks, tools, and standards to develop and/or
evaluate data.
Quality of Conclusions and Recommendations (20%). Develop well-reasoned,
appropriate conclusions or solutions.
Communication and organisation (10%). Uses language to convey ideas and
information effectively and accurately. Report should professionally presented.
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.
5% of the marks available for the assessment will be deducted for this assessment if you
do not submit a fully completed and signed cover page.
Word Limit
Your report will be evaluated on its quality and one dimension of the quality is being able
to express 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 Appendix. Otherwise, 5% of
the marks available for the assessment will be deducted for every 100 words over the
word limit (after the 10% leeway is applied).
Late Submission Penalties
1. Late submission will incur a penalty of 5% per day or part thereof (including
weekends) from the due date and time. An assessment will not be accepted
after 5 days (120 hours) of the original deadline unless 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.
2. No extensions will be granted except in the case of serious illness,
misadventure, or bereavement, which must be supported with documentary
evidence. Requests for extensions must be made to the Lecturer-in-charge by
email and be accompanied by the appropriate documentation no later than 24
hours before the due date of the assignment. In circumstances where this is not
possible, students must apply for Special Consideration.
3. The Course Convenor is the only person who can approve a request for an
extension. If you do make a request for an extension, the Lecturer in Charge
will email you and the course convener with the decision. Note: A request for
an extension does not guarantee that you will be granted one.
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 a variety of writing
areas”. https://www.student.unsw.edu.au/smarthinking.
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, about what you should expect
and the expectations teachers have of you in group learning situations.” Access via
https://www.student.unsw.edu.au/groupwork
Groups must plan, schedule and conduct activities in due time. Once groups are formed,
the teams should create and sign up for a teamwork contract that outlines the terms of
engagement. Please refer to the resources presented in the link above. Groups must meet
regularly (at least once per week) while the assignment is being undertaken and keep a
record (diaries, meeting minutes) of such meetings. The groups must ensure that all
members are involved in completing the assignment. The work is to be divided equally
among the group members. All group-related project management work should be done
using a suitable tool such as Trello, Microsoft Teams or Microsoft Planner.
All group members are expected to work diligently. Group members should contribute in
a valuable and constructive way to the teamwork. Deadlines should be kept, and work
should be delivered at a professional standard. If problems emerge in your group, then
these problems should, in the first instance, openly be discussed in the group (different
members might have different views), and resolutions should be agreed on. If internal
arrangements repeatedly fail to remedy the situation, then you should bring the issues to
the attention of the LIC.
The LIC/ACC may call a group meeting in which each group member will be asked to
describe their input into the assignment and provide supporting documentation of this
effort using individual diary, group diary, meeting notes, emails.
Note: non-university platforms such as Facebook messages, texts, Whatsapp Messages
will not be considered. If group members are found to be making inadequate effort or
delivering poor quality, then they will be counselled to improve their effort. If sufficient
improvement is not made despite group efforts and LIC interventions, the mark of
underperforming group member(s) may be moderated to reflect the relative lower input
into the assignment.
Marking Rubric for Individual Assessment
Criteria
High Distinction
(85%-100%)
Distinction
(75%-84%)
Credit
(65%-74%)
Pass
(50%-64%)
No Bueno
(0%-49%)
Team Project
Management
(10%)
There is clear and detailed
evidence on how your
group worked together and
how the work could be
improved.
The reflections are specific,
of high quality, and include
well-justified improvement
intentions for future group
work.
A graphic representation
(e.g., table, Gannt Chart) is
supplied for group work
breakdown.
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 Chart) is
supplied for group work
breakdown.
There is a discussion of
how the group work worked
together and how the work
could be improved.
These reflections are of
acceptable quality but
could be more specific (too
generic) or the reflections
are missing important
aspects.
There is a discussion on
how the group work went
but the discussion is
marginal.
Reflections/suggested
improvements are marginal
or generic.
No description of how your
work is divided.
No reflection of your project
is provided.
Problem Analysis
(60%)
Demonstrates a thorough
understanding of the
business problem or issue,
identifies relevant
questions and uses
appropriate frameworks,
tools, and standards to
develop and evaluate data.
Explicitly presents a
coherent and clear logic
between business issues,
analytical techniques, and
variable selection.
The justification is sound
and convincing. Skillfully
explores data
comprehensively with
compelling explanations of
the issues identified.
Demonstrates a good
understanding of the
business problem or issue,
identifies relevant
questions, and applies
appropriate frameworks,
tools, and standards to
develop. Explicitly presents
a coherent and clear logic
between business issues,
analytical techniques, and
variable selection.
The justification is
convincing. Explores data
comprehensively with
explanations of the issues
identified.
Demonstrates a
satisfactory understanding
of the business problem or
issue, identifies some
relevant questions, and
uses some appropriate
frameworks, tools, and
standards to develop and
evaluate data and the
potential ethical issues of
the scenario. Presents a
somewhat coherent and
clear logic between
business issues, analytical
techniques, and variable
selection.
The justification is partially
convincing. Explores data
with adequate explanations
of the issues identified.
Demonstrates a limited
understanding of the
business problem or issue,
does not identify relevant
questions, and does not
use appropriate
frameworks, tools, and
standards to develop and
evaluate data. Does not
present a coherent and
clear logic between
business issues, analytical
techniques, and variable
selection.
The justification is not
convincing. Explores data
inadequately with
insufficient explanations of
the issues identified.
Does not demonstrate a
basic understanding of the
business problem or issue,
does not identify relevant
questions, and does not
use appropriate
frameworks, tools, and
standards to develop and
evaluate data. Does not
present any coherent or
clear logic between
business issues, analytical
techniques, and variable
selection.
The justification is absent.
Does not explore data
inadequately with
insufficient explanations of
High Distinction
(85%-100%)
Distinction
(75%-84%)
Credit
(65%-74%)
Pass
(50%-64%)
No Bueno
(0%-49%)
Quality of
Conclusions and
Recommendations
(20%)
Develops well-reasoned,
appropriate conclusions or
solutions based on the
results of the analysis. The
results of each analytic
technique performance and
findings are correctly
interpreted and critically
examined supported by
academic references.
Results interpretation is
relevant and meaningful in
the case context.
Recommendations are
logically and consistently
tied to each issue
discussed, with critical
thinking manifest in
business recommendations.
Develops good conclusions
or solutions based on the
results of the analysis. The
results of each analytic
technique performance and
findings are correctly
interpreted and examined.
Results interpretation is
generally relevant and
meaningful in the case
context. Recommendations
are tied to each issue
discussed.
Develops satisfactory
conclusions or solutions
based on the results of the
analysis. The results of each
analytic technique
performance and findings
are partially interpreted
and examined.
Results interpretation is
somewhat relevant and
meaningful in the case
context. Recommendations
are somewhat tied to each
issue discussed.
Develops limited
conclusions or solutions
based on the results of the
analysis. The results of each
analytic technique
performance and findings
are not interpreted and
examined.
Results interpretation is not
relevant or meaningful in
the case context.
Recommendations are not
consistently tied to each
issue discussed.
Develops no conclusions or
solutions based on the
results of the analysis. The
results of each analytic
technique performance and
findings are not interpreted
and examined.
Results interpretation is not
relevant or meaningful in
the case context.
Recommendations are not
tied to each issue
discussed.
Communication
and Organisation
(10%)
Uses language effectively
and accurately to convey
ideas and information, with
clear and concise writing
that is well-structured and
free of errors.
Good structure with
organized headings and
coherent flow between
sections.
Uses language effectively
and accurately to convey
ideas and information, with
clear writing that is well-
structured and mostly free
of errors.
Structure is generally sound
and headings are well-
organized, but flow
between sections may be
uneven or unclear.
Uses language somewhat
effectively and accurately
to convey ideas and
information, but the writing
may lack clarity, structure,
or contain errors.
Structure is adequate, but
headings may be less well-
organized and flow
between sections may be
inconsistent.
Uses language ineffectively
or inaccurately to convey
ideas and information, with
unclear or poorly-
structured writing that
contains errors.
Structure is inadequate,
with poorly organized
headings and inconsistent
or incoherent flow between
sections.
Uses language incoherently
or inaccurately to convey
ideas and information, with
writing that is unclear,
poorly-structured, and
contains numerous errors.
Structure is extremely poor
or absent, with no
discernible organisation or
headings.