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COMM1110-论文代写
时间：2023-03-09
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COMM1110 Evidence-Based Problem Solving
Assessment 2a: Assessment Guide and Marking Rubric
Assessment 2 Summary:
Assessment 2a: Case Briefing Pack, Week 5 – 4.00pm Friday, 17th March (AEST)
Assessment 2b: Case Business Report, Week 11 – 4.00pm Friday 28th April (AEST)
Assessment 2a: 25%
Assessment 2b: 40%
Based on a real-world business problem, written response to questions
Assessment 2a: 1,500 words, excluding references
Assessment 2b: 2,000 words, excluding references
Via Moodle course site, through Turnitin
______________________________________________________________________
Project Overview
You are working for a consulting firm called Solve It! Your company has a reputation for
on-time and thorough problem-solving solutions that integrates different evidence
sources, namely statistical information with insights from literature and ethical decision-
making processes.
Solve It! won a contract with Australian Airlines Association (AAA). This contract has two
deliverables. A Briefing Pack (Assessment 2a) that will be considered by the AAA officials.
The format is written responses to the initial questions posed by AAA. You will be provided
with feedback on the Briefing Pack; there is no opportunity to meet with AAA officials to
present your Briefing Pack, however you may meet with them (your tutor) to further
understand the feedback they provide. It is normal for clients and consultants to have
such interactions to check progress and possibly refine the problem. The next deliverable
is a Business Report (Assessment 2b), which builds on the feedback you have received,
and you will also consider additional questions and material.
The contract is about flight cancellation. AAA is concerned with the increasing number of
flight cancellations since the COVID-19 pandemic. As a member of the SolveIt! Consulting
team, the overarching issue to be addressed is to: (1) explore the factors that lead to flight
cancellations. (Assessment 2a and 2b), and (2) give recommendations on how the AAA
needs to intervene to address the flight cancellation problem.
2
Assessment 2a: Case Briefing Pack (25%)
Determine the extent of the flight cancellation problem. You have been asked by your
team leader to address the questions in the Briefing Pack. You are required to use
different problem-solving toolboxes to address these questions.
1. Solve It! ‘Information Toolbox’
This section of the report is approximately 500 words (guide only, not a word limit).
• Frame the problem: clearly define what the problem you need to solve and bound it, which
helps you decide what to include and exclude in analysing and developing solutions is.
You may want to ask yourself the 5W questions (Week 1) when framing the problem: e.g.
What is the issue? Who is involved? What contributes to the problem?
• Construct a logic tree to break down the cancellation problem into component parts and
analyse what factors contribute to the problem.
• Use literature to frame the flight cancellation problem (use no more than four pieces of
literature: two academic papers, and two pieces of grey literature).
• Assumptions need to be explicitly identified.
• Word limit: A maximum of 1,500 words (no minimum word limit, no+10% tolerance; graphs,
figures and reference list are excluded from the word count). A 10% penalty will apply if you
exceed the word count.
• Structure and format: No introduction or executive summary are required. You are required
to write in a business report style (i.e. formal language, etc).
• Referencing style: Harvard (see The 'In-Text' or Harvard method for more information).
Note: A real consulting project and the resulting Business Reports typically run for
multiple months, by a large consulting team. The purpose of this project is to provide you
with a real business problem and tasks you would see as a graduate, plus importantly
give you awareness of and experience with applying the problem-solving tools to such
tasks. This assessment (Assessment 2a and 2b) is worth 65% of your final grade, so it
requires regular weekly study time to advance the analysis and solution design needed to
write the succinct report. Yet, this project is not expected to be industry standard. Please
use the guidance within the brief below to put boundaries on the breadth and depth of
your report (e.g., word length, number of tools and references). There is a delicate
balance between breadth and depth of analysis in business reports. If you have
questions, please post questions on the Moodle Discussion Forum and/or discuss with
the teaching team.
3
Please Note:
Frame a problem means to clearly define what the problem you want to solve is.
You may want to ask yourself the following questions when framing the problem:
What is the main problem? When and where is it occurring? Who are the
stakeholders? Why is there an increasing number of flight cancellation since the
pandemic?
A 5Ws table or factor logic tree could be used to summarise the problem.
2. Solve It! ‘Statistical Toolbox’
This section of the report is approximately 600 words (guide only, not a word limit).
One of your colleagues at Solve It! has just compiled and delivered to you a dataset. You
are asked to determine the extent of flight cancellations using this dataset.
• The first step of any data analysis is to understand and summarise the data. Use graphs
and descriptive statistics to provide a snapshot of flight cancellations in Australia. The
key variable of interest here is “Cancellations” (the number of flight cancellations).
• Your client, the Australian Airlines Association, is interested in whether cancellations may
be associated with any of the following variables:
• Whether “Cancellations” tends to be associated with the “Airline”
• Whether “Cancellations” tends to be associated with the “Staff Shortage”
• Whether “Cancellations” tends to be associated with any of the other variables
identified in the dataset.
• Use graphs and various summary measures (covered in descriptive statistics topics) to
provide an overview of the key features of the provided data. The objective is to provide
insights into and an understanding of cancellations.
• The first step of any data analysis is to understand and summarise the data. As part of
this process, you are expected to present key features of the data, including
associations between variables highlighting anything you consider to be interesting and
relevant to the overall problem of flight cancellations. The key variable of interest is
“Cancellations”.
• Your statistical toolbox should include descriptive statistics of key variables and an
analysis of the distribution of the data. It should also include correlations of key
variables and likely reasons for these correlations.
• Assumptions need to be explicitly identified.
4
3. Solve It! ‘Ethics Toolbox’
This section of the report is approximately 400 words (guide only, not a word limit).
• Identify an ethical dilemma that could be faced by Australian Airlines during the
pandemic. Use your moral imagination. Is there a risk of someone (or something)
being harmed? Explain your reasoning.
___________________________________________________________________________
The data set each of you will receive contains 200 observations that were collected
over a one-year period during 2020. Each observation refers to the number of
cancellations in the month for each airline on each route. The variables that have been
selected for your use are:
Other Resources:
- Library Expert on Demand for personalised support:
https://unsw.libcal.com/appointments/Main
- Research consultation: https://unswlibrary.libanswers.com/research-consultation
- Business guide: https://subjectguides.library.unsw.edu.au/business
Variable Descriptions
Departing
Port Port of departure
Arriving Port Port of destination
Airline Name of the airlines (Jets, Anta, Viria)
Year 2020
Month
Month (Jan, Feb, Mar, Apr, May, Jun, Jul, Aug, Sep, Oct, Nov,
Dec)
Month
Number Month (1,2,3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
Cancellations
No of cancellations of that particular route, by that particular
airline, in that particular month
Departures
On Time
The number of flights that depart on time, on that particular
route, by that particular airline, in that particular month.
Departures
Delayed
The number of flights that depart late, on that particular route,
by that particular airline, in that particular month.
Weather The number of flights that were cancelled due to bad weather.
Mechanical
Failure
The number of fights that were cancelled due to mechanical
failure.
Staff
Shortage
The number of flights that were cancelled due to staff
shortage.
Other Reason
The number of flights that were cancelled due to other reasons
(e.g. lack of passengers, etc.)
5
Access Data:
Your Assessment 2 data can be accessed via the R-Shiny App at the following site:
>>> https://comm1110.shinyapps.io/comm1110/ <<<
Click the link above and follow the steps below to obtain and download your
personalised Assessment 2 dataset:
(1) Click on “Assessment data”.
(2) Enter your student ID without the "z" to load your assessment data. Click
“Load Assessment Data” to access your assessment data.
(3) To download your data, click "Download Data".
*You can use the R-Shiny App to perform preliminary analysis to explore the
key features of the data. However, you are required to use Excel to analyse the
full data (see Note below).
Video Guide: R-Shiny App Overview Video This is a general video guide introducing
you to the R-Shiny App (NOT the assessment data or your Assessment 2 this term).
The dataset used in this example video is different from the one that you are required
to use for Assessment 2 (so please ignore any references to data or assessment
requirements in the video, and focus on the use of the R-Shiny App itself). Some of the
topics discussed in the video (e.g. hypothesis test) will be covered in the course in
later weeks.
Note: While the R-Shiny App allows you to perform some quick analysis to
understand the data, it is restricted to 50 observations. For Assessment 2, your
dataset contains 200 observations, which means that you are required to download
the data from the R-Shiny App and perform your final analysis in Excel.
6
Use of Generative Artificial Intelligence – such as ChatGPT
PLANNING ASSISTANCE
As this assessment task involves some planning or creative processes, you are permitted to use
software to generate initial ideas. However, you must develop or edit those ideas to such a
significant extent that what is submitted is your own work, i.e. only occasional AI generated words
or phrases may form part of your final submission. You are required to keep copies of the initial
prompts to show your lecturer and the University Conduct & Integrity Office if there is any
uncertainty about the originality of your work.
If the outputs of generative AI such as ChatGPT form a part of your submission, it will be regarded
as serious academic misconduct and subject to the standard penalties, which may include 00FL,
suspension and exclusion.
Please ensure that you include a copy of any generative AI outputs in your appendix (the
words from this will not be included as part of the word count for the assessment).
7
Marking rubric for Assessment 2a: Case Briefing Pack
Criteria 2a
%
Fail
Pass
Credit
Distinction
High Distinction
1. Information
problem-solving
Application of the
information toolkit
into well-structured
arguments
40% Does not apply information
problem-solving tools to the
Case, or application is
inaccurate. Unclear writing
style, which distracts from
arguments.
Applies information
problem-solving tools
to the Case
appropriately but may
include minor errors or
omissions. Generally,
clear writing style so
main arguments
articulated.
Accurately applies
information problem-
solving tools to the
Case. Generally,
expresses complex
ideas into well-reasoned
arguments.
Accurately and insightfully
applies information
problem-solving tools to
the Case. Consistently and
skillfully represents
complex ideas into well-
reasoned arguments.
Accurately and insightfully
applies information
problem-solving tools to
the Case demonstrating
breadth and depth of
analysis. Consistently and
eloquently represents
complex ideas into well-
reasoned arguments.
2. Statistical
problem-solving.
Application of the
statistical toolkit
40% Does not apply statistical
problem-solving tools to the
Case, or application is
inaccurate.
Applies statistical
problem-solving tools
to the Case
appropriately but may
include minor errors or
omissions.
Accurately applies
statistical problem-
solving tools to the
Case.
Accurately and insightfully
applies statistical problem-
solving tools to the Case.
Accurately and insightfully
applies statistical problem-
solving tools to the Case
highlighting novel insights
with extension material
from the course.
3. Ethical decision-
making
Clear and concise
description,
appropriateness of
chosen dilemma,
clear focus on
relevant details
20% Partial or limited description
of ethical dilemma.
Situation may not constitute
an ethical dilemma, or the
links with ethics are unclear
or inappropriate. Limited if
any focus on boundaries or
stakeholders.
Adequate description
of generally
appropriate ethical
dilemma. Some focus
on relevant details
and/or the boundaries
of the situation and/or
stakeholders.
Sound description of
generally appropriate
and well-specified
ethical dilemma. Solid
focus on relevant details
and the boundaries of
the situation and
stakeholders.
Clear and succinct
descriptions of an
appropriate and well-
specified ethical dilemma.
Generally clear focus on
relevant details, the
boundaries of the situation
and relevant stakeholders.
Clear, succinct and
compelling description of a
clearly specified and
appropriate ethical
dilemma. Very clear focus
on relevant details, the
boundaries of the situation,
and relevant stakeholders.
Assessment 2a: Assessment Guide and Marking Rubric
Assessment 2 Summary:
Assessment 2a: Case Briefing Pack, Week 5 – 4.00pm Friday, 17th March (AEST)
Assessment 2b: Case Business Report, Week 11 – 4.00pm Friday 28th April (AEST)
Assessment 2a: 25%
Assessment 2b: 40%
Based on a real-world business problem, written response to questions
Assessment 2a: 1,500 words, excluding references
Assessment 2b: 2,000 words, excluding references
Via Moodle course site, through Turnitin
______________________________________________________________________
Project Overview
You are working for a consulting firm called Solve It! Your company has a reputation for
on-time and thorough problem-solving solutions that integrates different evidence
sources, namely statistical information with insights from literature and ethical decision-
making processes.
Solve It! won a contract with Australian Airlines Association (AAA). This contract has two
deliverables. A Briefing Pack (Assessment 2a) that will be considered by the AAA officials.
The format is written responses to the initial questions posed by AAA. You will be provided
with feedback on the Briefing Pack; there is no opportunity to meet with AAA officials to
present your Briefing Pack, however you may meet with them (your tutor) to further
understand the feedback they provide. It is normal for clients and consultants to have
such interactions to check progress and possibly refine the problem. The next deliverable
is a Business Report (Assessment 2b), which builds on the feedback you have received,
and you will also consider additional questions and material.
The contract is about flight cancellation. AAA is concerned with the increasing number of
flight cancellations since the COVID-19 pandemic. As a member of the SolveIt! Consulting
team, the overarching issue to be addressed is to: (1) explore the factors that lead to flight
cancellations. (Assessment 2a and 2b), and (2) give recommendations on how the AAA
needs to intervene to address the flight cancellation problem.
2
Assessment 2a: Case Briefing Pack (25%)
Determine the extent of the flight cancellation problem. You have been asked by your
team leader to address the questions in the Briefing Pack. You are required to use
different problem-solving toolboxes to address these questions.
1. Solve It! ‘Information Toolbox’
This section of the report is approximately 500 words (guide only, not a word limit).
• Frame the problem: clearly define what the problem you need to solve and bound it, which
helps you decide what to include and exclude in analysing and developing solutions is.
You may want to ask yourself the 5W questions (Week 1) when framing the problem: e.g.
What is the issue? Who is involved? What contributes to the problem?
• Construct a logic tree to break down the cancellation problem into component parts and
analyse what factors contribute to the problem.
• Use literature to frame the flight cancellation problem (use no more than four pieces of
literature: two academic papers, and two pieces of grey literature).
• Assumptions need to be explicitly identified.
• Word limit: A maximum of 1,500 words (no minimum word limit, no+10% tolerance; graphs,
figures and reference list are excluded from the word count). A 10% penalty will apply if you
exceed the word count.
• Structure and format: No introduction or executive summary are required. You are required
to write in a business report style (i.e. formal language, etc).
• Referencing style: Harvard (see The 'In-Text' or Harvard method for more information).
Note: A real consulting project and the resulting Business Reports typically run for
multiple months, by a large consulting team. The purpose of this project is to provide you
with a real business problem and tasks you would see as a graduate, plus importantly
give you awareness of and experience with applying the problem-solving tools to such
tasks. This assessment (Assessment 2a and 2b) is worth 65% of your final grade, so it
requires regular weekly study time to advance the analysis and solution design needed to
write the succinct report. Yet, this project is not expected to be industry standard. Please
use the guidance within the brief below to put boundaries on the breadth and depth of
your report (e.g., word length, number of tools and references). There is a delicate
balance between breadth and depth of analysis in business reports. If you have
questions, please post questions on the Moodle Discussion Forum and/or discuss with
the teaching team.
3
Please Note:
Frame a problem means to clearly define what the problem you want to solve is.
You may want to ask yourself the following questions when framing the problem:
What is the main problem? When and where is it occurring? Who are the
stakeholders? Why is there an increasing number of flight cancellation since the
pandemic?
A 5Ws table or factor logic tree could be used to summarise the problem.
2. Solve It! ‘Statistical Toolbox’
This section of the report is approximately 600 words (guide only, not a word limit).
One of your colleagues at Solve It! has just compiled and delivered to you a dataset. You
are asked to determine the extent of flight cancellations using this dataset.
• The first step of any data analysis is to understand and summarise the data. Use graphs
and descriptive statistics to provide a snapshot of flight cancellations in Australia. The
key variable of interest here is “Cancellations” (the number of flight cancellations).
• Your client, the Australian Airlines Association, is interested in whether cancellations may
be associated with any of the following variables:
• Whether “Cancellations” tends to be associated with the “Airline”
• Whether “Cancellations” tends to be associated with the “Staff Shortage”
• Whether “Cancellations” tends to be associated with any of the other variables
identified in the dataset.
• Use graphs and various summary measures (covered in descriptive statistics topics) to
provide an overview of the key features of the provided data. The objective is to provide
insights into and an understanding of cancellations.
• The first step of any data analysis is to understand and summarise the data. As part of
this process, you are expected to present key features of the data, including
associations between variables highlighting anything you consider to be interesting and
relevant to the overall problem of flight cancellations. The key variable of interest is
“Cancellations”.
• Your statistical toolbox should include descriptive statistics of key variables and an
analysis of the distribution of the data. It should also include correlations of key
variables and likely reasons for these correlations.
• Assumptions need to be explicitly identified.
4
3. Solve It! ‘Ethics Toolbox’
This section of the report is approximately 400 words (guide only, not a word limit).
• Identify an ethical dilemma that could be faced by Australian Airlines during the
pandemic. Use your moral imagination. Is there a risk of someone (or something)
being harmed? Explain your reasoning.
___________________________________________________________________________
The data set each of you will receive contains 200 observations that were collected
over a one-year period during 2020. Each observation refers to the number of
cancellations in the month for each airline on each route. The variables that have been
selected for your use are:
Other Resources:
- Library Expert on Demand for personalised support:
https://unsw.libcal.com/appointments/Main
- Research consultation: https://unswlibrary.libanswers.com/research-consultation
- Business guide: https://subjectguides.library.unsw.edu.au/business
Variable Descriptions
Departing
Port Port of departure
Arriving Port Port of destination
Airline Name of the airlines (Jets, Anta, Viria)
Year 2020
Month
Month (Jan, Feb, Mar, Apr, May, Jun, Jul, Aug, Sep, Oct, Nov,
Dec)
Month
Number Month (1,2,3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
Cancellations
No of cancellations of that particular route, by that particular
airline, in that particular month
Departures
On Time
The number of flights that depart on time, on that particular
route, by that particular airline, in that particular month.
Departures
Delayed
The number of flights that depart late, on that particular route,
by that particular airline, in that particular month.
Weather The number of flights that were cancelled due to bad weather.
Mechanical
Failure
The number of fights that were cancelled due to mechanical
failure.
Staff
Shortage
The number of flights that were cancelled due to staff
shortage.
Other Reason
The number of flights that were cancelled due to other reasons
(e.g. lack of passengers, etc.)
5
Access Data:
Your Assessment 2 data can be accessed via the R-Shiny App at the following site:
>>> https://comm1110.shinyapps.io/comm1110/ <<<
Click the link above and follow the steps below to obtain and download your
personalised Assessment 2 dataset:
(1) Click on “Assessment data”.
(2) Enter your student ID without the "z" to load your assessment data. Click
“Load Assessment Data” to access your assessment data.
(3) To download your data, click "Download Data".
*You can use the R-Shiny App to perform preliminary analysis to explore the
key features of the data. However, you are required to use Excel to analyse the
full data (see Note below).
Video Guide: R-Shiny App Overview Video This is a general video guide introducing
you to the R-Shiny App (NOT the assessment data or your Assessment 2 this term).
The dataset used in this example video is different from the one that you are required
to use for Assessment 2 (so please ignore any references to data or assessment
requirements in the video, and focus on the use of the R-Shiny App itself). Some of the
topics discussed in the video (e.g. hypothesis test) will be covered in the course in
later weeks.
Note: While the R-Shiny App allows you to perform some quick analysis to
understand the data, it is restricted to 50 observations. For Assessment 2, your
dataset contains 200 observations, which means that you are required to download
the data from the R-Shiny App and perform your final analysis in Excel.
6
Use of Generative Artificial Intelligence – such as ChatGPT
PLANNING ASSISTANCE
As this assessment task involves some planning or creative processes, you are permitted to use
software to generate initial ideas. However, you must develop or edit those ideas to such a
significant extent that what is submitted is your own work, i.e. only occasional AI generated words
or phrases may form part of your final submission. You are required to keep copies of the initial
prompts to show your lecturer and the University Conduct & Integrity Office if there is any
uncertainty about the originality of your work.
If the outputs of generative AI such as ChatGPT form a part of your submission, it will be regarded
as serious academic misconduct and subject to the standard penalties, which may include 00FL,
suspension and exclusion.
Please ensure that you include a copy of any generative AI outputs in your appendix (the
words from this will not be included as part of the word count for the assessment).
7
Marking rubric for Assessment 2a: Case Briefing Pack
Criteria 2a
%
Fail
Pass
Credit
Distinction
High Distinction
1. Information
problem-solving
Application of the
information toolkit
into well-structured
arguments
40% Does not apply information
problem-solving tools to the
Case, or application is
inaccurate. Unclear writing
style, which distracts from
arguments.
Applies information
problem-solving tools
to the Case
appropriately but may
include minor errors or
omissions. Generally,
clear writing style so
main arguments
articulated.
Accurately applies
information problem-
solving tools to the
Case. Generally,
expresses complex
ideas into well-reasoned
arguments.
Accurately and insightfully
applies information
problem-solving tools to
the Case. Consistently and
skillfully represents
complex ideas into well-
reasoned arguments.
Accurately and insightfully
applies information
problem-solving tools to
the Case demonstrating
breadth and depth of
analysis. Consistently and
eloquently represents
complex ideas into well-
reasoned arguments.
2. Statistical
problem-solving.
Application of the
statistical toolkit
40% Does not apply statistical
problem-solving tools to the
Case, or application is
inaccurate.
Applies statistical
problem-solving tools
to the Case
appropriately but may
include minor errors or
omissions.
Accurately applies
statistical problem-
solving tools to the
Case.
Accurately and insightfully
applies statistical problem-
solving tools to the Case.
Accurately and insightfully
applies statistical problem-
solving tools to the Case
highlighting novel insights
with extension material
from the course.
3. Ethical decision-
making
Clear and concise
description,
appropriateness of
chosen dilemma,
clear focus on
relevant details
20% Partial or limited description
of ethical dilemma.
Situation may not constitute
an ethical dilemma, or the
links with ethics are unclear
or inappropriate. Limited if
any focus on boundaries or
stakeholders.
Adequate description
of generally
appropriate ethical
dilemma. Some focus
on relevant details
and/or the boundaries
of the situation and/or
stakeholders.
Sound description of
generally appropriate
and well-specified
ethical dilemma. Solid
focus on relevant details
and the boundaries of
the situation and
stakeholders.
Clear and succinct
descriptions of an
appropriate and well-
specified ethical dilemma.
Generally clear focus on
relevant details, the
boundaries of the situation
and relevant stakeholders.
Clear, succinct and
compelling description of a
clearly specified and
appropriate ethical
dilemma. Very clear focus
on relevant details, the
boundaries of the situation,
and relevant stakeholders.
