Introduction
Data Story Project Guide
The major project for COMM5501 is structured to provide students a step-by-step guide to building their own data story on a topic of their own choosing, related to the UN Sustainable Development Goals (SDGs). A link to the SDGs is included HERE for your convenience.
Students will need to select a contemporary challenge related to the SDGs, find the relevant data, process and present this data in an insightful and coherent manner, and apply their own judgement based on their findings to give an evidence-based recommendation to the identified challenge.
Whilst there is a “Data Story Content” assessment and a “Data Story Project” assessment as part of this course, we will use the term “Data Story Project” to refer to the overall process of creating your data story.
The first three components of the Data Story Project will focus on building content for your data story. The fourth component will combine the content from the first three into the final version of the data story, and students will present their collated work in an appropriate format (guidance will be provided). The fifth component will require students to showcase their work as part of their profes- sional portfolio.
This Data Story Project has a total weighting of 80% of your final grade for this course. The 5 com- ponents mentioned above will be submitted throughout the term. The key details for each component are provided below.
Please note that this document is only a guide for what to expect, as we may make changes during the term to respond to unforeseen circumstances. This document should not be seen as being set in stone.
1 Choosing your Challenge 3
1.1 Description …………………………………… 3
1.2 SupportingActivities………………………………. 3
1.3 Deliverables…………………………………… 3
1.4 DueDate ……………………………………. 3
1.5 Whatmakesagoodsubmission? ………………………… 4
2 Good Graph, or Good Grief 5
2.1 Description …………………………………… 5
2.2 SupportingActivities………………………………. 5
2.3 Deliverables…………………………………… 5
2.3.1 GrowingmyGraph……………………………. 5
2.3.2 ThankYouteam!…………………………….. 6
2.4 DueDate ……………………………………. 6
2.5 Whatmakesagoodsubmission? ………………………… 6
2.5.1 GoodandBadVisualisations ………………………. 6 2.5.2 ThankYouteam!…………………………….. 7
3 Writing a Wrong 8
3.1 Description …………………………………… 8
3.2 SupportingActivities………………………………. 8
3.3 Deliverables…………………………………… 8
3.4 DueDate ……………………………………. 9
3.5 Whatmakesagoodsubmission? ………………………… 10
4 Making your Case 11 4.1 Description …………………………………… 11 4.2 SupportingActivities………………………………. 11 4.3 Deliverables…………………………………… 11 4.4 DueDate ……………………………………. 11 4.5 Whatmakesagoodsubmission? ………………………… 12
5 Publish your work 13 5.1 Description …………………………………… 13 5.2 SupportingActivities………………………………. 13 5.3 Deliverables…………………………………… 13 5.4 DueDate ……………………………………. 13 5.5 Whatmakesagoodsubmission? ………………………… 13
1 Choosing your Challenge 1.1 Description
The first component of the Data Story Project will introduce students into this task by proposing a topic that is both of interest to them and has a meaningful impact to the broader society. The chosen topic will need to connect to at least one if the UN SDGs.
For this chosen topic students will need to provide:
• An Impact Statement explaining why that proposed topic is important, both in general and to them individually, and
• Identify a relevant data set from a reputable source that can support this topic. This will serve as a starting point for subsequent components of the Data Story Project.
The purpose of this submission (in particular, proposing three topics) is to receive feedback from a member of the teaching team as well (students would already have received peer feedback before submitting).
NOTE: Students are NOT locked into this topic for the final version of their data story, and are allowed to adjust their topic statement/question as they progress through the semester.
This component is has a 5% weighting towards your final grade.
1.2 Supporting Activities
Topic 1 will contain various activities to support students in exploring the SDGs broadly. The lecture for Topic 2 will provide an introduction into writing an effective Impact Statement, and the correspond- ing workshop in week 2 will contain a guided activity for students to write their own Impact Statement.
Students will also post a copy of this component for their formative forum post for week 2, where they will receive peer feedback. Students are encouraged to take any additional feedback they receive here into consideration before submitting the deliverable for this task.
1.3 Deliverables
Students will gather all the feedback they’ve received and make any changes they feel are necessary, then post an updated version of their work to the Deliverables section on Moodle to receive feedback from the teaching team. Your post will need to contain the following:
• A single-sentence topic statement/question,
• A corresponding Impact Statement (max 150 words),
• A link to the chosen data set, a brief description of the data set, and a proposal for how the chosen data set might be used to support the Impact Statement (max 50 words).
1.4 Due Date
Early week 3 to receive feedback from a tutor. If you submit later during week 3, there’s a chance the tutor has already completed giving feedback and you may miss out.
Aim to submit your work by Friday 11:59PM in week 3 at the latest. Any submissions made after Friday 11:59PM in week 4 will likely not receive feedback.
1.5 What makes a good submission?
N/A, the first component is formative in nature and it is assumed that students have already incor- porated feedback they’ve received. Students will receive some additional feedback from the teaching team for their work.
2 Good Graph, or Good Grief 2.1 Description
The second component of the Data Story Project will take the ideas of “good” and “bad” data visu- alisations and apply them to their chosen topic.
Students will take the data set they chose from the “Choosing your Challenge” component (or another data set if necessary) and document their process of improving their first chart, the types of feedback they received, and how they implemented this feedback.
This task serves multiple purposes:
• Documenting the process with clear notes creates a reusable resource for referring back to the process you used to create your graph.
• It reduces the chance of repeating the same mistakes and speeds up the process for creating your subsequent graphs.
• More broadly, it reinforces the learning process. You are very likely learning a relatively new skill, and it’s very easy to forget a detail if you don’t write it down (this is still true if you’re refining an existing skill).
You will receive peer feedback throughout this process. This component will have very limited tutor feedback.
This component is has a 15% weighting towards your final grade.
The and give also
Supporting Activities
lab in week 3 will contain guided activities to help students build effective data visualisations, receive peer feedback on their work before submitting. The formative forum post in week 3 will students an opportunity to get additional feedback from other students. The lab in week 4 will
have an activity to help you start on the Thank You deliverable (Section 2.3.2).
Some of the elements from Topic 4 on stakeholders may also be relevant for this component, as a large portion of understanding the purpose of a graph comes from understanding the target audience as a stakeholder.
2.3 Deliverables
There are 2 sets of deliverables for this second component.
2.3.1 Growing my Graph
Students will submit a single PDF document to Turnitin containing the main iterations of their graph supporting the Impact Statement. You do not need to include every single version of your graph, just key checkpoints and major changes.
This document also needs to have brief notes on the changes made between each iteration. These notes should contain not only the change being made, but should also mention the rationale behind the change (i.e. Why did you make that change?). The notes can be dot points, but you can also have more text if you feel this is necessary.
These notes should be detailed enough to be a convenient reference material for yourself later in the term. A sample has been provided on Moodle for what this may look like.
Code Help, Add WeChat: cstutorcs
2.3.2 Thank You team!
The deliverable for this task is a completed ”Thank you team!” form (available on Moodle) and a follow-up Moodle post.
The activity for completing the form will be completed in the week 5 lab and the form will be collected by your tutor. Details for this task can be found in the week 4 and week 5 lab activities document, as well as the form provided on Moodle.
After the activity, students will need to make a follow-up post in the Deliverables section on Moodle to summarise the key parts of your presentation. A sample has been provided on Moodle for what this may look like.
2.4 Due Date
This activity will be conducted in the week 5 labs.
2.5 What makes a good submission?
The purpose of deliverable 2.3.1 is to create a record that you can revisit when making subsequent data visualisations to speed up that process and make better visualisations. The information below is a more detailed guide for making a better set of resources for yourself (traditionally, this might sometimes be called a “marking rubric”).
2.5.1 Good and Bad Visualisations
What separates a poor from a useful resource lies in the notes. It’s entirely possible that you created a very good graph in your first attempt and you didn’t need to make many changes. If there were elements of your first draft that were good that you deliberately kept the same, document your reasons for doing that as well.
There is little documentation explaining the process of iterating the graph. At best, the documentation is largely declarative, e.g. “colour scheme changed from bright red to dark blue”, instead of explanatory, e.g. “The bright red colour scheme was uncomfortable to look at, so I changed to dark blue. Much more comfortable”.
Acceptable
Changes (or lack thereof) are largely driven by the visualisation prin- ciples covered in class (e.g. Gestalt or Tufte’s principles), and this is documented.
Changes are driven primarily by the underlying purpose of the graph: the message being conveyed and the target audience. The visualisation principles covered in class are also considered, but these are secondary concerns.
2.5.2 Thank You team!
The “formal” term for this deliverable is a “reflection”, and should be based on the Gibbs’ Reflective Learning Cycle. For example, if you want to reflect on a particular piece of feedback (e.g. your group did not see the pattern you intended in your graph), then run through the six steps. Use the table below to help you write your reflection, then again to help you make a self-assessment.
Acceptable
Use of reflective process
The reflection does not seem to engage with the reflective cycle at all or only minimally, missing a number of elements or misunderstanding their purpose. There does not appear to be any genuine attempt to en- gage with feedback re- ceived.
The reflection covers most of Gibbs’ Reflec- tive Cycle adequately, perhaps lacking com- prehensive coverage in some places. At least attempts to genuinely engage with the reflec- tive process linked to the feedback received.
Covers all aspects of Gibbs’ Reflective Cycle to an appropriate de- gree, showing genuine engagement with the re- flective process directly linked to the feedback received.
Areas of Improvement
Does not highlight any areas for improvement, perhaps believing there are no gaps or opportu- nities to grow.
Highlights some ar- eas for improvement, whether self-assessed or noted by teammates, and provides limited reasoning as to why these gaps occurred. Reflects on what else could have been done, but this may be limited, perfunctory, or not par- ticularly relevant.
improvement, whether self-assessed or noted by teammates, and provides clear reasoning as to why these gaps occurred. Displays a growth mindset by reflecting substantially on what else could have been done.
self- high- for
Action Plan
Does not include an ac- tion plan for the fu- ture, or does so to a bare minimum in a way that is not particularly specific, actionable, rel- evant or realistic.
Has outline a reason- able action plan for self- improvement, though it may not be specific or clearly actionable in the near future.
Has clearly outlined an actionable, realistic, relevant and specific action plan for self- improvement in the future.
3 Writing a Wrong 3.1 Description
The third component of the Data Story Project will explore an opposing perspective to that chosen by the student. It is very easy to find information supporting any given perspective (confirmation bias), so students will need to genuinely consider this opposing perspective, assess its merits, and create an appropriate counter-argument. Students will need to find a source that opposes their chosen stance, analyse this stakeholder using the framework from Topic 4, and provide an evidence-based assessment of the validity of this source. The focus of this component is to use data to provide the counter-argument.
The purpose of this task is for students to show versatility by working outside their own boundaries and considering an opposing perspective. There will again be opportunities to receive feedback from peers and from a tutor.
Please note that this component is a summative task and will be graded by tutors. This component is has a 25% weighting towards your final grade
3.2 Supporting Activities
The lab in weeks 5 will contain guided activities to help students nominate and analyse the opposing perspective, including identifying the corresponding stakeholder that might hold this opposing per- spective. The stakeholder framework from Topic 4 can then be used to understand this stakeholder further, so that a response can be planned.
As with previous components, there will also be formative discussion forum posts for getting further peer feedback.
3.3 Deliverables
Students will submit a single PDF document to Turnitin containing their finalised work from week 5. This document will need to include:
• Citing the chosen opposing perspective (for example, a link would suffice), and the likely stake- holder with this view.
• A brief summary of the opposing perspective. (max 200 words)
• Any relevant data visualisations used in the opposing perspective (clearly label and caption these
as appropriate).
• Data visualisations created by the student that form the bulk of the counter-argument.
• Accompanying written notes to give context to student’s data visualisations and express the overall approach of the counter-argument. (max 200 words)
To help markers, students will also include their topic question/statement and summary of the chal- lenge for reference. This will not be marked. This can be the same as what was submitted in the first component of the Data Story Project, or changed as appropriate if the topic question/statement has changed since submitting the first component.
NOTE: Whilst the stakeholder framework from week 4 is not an explicit part of the deliverables for this component, it is highly recommended that you use it to help structure your counter-argument.
3.4 Due Date
Friday of flexibility week. The teaching team will try to do our best to provide feedback in a timely manner. Unfortunately, we cannot guarantee a 1-week turnaround. However, there will still be peer feedback from the week 5 formative assessment to help you refine this third component for use in the fourth (and fifth) component(s).
程序代写 CS代考 加微信: cstutorcs
Mind Blowing!
Provides a clear and con- cise summary based on op- posing perspective and re- lated data visualisations.
Visual elements are con- sistently used to commu- nicate key trends through impactful, sleek formatting choices using colour, sizing, axis headings and inclu- sion/highlighting of most relevant details only.
Shows strong understand- ing of the opposing per- spective and its limitations by making compelling counter-arguments linked to opposing points.
Overall structure of the counter-argument is not only clear, but also com- pelling, written with flow and sophistication.
Provides a clear summary based on the opposing per- spective and related data visualisations.
Visual elements are used to communicate key trends through format- ting choices using colour, sizing, axis headings and inclusion/highlighting of most relevant details only.
Shows good understand- ing of the opposing per- spective’s limitations by making counter-arguments linked to opposing points.
Overall structure of the counter-argument is clear and flows generally well.
Provides a summary based on the opposing perspec- tive and related data visu- alisations, however may be somewhat underdeveloped or unclear.
Visual elements are some- what used to communicate key trends; includes some good formatting choices using colour, sizing, axis headings and inclu- sion/highlighting of most relevant details only.
Shows some understanding of the opposing perspec- tive’s limitations; may not clearly link counter- arguments to opposing points in all instances.
Overall structure of the counter-argument is sound
with all elements (e.g. link
to summary, data evi- dence, explanation) pro-
Minimally Acceptable
Attempts to summarise opposing perspective but may omit key points alto- gether, indicating poor un- derstanding of the source.
Visual elements only mini- mally add to the clarity or coherence of the intended trend but avoid causing confusion or distraction. May include excess clut- ter, detail, or elements which detract from clearly illustrating/supporting the counter-argument.
Shows limited under-
standing of the opposing perspective’s limitations;
links between counter-
arguments and opposing
points may be omitted or
Overall structure of the
counter-argument is weak
with some elements (e.g.
link to summary, data ev-
idence, explanation) omit-
More Effort Needed
Does not summarise the opposing perspective and related data visualisations, or does so overly briefly or without any real under- standing shown.
Visual formatting choices
are not included or cause
confusion or distraction
from the counter-argument
Altogether inappropri-
ate choice of counter-
arguments to oppos-
ing perspective, or not
counter-arguments pro-
Counter-argument is con-
fusing, with minimal to
no structure and signifi-
cant components omitted.
Summary of
opposing per-
spective and
related data
visualisations
data visuali-
sations clearly
showing the
intended trend
of counter-
to opposing
perspective
Consistent and
clear structure
of counter-
3.5 What makes a good submission?
Unlike the previous components, this component will be graded by a tutor. Treat the following table as guide for compiling a brilliant counter-argument.
4 Making your Case 4.1 Description
The fourth component of the Data Story Project will put together all three components that students have created so far, as well as all feedback received in the process, to create a final artifact for their professional portfolio.
The format of this artifact is (almost) completely open-ended! Students are encouraged to be creative with the format of this artifact. For example, it can be a report, a video presentation, an infographic, or a self-produced music video, the possibilities are endless! There are only 2 requirements on the format:
• It MUST be appropriate for the chosen target audience.
• It needs to have a video/audio element (i.e. it can’t be purely written).
This artifact for the student’s professional portfolio. You will also publish this presentation in the final component of this project. This artifact gives insight into your own passions, who you are as a professional, and possibly where you want to go in your future career.
Please note that this component is a summative task and will be graded by tutors.
This component is has a 25% weighting towards your final grade
4.2 Supporting Activities
The labs in weeks 8, 9, and 10 will contain guided activities to help students put together your artifact. More specifically:
• The week 8 lab will help students plan a narrative to give overarching structure to their data story.
• The week 9 lab will give guidelines to help students plan their data story more concretely.
• The week 10 lab will be a final opportunity for students to get feedback on their artifact.
4.3 Deliverables
Students will submit a single PDF document to Moodle. This document will need to include a cover page containing the student’s name and zID, as well as either:
• The artifact itself, if it is static media (such as a poster or infographic)
• Basic instructions for accessing the artifact if it is a non-static format (e.g. a video presentation
or a music video). This might simply be a YouTube link.
• A separate bibliography citing data sets and any other resources you have used.
If you are unsure about your chosen format, please speak with your tutor or the LIC for clarification.
Whilst the list above contains a separate bibliography, your artifact also needs to explicitly show your bibliography. Please also make sure your any links you’ve included in this deliverable works and can be accessed by anyone with the link (for example, you can send it to one of your group members to confirm it works).
4.4 Due Date
Friday week 11. Specific instructions for submission will be provided on Moodle. 11
Mind Blowing!
Data visualisations are consis- tently used to make complex concepts and conclusions eas- ily understood and actionable, as well as helping guide the audience to the most relevant aspects of the presentation.
Presentation content and methods are excellently adapted to the target stake- holder and use an appropriate blend of practicality, theory, and complexity.
The presentation demon- strates a strong and logical structure, with all ideas interconnected and building upon each other effectively. Transitions between sections or topics are flawless, result- ing in a highly coherent and engaging presentation.
Data visualisations are mostly used to make complex con- cepts and conclusions easily understood and actionable, as well as generally helping guide the audience to the most rel- evant aspects of the presenta- tion.
Presentation content and methods are consistently well adapted to the target stakeholder and mostly use an appropriate blend of practi- cality, theory, and complexity.
The presentation demon- strates a well-developed and consistent flow of ideas throughout. Transitions between different slides or ideas are seamless, enhancing the understanding of and engagement with the ideas being presented.
Data visualisations are sometimes used to make complex concepts and conclusions easily under- stood and actionable. At times they also help guide the audience to the most relevant aspects of the presentation.
Presentation content and methods are mostly well adapted to the target stakeholder and attempt to appropriately blend practicality, theory, and complexity.
The presentation demon- strates a clear structure and flow of ideas. Tran- sitions between different slides or ideas are gener- ally smooth and the over- all message can be under- stood.
Minimally Acceptable
Data visualisations only minimally add to the clarity or coherence of the presentation but avoid introducing con- fusion or distraction.
The presentation con- tent and methods are sometimes or partially appropriate to the tar- get stakeholder.
The presentation shows
some attempts at co-
hesion but lacks con-
sistency. The transi-
tions between different
slides or ideas gener-
ally are not smooth or
well-integrated, causing
some confusion.
More Effort Needed
Data visualisations are not included or are con- fusing or disconnected from the rest of the pre- sentation.
The presentation con-
tent and methods are
not appropriate to the
target stakeholder.
The presentation does
not provide a clear
structure or flow of
ideas. Transitions be-
tween different slides or
ideas are abrupt and
confusing.
Effective use of
data visualisa-
Suitability
of presenta-
tion to target
stakeholder
Cohesion of
the presenta-
4.5 What makes a good submission?
This component will be graded by a tutor. Treat the following table as guide for compiling a brilliant artifact.
5 Publish your work 5.1 Description
The fifth and final component of the Data Story Project will share the student’s work on the profes- sional social networking platform LinkedIn (alternatives will be discussed in more detail later in the term) as part of the student’s professional portfolio.
Students will use the artifact they have created in the fourth component as part of a LinkedIn post to showcase their work. The post will also give students an opportunity to introduce their work (and possibly themselves) to the online professional community. Students are also encouraged to share why their chosen topic is important to them as part of this post, and any other relevant information (guidance will be provided here).
This component is has a 10% weighting towards your final grade, and is a HURDLE assessment (you just have to complete this component, you don’t necessarily need to have 5 marks). This means that students MUST complete this final fifth component to be eligible to pass this course.
5.2 Supporting Activities
There will be time in the week 10 lecture and lab allocated to helping students with this final compo- nent. There will also be relevant instructional resources posted on Moodle to guide students. We will also discuss the requirements of this post in the week 10 lecture.
5.3 Deliverables
Students will need to upload a screenshot of their LinkedIn post to Moodle as evidence that this component has been complete. Note that the LinkedIn post needs to meet the requirements that we will discuss in week 10.
5.4 Due Date
Friday week 11. Specific instructions for submission will be provided on Moodle.
5.5 What makes a good submission?
The 10% weighting for this component will be based on a student self assessment. As part of the LinkedIn post, students will need to give themselves a rating of their work out of 10 for their work. We recommend using the table in Section 4.5 as the criteria for this rating. This self-rating will be the mark they receive for this component.
Weighting Summary
A table containing the weighting of each component towards the final grade is included below for your convenience.
Component 1 2 3 4 5 Total Weighting 5% 15% 25% 25% 10% 80%
Code Help