SCHOOL OF INFORMATION AND PHYSICAL SCIENCES
INFT6201 – BIG DATA
ASSESSMENT 2: PRESENTATION
OVERVIEW
§ Weighting: 30%
§ Due date: ongoing (Weeks 8–11 during Lab)
§ Method of submission: Lab Presentation
§ Content: Presentation (individual assessment)
§ Length of submission: 8–10 minutes (+references)
DESCRIPTION
This assessment encourages students to expand and deepen their conceptual knowledge of big data within
real-world applications (e.g., business, health). They do this through discussion of a data analytics concept
(e.g. big data framework, data visualisation, natural language processing) in practice. In their presentation,
they are required to provide evidence that they have researched the concept extensively using information
resources such as academic journals, professional press and the popular media. It is expected that they will
demonstrate both reflection and analysis related to the data analytics concept posed, and produce an
articulate and concise response conveying evidence-based understanding of the concepts and topics.
TOPIC
In your presentation, we ask you to provide a practical case study of a specific data analytics concept. Each
student will be assigned one specific data analytics concept such as a specific data visualisation technique
(e.g. heat maps) or a specific phenomenon (e.g. Simpson’s paradox). The topics will be assigned on Canvas. The
presentation first provides a background on the data analytics concept and then continues to provide a
practical example using python code on a dataset. Identifying a suitable dataset and creating the python code
for the case study is part of the assessment. The final part of the presentation provides a brief overview of
two or more application areas of the data analytics concept beyond the case study.
The presentation should follow the following structure:
1. Title page (1 slide, title of presentation and student name)
2. Data Analytics Concept (1-2 slides providing background on the data analytics concept)
3. Case Study (3-4 slides on a specific example with python code)
4. Applications in Practice (1-2 slides on discussing further applications in practice beyond the case study)
5. References
Students who wish to earn high marks will ensure that their presentation is clearly linked to items pointed
out in the marking criteria. The presentations are to be delivered during a lab session. However, for students
who are unable to participate in the lab sessions, an alternative arrangement can be made.
[THE MARKING CRITERIA ARE SUMMARISED ON PAGES 2 AND 3]
1/3
2/3
MARKING CRITERIA FOR CASE STUDY PRESENTATION
Criterion
Mark
Absent or poor
Below average
Average
Good
Excellent
1) Data Analytics Concept: Background
on the data analytics concept with
references to the literature.
/5
0-1: No or very limited
explanation and shallow
elaboration of the data
analytics concept.
2: Superficial explanation
and relatively shallow
elaboration of the data
analytics concept.
3: Adequate. Explanation
and discussion of the data
analytics concept showing
some depth and breadth.
4: Good. Explanation and
discussion of the data
analytics concept with
good depth and breadth.
5: Excellent and well
balanced explanation of
the data analytics
concept.
2) Practical Case Study: Application of
the data analytics concept to a specific
case study (including dataset selection,
python code, and output).
/10
0-2: No or very superficial
case study that only
provides a very shallow
illustration of the data
analytics concept.
3-4: Superficial case study
that offers only limited
illustration of the
application of the data
analytics concept and that
is inadequately
underpinned by code
and/or builds on an
unsuitable dataset.
5-6: Adequate.
Explanation and
discussion of the case
study provide some depth
and breadth into the
application of the data
analytics concept. Limited
underpinning by python
code on a suitable
dataset.
7-8: Good. Explanation
and discussion of the case
study show good depth
and breadth of the
application of the data
analytics concept. The
case study is underpinned
by accurate python code
on a suitable dataset.
9-10: Excellent and well
described case study that
clearly illustrates the
application of the data
analytics concept and that
is underpinned by highly
accurate python code on a
suitable dataset.
3) Applications in Practice: Discussion
of two or more example application
areas of the presented data analytics
concept in practice.
/5
0-1: No or poorly
presented and discussed
examples for further
applications of the data
analytics concept in
practice.
2: Very limited or overly
general discussion of
further applications of the
data analytics concept in
practice.
3: Adequate discussion of
further applications of the
data analytics concept in
practice.
4: Good discussion of
further applications of the
data analytics concept in
practice with clear links to
the potential benefits.
5: Excellent discussion of
further applications of the
data analytics concept in
practice with very clear
links to the potential
benefits.
4) Overall quality of presentation: The
material is presented in logical
sequence which audience can follow.
Students are expected to speak freely
about the subject with confidence. The
presentation should be well-structured
and supported by media files where
appropriate (e.g., figures, images). All
text should be clearly readable and
grammatically sound. Please note that
the presentation file needs to include a
complete list of references.
0-2: Poor or no structure,
many language issues.
Poor or no use of media
files. Issues in the delivery
of the presentation (e.g.,
only reading from a script).
3-4: Mix of major and
minor language issues.
Some issues in the
structuring of the
presentation and the use
of issues media in the files. delivery Some of
the presentation (e.g.,
mostly reading from a
script).
5-6: Adequate quality of
language. Presentation
has a discernible structure
and uses media files to
support the delivery of
the content.
7-8: Good quality of
language. Well thought
out structure with a
logical sequence that
makes it easy and
intriguing audience to forfollow. the Good
use of media files to
support the presentation.
Presentation is delivered
speaking freely and with
confidence.
9-10: Excellent quality of
language. Very well
thought out structure
with a logical sequence
that makes it easy and
intriguing to follow. Excellent for the audience use of
media files to support the
presentation.
Presentation is delivered
speaking freely and with
confidence.
/10
SUBTOTAL
/30
3/3
Presentation too short or too long
–
The presentation is scheduled for 8-10 minutes (not counting potential questions from the audience). Presentations that are substantially
shorter (less than 6 minutes) will result in a deduction of 2 marks. Content that is substantially longer (more than 12 minutes) may not be
considered in the marking.
Failure to format the references in APA
style (up to –3 marks)
–
All references need to be formatted in APA referencing style (American Psychological Association; https://apastyle.apa.org). This holds both
for the list of references and for in-text references.
Late penalty (–2 marks for each day or
part of day that the submission is late)
–
The mark will be reduced by 10% of the possible maximum mark for that assessment item for each day or part day that the assessment item is
late (in cases without an approved extension of time).
SACO Penalty
–
There is a fine line between poor referencing and plagiarism. Submissions that appear to be plagiarised will be referred to the Student
Academic Conduct Officer (SACO), with possible outcomes such as a mark of zero for the entire submission. Students are strongly advised to
repeat the University’s Academic Integrity Module, and to be sure never to take text, ideas, or images from anywhere without clearly noting
the source.
TOTAL
/30
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