Tutorial Presentation

10/1/22, 2:59 PM Assessment 2: Tutorial Presentation
https://canvas.newcastle.edu.au/courses/20984/assignments/180378 1/5
Assessment 2: Tutorial Presentaঞon 30 Possible Points
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Assessment 2
Tutorial Presentation

Assessment Type
Presentaঞon

Descripঞon
This assessment encourages students to expand and deepen their conceptual
knowledge of big data within real-world applicaঞons (e.g., business, health). They do
this through discussion of a data analyঞcs concept (e.g. big data framework, data
visualisaঞon, natural language processing) in pracঞce. In their presentaঞon, they are
required to provide evidence that they have researched the concept extensively using
informaঞon resources such as academic journals, professional press and the popular
media. It is expected that they will demonstrate both reflecঞon and analysis related to
the data analyঞcs concept
posed, and produce an arঞculate and concise response conveying evidence-based
understanding of the concepts and topics.

Weighঞng
30%

Due Date
During labs (Weeks 8 to 11)

Submission Method
In Class

Assessment Criteria
See Canvas

Return Method
Online

Feedback Provided
Online

This folder contains the specificaঞon of the assessment item 2. Over the course of the trimester, a list of topics and
presentaঞon slots will be added.
Important: This is an individual assessment item. Hence, while we use the group funcঞon to make it easier to select
presentaঞon slots and topics, you will need to prepare and deliver your presentaঞon as an individual assessment
item (as per the assessment specificaঞon and the course outline). Hence, in case two students choose the same topic
for the presentaঞon in any parঞcular week, these will have to be two completely separate presentaঞons with
absolutely no interacঞon and no collaboraঞon between the students. This is not a group assessment item.
Additional Resources
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ps://canvas.newcastle.edu.au/courses/20984/modules/items/919913)
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assignment
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10/1/22, 2:59 PM Assessment 2: Tutorial Presentation
https://canvas.newcastle.edu.au/courses/20984/assignments/180378 2/5
This assessment encourages students to expand and deepen their conceptual knowledge of big data within realworld applicaঞons (e.g., business, health). They do this through discussion of a data analyঞcs concept (e.g. big data
framework, data visualisaঞon, natural language processing) in pracঞce. They do this by means of an individual
presentaঞon (not a group presentaঞon). In their presentaঞon, students are required to provide evidence that they
have researched the concept extensively using informaঞon resources such as academic journals, professional press
and the popular media. It is expected that they will demonstrate both reflecঞon and analysis related to the data
analyঞcs concept posed, and produce an arঞculate and concise response conveying evidence-based understanding of
the concepts and topics.
Important: This is an individual assessment item. Hence, while we use the group funcঞon to make it easier to select
presentaঞon slots and topics, you will need to prepare and deliver your presentaঞon as an individual assessment
item (as per the assessment specificaঞon and the course outline). Hence, in case two students choose the same topic
for the presentaঞon in any parঞcular week, these will have to be two completely separate presentaঞons with
absolutely no interacঞon and no collaboraঞon between the students. This is not a group assessment item.
INFT6201 T3 2022 Assessment 2.pdf (h‚ps://canvas.newcastle.edu.au/courses/20984/files/3803784?wrap=1)
(h‚ps://canvas.newcastle.edu.au/courses/20984/files/3803784/download?download_frd=1)
(h‚ps://canvas.newcastle.edu.au/courses/20984/files/3742011/download?wrap=1)
Assignment 2: Topic List

Week
Topic List

Week
08
1. Simpson’s Paradox; 2. Berkson’s Paradox; 3. Survivorship Bias; 4. Spurious Correlaঞons

Week
09
1. Cartograms; 2. Geospaঞal Map Visualisaঞon (with Plotly); 3. Geospaঞal Map Visualisaঞon (with
GeoPandas); 4. Heat Maps; 5. Spider charts

Week
10
1. Edge Bundling; 2. Network Diagrams; 3. Black Swan Events; 4. Venn Diagrams; 5. Data Handling with
Regular Expressions

Week
11
1. Acঞon Recogniঞon; 2. Image Super-Resoluঞon; 3. Senঞment Analysis based on Text; 4. Web Scraping (e.g.
Scrapy); 5. Voice Emoঞon Recogniঞon (e.g. Librosa)

Overall Specification
View Rubric
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10/1/22, 2:59 PM Assessment 2: Tutorial Presentation
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Marking Criteria for Case Study Presentaঞon

Criteria
Raঞngs
Points

1) Data Analyঞcs
Concept: Background
on the data analyঞcs
concept with
references to the
literature.
view longer descripঞon
/ 5 pts
5 pts
High
Disঞncঞon
(HD)
Excellent
and well
balanced
explanaঞon
of the data
analyঞcs
concept.
4 pts
Disঞncঞon
(D)
Good.
Explanaঞon
and
discussion
of the data
analyঞcs
concept
with good
depth and
breadth.
3 pts
Credit (C)
Adequate.
Explanaঞon
and
discussion
of the data
analyঞcs
concept
showing
some depth
and breadth.
2 pts
Pass (P)
Superficial
explanaঞon
and
relaঞvely
shallow
elaboraঞon
of the data
analyঞcs
concept.
1 pts
Fail (F)
No or very
limited
explanaঞon
and shallow
elaboraঞon
of the data
analyঞcs
concept.

2) Pracঞcal Case
Study: Applicaঞon of
the data analyঞcs
concept to a specific
case study (including
dataset selecঞon,
python code, and
output).
view longer descripঞon
/ 10 pts
10 to >8 pts
High
Disঞncঞon
(HD)
Excellent
and well
described
case study
that clearly
illustrates
the
applicaঞon
of the data
analyঞcs
concept and
that is
underpinned
by highly
accurate
python code
on a suitable
dataset.
8 to >6 pts
Disঞncঞon
(D)
Good.
Explanaঞon
and
discussion
of the case
study show
good depth
and breadth
of the
applicaঞon
of the data
analyঞcs
concept.
The case
study is
underpinned
by accurate
python code
on a suitable
dataset.
6 to >4 pts
Credit (C)
Adequate.
Explanaঞon
and
discussion
of the case
study
provide
some depth
and breadth
into the
applicaঞon
of the data
analyঞcs
concept.
Limited
underpinnin
g by python
code on a
suitable
dataset.
4 to >2 pts
Pass (P)
Superficial
case study
that offers
only limited
illustraঞon
of the
applicaঞon
of the data
analyঞcs
concept and
that is
inadequately
underpinned
by code
and/or
builds on an
unsuitable
dataset.
2 to >0 pts
Fail (F)
No or very
superficial
case study
that only
provides a
very shallow
illustraঞon
of the data
analyঞcs
concept.

(h‚ps://canvas.newcastle.edu.au/courses/20984/modules/items/919913)
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assignment
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10/1/22, 2:59 PM Assessment 2: Tutorial Presentation
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Marking Criteria for Case Study Presentaঞon

Criteria
Raঞngs
Points

3) Applicaঞons in
Pracঞce: Discussion of
two or more example
applicaঞon areas of
the presented data
analyঞcs concept in
pracঞce.
view longer descripঞon
/ 5 pts
5 pts
High
Disঞncঞon
(HD)
Excellent
discussion
of further
applicaঞons
of the data
analyঞcs
concept in
pracঞce
with very
clear links to
the potenঞal
benefits.
4 pts
Disঞncঞon
(D)
Good
discussion
of further
applicaঞons
of the data
analyঞcs
concept in
pracঞce
with clear
links to the
potenঞal
benefits.
3 pts
Credit (C)
Adequate
discussion
of further
applicaঞons
of the data
analyঞcs
concept in
pracঞce.
2 pts
Pass (P)
Very limited
or overly
general
discussion
of further
applicaঞons
of the data
analyঞcs
concept in
pracঞce.
1 pts
Fail (F)
No or poorly
presented
and
discussed
examples for
further
applicaঞons
of the data
analyঞcs
concept in
pracঞce.

4) Overall quality of
presentaঞon: The
material is presented
in logical sequence
which audience can
follow. Students are
expected to speak
freely about the
subject with
confidence. The
presentaঞon should
be well-structured and
supported by media
files where
appropriate (e.g.,
figures, images). All
text should be clearly
readable and
grammaঞcally sound.
Please note that the
presentaঞon file
needs to include a
complete list of
references.
view longer descripঞon
/ 10 pts
10 to >8 pts
High
Disঞncঞon
(HD)
Excellent
quality of
language.
Very well
thought out
structure
with a
logical
sequence
that makes it
easy and
intriguing
for the
audience to
follow.
Excellent
use of media
files to
support the
presentaঞon
. P
resentaঞon
is delivered
speaking
freely and
with
confidence.
8 to >6 pts
Disঞncঞon
(D)
Good quality
of language.
Well
thought out
structure
with a
logical
sequence
that makes it
easy and
intriguing
for the
audience to
follow. Good
use of media
files to
support the
presentaঞon
. P
resentaঞon
is delivered
speaking
freely and
with
confidence.
6 to >4 pts
Credit (C)
Adequate
quality of
language.
Presentaঞon
has a
discernible
structure
and uses
media files
to support
the delivery
of the
content.
4 to >2 pts
Pass (P)
Mix of major
and minor
language
issues. Some
issues in the
structuring
of the
presentaঞon
and the use
of media
files. Some
issues in the
delivery of
the
presentaঞon
(e.g., mostly
reading from
a script).
2 to >0 pts
Fail (F)
Poor or no
structure,
many
language
issues. Poor
or no use of
media files.
Issues in the
delivery of
the
presentaঞon
(e.g., only
reading from
a script).

Total points: 0

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