COIT20249 Professional Skills Portfolio: FP1 & FP2 Case Study Analysis

This assignment analyzes professional skills within the context of Information and Communication Technology (ICT). The first part (FP1) critiques the importance of soft skills like communication and interpersonal abilities for ICT professionals, arguing against prioritizing technical skills exclusively. The second part (FP2) involves a case study analysis, focusing on reading strategies and academic integrity. It examines the use of machine learning in Australian businesses and highlights the importance of proper referencing and avoiding plagiarism. The assignment also includes an analysis of reading strategies used and provides examples of relevant research articles. The student demonstrates understanding of academic integrity policies by identifying and explaining instances of academic misconduct and suggests solutions. The assignment aims to develop professional skills relevant to ICT roles, emphasizing both technical proficiency and soft skills like communication and research methods.

PROFESSIONAL SKILLS
NAME
DATE

FP1
1. I do not agree at all with the statement that ICT students ought to focus on the improvement of
their technical skills at the expense of soft skills such as communication and interpersonal skills
premised on the fact that ICT professionals are tasked with writing programs. In the modern ICT
environment, ICT is more about people; ICT has become more people centered and so ICT
professionals require soft skills in order to effectively communicate with clients and team members.
ICT professionals involved with writing code or developing applications must clearly understand
client needs and this requires high level communication and interaction skills. Further, ICT projects
are now characterized by high level team work and collaboration, including in managing ICT
projects. Achieving these objectives do require high level soft skills to get teams motivated, to
effectively communicate requirements, obtain feedback, and work with diverse clients with equally
diverse needs and cultural, social, and cultural backgrounds. Developing ICT solutions that meet
client or organizational needs require soft skills such as determination to solve problems,
troubleshoot issues, and manage projects, creativity to develop forward thinking strategies,
flexibility, effective negotiation skills, presentation skills and leadership skills; all essential for
successful ICT careers
2
a. The text was located and read using effective reading strategies suitable for the subsequent tasks
b. The information contained in the paragraph cannot be located anywhere in the reference (the
article by Sun). While the paper discusses about machine learning (ML), there is nowhere in the text
where there is reference to Australian businesses, particularly, there is no mention or reference to
the percentage of Australian businesses that have implemented machine learning in their businesses.
The reference cannot support the above paragraph since while the reference discusses machine
learning, it is not in reference to Australia or the percentage of businesses implementing ML as
these are very specific empirical data that the article could not miss. Using the reference as done in
the paragraph constitutes a serious form of academic misconduct and malpractice because it
essentially implies the use of fictitious and misleading citations to reference a passage. It is
academic dishonesty and is a form of plagiarism to create or use wrong references in ones’ citations.
The specific offense as relates to the paragraph is Cheating under 3.26 of the CQU Student
Academic Integrity Policy and Procedure; the paragraph denotes deceitful behavior on the part of
the student (CQU, 2018).
c. Reading strategies
The reading strategies used in reading the above passage include:
Monitoring-clarifying is a reading strategy that involves thinking about the content one is reading as
well as how the content is being read both during the act of reading and after reading. The goal of

this strategy is to determine whether the reader is comprehending the text being read and be able to
fix and clarify any mix-ups in the content being read.
Searching-selecting is a reading strategy that entails searching sources or content within a reading
material with the goal of selecting suitable information to use in defining words, answering
questions, defining terms, solving problems, clarify misunderstandings, or just to gather information
(Cottrell, 2019). This method was especially appropriate in resolving the issue because the reader
was required to search and select passages or material in the referenced material similar in meaning
or similar grammar with the written and cited paragraph

FP2
 Case Study Analysis
In undertaking research, students are required to use appropriate strategies for reading in order to
find relevant material for use in their respective topic studies/ research topics. This means using
suitable search parameters, for instance, in the university digital library to find relevant content for
their topics. Relevance is set by the objectives of their research/ study topics: this should be
followed by using an appropriate reading strategy to determine relevant content that is then
referenced in the written work. This is done by complying with the CQU academic conduct
regulations by paraphrasing content to avid plagiarism while still retaining their meaning and
context, and then properly citing the used references in the written material. In the paragraph, the
student should have used articles relevant to the use of machine learning among Australian
businesses as references.
 Articles
Gouveia, M. (2017). Australian CIOs lead in machine learning adoption: Study - Which-50.
[online] Which-50.
In the article, the author alludes to the increasing use of machine learning among Australian
Companies, despite there being several barriers and the persons at the forefront in leading this
adoption are the CIOs. The article states that 89% of Australian CIOs were either already using ML
or had elaborate plans to start using it. One of the contributing factors to the businessesa dopting
ML is increased confidence in ML. H0owever, challenges remain, such as insufficient data quality,
a complex regulatory environment, and outdated processes. 59% of Australian CIOs reported lack
of technology funding as being a barrier as well (Gouveia, 2017).
Venture Insights (2017). AI in Financial Services: Who wins the future of banking? - Venture
Insights. [online] Venture Insights.
According to this article, the AI services market to financial services firms in Australia is rapidly
growing and is worth an estimated $ 117 million and is expected to rise to $ 367 million by 2021.
Many financial technology firms in Australia claim to be using AI (artificial intelligence)/ ML.
Australian banking firms are pursuing several AI strategies including ventures, partnerships, and in
house ML builds. ML is applied in Australian financial services in business process automation
(47%), gaining deep insights via data analysis (38%), and employee and customer engagement
(16%). However, Australia still lacks a deep bench of AI talent from start up (Venture Insights,
2017).
 Paraphrase
Machine Learning is a new exciting and actively developing field with several applications in
diverse industry sectors. It is gaining wide application in businesses in Australia with 83% of

businesses claiming to have implemented ML applications in one form or the other . The various
ML types are explored in this article, including its applications in electronic commerce, education,
the transport sector. Along with this, the legal, ethical, and social aspects of ML applications are
also explored and thereafter, personalized recommendations given on how ML can successfully be
used by online retail stores.

References
Cottrell, S. (2019).The study skills handbook. 5th ed. London: Macmillan, p.63.
CQU (2018).CQU Student Academic Integrity Policy and Procedure. 2nd ed. Brisbane: CQU, pp.4-
5.
CQU (2018). CQU Student Academic Integrity Policy and Procedure. 2nd ed. Brisbane: CQU,
pp.4-5.
Gouveia, M. (2017). Australian CIOs lead in machine learning adoption: Study - Which-50.
[online] Which-50. Available at: https://which-50.com/australian-cios-lead-machine-learning-
adoption-study/ [Accessed 10 Aug. 2019].
Venture Insights (2017). AI in Financial Services: Who wins the future of banking? - Venture
Insights. [online] Venture Insights. Available at: https://www.ventureinsights.com.au/product/ai-in-
financial-services/ [Accessed 10 Aug. 2019].