NEF6002 Research Proposal: Big Data Analytics in Higher Studies

This report presents a research proposal focused on the application of big data analytics to improve the academic performance of students in higher education. The proposal begins with an introduction to the topic, defining key terms and highlighting the significance of big data in various industries and its potential benefits in education. It provides a research project background by reviewing relevant literature, discussing the evolution of big data technology, its advantages, and its limitations in the context of higher studies. The proposal outlines specific research problems, including factors to consider before implementing big data, limitations, and data security concerns. The research methodology involves text, video, audio and social media analytics, NLP techniques, and model simulation software. The research aims to understand the impact of big data on student performance, data management, and the overall educational environment. The proposal also includes a research planning section, outlining the duration and resources required for each task, and concludes by emphasizing the significance of the research and its potential to enhance student outcomes.

Running head: BIG DATA ANALYTICS TO IMPROVE ACADEMIC PERFORMANCE
Big Data Analytics to improve academic performance
Enter: Name of the Student
Enter: Name of the University
Author Note

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Table of Contents
1. Introduction............................................................................................................................2
2. Research project background.................................................................................................2
3. Research problems.................................................................................................................5
4. Research methodology...........................................................................................................6
5. Research significance.............................................................................................................7
6. Conclusion..............................................................................................................................7
7. Research Planning..................................................................................................................8
8. Reference................................................................................................................................9

2BIG DATA ANALYTICS TO IMPROVE ACADEMIC PERFORMANCE
1. Introduction
The notable determination of this project proposal is to focus on the impact of big
data technology on the academic performance of the students of higher studies.
It is one of the increasingly used technologies in numerous industries like IT industry
as well as for personal benefits like higher studies.
This research proposal will be very much significant as compared with the other
researches as big data technology are increasingly deployed both in our society as well as in
commercial establishments. This technology has numerous benefits associated with it in
terms of keeping the raw data as well as the structured data in a systemized manner.
This proposal was incorporated after 2005, numerous business intelligence tools can
be associated with this technology as well as it can bring transparency in the entire data
management procedure.
Considering the recent IT innovations it can be said that this technology is one of the
fastest growing technology among the other technologies like Artificial Intelligence and
Cloud Computing.
2. Research project background
Improvement of academic performance
As discussed by Calli et al. (2015), data management is one of the most significant
specification provided by big data technology. This paper successfully highlighted that this
specification can be very much significant to maintain transparency in data management. The
paper suggested that higher studies usually contains both raw data and semi structured data,
each of these two categories of data can be managed, monitored and assessed using this
technology.

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However as instructed by Carraher and Steinberg (2017), the introduction of the big
data technology have a few limitations associated with it in terms of the changing pattern of
studying and study material. The lecture notes, approach of the study keeps on changing
every moment and it is a serious concern regarding the introduction of the big data
technology. The paper suggested that big data technology has to be successfully evaluated on
a regular basis so that there are very less inconsistencies associated with the data management
capability required for higher studies (Selwyn 2016). The paper highlighted that online
conferences can be maintained in an organized manner using this technology as well.
Positives and negative of the technology in higher studies
As instructed by Dubey and Gunasekaran (2015), big data technology can provide
many new opportunities for the studies of higher studies. The paper suggested that the e-
learning materials are mostly semi structured in nature these semi structured data can be
easily managed using this technology. This paper also recommended that categorization of
the data of each of the subjects in the high studies can be done using system which uses big
data technology. The paper suggested that decision making is very much significant for most
of the students who are pursuing their high studies and the introduction of this technology can
have a huge impact on the decision making ability of the students.
However, as deliberated by Hogan (2019), students of the higher studies must be
aware of the limitations associated with big data technology in terms of the structural changes
of the technology. The paper emphasised the limitations of deploying big data technology in
an organised manner such as the biasedness of the use data associated with this technology.
The paper was very much significant to understand that latest educational models which are
increasingly used in the higher studies can use big data technology, at the same time it can
also be said that customised curricula of the higher studies can be huge supported by big data

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technology (Xu et al. 2015). Understanding behaviour of a new model in the research labs
can be improved significantly due to the introduction of the big data technology. New
learning plans can be created using big data systems as instructed by the researchers of this
data source. The paper also suggested that the instructional records, online discussions, and
data from the feedback forums are very much significant in the higher studies and each of
these can be very much significant to enhance the academic performance of the students.
This paper stated that the students as well as tutors of the higher studies can be significantly
affected using the specifications provided by this technology.
Specific impact of the technology
According to Huda et al. (2018), feedback from the tutors can be organized in a better
modus using the big data technology; at the same time, personalization of the data can have a
huge impact on the students of higher studies as it can contribute to enhance the performance
of the students of higher studies. This paper also deliberated that the deployment of big data
technology can be very much significant for prediction performances. The paper suggested
that mapping is very much significant for most of the students of higher studies and the
concept of mapping can be enhanced and re-examined in an organized manner using this
technology as well.
This research paper is very much significant as it will highlight both the positives as
well as the negative of deploying big data technology to improve the academic performance
of the students of higher studies.
Methodologies, tools hardware software
As discussed by Reyes (2015), machine learning ability of the advanced computer
systems are increasingly due to the usage of methodologies like Naïve Base Classifier, K-
Means clustering, decision trees, text analytics and time series. The paper suggested that there

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are many new tools such as Apache storm and Hadoop uses the concept of big data and each
of these tools can be deployed by the students of the higher studies to enhance their academic
performance. This paper helped in understanding that diverse categories of software are
increasingly used by the students of the higher studies in order to enhance their academic
performance like Google Big-data. The paper also highlighted about the usability and role of
the big data hardware vendors like Oracle which can be very much significant in order to
enhance the academic performance (Wang 2016). The future trending research about this
technology was also discussed in this paper in terms of the security of the data which are
already process and refined using this technology. Thus, the inconsistencies of entire
education procedure of higher studies can be reviewed and re-examined using this technology
as well (Selwyn 2015). The unpredictable outcomes of the essential data is about to be
minimised in the coming years as stated by the investigators of this paper. Data breaching
activity and the concept of plagiarism can be successfully avoided in the coming if this
technology is successfully introduced in higher studies.
3. Research problems
Co-relation between each of the data sets has to be set by the students of the higher
studies in order to improve the specifications of this technology. Changes in the education
polices in higher studies also needs to be improvised in the systems which uses big data
technology. This one of the most significant contemporary settings associated with this
technology.
The research problems of this proposal are listed as followings:
 What factors are needed to be considered before considering this technology to
improve the academic performance?

6BIG DATA ANALYTICS TO IMPROVE ACADEMIC PERFORMANCE
 Which uncovered factors can limit the advantages of this technology in the higher
studies?
 How can the data security issue of data of the higher studies maintained?
Based on the literature review it can be said that there are many new opportunities
associated with this technology in terms of its association with other technologies like
artificial intelligence which can be very much useful to improve the academic performance of
the higher school students.
Configuration of the systems using big data technology has to be revised according to the
new education concepts and ideologies (Sun et al. 2016). These opportunities and need for
changes can be understood from the following section of this proposal
4. Research methodology
The research problems which has to be studied in this proposal is to identify the
factors which has to be considered while incorporating this technology in higher studies and
the ways to maintain security of the new data.
Based on the research project part A it can be stated that each of these factors which
can have an impact on this technology shall be evaluated in the literature view of this
proposal.
Text analytics, video analytics, audio analytics and social media content analytics
have been considered in the part A of this assignment. Data from each of those analytics
method were very much significant to identify the solutions of the identified research
questions. The data from each of the analytics methods will be evaluated using NLP (Sin and
Muthu 2015). The Large Vocabulary Continuous Speech Recognition (LVCSR) was also

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used in order to study the data collected from primary data collection procedure. The video
analytics considered the use of video transcripts from were data was analysed.
The independent variable associated with this research is the impact of big data and
the dependent variable of this project is the higher studies where this technology can have a
huge impact.
Model simulation software was considered in this research as it helped to check the
estimators and characteristics of the entire estimation procedure. Estimation of the model
parameters can also be calculated using this simulation procedure.
Model simulation software like GNU Octave can be very much significant in the
entire data simulation procedure of this proposal.
5. Research significance
This research is very much significant to understand the positives of big data in higher
studies. The literacy rate of the country and the data management procedure can also be
reviewed as per the discussion made in the literature review unit of this proposal. The entire
educational environment considering the students and teachers can also be significant
improved as per the contributions of big data which are discussed in the literature review unit
of this proposal.
Unlike other research paper this paper have critically analysed both the positives and
negative and also the uncertainties of this technology.
6. Conclusion
The uncertainties of the data management for the students of the higher studies can be
purposefully minimised if big data is successfully introduced in the educational facility. This
proposal also helped in understanding that both the raw data and the semi structure data from

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the university can be easily understood by the academic students using the big data
technology. This proposal also helps in concluding that participation of the students can be
improved after using this technology.
It can also be found that the incorporation of the big data technologies can also be
very much useful to address the changing pattern of study and study materials of the higher
studies.
7. Research Planning
Task Name Duration Start Finish Resource Names
Introduction of the topic Week6 03.09.2018 09.09.2018 Internet sources
Identification of the research
objectives
Week7 10.09.2018 20.09.2018 Researcher
Identification of research
problems
Week8 21.09.2018 22.09.2018 Researcher
Selection of research
methodology
Week9 23.09.2018 30.09.2018 Researcher
Identification of variables Week10 01.10.2018 10.10.2018 Researcher
Implementation of the
research methodology
Week11 15.10.2018 20.10.2018
Large Vocabulary
Continuous Speech
Recognition
Identification of research
significance
Week
12
25.10.2018 30.10.2018 Researcher

9BIG DATA ANALYTICS TO IMPROVE ACADEMIC PERFORMANCE

10BIG DATA ANALYTICS TO IMPROVE ACADEMIC PERFORMANCE
8. Reference
Calli, B., Singh, A., Walsman, A., Srinivasa, S., Abbeel, P. and Dollar, A.M., 2015, July. The
ycb object and model set: Towards common benchmarks for manipulation research. In 2015
international conference on advanced robotics (ICAR) (pp. 510-517). IEEE.
Carraher, S.M. and Steinberg, H., 2017, April. BIG DATA & STRATEGIC LEARNING IN
EDUCATION. In Allied Academies International Conference. Academy of Educational
Leadership. Proceedings (Vol. 22, No. 1, p. 1). Jordan Whitney Enterprises, Inc.
Dubey, R. and Gunasekaran, A., 2015. Education and training for successful career in big
data and business analytics. Industrial and Commercial Training, 47(4), pp.174-181.
Hogan, A., 2019. Review of Ben Williamson (2017). Big Data in Education: the Digital
Future of Learning, Policy and Practice. Postdigital Science and Education, pp.1-4.
Huda, M., Maseleno, A., Atmotiyoso, P., Siregar, M., Ahmad, R., Jasmi, K. and Muhamad,
N., 2018. Big data emerging technology: insights into innovative environment for online
learning resources. International Journal of Emerging Technologies in Learning (iJET),
13(1), pp.23-36.
Reyes, J.A., 2015. The skinny on big data in education: Learning analytics simplified.
TechTrends, 59(2), pp.75-80.
Selwyn, N., 2015. Data entry: towards the critical study of digital data and education.
Learning, Media and Technology, 40(1), pp.64-82.
Sin, K. and Muthu, L., 2015. APPLICATION OF BIG DATA IN EDUCATION DATA
MINING AND LEARNING ANALYTICS--A LITERATURE REVIEW. ICTACT journal
on soft computing, 5(4).

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Sun, A., Ji, T., Wang, J. and Liu, H., 2016. Wearable mobile internet devices involved in big
data solution for education. International Journal of Embedded Systems, 8(4), pp.293-299.
Wang, Y., 2016. Big opportunities and big concerns of big data in education. TechTrends,
60(4), pp.381-384.
Xu, J., Huang, E., Chen, C.H. and Lee, L.H., 2015. Simulation optimization: A review and
exploration in the new era of cloud computing and big data. Asia-Pacific Journal of
Operational Research, 32(03), p.1550019.
Selwyn, N., 2016. Education and technology: Key issues and debates. Bloomsbury
Publishing.