Data Science in Education

1. DATA SCIENCE
IN EDUCATION
ATHENA S JOSEPH
2137035
M A APPLIED ECONOMICS

2. WHAT IS DATA
SCIENCE?
Data science is the field of study that combines
domain expertise, programming skills, and
knowledge of mathematics and statistics to
extract meaningful insights from data. Data
science practitioners apply machine
learning algorithms to numbers, text, images,
video, audio, and more to produce artificial
intelligence (AI) systems to perform tasks that
ordinarily require human intelligence. In turn,
these systems generate insights which analysts
and business users can translate into tangible
business value.

3. WHY DATA
SCIENCE IS
IMPORTANT?
More and more companies are coming to realize the
importance of data science, AI, and machine learning.
Regardless of industry or size, organizations that wish to
remain competitive in the age of big data need to
efficiently develop and implement data science
capabilities or risk being left behind.

5. DATA SCIENCE IN THE EDUCATION
1. Educational data science will assist and train 'educators' or 'teachers' in order
for them to improve their teaching style and have a better understanding of
numerous strategies that engage students more.
2. Educators will be encouraged to incorporate data visualisation, data reduction
and description, and prediction challenges into their curricula.
3. Data minimization will streamline the grading and assignment processes for
students.
4. The data visualisation technique will assist students in absorbing complex data
in a more simple manner and will be taught through a narrative approach.

6. APPLICATIONS OF DATA SCIENCE IN EDUCATION
1. Student Assessment Data
The post-pandemic period has opened the window of online classes but the
question of effective learning among the students is a deep concern. Thus, to
comprehend the many variables such as the number of pupils who are attentive,
participating, or when a student loses interest, and so on. Everything may be
evaluated in real time with Big Data Analytics. Teachers can use this application to
assess their students and then improvise and strategize for their next class.

7. 2. Social and Behavioural Skills
There are numerous data science tools available that assist
teachers in determining whether kids are able to use their social
skills throughout class. It enables the teacher to recognise
children who are unable to connect with or interact
appropriately with peers or their behaviour. Teachers expect
their pupils to behave responsibly, even if their classes are not
delivered in a formal manner. This is where data science in
education comes into play, as it enables pupils to further
develop their whole personality. Additionally, teachers will be
able to devote additional time to pupils who require 'assistance'
and conduct sessions with counsellors or therapists.

8. 3. Student’s Demographics
From an organisational standpoint, data science in education is critical since various methodologies
will help organisations enhance and change their current leadership methods. They will be aware of
specific places that require modification, replacement, or repair. Then educational institutions
(schools, colleges, and private educational institutions) will be able to plan and implement their
missions more effectively.

9. THE UNIVERSITY OF FLORIDA – USING BIG DATA
ANALYTICS TO MITIGATE STUDENT DROPOUT
• IBM InfoSphere is used by the University of Florida to extract, load, and transfer
data from a variety of sources.Additionally, predictive analytics and data
modelling are performed using IBM SPSS Modeler. It integrates these two
systems with IBM Cognos Analytics.IBM Cognos is a robust, web-based business
intelligence solution that includes a variety of tools for reporting, evaluating, and
monitoring events via interactive visualisations. The university can assess and
forecast student performance using IBM Cognos Analytics.It assesses pupils'
dropout probability using a variety of criteria such as their background,
demographics, high school grades, and economic background. As a result, it will
aid the university in developing policies and intervening early with students on
the edge of dropping out.

10. CIVITAS
Civitas Learning delivers an intelligence platform for student achievement that
includes academic and career planning, student support, efficacy evaluation, and
data-informed advisors.Texas State University's enrollment boom necessitated
scaling up its registration and planning processes for incoming freshman classes.
TSU utilised Civitas' Schedule Planner, which enabled them to generate reports that
compared incoming students to available seats in required courses. In total, it takes
around two days for three administrators to register thousands of freshman
students.

11. CONCLUSION
• Internationally, education policies are always changing and should
be supported by each country's government. The government
must recognise that data science in education will be an integral
element of this 'new normal' way of living.
• As a result, it is critical to promote lifelong learning, provide
teacher education programmes, and organise workshops on data
protection for teachers and students alike.
• This is a transformative and wonderful step for our future
generations, which will reciprocate. Countries shall develop
mutually beneficial connections aimed at fostering academia-
industry collaboration in the pursuit of a prosperous and
progressive future.