It is a known fact that any update in the history of educational sector has always been a positive impact in the livelihood of people towards technology. Our project is one such a kind where rating essays is the major criteria we want to work on. Essay evaluation is considered as a systematic way to give rating to the essays written. Automatic essay scoring is a process of grading essays without human intervention. The computer systems are trained using technical, artificial intelligence architectures where natural language processing comes into picture. The process of making machine resembles to the human intelligence and to work, as if as a human could is the main motive of natural language processing. Under this criterion, we have chosen a part of educational preview to build a system that is capable of rating written work, namely essays. Our project aims to provide a solution that evaluates essays as an automatic process. The basic idea here is to develop a software system that can be beneficial to educational institutions, business organizations, researchers, etc. Automatic essay scoring has a powerful gain over making it work, because it helps in reduction of manual work, gives a scope for every element without bias, also act as a key role in being time-efficient. There are past approaches in finding a way to develop an automated system to score essays using regression analysis, convolution neural networks, while we worked through transformer-based model, named BERT.

1.
Nguyen
,
H.
, &
Dery
,
L.
,
Neural networks for automated essay grading
.
CS224d Stanford Reports
,
1
11
. (
2016
).
2.
Taghipour
,
K.
, &
Ng
,
H. T.
,
A neural approach to automated essay scor-ing
.
In Proceedings of the 2016 conference on empirical methods in natural language pro-cessing
(
2016
), pp.
1882
1891
.
3.
Sharma
,
C.
,
Bishnoi
,
A.
,
Sachan
,
A. K.
, &
Verma
,
A.
Automated Essay Evaluation using Natural Language Processing.
, (
2019
).
4.
Burstein
,
J.
, &
Chodorow
,
M.
,
Automated essay scoring for nonnative English speakers
.
In Computer mediated language assessment and evaluation in natural language processing
, (
1999
).
5.
Kakkonen
,
T.
,
Myller
,
N.
,
Timonen
,
J.
, &
Sutinen
,
E.
Automatic essay grading with probabilistic latent semantic analysis
.
In Proceedings of the second workshop on Building Educational Applications Using NLP
, (
2005
), pp.
29
36
).
6.
Sheshikala
,
M.
,
Ramesh
,
D.
,
Mohmmad
,
S.
and
Pasha
,
S.N.
, An Enhanced Approach to Predict Re-occurrences of Breast Cancer Using Machine Learning. In
Proceedings of Third International Conference on Communication, Computing and Electronics Systems
,
Springer
,
Singapore
, (
2022
), pp.
107
117
.
7.
Hearst
,
M. A.
The debate on automated essay grading
.
IEEE Intelligent Systems and their Applica-tions
,
15
(
5
),
22
37
, (
2000
).
8.
Mothe
,
R.
,
Tharun
Reddy
, S.,
Vijay
Kumar
, B.,
Rajeshwar
Rao
, A. and
Chythanya
,
K.R.
,
A Review on Big Data Analytics in Internet of Things (IoT) and Its Roles, Applications and Challenges
.
ICDSMLA 2020
, pp.
765
773
.
9.
Landauer
,
T. K.
,
Automatic essay assessment. Assessment in education: Principles, policy & prac-tice
,
10
(
3
),
295
308
, (
2003
).
10.
Sheshikala
,
M.
,
Kothandaraman
,
D.
and
Roopa
,
G.
,
Natural language processing and machine learning classifier used for detecting the author of the sentence
.
International Journal of Recent Technology and Engineering
,
8
(
3
), (
2019
). pp.
936
939
.
11.
Zupanc
,
K.
, &
Bosnic
,
Z.
,
Advances in the field of automated essay evaluation
.
Informatica
,
39
(
4
), (
2016
).
12.
Reilly
,
E. D.
,
Stafford
,
R. E.
,
Williams
,
K. M.
, &
Corliss
,
S. B.
Evaluating the validity and applicability of automated essay scoring in two massive open online courses
.
International Review of Research in Open and Distributed Learning
,
15
(
5
),
83
98
, (
2014
).
13.
Mothe
,
R.
,
Tharun
Reddy
, S.,
Chythanya
,
K.R.
and
Supraja
Reddy
, Y.,
Challenges, open research issues and tools in bigdata analytics
.
Int J Recent Technol Eng
,
8
(
11
),
2634
2641
, (
2019
).
14.
Shermis
,
M. D.
, &
Burstein
,
J.
,
Handbook of automated essay evaluation.
NY
:
Routledge
, (
2013
).
15.
Valenti
,
S.
,
Neri
,
F.
, &
Cucchiarelli
,
A.
An overview of current research on automated essay grad-ing
.
Journal of Information Technology Education: Research
,
2
(
1
),
319
330
, (
2003
).
16.
Warschauer
,
M.
, &
Ware
,
P.
Automated writing evaluation: Defining the classroom research agen-da
.
Language teaching research
,
10
(
2
),
157
180
, (
2006
).
17.
Balasundaram
,
A.
,
Ashokkumar
,
S.
and
Kothandaraman
,
D
,
Seena
Naikkora
. In
E
Sudarshan
and
A
Harshaverdhan
, “
Computer vision based fatigue detection using facial parameters, IOP Conference Series: Materials Science and Engineering
”,
981
(
2
),
2020
, pp.
022005
.
18.
A
Balasundaram
,
D
Kothandaraman
,
S
Ashokkumar
,
E
Sudarshan
,
Chest X-ray image based COVID prediction using machine learning
,
AIP Conference Proceedings
,
2418
(
1
),
2022
, pp.
020079
, .
19.
Sheshikala
,
M.
,
Rao
,
D.R.
and
Prakash
,
R.V.
,
Parallel approach for finding co-location pattern–a map reduce framework
.
Procedia Computer Science
,
89
, pp.
341
348
, (
2016
).
20.
Mothe
,
R.
,
Reddy
,
S.T.
,
Sunil
,
G.
and
Sidhardha
,
C.
,
An IoT based obstacle avoidance robot using ultrasonic sensor and arduino
. In
IOP conference series: materials science and engineering
,
981
(
4
),
2020
, pp.
042002
.
21.
Dasgupta
,
T.
,
Naskar
,
A.
,
Dey
,
L.
, &
Saha
,
R.
Augmenting textual qualitative features in deep con-volution recurrent neural network for automatic essay scoring
.
In Proceedings of the 5th Workshop on Natural Language Processing Techniques for Educational Applications
,
2018
, pp.
93
102
.
22.
Chen
,
H.
, &
He
,
B.
Automated essay scoring by maximizing human-machine agreement
.
In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing
,
2013
, pp.
1741
1752
.
23.
Phandi
,
P.
,
Chai
,
K. M. A.
, &
Ng
,
H. T.
,
Flexible domain adaptation for automated essay scoring using correlated linear regression
.
In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing
(
2015
), pp.
431
439
.
24.
Mothe
,
R.
,
An Overview of IOT towards Irrigation System
.
Indian Journal of Public Health Research & Development
,
9
(
11
), (
2018
)
25.
Sheshikala
,
M.
,
Rao
,
D.R.
and
Prakash
,
R.V.
,
Computation Analysis for Finding Co–Location Patterns using Map–Reduce Framework
.
Indian Journal of Science and Technology
,
10
(
8
), pp.
7108
7110
. (
2017
).
26.
M
Sheshikala
,
Sallauddin
Mohmmad
,
D
Kothandaraman
,
Dadi
Ramesh
,
Ranganath
Kanakam
, Emotion Recognition Based on Streaming Real-Time Video with Deep Learning Approach,
Computer Communication, Networking and IoT
,
Springer
,
Singapore
,
2023
, pp.
393
401
.
27.
Mendu
,
M.
,
Krishna
,
B.
,
Sandeep
,
C.H.
,
Mahesh
,
G.
,
Pallavi
,
J.
Development of real time data analytics based web applications using NoSQL databases
2022
AIP Conference Proceedings
2418
020038
, .
28.
Karre
R.K.
,
Srinivas
K.
,
Mannan
K.
,
Prashanth
B.
,
Prasad
C.R.
A review on hydro power plants and turbines
2022
AIP Conference Proceedings
2418
30048
29.
Kishan
P.A.
,
Sandeep
C.H.
,
Tirupathi
V.
,
Syed Nawaz
M.D.
,
Sudarshan
E.
Time-lined capturing & delivering of events with SVG & audio overlays: An interactive & versioned content delivery
2022
AIP Conference Proceedings
2418
20075
30.
Murthi
P.
,
Poongodi
K.
,
Rajasri Reddy
I.
Effect of bacteria on strength and porosity of M-sand based pumpable concrete
2020
IOP Conference Series: Materials Science and Engineering
981
3
32078
31.
Rajasri Reddy
I.
,
Reddy
C.V.K.
,
Rao
Y.V.D.
,
Chandra Shekar
A.
Comparison of Tests for Isomorphism in Planetary Gear Trains
2020
IOP Conference Series: Materials Science and Engineering
981
4
42023
32.
Rashmi
S.M.
,
Rajesh Kumar
K.
,
Akki
B.
,
Rajasri Reddy
I.
Performance Studies on white topping layers over flexible pavement
2020
IOP Conference Series: Materials Science and Engineering
981
3
32076
33.
Reddy
Ch.V.K.
,
Rajasri
I.
,
Mahesh
V.
Comparison between hamming method and modified path matrix approach to identify isomorphism in PGTs
2020
Materials Today: Proceedings
39
66
69
34.
Sammaiah
P.
,
Chaitanya Krishna
D.
,
Sai Mounika
S.
,
Rajasri Reddy
I.
,
Karthik
T.
Effect of the Support Structure on Flexural Properties of Fabricated Part at Different Parameters in the Fdm Process
2020
IOP Conference Series: Materials Science and Engineering
981
4
42030
35.
Kanakam
R.
,
Mohmmad
S.
,
Sudarshan
E.
,
Shabana
,
Gopal
M.
A survey on approaches and issues for detecting sarcasm on social media tweets
2022
AIP Conference Proceedings
2418
20045
36.
Kumaraswamy
E.
,
Mahender
K.
,
Prasad
C.R.
,
Govardhan
N.
,
Yadav
B.P.
Digital watermarking techniques: Comparative analysis and robustness for real time applications
2022
AIP Conference Proceedings
2418
30070
37.
Kumaraswamy
E.
,
Mahesh Kumar
G.
,
Mahender
K.
,
Bukkapatnam
K.
,
Prasad
C.R.
Digital Watermarking: State of the Art and Research Challenges in Health Care & Multimedia Applications
2020
IOP Conference Series: Materials Science and Engineering
981
3
32031
38.
Prashanth
B.
,
Krishna
D.B.
,
Balasundaram
A.
,
Tejaswi
B.
,
Govardhan
N.
Implementation patterns of high performance machine learning algorithms using Apache Mahout
2022
AIP Conference Proceedings
2418
20044
39.
Prashanth
B.
,
Krishna
D.B.
,
Shaik
M.A.
,
Tejaswi
B.
,
Kiran
K.R.
Optimization factors with high performance computing and data science based implementations with metaheuristics
2022
AIP Conference Proceedings
2418
20043
40.
Prashanth
B.
,
Neelima
G.
,
Dule
C.S.
,
Chandra Prakash
T.
,
Tarun Reddy
S.
Data Science and Machine Learning Integrated Implementation Patterns for Cavernous Knowledge Discovery from COVID-19 Data
2020
IOP Conference Series: Materials Science and Engineering
981
2
22004
41.
Shaik
M.A.
,
Manoharan
G.
,
Prashanth
B.
,
Akhil
N.
,
Akash
A.
,
Reddy
T.R.S.
Prediction of crop yield using machine learning
2022
AIP Conference Proceedings
2418
20072
42.
Sravanthi
T.
,
Hema
V.
,
Tharun Reddy
S.
,
Mahender
K.
,
Venkateshwarlu
S.
Detection of Mentally Distressed Social Media Profiles Using Machine Learning Techniques
2020
IOP Conference Series: Materials Science and Engineering
981
2
22056
43.
Sudarshan
E.
,
Kumari
D.A.
,
Reddy
Y.C.A.P.
,
Balasundaram
A.
,
Mahender
K.
Machine learning based automatic vehicle alert system
2022
AIP Conference Proceedings
2418
20058
44.
Sudarshan
E.
,
Naik
K.S.
,
Kumar
P.P.
Parallel approach for backward coding of wavelet trees with CUDA
2020
ARPN Journal of Engineering and Applied Sciences
15
9
1094
1100
This content is only available via PDF.
You do not currently have access to this content.