Dr. Deepak K. Sinha has over 10 years of experience as an Assistant Professor and Associate Professor. He received his Ph.D. in Computer Science in 2011 from M.U. Bodh Gaya. His research focuses on pointer free codes to build complex data structures. He has published papers on topics like ticketing systems, cloud computing, and cybercrime investigations. Currently he is an Assistant Professor at Jimma Institute of Technology in Ethiopia.
Moodle Platform to Support Interactive eLearning at GJUOpenMed Project
Presentation of Moodle Platform to Support Interactive eLearning at GJU (by Mohammad Daoud, German Jordanian University), Jordan OER Strategy Forum in Amman, Jordan, February 28, 2017
Moodle Platform to Support Interactive eLearning at GJUOpenMed Project
Presentation of Moodle Platform to Support Interactive eLearning at GJU (by Mohammad Daoud, German Jordanian University), Jordan OER Strategy Forum in Amman, Jordan, February 28, 2017
Online Intelligent Semantic Performance Based Solution: The Milestone towards...AM Publications
As we analyse the computer application undergraduate logical-based courses in an assorted
environment of online assignments and exams and offline lectures, and exhibit the impact on academic routine of
factors such as classroom attendance, web-based course complement, and homework. We present grades from both
ordinary front ends and where the latter method controls for unobserved variation among students. A system
tailored intelligent instructional evaluation will generate the students, teachers & administration concepts,
discussing the predisposition in estimation when the ordinary evaluation method is used, resulting from the fact
that it ignores unobserved assorted. It also reduces the administrator’s load and helps provide the flexibility to
teacher’s need for mass evaluation. The Online Intelligent Semantic Performance based Solution is web
applications that ascertain an association between the institutes and the students. Institutes enter on the site, the
concepts they want in the exam. The questions based on the relevant concept and the syllabus is displayed as a test
to the eligible students. The answers entered by the students are then evaluated and their score is calculated and
saved. This score then can be accessed by the institutes to determine the passes students or to evaluate their
performance. It has been successfully applied to the distance evaluation of basic operating skills of computer
science, such as the course of computer skills in Universities and the local examination for the under graduates in
faridabad, Haryana.
Data science for digital culture improvement in higher education using K-mean...IJECEIAES
This study aims to investigate the meaningful pattern that can be used to improve digital culture in higher education based on parameters of the technology acceptance model (TAM). The methodology used is the data mining technique with K-means algorithm and text analytics. The experiment using questionnaire data with 2887 respondents in Universitas Islam Negeri (UIN) Sunan Gunung Djati Bandung. The data analysis and clustering result show that the perceived usefulness and behavioral intention to use information systems are above the normal value, while the perceived ease of use and actual system use is quite low. Strengthened with text analytics, this research found that the EDA and K-means result in harmony with the hope or desire of academic society the information system implementation. This research also found how important the socialization and guidance of information systems, especially the new one information system, in order to improve digital culture in higher education.
Student Performance Evaluation in Education Sector Using Prediction and Clust...IJSRD
Data mining is the crucial steps to find out previously unknown information from large relational database. various technique and algorithm are their used in data mining such as association rules, clustering and classification and prediction techniques. Ease of the techniques contains particular characteristics and behaviour. In this paper the prime focus on clustering technique and prediction technique. Now a days large amount of data stored in educational database increasing rapidly. The database for particular set of student was collected. The clustering and prediction is made on some detailed manner and the results were produce. The K-means clustering algorithm is used here. To find nearest possible a cluster a similar group the turning point India is the performance in higher education for all students. This academic performance is influenced by various factor, therefore to identify the difference between high learners and slow learner students it is important for student performance to develop predictive data mining model.
Online Intelligent Semantic Performance Based Solution: The Milestone towards...AM Publications
As we analyse the computer application undergraduate logical-based courses in an assorted
environment of online assignments and exams and offline lectures, and exhibit the impact on academic routine of
factors such as classroom attendance, web-based course complement, and homework. We present grades from both
ordinary front ends and where the latter method controls for unobserved variation among students. A system
tailored intelligent instructional evaluation will generate the students, teachers & administration concepts,
discussing the predisposition in estimation when the ordinary evaluation method is used, resulting from the fact
that it ignores unobserved assorted. It also reduces the administrator’s load and helps provide the flexibility to
teacher’s need for mass evaluation. The Online Intelligent Semantic Performance based Solution is web
applications that ascertain an association between the institutes and the students. Institutes enter on the site, the
concepts they want in the exam. The questions based on the relevant concept and the syllabus is displayed as a test
to the eligible students. The answers entered by the students are then evaluated and their score is calculated and
saved. This score then can be accessed by the institutes to determine the passes students or to evaluate their
performance. It has been successfully applied to the distance evaluation of basic operating skills of computer
science, such as the course of computer skills in Universities and the local examination for the under graduates in
faridabad, Haryana.
Data science for digital culture improvement in higher education using K-mean...IJECEIAES
This study aims to investigate the meaningful pattern that can be used to improve digital culture in higher education based on parameters of the technology acceptance model (TAM). The methodology used is the data mining technique with K-means algorithm and text analytics. The experiment using questionnaire data with 2887 respondents in Universitas Islam Negeri (UIN) Sunan Gunung Djati Bandung. The data analysis and clustering result show that the perceived usefulness and behavioral intention to use information systems are above the normal value, while the perceived ease of use and actual system use is quite low. Strengthened with text analytics, this research found that the EDA and K-means result in harmony with the hope or desire of academic society the information system implementation. This research also found how important the socialization and guidance of information systems, especially the new one information system, in order to improve digital culture in higher education.
Student Performance Evaluation in Education Sector Using Prediction and Clust...IJSRD
Data mining is the crucial steps to find out previously unknown information from large relational database. various technique and algorithm are their used in data mining such as association rules, clustering and classification and prediction techniques. Ease of the techniques contains particular characteristics and behaviour. In this paper the prime focus on clustering technique and prediction technique. Now a days large amount of data stored in educational database increasing rapidly. The database for particular set of student was collected. The clustering and prediction is made on some detailed manner and the results were produce. The K-means clustering algorithm is used here. To find nearest possible a cluster a similar group the turning point India is the performance in higher education for all students. This academic performance is influenced by various factor, therefore to identify the difference between high learners and slow learner students it is important for student performance to develop predictive data mining model.
A dynamic professional with 6 months of experience in the field of production, planning, operation, channel management.
A dynamic Professional with 2 years experience in the field of teaching to expand my technical knowledge and to work in the field of research & development
Involved as coordinator in the department for smooth and proper conduction of academic activities.
A dynamic professional with 6 months of experience in the field of production, planning, operation, channel management.
A dynamic Professional with 2 years experience in the field of teaching to expand my technical knowledge and to work in the field of research & development
• Involved as coordinator in the department for smooth and proper conduction of academic activities.
B.p. poddar group department of information technology | bppimtShirsendu Kar
B P Poddar is one of the best Institute of Management and Technology in Kolkata accredited with all 4 B.Tech programs accredited by National Board of Accreditation NBA
http://www.bppimt.ac.in/
IoT-based students interaction framework using attention-scoring assessment i...eraser Juan José Calderón
IoT-based students interaction framework using attention-scoring assessment in eLearning. Muhammad Farhan a,b, Sohail Jabbar a,c,d, Muhammad Aslam b, Mohammad Hammoudeh e, Mudassar Ahmad c, Shehzad Khalid f, Murad Khan g,Kijun Han d,
21st Century School Presentation - Acorn High SchoolLisa Nielsen
This presentation provides an overview of how Acorn high school has made strides to become a school that prepares students for 21st century teaching and learning.
Learning analytics to quantize and improve the skills development and attainm...eSAT Journals
Abstract
The intervention of technology in the teaching and learning processes is bringing change. There is requirement of methods and techniques to analyze the generated data in these processes. Traditional way of delivery and assessment is becoming more focused by the application of technology. In this paper, we propose and illustrate an algorithmic methodology that shall allow the stakeholders in education to focus more on skills attainment effectively.
In large size class, there is huge data generated by registration system, administration system, and the learning management system together. We propose the methodology that mainly maps and quantizes the learning outcomes, and that relates to the successful and weaker range of attainments of stakeholders. This algorithmic methodology reads the data viz. course details, outcomes, and assessment scores of a large class and analyzes the skills attainment with respect to the planned each course outcome. The detailed report is generated with the average of attainment of the class strength, highest attainment, and lowest attainment in each of the course outcomes for each student.
Key Words: Learning Analytics, Software tool, System Architecture, Course Outcomes, and Skills Attainment
Learning analytics to quantize and improve the skills development and attainm...
Deepakresume1
1. Dr. DEEPAK K. SINHA
dipu_sinha@yahoo.co.in
Permanent Address:
16, ShipraVihar,
Ganga Nagar,
Meerut, UP (India)
+919412835387,+2510935116840
Profile : An excellent professional responsible in preparing and delivering lectures in
classroom discussions; a leader and is well-versed in a variety of the field’s concept and
practices; has formed lesson strategies, presented creative presentation material to
students, responding to students learning needs and evaluating students’ progress; has
strong background in Computer Science and other related fields; has the ability to
conduct research and feasibility studies in fields of interest; has secured doctorate degree
in the area of “Pointer Free Codes to build Complex Data Structures”; has a touch base
with other Computer professionals to update on latest principles that govern the field that
will enhance the learning experience of the students.
Professional Experiences:
Assistant Professor,
Department of Computing,
Jimma Institute of Technology,
Jimma, Ethiopia.
October 2013- till date
2. Associate Professor and Head of the Department (MCA),
IIMT Management College, Meerut.
July 2004 – October 2013,
Responsibilities:-
Administered several classes and graded examinations.
Offered optional independent career counseling opportunities to other students.
Provided subject consultations, led and directed the work of faculty instructors.
Conducted college-level courses in the field of Computer Science.
Collaborated with faculty and research centers to enhance external researches.
Executed administrative functions in the faculty.
Shared guidance duties, committee and department assignments with other faculty
members.
Involved in initiatives to maintaining productive forums with students.
Educational Qualification:
---------------------------------------------------------------------------------------------------
Exam Passed year Univ/Board %age
---------------------------------------------------------------------------------------------------
Ph.D. (CS) 2011 M.U., Bodh Gaya Awarded
M.Tech(CS) 2008 JNRV 76%
M.C.A. 2004 IGNOU 61.3
B.C.A. 1999 T.M.Bh.U. 76
--------------------------------------------------------------------------------------------------
Training/Workshop Attended:
Faculty Development Programme on”Excellence in Research” during the
session 2009-10 at IIM Indore.
6 Days workshop on “Human Values and Professional Ethics” during the
session 2008-2009 at IIT Kanpur.
3. Workshop on “Conduction of Seminar and Workshops” during the session
2007-08 at NITTTR Chandigarh.
Attended and Organized various Seminars and Workshops held at IIMT
Group of Colleges.
Research Paper Published:
(1)Ticketing System of Indian Railways through SMS and swapping machine.
Published in International Journal of Advanced Research in Computer Science and
Software Engineering , Volume 3, Issue 8, August 2013 ISSN: 2277 128X, page No-
543 to 548
(2) Cloud Computing: Study & Scope, IJAIR Vol. 2 Issue 7 ISSN: 2278-7844, page
No.25- to 255
(3) cyber crime investigations in India: Rendering knowledge from the past to
address the future: published in Springer Oct 2013.
Professional Body Membership:
(1) IAENG Member (Membership Number : 148690
(2) ResearchrID (http://researcherid.com) : O-3199-2014
(3) LiveDNA (http://livedna.net) : 91.7186
Rreferences.
(1) Proff. P.K Ghosh
Director IIMT Management College, Meerut, U.P, India
Email: pkghoshindore@gmail.com, Mobile No: +91 -9760099767
(2) Proff. V. K Agarwal
Ex Principal D.N college ,Meerut, U.P , India
Email: vkagarwalbit@gmail.com, Mobile No:+91-9012211666
(3) Prof. V. D. Kaushik
Professor, School of Social Sciences,
Jimma University, Jimma, Ethiopia.
E-mail:vdkaushik@yahoo.com, Mobile: +251-932019754
4. Personal Skills:
Proven Organizational Skills
Team Spirit
Effective and Disciplined
Self motivated and Organized
Personal Biographic:
Father's Name : Sri S. P. Sinha
Date of birth : 03-07-1976
Marital status : Married
Language known : English and Hindi.
Nationality : Indian
Date Signature