Active common places for various times of

Learning through Social Media :     A

S. Sankari1                                                                              Dr.P. Sripriya2

Best services for writing your paper according to Trustpilot

Premium Partner
From $18.00 per page
4,8 / 5
Writers Experience
Recommended Service
From $13.90 per page
4,6 / 5
Writers Experience
From $20.00 per page
4,5 / 5
Writers Experience
* All Partners were chosen among 50+ writing services by our Customer Satisfaction Team

                   M.Phil  Research Scholar                                                      
       Associate Professor

of Computer Application                                               Dept of Computer

                        VELS (VISTAS)                                                                         VELS (VISTAS)

3-City, Country                                                                line 3-City, Country

[email protected]                                                       line 4-e-mail
address if desired


This survey is based on how to make utilize the social media into a game-based
learning and with the help of various applications instead of affecting
students by using social media discussed related based on the active learning,
with the main intention of provoking learners’ aim instead of instructing the
courses. Thus, increasing learning purpose by game-based learning becomes a
typical tutorial strategy to boost learning actions. However, it’s challenging
to design fascinating games combined with courses. However, in the past game-based
learning, students were brought together in common places for various times of
game-based learning. Students learning was restricted by time and area.
Therefore, for students’ game-based learning at any time and in any places,
based on theories of design elements of online community game with the help of
social media. Questionnaire survey is conducted to seek out if the design of non-single
user game is adorable for students to take part in game-based learning. In
order to make sure that the questionnaires can be the test to analyse students
motive to play games, by statistical program of social science; this study
endorse reliability and validity of items of questionnaire to effectively
control the result of online community games on students learning intention.

Network game,game-based learning


Learning based game has been proven
to be a kind of learning method that allows students to organize knowledge
through the game content in the game process and in turn elevate learning
motivation 1. Compared to traditional education in which students passively
receive knowledge. Game -based learning allows students to actively participate
in game activities 2, which not only strengthens but also maintains student
learning motivation, making them willing to spend time on learning 3.
However, in view of the fact that it is not easy to design a system that
combines game elements and course content, Echeverria proposed the design
method for course knowledge systems, combining game elements and course
knowledge. The fictional story of the story or the interaction with fictional
characters corresponds to suitable course content, in turn combining the course
and the game 4. However, since traditional game-based learning tends to cause
temporal and spatial constraints for students, in order to break through these
constraints, so that students can conduct game based learning at any time and
place, this study uses Aki Järvinen’s theory of social network game design
elements as the basis to create the game in Facebook 5. Other than using the
2006 feature of Facebook that permits third party development of apps, at the
same time the development of social network games is relatively simpler than
traditional video games, as well as faster and cheaper. Facebook provides a
platform for students to learn as they socialize, and this is used to explore
the activity process of students in social network games, further using
questionnaires to explore whether the design of social network games can
attract students to conductgame-based learning. In order to understand the
gaming intentions of students, this study also uses SPSS to conduct reliability
and validity testing on questionnaire questions, in hopes of understanding how
social network games affect the learning.


Fig 1. Different ideas to utilize social networks

Social media for personal resons:





Mental  break at work



Friends &family from work



Information & helps



Social media platform:






Face book

One month

One week




One week

One day



You Tube

One day

Two week




One hours

Two month




One week

Tow day




One month

One month





One day




) Social Media Usage Agreement Social Media Terms and Conditions

·    Students are expected to act safely by keeping personal
information out of their posts.


·    Students agree to not use their family name, password,
school name and location, or the other data that would change somebody to find
and get in touch with them.


·    Students are to use social media as an academic resource
only and therefore behave as in the classroom.


·  Students shouldn’t reply to comments that make them
uncomfortable. Instead, they ought to report these comments to the trainer immediately.







Abstract-Social Learning Network (SLN)


In this paper, Abstract-Social
Learning Network (SLN) type of social network implemented among students,
instructors, and modules of learning. It consists of the dynamics of learning
behaviour over a variety of graphs representing the relationships among the
individuals and processes involved in learning. Recent innovations in online
education, together with open online courses at numerous scales, in flipped
classroom instruction, and in professional and corporate training have conferred attention
grabbing questions about SLN. Collecting, analyzing, and leveraging data about
SLN causes potential answers to these queries,
with facilitate from a convergence of modelling languages and style
ways, like social network theory, science of learning, and
education information technology. This survey article overviews a number of
these topics, together with prediction, recommendation, and personalization, in
this emergent research area.


Advanced educational technologies
are developing rapidly and online MOOC courses have become more prevalent,
creating an enthusiasm for the seemingly limitless datadriven potentialities
to have an effect on advances in learning and enhance the learning experience.
For these potentialities to unfold, the experience and collaboration of the many
specialists are necessary to improve data collection, to foster the development
of better predictive models, and to assure models are interpretable and
actionable. The massive knowledge collected from MOOCs must be larger, not in
its height (number of students) however in its width—more meta-data and data on
learners’ cognitive and self-regulatory states must be collected additionally
to correctness and completion rates. This more detailed articulation will help
open up the black box approach to machine learning models where prediction is
the primary goal. Instead, data-driven learner model approach uses fine grain
data that is conceived and developed from cognitive principles to make
explanatory models with practical implications to boost student learning. Using
data-driven models to develop and improve educational materials is
fundamentally different from the instructor-centred model. In data-driven modelling,
course development and improvement is predicted on data-driven analysis of
student difficulties and of the target experience the course is supposed
produce; it’s not supposed instructor self-reflection as found in purely
instructor-centred models. To be sure, instructors will and may contribute to
interpreting data and making course redesign decisions, however ought to
ideally do so with support of cognitive psychology expertise. Course
improvement in data-driven modelling is additionally supported course-embedded
in vivo experiments(multiple instructional designs randomly assigned to
students in natural course listening to an instructor’s delivery of information,
but is primarily regarding students’ learning . By example, by doing and by
explaining. In addition to avoiding the pitfall of developing interactive
activities that don’t offer enough helpful information to reveal student
thinking, MOOC developers and information miners should avoid potential
pitfalls within the analysis and use of data.


basic objective of science and engineering education in India is to plan and
guide reforms that may remodel India into a strong and vibrant knowledge economy.
In this context, the focus areas for NPTEL project are

higher education,

professional education,

 distance education and

 continuous and open learning, roughly in this
order of preference.


force demand for trained engineers and technologists is way over the amount of
qualified graduates that Indian technical institutions will offer presently.
Among these, the number of institutions having fully qualified and trained
lecturers altogether disciplines being tutored forms a small fraction. A
majority of lecturers are young and inexperienced and are undergraduate degree
holders. Therefore, it is important for institutions like IITs, IISc, NITs and
other leading Universities in India to disseminate teaching/learning content of
high quality through all available media. NPTEL would be among the foremost and
a crucial step during this direction and can use technology for dissemination.
India needs many more teachers for effective implementation of higher education
in professional courses. Therefore, strategies for coaching young and
inexperienced lecturers to enable them carry out their academic
responsibilities effectively are a must. NPTEL contents are often used as core
curriculum content for training purposes. A large range of students who are
unable to attend scholarly institutions through NPTEL will have access to
quality content from them.

      All those who are gainfully employed in
industries and all other walks of life and who need continuous training and
updating their knowledge can benefit from well-developed and peer-reviewed
course contents by the IITs and IISc.


D. Flipped
Digital Classrooms

Flipped digital classroom is a
tutorial strategy and a type of integrated learning that reverses the
traditional learning environment by delivering instructional content, often
online, outside of the classroom. It moves activities, together with people who
might have traditionally been thought-about homework, into the classroom.
During flipped classroom, students watch online lectures, collaborate in online
discussions, or perform analysis and have interactions in ideas among the
classroom with the guidance of a mentor.

In the traditional model of
classroom instruction, the teacher is commonly the central focus of a lesson
and the primary disseminator of information during the class period. The
teacher responds to queries whereas students defer on to the teacher for
guidance and feedback. In a classroom with a traditional style of instruction, individual
lessons may be focused on an explanation of content utilizing a lecture-style.
Student engagement among the traditional model is also restricted to activities
in which students work independently or in small teams on an application task
designed by the teacher. Class discussions are typically focused on the
teacher, who controls the flow of the spoken communication. 1 Generally, this
pattern of teaching additionally involves giving students the task of reading
from a textbook or functioning a concept by working on a problem set, for
example, outside school. 2

The flipped classroom purposely
shifts instruction to a learner-centred model in which class time explores
topics in greater depth and creates purposeful learning opportunities, whereas
instructional technologies like online videos are used to ‘deliver content’
outside of the classroom. In a flipped classroom, ‘content delivery’ might take
a variety of forms. Often, video lessons prepared by the teacher or third
parties are used to deliver content, although online collaborative discussions,
digital analysis, and text readings could also be used. 345

Flipped classrooms additionally
redefine in-class activities. In-class lessons accompanying flipped classroom
may include activity learning or more traditional homework problems, among
other practices, to engage students in the content. Class activities vary but
may include: using math manipulative and emerging mathematical technologies,
in-depth laboratory experiments, original document analysis, debate or speech
presentation, current event discussions, peer reviewing, project-based
learning, and skill development or idea practice67 as a result of  these varieties of active learning allow for
highly differentiated instruction,8 more time can be spent in class on
higher-order thinking skills like problem-finding, collaboration, design and
problem solving as students tackle troublesome issues, work in groups,
research, and construct knowledge with the assistance of their teacher and peers.9
Flipped classrooms are enforced in both schools and colleges and been found to
have varying differences in the method of implementation.10

Learning Management System

An LMS delivers and manages tutorial
content, and generally handles student registration, online course
administration, and tracking, and assessment of student work.2 Some LMSs help
identify progress towards learning or training goals.3 Most LMSs are
web-based, to facilitate access. LMSs are often used by regulated industries (e.g.
financial services and biopharma) for compliance training. Some LMS providers
include “performance management systems”, which encompass employee
appraisals, competency management, skills-gap analysis, succession planning,
and multi-rater assessments (i.e., 360 degree reviews). Some systems support
competency-based learning. Though there are a wide variety of terms for digital
aids or platforms for education, such as course management systems, virtual or
managed learning platforms or systems, or computer-based learning environment,
the term learning management system has become the ubiquitous term for products
that help administer or deliver part or all of a course.







Thus the social network has created
a meth, psychologically around the mindset of students, as emotionally by
collaboration and communication because of the growth and popularity. Our
country has two set of students, one side the well educated students and the
other side uneducated students. Despite the importance of education, the
students’ emotions are relatively little theory-driven empirical research
available to address this new type of communication and interaction phenomena.
In this paper, we explored the factors that drive students to differentiate the
educated and uneducated student’s mindset. Specifically, we conceptualized the
use of social networks as intentional social action and we examined the
relative impact of social influence, social presence, and the five key values
from the uses and gratification paradigm on We-Intention to use online social
networks. An empirical study of students mindset (n = 182) revealed that our
intension is to utilize social networks strongly that is determined by social
presence. Among the five values, social related factors had the most significant
impact on the intention to use. Implications for research and practice are




Pool, Lorraine Dacre, Pamela
Qualter, and Peter J. Sewell. “Exploring the factor structure of the
CareerEDGE employability development profile.” Education+ Training 56.4
(2014): 303-313.


Saranya, S., R. Ayyappan, and N.
Kumar. “Student Progress Analysis and Educational Institutional Growth
Prognosis Using Data Mining.” International Journal Of Engineering
Sciences & Research Technology, 2014


Hicheur  Cairns, 
Awatef,  et  al.”Towards Custom-Designed Professional
Training Contents and Curriculums through Educational Process Mining.”
IMMM 2014, The Fourth International Conference on Advances in Information
Mining and Management. 2014.


Archer, Elizabeth, Yuraisha Bianca
Chetty, and Paul Prinsloo. “Benchmarking the habits and behaviors of
successful students: A case studyofacademic-business collaboration.” The
International Review of Research in Open and Distance Learning 15.1 (2014).



Arora,   Rakesh  
Kumar,   and Dharmendra Badal. “Mining
Association Rules to Improve Academic Performance.” (2014).


Peña-Ayala, Alejandro.
“Educational data mining: A survey and a data mining-based analysis of
recent works.” Expert systems with applications 41.4 (2014): 1432-1462.



Vanhercke, Dorien, Nele De Cuyper,
Ellen Peeters, and Hans De Witte.”Defining perceived employability: a
psychological approach.” Personnel Review 43, no. 4 (2014): 592-605.


Potgieter, Ingrid, and Melinde
Coetzee. “Employability attributes and personality preferences of
postgraduate business management students.” SA Journal of Industrial
Psychology 39.1 (2013): 01-10.


Jantawan, Bangsuk, and Cheng-Fa
Tsai. “The Application of Data Mining to Build Classification Model for
Predicting Graduate Employment.” International Journal Of Computer Science
And Information Security (2013).


10  Bakar, Noor Aieda Abu, Aida Mustapha, and Kamariah Md Nasir.
“Clustering Analysis for Empowering Skills in Graduate Employability
Model.” Australian Journal of Basic and Applied Sciences 7.14 (2013):


11  Singh, Samrat, and Vikesh Kumar. “Performance Analysis
of Engineering Students for Recruitment Using Classification Data Mining
Techniques.” International Journal of Computer Science & Engineering
Technology, (2013).


12  Finch, David J., Leah K. Hamilton, Riley Baldwin, and Mark
Zehner. “An exploratory study of factors affecting undergraduate employability.”
Education+ Training 55, no. 7 (2013): 681-704.


13  Jackson, Denise, and Elaine Chapman. “Non-technical
skill gaps in Australian business graduates.” Education+ Training 54.2/3
(2012): 95-113.


14  Dejaeger, Karel, et al. “Gaining insight into student satisfaction
using comprehensible data mining techniques.” European Journal of
Operational Research 218.2 (2012): 548-562.


15  Padhy, Neelamadhab, Dr Mishra, and Rasmita Panigrahi.
“The survey of data mining applications and feature scope.” Asian
Journal Of Computer Science And Information Technology (2012).


16  Osmanbegovi?, Edin, and Mirza Sulji?. “Data mining
approach for predicting student performance.” Economic Review 10.1 (2012).






I'm Isaac!

Would you like to get a custom essay? How about receiving a customized one?

Check it out