Active VELS (VISTAS) VELS (VISTAS) line 3-City, Country line

Active
Learning through Social Media : A Survey

S. Sankari1                                                                             
Dr.P. Sripriya2

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                   M.Phil  Research Scholar                                                          
   Associate Professor

Dept
of Computer Application                                               Dept
of Computer Application

                        VELS (VISTAS)                                                                         VELS
(VISTAS)

line
3-City, Country                                                                line
3-City, Country

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

 

Abstract—
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.

Keywords—Social
Network game,game-based learning

I.       
INTRODUCTION

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.

II.    
METHODOLOGY USED

 

Fig 1. Different ideas to utilize social networks

 

Social media for personal resons:

S:NO

JOB

%

1

Mental  break at work

40

2

Friends &family from work

60

3

Information&hlps

20

 

Social media platform:

S:NO

SOCIAL

EDUCATION

PROFESSIONAL

%

Face book

One month

One week

Never

10

Twitter

One week

One day

Never

30

You Tube

One day

Two week

Never

74:50

Wikipedia

One hours

Two month

Never

45

Blogs

One week

Tow day

Never

150

Linkedin

One month

One month

Never

4

Other

Never

One day

Never

26

 

 

a
) Social Media Usage Agreement Social Media Terms and Conditions

·    Students are advised to act safely by hiding their 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 those who use social media for the purpose of
academic resource they can enhance several activities in classroom.

 

·  Students must not  reply to the comments that make them
uncomfortable. Instead, they ought to report these comments to the trainer
immediately.

 

III.  
RESEARCH STUDY- A SURVEY

 

A.
Abstract-Social LearningNetwork (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.

B.  MOOC

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. Thus the data-driven learner model approach that uses fine
grain data 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 improved
in the data-driven modelling and it 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.

C.  NPTEL

      The
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

i)        
higher education,

ii)      
professional education,

iii)     
distance education and

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

 

     Work
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 wide range of students those who
are unable to attend scholarly in institutions through NPTEL will have access
to quality index 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. In
flipped classroom, students watch online lectures, student collaborate and
interact in online discussions, or they perform analysis and have interactions
in ideas among the classroom with the guidance of a mentoror the respective
faculty.

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 that wantedly
shifts the instruction to a learner-centred model in which class time can be
utilized that explores the vast topics in greater depth and creates purposeful
learning opportunities, whereas instructionaltechnologies like online videos
are used to ‘deliver content’ outside of the classroom. In a flipped classroom,
‘content delivery’ might take a variety of forms. In general, the video lessons
are prepared by the teacher or any parties are used to deliver content, eventhough
the 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

E. Learning
Management System

An LMS which delivers and manages tutorial
documents or datas, and basically handles student registration, online course
administration, and tracking, and assessment of student work.2 Some LMSs helpsthe
progress towards learning goals and this can be identified.3 Most LMSs may be
web-based, to facilitate the access. LMSs are often used by regulated
industries used for the training. This system include the performance based on
the management, which facilitate the employee appraisals, competency
management, skills-gap analysis, succession planning, and multi-rater
assessments. Some systems support competency-based learning. Though there are a
large 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.

IV.  
CONCLUSION

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 littletheory-drivenempiricalresearch
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. Exactly, we mainly focus on the use
of social networks as intentional social action this can be examined using 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 discussed.

 

V.     
REFERENCES

 

1    
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Qualter, and Peter J. Sewell. “Exploring the factor structure of the
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2    
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

 

3    
Hicheur  Cairns, 
Awatef,  et  al.”Towards Custom-Designed Professional
Training Contents and Curriculums through Educational Process Mining.”
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4    
Archer, Elizabeth, Yuraisha Bianca
Chetty, and Paul Prinsloo. “Benchmarking the habits and behaviors of
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5    
Arora,   Rakesh  
Kumar,   and
DharmendraBadal.”Mining Association Rules to Improve Academic
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6    
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.

 

 

7    
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.

 

8    
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.

 

9    
Jantawan, Bangsuk, and Cheng-Fa
Tsai. “The Application of Data Mining to Build Classification Model for
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And Information Security (2013).

 

10  Bakar, Noor Aieda Abu, Aida Mustapha, and Kamariah Md Nasir.
“Clustering Analysis for Empowering Skills in Graduate Employability Model.”
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11  Singh, Samrat, and Vikesh Kumar. “Performance Analysis
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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
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15  Padhy, Neelamadhab, Dr Mishra, and Rasmita Panigrahi.
“The survey of data mining applications and feature scope.” Asian
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16  Osmanbegovi?, Edin, and Mirza Sulji?. “Data mining
approach for predicting student performance.” Economic Review 10.1 (2012).