首页    期刊浏览 2025年02月22日 星期六
登录注册

文章基本信息

  • 标题:Opportunity analysis of educational mobile app to provide higher education in rural India.
  • 作者:Ahmed, Neetu ; Kaur, Gurleen
  • 期刊名称:Abhigyan
  • 印刷版ISSN:0970-2385
  • 出版年度:2017
  • 期号:April
  • 出版社:Foundation for Organisational Research & Education

Opportunity analysis of educational mobile app to provide higher education in rural India.


Ahmed, Neetu ; Kaur, Gurleen


Introduction

Education is one of the most important instruments for growth of an economy. It is the key for many developing economies to increase its competitiveness in the era of knowledge. While all other resources deplete with their use, knowledge expands by its application. With the 21st century world widely claimed to be a "knowledge" and increasingly, more "technology" driven one, a very sharp focus on education (primary, secondary, higher, and vocational) would have been one of the top priorities of all governments. Therefore this is the central objective for every government to ensure access to quality education for all, in particular for the poor and rural population. However, the rapid expansion of higher education system has brought several pertinent issues related to the standards of its quality and equal availability of higher education facilities to all the categories of people of the society.

India has a huge share of young population and it is continuously rising, whereas youth population is declining in the developed world. Nearly 450 million people in India are ageing between 5-24 years, making India the country of highest population in this age group. Thus India can take the advantage of its demographic dividend to meet the global demand. In order to benefit from this demographic advantage, India will be required to significantly improve the quality of its higher education. India is a country with severe economic and social inequalities (Kim, P., et al 2011). In this digital era, characterized by the rapid development of Information and Communication Technologies (ICT), illiterate people are at greater risk than ever (Avgerou, 2008; Prakash and De, 2007; Walsham, 2010). Those with less education will find it increasingly difficult to participate in developing knowledge-based societies, thus increasing social division and the digital and knowledge divide (Reimers, 2000). In India a large number of populations fall under middle class family and lower middle class families. At the same time lower economy class families also exist in large numbers. Now, when a large number of families and their youth are struggling hard to fulfill their basic needs, they naturally have to compromise with the higher education specially the youth of rural and remote areas.

Normally higher education institutions are located in urban areas or big towns, which are creating hindrance for youth to access higher education as they are generally sole earner of their families. According to the survey done by the Annual status of education report (ASER) 2014, states that most of the graduate students in rural areas are unemployed as they don't have resources to pursue post-graduation. There are several students in the rural areas that are willing to study but are not well equipped with the resources to proceed. There are financial problems as well as communication and transportation problems.

While on one side rural India is lacking in basic amenities like schools, colleges, universities, library, hospitals, transportation, on the other side mobile subscriptions are increasing year on year. The number of telephone subscribers in India has reached the level of 933.00 million at the end of March, 2014 (TRAI, 2014). The data reported by service providers indicates that rural India is emerging as the growth driver. According to sectoral regulator TRAI, total number of rural subscribers stood at 377.73 million as of March 2014. Rural users accounted for 40.49 percent of total telephony base in India. Of these, 371.78 million were wireless customers, while the remaining 5.96 million were wire line users. Rural teledensity (number of telephones per 100 people) was 43.96 in March, 2014. In 2000 there were approximately 700 million mobile subscriptions in world where developing economies were having the share of 30 per cent. By 2012 there were more than six billion subscriptions and over 75 per cent of which were in developing economies (WDI, 2014). According to World Bank estimate three quarter of the people on the planet have the access to a mobile phone, in those countries where they don't have electricity and clean water (World Bank 2012).

Acknowledging the potential advantage of mobile penetration in rural India, the current paper presents initial exploration of mobile learning perception through acceptance of mobile apps in rural area. An investigation was carried to test the acceptance of educational mobile app aimed for rural youth, which will provide all the information regarding important educational tools, seminars & quarterly magazine that would be helpful to select better colleges in India & outside of India also. The objective of this proposed app is to increase the rate of youth involvement through knowledge creation, better employment opportunities, and skill development to increase the quality of human resource to tab the opportunities available in the global world. The app would provide the entire important lecture regarding management aptitude preparation to user, generally, undergraduates & graduates.

Mobile Learning in Developing Economies

The World Bank education policy specialist Michael Trucano (2007), said "Broadband will come, but it will not come quickly enough. Computers, as we think of them sitting on someone's lap or on a desktop, will come, but not quickly enough. Phones are already there ... We think there's a real opportunity there to explore."

For example In Pakistan, efforts have been made by one group of educators to experiment with sending SMS quizzes to students. After the student answers a question, he receives an automated response, which varies depending on whether the answer was correct. Similar effort is made in India by Mathematician to provide maths quiz with answers to help students to evaluate their answers.

This is completely a different kind of experience in a system where very large, lecture-based classes are the norm, this may be the first time they have received 'personalized' feedback of any sort from their instructors. In Philippines and Tanzania the programs like texttoteach and BridgeIT program is running to deliver educational video content to classrooms through phones. The Human Development Lab at Carnegie Mellon University runs a program called MILLEE, which has used custom mobile games to teach language in India for the past seven years (the program has also expanded to rural China and sub-Saharan Africa).

In India, the mobile phone has revolutionized communication. India is now one of the fastest growing markets for mobile phone services, with growing usage and increasing market penetration. As stated in a report published by the Internet and Mobile Association of India, (IAMAI), 2016, the number of mobile internet users in India is expected to reach 371 million by June 2016. There were 306 million mobile internet users in India in December, 2015. Of the 306 million internet users, 219 million users are from Urban India, which registered a Y-o-Y growth of 71 percent, while the user base in Rural India has gone up by 93 percent from December 2014, to reach 87 million in December 2015. This means that mobile devices are not only communication devices but channels for interactions and learning as well.

Finally, there is a need to consider m-learning as an evolutionary trend. It not only grows in numbers but changes its face each time when there is a new technological opportunity or new business model. Let's think about m-learning in two years from now, besides smart phones and tablets, there will also be smart wearable devices such as smart watches and smart glasses.

A number of studies are focused on to utilize mobile technologies in learning development and for informal literacy (Chinnery, 2006; Joseph et al., 2005; Kadyte, 2004; Kiernan and Aizawa, 2004; Levy and Kennedy, 2005; Norbrook and Scott, 2003; Ogata and Yano, 2004; Paredes et al., 2005; Thornton and Houser, 2005). Acknowledging the potential advantage of mobile penetration in rural India, the current paper presents initial exploration of mobile learning perception through acceptance of mobile apps in rural area.

Mobile Learning in Rural Areas

Today's mobile devices can store and deliver a vast amount of information, including a wide variety of curricular materials targeted at appropriate ages. The rapid innovations and advances in ICT leads to increase in processing power, memory, and connectivity for mobile, handheld devices and the result has made mobile devices more interactive and media-rich than ever before (Pea and Maldonado 2006). Mobile devices have already reached the most isolated populations and had a tremendous impact on individuals' lives (Attewell and Smith 2005). Mobile devices also have an advantage over computers with respect to educational content. A key limitation of computer-centric initiatives is the lack of varied and robust learning software applications. The rapid growth of mobile applications (i.e. apps) on mobile phones has greatly expanded opportunities for learning with mobile devices. In a comprehensive study of the educational app, Shuler (2012) reports that: "Apps are an important and growing medium for providing educational content to children, both in terms of their availability and popularity". Moreover, many apps are able to promote learning in a game-like environment, making them far more engaging than traditional learning pedagogies.

As things stand now, mobile learning technology makes sense for children living in rural areas or areas without many resources, including electricity. A mobile learning device that can be mass-produced at an affordable price, along with a solar-cell charger, can be useful even without the actual ability to connect to the Internet. However, since many developing countries are prioritizing the direct installation of cell phone networks in rural areas instead of connecting conventional landlines, we can expect that in the future more and more disadvantaged people in both rural and urban areas obtain the advantage of mobile networks and the information superhighway (Sharples et al., 2005) and increasingly leverage technology for mobile learning.

The many advantages of mobile devices make them particularly apt for supporting student-centered learning. Prior studies have documented how mobile devices can facilitate experimentation in real-world settings, help students collect and record information, and allow learners to share their experiences and information with peers (Looi et al. 2010; Squire and Klopfer 2007). According to Looi (2010) "the portability and versatility of mobile devices has significant potential in promoting a pedagogical shift from didactic teacher-centered to participatory student-centered learning" (156).

Learning Theories

As mobile penetration is increasing many researchers, educationists are working to explore theories related to m-learning. These theories may help to provide groundwork for lots of techniques needed for educational developers to make significant learning systems. The era of m-learning is characterized by mobility of people and knowledge (Rheingold 2003). These systems can support a society where people on the move increasingly try to cram learning into an intervening space of daily life. The learning is not limited to classrooms only, it is occurring at different places like home, offices, leisure places, cafes, cars, hospitals, airports and so on. A central concern must be to understand how people artfully engage with their surroundings to create impromptu sites of learning. The application of m-learning range widely from K-12 to higher education, from formal and informal learning to class room learning, distance learning and field study. There are different learning theories which are supporting mobile activity as cognitivism, constructivist, situated, problem based, socio cultural, connectivism, collaborative, informal/lifelong, and supportive/coordination.

The Cognitivism theory mainly focuses on learner's particular variations and tries to provide material in different way (Allen 2007). It represents the process of thinking while someone is in action of learning. Learning is shaped by acquired learning strategies and prior knowledge and attitudes, called schemas. The cognitive view of learning is teacher-centered, and information must be presented in an organized manner in order to achieve the most efficient learning. Cognitivism is suited well for problem solving, where the concepts are complex and must be broken down into smaller parts. Ideas and concepts from these problems are linked to prior knowledge, which in turn helps the learner develop a stronger comprehension (Stavredes, 2011)

Constructivist learning emphasizes the importance of the active involvement of learners in constructing knowledge for themselves, and building new ideas or concepts based upon current knowledge and past experience (Bruner, 1966). Within a constructivist learning framework, instructors should encourage students to discover principles for themselves. The major concentration here is on learning rather than teaching in which learners develop new thoughts in relation to their present knowing e.g. Participatory simulations.

The situated learning paradigm (Lave and Wenger, 1991) explains that learning is not merely the acquisition of knowledge, but instead a process of social participation. Under this kind of learning teachers work alongside students to create situations where the students can begin to work on problems even before they fully understand them (Brown et. al. 1989).

Situated learning requires knowledge to be presented in authentic contexts (settings and applications that would normally involve that knowledge) and learners to participate within a community of practice e.g. MOBIlearn (Lonsdale et al 2003, 2004).

Problem-based learning (Koschmann et al 1996) is one of the examples of situated learning which aims to develop students' critical thinking skills by giving them an ill-defined problem that is reflective of what they would encounter as a practicing professional. Throughout the process of exploring a problem, students are encouraged to identify the areas of knowledge they will require to understand the problem. The group then collects these learning issues, along with data, hypotheses and plans for future inquiry in a structured manner, which can be facilitated by shared information resources (e.g. physical or electronic whiteboard), and uses the collected information to develop a plan for the next iteration of problem formulation, solution, reflection and abstraction.

The collaborative theory of learning views that learning takes place in a social context (Rogers et al 2002), and the forming and re-forming of concepts are influenced with the knowledge of others. The collaborative groups working and sharing with others can be a powerful way of confronting one's own conceptions (preconceptions), contributing to the need to restructure one's cognitive schemas. e.g. online discussion boards which substitute for face-to-face discussions (Zurita et al 2003; Cortez et al 2004; Zurita and Nussbaum 2004). Thus, it is through mutual conversation that one can come to a shared understanding of the world.

Informal and lifelong learning are intentional in nature. Sometime it happens accidently like by reading newspapers or watching TV or you deliberately acquire knowledge with intentions. Informal learning is a reality in people's lives; they may not recognize it as learning. People learn to perform a new task or they learn to perform the old task in an efficient way. Technology that is used to support learning should be blended with everyday life in the same way that learning is blended with everyday life: seamlessly and unobtrusively. Mobile technologies, with their reduced size and ease of use, provide the potential to support such activities.

Connectivism is a theoretical framework for understanding learning. In connectivism, the starting point for learning occurs when knowledge is actuated through the process of a learner connecting to and feeding information into a learning community. According to this theory knowledge exists outside of the learner, and the learner makes connections between information to build knowledge. The connections that learners make help them create their own learning network. Through this connected web, learners will be able to stay up-to-date with content as it changes. It is important for the learner to be able to identify credible resources. (Siemens 2004)

Mobile devices provide a unique opportunity to have learners embedded in a realistic context at the same time as having access to supporting tools. Each learner carries a networked device which allows them to become part of the dynamic system they are learning about. Learning will move more and more outside of the classroom and into the learner's environments, both real and virtual. No single theory could be relevant to learning through mobile technology. However, there is a need of an integrated pedagogy for the use of mobile devices that draws on a number of areas. Learning will involve making rich connections within these environments to both resources and to other people. Now the future of learning is going to be learner centric. Whether mobile devices are welcome in learning or not they are finding their own way. Now it is a challenge for the educators, technology developers and policy makers to use it in an effective way.

Challenges and Limitations in M-learning

The learning environment of m-learning is changing every day which is bringing new challenges to students as well as teachers. The rapid change in the level of learning technology requires change in the way how we teach and learn. The plain old telephone technology, the powerful tool of communication has morphed into internet, multimedia, cellular wireless devices. It is not only growing in numbers but changing its face every time, when there is some technological change. Let's imagine m-learning platforms in next two years when besides smart phones and tablets we will also have smart wearable devices like smart watches and smart glasses.

The same pedagogy cannot be implemented in m-learning. In order to implement m-learning we need basic infrastructural facilities like stable electricity, network coverage and high speed broad band. There must be acceptance of smart phones among students and ability to identify mobile applications, they are also required to pay for mobile broadband and services like SMS and voice call.

There are cognitive challenges in m-learning in the form of adjusting learning process to m-learning like traditional teaching material or e-learning material cannot be directly used in case of m-learning. Another cognitive challenge for mobile learning implementation is how to manage and evaluate the assessment of the learning processes and outcomes. It may also be difficult to track the progress of learning if it occurs across multiple/different settings using a variety of devices. Insufficient text and content display of mobile devices to support mobile learning is also another cognitive challenge. The learning procedure, context and usability factors such as display size and battery life affect user practices. This is equally important for features of smart phones and tablets.

Problem Statement

Apps may be the lifeblood of smart phones in today's world. Yet, app downloads in India are estimated to account for less than 5 percent of global app downloads despite the country being the world's second largest mobile user market after China. Besides, the top 10-15 apps comprise 80 percent those downloaded globally, posing a challenge for developers to make money through app development. In 2009, worldwide mobile app downloads amounted to approximately 2.52 billion and are expected to reach 268.69 billion in 2017 (Saxena percent Sen, 2013). India ranks fifth among the emerging markets based on revenues, according to the PwC Global 100 Software Leaders report (2013), a revenue-based study on the world's top 100 software vendors. The Indian IT industry has been primarily identified with software services and this focus has relegated the software products segment to the background. However, off late, we are seeing a change in the fortunes of this segment due to significant growth. Emerging technologies such as social media, mobility, analytics and cloud (SMAC) are driving the growth in this segment and helping it move to the next level. A number of software product firms have grown over the last decade from a little over 100 in the year 2000 to nearly 2,400 in 2013. According to the National Association of Software and Services Companies (NASSCOM), the revenue from the software product segment currently stands at $2.2 billion and is expected to reach $10 billion by 2020 (TRAI 2013).

The current study is based on mobile application compatible in both android and ios, developed for students in rural areas who are not having access to higher education and information of various exams, study material, expert's advice and so on. According to various government reports almost 50 percent of the population in India stays in rural areas hence the educational software and the application will be launched for such people who hail from rural areas and are not well equipped with the resources of preparation for their higher education. This application will allow them to look for best fit institutions for them and also the eligibility criteria. Not only it will help in finding the institutions but it will also help the students to prepare for the examinations so as to get admissions in those institutions. This application will also be fortified with the recorded lectures which will further enhance the students' knowledge and help them to prepare efficiently. Students can also download lectures that are designed so as to gather the students who are not in condition of paying the fee of coaching institutes made for the preparation of entrance examination charging big amounts. The government may also be benefitted by this as they can track the areas with high response and start developing the suitable apps and also get the data of students.

Objectives of the Study

With this background an investigation was carried to understand the requirements of rural youth in higher education, their technology readiness towards m-learning and their acceptance level of educational software app. the specific objectives of this study are:

* To identify the educational services needed in higher education by rural youth.

* To determine the usage pattern of mobile phones in rural India.

* To assess the technology readiness among the higher education students.

Methodology

The exploratory approach was used with the objective of identifying need of rural youth for higher education. The target respondents for this study were individuals pursuing 12th, pursuing graduation and graduates. The area of study was 13 districts of Madhya Pradesh such as Dhar, Sioni and Narsinghpur district. In total 43 villages were covered and 8300 questionnaires were distributed. The total numbers of respondents considered for the analysis are 8273, which includes respondents from schools, colleges and local libraries. The survey is certified by the colleges and schools with their seal and signatures. The data was collected empirically through two questionnaires to understand their requirements and to check the acceptance level of educational software app in the rural areas.

The first questionnaire was developed to understand about the career objectives for those students who were preparing for management courses like CAT, MAT, XAT, IIFT, GMAT, NMAT, SNAP, CMAT, Bank P.O., & others competitive exams & they were not having enough resources to find the information about exam, colleges & criteria's of these colleges. The questions were developed to understand which kind of magazines they are reading to collect information. Second questionnaire was prepared to assess the technology readiness level and acceptance of mobile software apps in rural areas. The devices they own, what kind of applications they use most, how much they are ready to spend for educational apps.

Results

Demographics of Respondents

Out of 8273 respondents 60 percent were male and 40 percent were female. Majority of the respondents were in the age category of above 18 i.e. in between 18-20 (42 percent) and 21-25 (48 percent).

Information Needed by Respondents

To understand the information required, respondents were asked to name the magazines they prefer most. Fig I indicates that they mostly prefer Pratiyogita Darpan (31 percent) among the available magazines. The second most preferred magazine was Competition Master with percentage of 21. Most of the respondents gave their language preference as Hindi (68 percent). When respondents were asked about the section that they prefer in these magazines, they mainly preferred exam notifications (92 percent), Mock papers (82 percent), Exam tips (72 percent), articles on institutes (68 percent) and career articles (63 percent) (Table I).

Mobile Demographic Results

Mostly all students were using android based (56 percent) or windows based phones (41 percent), very few students (3 percent) were using iphone. The internet facility was not available on regular basis to these respondents. They were mainly using it on irregular basis like they were buying internet recharge of Rs. 10, 15, 50, 100 once or twice in a month. The WiFi facility was not available in any of the school, colleges or libraries. However internet facility was available through desktop and few district school and colleges were running weekend classes to provide computer education and information regarding different apps available for different purposes. Students were mainly using internet for services like downloading game apps, social networking apps, weather apps and travel apps (Table II). One of the interesting observations regarding internet usage was that maximum usage was done by girl students for social networking and downloading music.

Preference regarding Educational Apps

When respondents were asked about their preference for the educational apps for which this study is based, 94 percent of them said they will prefer such educational app. They gave their preference regarding app which can provide them information of different exams, institutes, articles on career, lecture on various topics, mock papers, MCQs etc. By asking how much money they are ready to spend for such educational app, most of them wanted it for free (39 percent) or in less than Rs. 100 per month (32 percent). Around 23 percent were ready to pay in between Rs. 100 to 150 per month.

Conclusion

In summary this study shows that there is a high possibility of providing educational information through mobile apps. Although it is not related to the implementation process of mobile apps, current study provides the empirical exploration of mobile demographics and the readiness level of rural youth towards mobile apps. Mobile learning is learning on-the go and learning at the point of need, but it is also a way of consuming content, a social experience and an informal way to learn. This shows that there is an increase in usage of mobile by those who are new to using technologies, implying that some are adopting mobile solutions as part of their first steps with learning technologies. It provides the idea to the educators and even to the government to utilize mobile learning tools to spread knowledge in education deficit areas. This paper serves as a reference base for future studies focused on development of mobile learning applications specially for improving education levels of rural students.

Neetu Ahmed

Assistant Professor, Vedatya Institute, Gurgaon, Haryana.

Gurleen Kaur

Assistant Professor, Sri Guru Gobind College of Commerce, University of Delhi, New Delhi.

References

Allen S. J. (2007). Adult learning theory & leadership development, Leadership Review, 7, 26-37.

ASER (2014). Annual Status of Education Report (Rural) Retrieved from www.asercentre.org/P/51.html?P=61

Attewell, J., & Savill S. C. (2003). M-learning and social inclusion--focusing on learners and learning. Proceedings of MLEARN 2003: Learning with Mobile Devices (pp. 3-12). London, UK: Learning and Skills Development Agency.

Avgerou, C. (2008). Information systems in developing countries: A critical research review. Journal of Information Technology, 23 (3), 133-146.

Brown, J.S., Collins, A., & Duguid, S. (1989). Situated cognition and the culture of learning. Educational Researcher, 18 (1), 32-42.

Bruner, J. (1966). Toward a theory of instruction. Cambridge, MA: Harvard University Press.

Chinnery, G.M. (2006). Emerging technologies going to the MALL: Mobile assisted language learning. Language Learning & Technology, 10, 9-16.

Cortez, C., Nussbaum, M., Santelices, R., Rodriguez, P., Zurita, G., Correa, M., & Cautivo, R. (March, 2004). Teaching science with mobile computer supported collaborative learning (MCSCL). Proceedings of the 2nd International Workshop on Wireless and Mobile Technologies in Education (pp. 67-74). JungLi, Taiwan: IEEE Computer Society.

Joseph, S., Binsted, K., & Suthers, D. (Nov, 2005). Photo study: Vocabulary learning and collaboration on fixed and mobile devices. Proceedings of the 3rd International Workshop on Wireless and Mobile Technologies in Education (pp. 206-210). Tokushima, Japan: IEEE Computer Society.

IAMAI says India will have 500 Million Internet users by 2017. (2015, July 21). The Indian ExpressRetrieved from: http://indianexpress.com/article/technology/tech-news-technology/iamai-says-india-to-have-236-million-mobile-internet-users-by-2016/#sthash.ckWCjAvi.dpuf.

Kadyte, V. (2003). Learning can happen anywhere: A mobile system for language learning. In J. Attewell & C. Savill-Smith (Eds.) Learning with mobile devices research and development Proc MLEARN2003 (pp. 73-78). London: Learning and Skills Development Agency.

Kiernan, P.J., & Aizawa, K. (2004). Cell phones in task based learning: Are cell phones useful language learning tools? ReCALL, 16 (1), 71-84.

Kim, P, Buckner, E., Kim, H., Makany, T., Taleja, N., & Parikh, V. (2012). A comparative analysis of a game-based mobile learning model in low-socioeconomic communities of India. International Journal of Educational Development, 32 (2), 329-340. Elsevier Ltd.

Koschmann, T., Kelson, A. C., Feltovich, P J., & Barrows, H. S. (1996). Computer-supported Problem-Based Learning: A principled approach to the use of computers in collaborative learning. In T.D. Koschmann (Ed.), CSCL: Theory and Practice of an Emerging Paradigm (pp. 83-124). Hillsdale, NJ: Lawrence Erlbaum.

Lave, J., & Wenger, E (1991). Situated learning: Legitimate peripheral participation. Cambridge, England: Cambridge University Press.

Levy, M., & Kennedy, C. (2005). Learning Italian via mobile SMS. In: Mobile Learning: A Handbook for Educators and Trainers. (pp. 76-83.) Taylor and Francis, London.

Lonsdale, P, Baber, C, Sharples, M ., & Arvanitis, T. N. (2003). A context-awareness architecture for facilitating mobile learning. Proceedings of MLEARN 2003: Learning with Mobile Devices (pp. 79-85). London, UK: Learning and Skills Development Agency.

Looi, C. K., Scow, P, Zhang, B.H., So, H, J., Chen, W L., & Wong, L. H. (2010). Leveraging mobile technology for sustainable seamless learning: A research agenda. British Journal of Educational Technology, 41(2), 154-169.

Ogata, H., & Yano, Y. (2004). Knowledge awareness map for computer-supported ubiquitous language-learning, Proceedings of 2nd International Workshop on Wireless and Mobile Technologies in Education, JungLi, Taiwan, 2325 March.

Pea, R., & Maldonado, H. (2006). WILD for learning: Interacting through new computing devices anytime, anywhere. In R. K. Sawyer (Ed.), The Cambridge handbook of the learning sciences (pp. 427-441). Cambridge: Cambridge University Press.

Prakash, A., & De, R. (2007). Importance of development context in ICT4D projects: A study of computerization of land records in India. Information Technology and People, 20 (3), 262-281.

PwC Global 100 Software Leaders report (2013), Retrieved from http://www.pwc.in/press-releases/indian-software-industry-poised-for-strong-revenue-growth.html.

Saxena R., Sen A., Indian app makers struggle for download breakthroughs (2013, March 4) Live Mint, Retrieved from http://www.livemint.com/Industry/rKbwPPa4A11X4952SVwcuJ/Indian-app-makers-struggle-for-download-breakthroughs.html.

Sharples, M., Taylor, J., & Vavoula, G. (2005). Towards a Theory of Mobile Learning, in van der Merwe H, Brown T, Mobile Technology: The Future of Learning in Your Hands, mLearn 2005 Book of Abstracts, 4th World Conference on mLearning, Cape Town, 25-28 October 2005, Cape Town: mLearn 2005, p. 58.

Reimers, F. (2000). Unequal schools, unequal chances: The challenges to equal opportunity in the Americas, Harvard University Press.

Rheingold, H. (2003). Smart mobs: The next social revolution, Cambridge, MA: Perseus.

Rogers, Y, Price, S, Harris, E, Phelps, T, Underwood, M, Wilde, D, Smith, H, Muller, H, Randell, C, Stanton, D, Neale, H, Thompson, M, Weal, M., & Michaelides, D (2002). Learning through digitallyaugmented physical experiences: reflections on the Ambient Wood project. EQUATOR IRC. Retrieved from http://mcs.open.ac.uk/ yr258/papers/Rogers_Ambient_Wood2.1.pd.

Siemens, G. (2004). Connectivism: A learning theory for the digital age. International journal of instructional technology and distance learning, 2 (1), 3-10.

Squire, K. D., & Klopfer, E. (2007). Augmented reality simulations on handheld computers, Journal of the learning Sciences, 16 (3), 371-413.

Stavredes, T. (2011). Effective online teaching: Foundations and strategies for student success. San Fransisco, CA: Jossey-Bass.

Shuler, C. (2009). iLearnII; An Analysis of the education category of Apple's App store. New York: The Joan Ganz Cooney Center at Sesame Workshop.

Thornton, P., & Houser, C. (2005). Using mobile phones in English education in Japan. Journal of Computer Assisted Learning, 21, 217-228.

TRAI (2014) report retrieved from http://www.trai.gov.in/

Trucano M. (2007). What do we know about the effective uses of information and communication technologies in education in developing countries?, Assessing the effects of ICT in education, OECD, 61-67.

Walsham, G. (2010). ICTS for the broader development of India: An analysis of the literature. Electronic Journal of Information Systems in Developing Countries, 41 (4), 1-20.

The World Bank, World Development Indicators (2014) retrieved from http://data.worldbank.org/ sites/default/files/wdi20l4-highlights.pdf.

Zurita, G., Nussbaum, M., & Sharples, M. (2003). Encouraging face-to-face collaborative learning through the use of hand-held computers in the classroom: Proceedings of Mobile HCI 2003 (pp. 193-208). Udine, Italy: Springer-Verlag.

Zurita, G., & Nussbaum, M. (2004). Computer supported collaborative learning using wirelessly interconnected hand-held computers. Computers & Education, 42(3), 289-314. Table I--What are the sections which you read most in these magazines? Option Result in % Articles on careers 63 Articles on various 72 exams Advertisements of 1 institutes Aptitude testing 72 Interviews of students 44 Mock paper 82 Tips on cracking exams 68 Group Discussion tips 32 Interview tips 32 Exam notification ads 92 Articles on IIM & B 71 schools cutoff Articles on B school 68 information with ranking on the basis of actual data Articles on current 32 affairs Others articles 6 Table II--What kind of the application do you use most? Option Result in % Games Apps 80 Calculate / Utilities 43 Apps (convert units, estimate bill payment, etc.) Educational Apps 0 News Apps 12 Productivity Apps 0 (manage bank accounts, time organizer, etc.) Search Tool Apps 12 Social Networking 91 Apps Sports Apps 22 Travel Apps, maps, 74 GPS Weather Apps 80 Music 30 Fig I Which magazine do you prefer to read to gather information on career opportunity? in % Competition ... 18 Pratiyogita Darpan 31 Competition Master 21 Chronicles 15 G.K. Today 5 G.K. Refresheer 8 Education today 1.5 Others 0.5 Note: Table made from bar graph.
联系我们|关于我们|网站声明
国家哲学社会科学文献中心版权所有