Differences of Web Computing and Cloud Computing

timer Asked: Feb 21st, 2019
account_balance_wallet $100

Question Description

I have chosen it, but you have to read it and extract it

differences between web computing and cloud computing

. A research question based on a topic needs to be the organizational driver of the literature review.

Include the following:

  • All sources must be from peer-reviewed journal articles published within the last 10 years.
  • The focus should be on scholarly dialogue, not simply a summary or list of research studies.
  • Identify common threads among the research studies and use those as subheadings.
  • Offer critiques of the individual studies.
  • Indicate any conflicts in findings among studies.
  • Identify gaps in knowledge – what has not been studied?
  • Students are required to use citation management software (e.g. Zotero) to manage their articles and create their reference list in APA format.

Available online at www.sciencedirect.com Procedia Social and Behavioral Sciences 2 (2010) 938–942 WCES-2010 Effective use of cloud computing in educational institutions Tuncay Ercana * a Yasar University, Department of Computer Engineering, Selcuk Yasar Kampusu, Agacl Yol, No:35-37, Bornova 35500, Izmir, Turkey Received October 8, 2009; revised December 17, 2009; accepted January 5, 2010 Abstract Cloud computing is becoming an adoptable technology for many of the organizations with its dynamic scalability and usage of virtualized resources as a service through the Internet. It will likely have a significant impact on the educational environment in the future. Cloud computing is an excellent alternative for educational institutions which are especially under budget shortage in order to operate their information systems effectively without spending any more capital for the computers and network devices. Universities take advantage of available cloud-based applications offered by service providers and enable their own users/students to perform business and academic tasks. In this paper, we will review what the cloud computing infrastructure will provide in the educational arena, especially in the universities where the use of computers are more intensive and what can be done to increase the benefits of common applications for students and teachers. © 2010 Elsevier Ltd. All rights reserved. Keywords: Cloud computing; virtualization; SaaS. 1. Introduction Nowadays, the term “cloud computing” has been an important term in the world of Information Technology (IT). Cloud computing is a kind of computing which is highly scalable and use virtualized resources that can be shared by the users. Users do not need any background knowledge of the services. A user on the Internet can communicate with many servers at the same time and these servers exchange information among themselves (Hayes, 2008). Cloud Computing is currently one of the new technology trends (broadband internet, fast connection and virtualization) will likely have a significant impact on teaching and learning environment. Senior people in charge of their business place challenge how to redesign their IT operations to support their business units in the light of different technology trends so they can achieve their corporate objectives. Rising business demands are forcing responsible IT people to consider new ways to reallocate their limited internal resources to better support their corporate priorities. This is driving them to rely more heavily on third-party services to increase their in-house capabilities and better satisfy the needs of their end-users, as well as their customers and strategic partners. * Tuncay Ercan. Tel.: +90-232-411-5287; fax: +90-232-411-5020 E-mail address: tuncay.ercan@yasar.edu.tr 1877-0428 © 2010 Published by Elsevier Ltd. doi:10.1016/j.sbspro.2010.03.130 Tuncay Ercan / Procedia Social and Behavioral Sciences 2 (2010) 938–942 939 Today’s “cloud” platforms such as “Microsoft” and “Google” are providing free services to students and staff at educational institutions which include email, contact lists, calendars, document storage, creation and sharing documents and the ability to create websites (Sclater, 2009). He surveyed in different companies from different industries who have built custom applications in the cloud and analyzed how cloud computing affected their operations in three important areas: Security, Integration, and Time-to-Value. 2. Previous Studies Many of the previous work in the field of cloud computing have been in the areas of new technologies, general explanation of the cloud technology, differences among similar technologies, security requirements and the future expectations in these emerging environments. While Banerjee (2009) provides an overview of technological researches performed in HP labs, and a cloud-scale intelligent infrastructure attracts, smart environments like utility computing, smart data centers, pervasive computing, automation, virtualization and intelligent networks already penetrate many spaces of our daily live (Klein & Kaefer, 2008). Cloud computing is an emerging application platform and aims to share data, calculations and services among users. The methods to model it with the challenges like user interface, task distribution and coordination issues are explained and evaluated in (Lijun, Chan, & Tse, 2008). Grossman et a1, (2009) developed a cloud-based infrastructure which had been optimized for wide area, performance networks and supported necessary data mining applications. Cloud computing infrastructures accelerated the adoption of different technological innovations in academia and its facilities and resources could be accessed by the colleges as on–demand. Praveena & Betsy, (2009) provided a comprehensive introduction to the application of cloud in universities. Delic & Riley (2009) assessed the current state of the Enterprise Knowledge Management and how it would turn into a more global, dependable and efficient infrastructure namely cloud computing. They discussed architectural technologies and related applications. The basic features of cloud computing are presented and compared with the original “Grid Computing” technology (Aymerich, Fenu & Surcis, 2008). They introduced new services that will replace many types of computational resources currently used. In that perspective, they also consider that grid computing will play a fundamental role in defining how cloud services will be provided. SaaS, the software deployment service provided by the Internet Service Providers (ISP) and the carrier companies is expected to change the current system architecture of the organizations and thus is accepted as another innovation for the network society (Hirata et a1, 2008). In the software-as-a-service (SaaS) cloud model, service providers supply the hardware and software products and interact with the user through a web portal. Services can be anything from Web-based email to inventory control and database processing (Newton, 2009). Cloud provides the opportunity of flexibility and adaptability to use the computing resources on-demand. Contrary to having only one service provider, different providers use different interfaces to their compute resources utilizing varied architectures and implementation technologies for customers. Although this creates a management problem, a common architecture facilitates the management of compute resources from different Cloud providers in a homogenous manner (Dodda, Smith & van Moorsel, 2009). Mitchell (2008) provided an overview of existing learning architectures, and raised questions about how educational institutions are managing the cloud computing resources. He also brought reasonable explanations for the challenge of indexing web resources for optimum discoverability by students and educators. After this brief literature review providing the context from the infrastructure, application and services aspect of cloud computing, this paper focuses on the educational usage of the cloud services and how it will support these virtual services in a secure manner. We will also look for the answers of its benefits to higher education institutions and different educational uses. Based on the literature review and analysis of the current cloud computing service provisions and applications in institutions, we also introduce cloud computing to educators and help them to gain a better understanding of the conception of cloud technology and its impact on teaching and learning in institutions. 940 Tuncay Ercan / Procedia Social and Behavioral Sciences 2 (2010) 938–942 3. Educational Usage of Cloud Computing The Cloud delivers computing and storage resources to its users/customers. It works as a service on demand policy. Cloud computing is a new business model wrapped around new technologies like virtualization, SaaS and broadband internet. Recent interests offered new applications and elastic scalability with higher computing parameters. So that, these positive effects have shifted to outsourcing of not only equipment setup, but also the ongoing IT administration of the resources as well (Open Grid Forum, 2009). The results of a survey that have been completed in 2009 by Gartner analysts (Figure 1) about the IT trends (especially cloud computing) show that it is being used more in the areas of finance and business when compared to other sectors (Gartner, 2009). Results are shown as a pie chart and the labels on each different slice represent different industrial sectors and services. The “/” is used to separate different sectors with the same percentage. Percentages for cloud usage in different Industrial Sectors and Services Freight services / Energy management / Membership organizations ; 2,2,2 Media / Military and National Security; 3,3 Chemical and pharmaceutical; 3 Commercial physical research; 1 Financial services; 12 Other; 4 Business and management services; 10 Food / Retail / Healthcare; 4,4,4 Schools and education services ; 4 Oil, gas and electric; 5 specialized services ; 5 Manufacturing; 10 Professional; 5 Insurance; 6 Government; 7 Telecommunications and equipment; 9 Figure 1. Cloud usage 3.1. Requirements Many technologies that were previously expensive or unavailable are now becoming free to anyone with a web browser. This is true for all web sites, blogs, video sharing, music sharing, social sharing, collaboration software, editing/presentation and publishing, and computing platforms in the “cloud”. Students are already using many of these technologies in their personal lives. In the professional world, the trend of discovering and using technologies in our personal life is called “consumerization”. This means we should demand and consume the required services. Our education system should take advantage of this same trend, which will both enrich our student’s technologyenabled education, and importantly, reduce the budget impact in academic institutions. University management Tuncay Ercan / Procedia Social and Behavioral Sciences 2 (2010) 938–942 941 should identify and leverage emerging technologies that are cost-effective, and strive for the broadest feasible and equitable access to technology for students and staff. The need for hardware and software isn’t being eliminated, but it is shifting from being on-premises to being in the cloud. All that is needed is a cheap access device and a web browser, broadband in the schools, perhaps wireless hotspots. 3.2. Proposed Model The model we will try to offer in this study, should easily meet the needs of the administrative staff (student affairs, finance and accounting, purchasing and procurement, etc.) and education, training and research related needs of students and academic staff who work especially in the educational institutions. Universities should perform all the necessary stages in order to establish infrastructure for cloud as they work for an appropriate network design and should work together with the units and personnel mentioned in the above paragraph in order to optimize all the requirements (Figure 2). Compute resources (processors, memory, storage, bandwidth, etc.) are provided in an asneeded, pay-as-you-go model. Infrastructure scales up and down quickly to meet demand. Infrastructure model User Devices Network Resources Memory Resources Data Resources Business Continuity Virtualization CPU Resources Storage Resources Security Firewall/ IDS/Perimeter Security Figure 2. Required infrastructure model The most important feature of the various applications offered by cloud is their availability and scalability. Userfriendly interfaces of cloud based applications enable users successfully enlarge their computing environment. A cloud-based platform planned by (Erickson et a1, 2009) places the application-content rather than applications themselves at the center. This enables users to rapidly build customized solutions around their content items. Cloud content (scientific and social subjects, art, opinions, textbooks, encyclopedias, etc.) is controlled by the service providers and available to users whenever they request. Improved data mining techniques filter and find the requested content in order to help students (Figure 3). Student’s objectives are not limited to their courses or schools, hence existing content should be changed dynamically and frequently. Custom services are combined with 3rd party commercial services to create new applications. Application model App-1 App-2 App-n Application Management Data Management Service Level QoS Support Security Figure 3. Required application model Subscription Billing 942 Tuncay Ercan / Procedia Social and Behavioral Sciences 2 (2010) 938–942 4. Conclusion Cloud computing as an exciting development is a significant alternative today’s educational perspective. Students and administrative personnel have the opportunity to quickly and economically access various application platforms and resources through the web pages on-demand. This automatically reduces the cost of organizational expenses and offers more powerful functional capabilities. There will be an online survey to collect the required data for the use of cloud computing in the universities and other governmental or private institutions in the region. This will help us review the current status and probable considerations to adopt the cloud technology. Beginning with the outsourcing of email service seems attractive. The gradually removal of software license costs, hardware costs and maintenance costs respectively provides great flexibility to the university/corporate management. From the points of advantages provided by cloud, there is a great advantage for university IT staff to take them away the responsibility of the maintenance burden in the university. Cloud provides instant global platforms, elimination of H/S capacities and licenses, reduced cost, simplified scalability. Adopting cloud network redundancy eliminates disaster recovery risks and its high costs. There can always be new tools and applications to improve IT features. There are of course some disadvantages too. The cloud computing services needed to deliver the majority of IT services needed by customers do not yet exist. There are still problems and constraints with application offerings, service-level agreements, more importantly security issues. All of the cloud providers do not have the same capability for their technological levels. References Aymerich, F. M., Fenu, G., Surcis, S., & IEEE. (2008). An Approach to a Cloud Computing Network. 1st International Conference on the Applications of Digital Information and Web Technologies, Ostrava, CZECH REPUBLIC, 120-125. Banerjee, P. (2009). An intelligent IT infrastructure for the future. 15th International Symposium on High-Performance Computer Architecture, Proceedings, Feb 14-18, 3. Delic, K. A., & Riley, J. A. (2009). Enterprise Knowledge Clouds: Next Generation KM Systems? International Conference on Information, Process, and Knowledge Management, Cancun, MEXICO. 49-53. Dodda, R. T., Smith, C., & van Moorsel, A. (2009). An Architecture for Cross-Cloud System Management. 2nd International Conference on Contemporary Computing, Nioda, INDIA. 40, 556-567. Erickson, J. S., Spence, S., Rhodes, M., Banks, D., Rutherford, J., Simpson, E., et al. (2009). Content-Centered Collaboration Spaces in the Cloud. IEEE Internet Computing, 13(5), 34-42. Gartner. (2009). Cloud Computing Inquiries at Gartner, http://blogs.gartner.com/thomas_bittman/2009/10/29/cloud-computing-inquiries-atgartner. Grossman, R. L., Gu, Y. H., Sabala, M., & Zhang, W. Z. (2009). Compute and storage clouds using wide area high performance networks. Future Generation Computer Systems-the International Journal of Grid Computing Theory Methods and Applications, 25(2), 179-183. Hayes, B. (2008). Cloud computing. Communications of the ACM, 51 (7), 9-11. Hirata, H., Imai, K., Noguchi, M., & Asano, T. (2008). Acceleration of unified communications with NGN and SaaS. NEC Technical Journal, 3(3), 59-64. Klein, C., & Kaefer, G. (2008). From smart homes to smart cities: Opportunities and challenges from an industrial perspective, Next Generation Teletraff c and Wired/Wireless Advanced Networking, Proceedings, Lecture Notes in Computer Science, 5174, 260. Lijun, M., Chan, W.K., & Tse, T.H. (2008). A tale of clouds: Paradigm comparisons and some thoughts on research issues. IEEE Asia-Pasific Services Computing Conference, APSCC’08, 464-469. Mitchell, P. (2008). Learning architecture: issues in indexing Australian education in a Web 2.0 world. Indexer, 26(4), 163-169 Newton, J. (2009). Are SaaS & Cloud Computing Interchangeable Terms?. http://www.daniweb.com/blogs/entry3993.html. Open Grid Forum. (2009). Cloud Storage for Cloud Computing, Storage Networking Industry Association. http://www.snia.org/cloud/ CloudStorageForCloudComputing.pdf. Praveena, K., & Betsy T. (2009). Application of Cloud Computing in Academia. IUP Journal of Systems Management, 7 (3), 50-54. Sclater, N. (2009). Cloudworks, eLearning in the Cloud, http://cloudworks.ac.uk/cloud/view/2430/.
International Conferences ITS, ICEduTech and STE 2016 CLOUD COMPUTING IN HIGHER EDUCATION SECTOR FOR SUSTAINABLE DEVELOPMENT Yuchao Duan School of Information Systems, Curtin University, Kent St, Bentley WA 6102, Australia ABSTRACT Cloud computing is considered a new frontier in the field of computing, as this technology comprises three major entities namely: software, hardware and network. The collective nature of all these entities is known as the Cloud. This research aims to examine the impacts of various aspects namely: cloud computing, sustainability, performance management, government and other aspects in line to develop a new sustainable cloud computing model for the higher education sector in China. Currently, there are several obstacles facing the adoption of cloud computing in China, namely: lack of standards; insufficient educational data and disregard for environmental impacts. A mixed method approach will be employed in this research comprising at least 20 interviews to elicit the attitudes of the cloud users towards the initial model, based on the interviews feedback, the model will be optimized and an online survey will be conducted with a sample size of minimum 390 to examine the perceptions and attitudes of participants towards the new model. The main target participants will be students, academic staff and personnel working in IT departments in Chinese universities. KEYWORDS Cloud Computing, Sustainability, Model, China 1. INTRODUCTION The concept of cloud computing was jointly proposed by Google and IBM in 2007 (Wang and Xing, 2011). Cloud computing is a computing platform that resides in a large data centre and is able to dynamically provide servers with the ability to address a wide range of needs, from scientific research to e-commerce (Jaeger et al., 2008). The global cloud computing market is expected to grow from US$40 billion in 2011 to US$241 billion in 2020 (Ried and Kisker 2011, quoted in Cheng et al., 2016). The development of cloud computing is growing rapidly and the cloud computing industry has great market potential in China (Yu et al., 2016). This research aims to examine the current cloud computing models, with the purpose of developing and evaluating a new cloud computing model for the higher education sector in China. An in-depth analysis of cloud computing will be conducted with respect to cloud computing, sustainability, performance management, government and other aspects in order to develop appropriate solutions for China. 2. UNDERSTANDING CLOUD COMPUTING Cloud computing generally refers to an Internet-based computing model that various PCs and servers are associated with Internet, operating systems, software and database. These resources can be shared by multiple clients based upon their demands (Chi and Gao, 2011). Similarly, Vouk (2008) claims that cloud computing aims to maximize the profit and minimize the cost of computing by migrating software, hardware, operating systems and other computing service-related devices from local data centres to cloud servers provided by cloud venders, thereby enabling cloud clients to utilize the computing resources which are available in the cloud servers via client program at any time from any location where there is access to the Internet. 333 ISBN: 978-989-8533-58-6 © 2016 2.1 Service Models According to Metz (2011), three cloud computing service models have been defined by NIST (National Institute of Standards and Technology): Software as a Service (SaaS); Platform as a Service (PaaS) and Infrastructure as a Service (IaaS). Software as a Service enables cloud software or applications to be operated on the cloud-based virtual server, so the clients can access the resources at anytime from anywhere once they have linked to the network (Cusumano, 2010, Armbrust et al., 2010). Google Mail and Google Calendar are good examples of SaaS. Platform as a Service is the second cloud server model. Applications and services can be built in the cloud based on clients’ requirements, so the cloud users can access the online applications without having to download or install them (Qayyum et al., 2011).Google App Engine is one example of PaaS. The third cloud server model is Infrastructure as a Service. The IaaS platform provider supplies the hardware, storage space servers and other computing devices to cloud clients. The platform can be utilized immediately which saves a lot of time for clients, and routine equipment maintenance is carried out by providers (Bhardwaj et al., 2010). 2.2 Deployment Models Just as cloud services have different models such as SaaS, PaaS and IaaS, there are different deployment models of cloud computing as well. According to Metz (2011), four different deployment models for cloud computing have been outlined by NIST: Private cloud, Public cloud, Hybrid cloud, and Community cloud. Private cloud is defined as an individual institution operating its own cloud (Metz, 2011). According to Wyld (2010), in the private cloud method, the cloud infrastructure is owned solely by a company and it may be managed by the organization or a third party and may exist on the premises or off-premises. Schubert et al. (2010) point out that private clouds are normally operated by the respective organization; the functionalities are not exposed to the customers directly and it is similar to Software as a Service from the customer‘s perspective. A public cloud service is used by the general public(Metz, 2011). The cloud infrastructure can be accessed by the public cloud users or a large scale industry group and is owned by the cloud provider (Wyld, 2010). Public cloud is based on the standard cloud computing model and the cloud service provider will make resources such as storage space or applications available to the general public cloud computing users through the Internet. The subscription models of public cloud services include a pay-per-usage model or may even be free. Hybrid cloud allows institutions to deploy an application or system using more than one type of deployment model (Metz, 2011). Finally, the term "private cloud" refers to a proprietary network or data centre managed by the organization; "public cloud" means that public cloud users can share the cloud infrastructure; the hybrid cloud is maintained by both internal and external providers. According to VMware (Chang et al., 2010), hybrid cloud is a cloud infrastructure consisting of two or more clouds; private and public cloud can be combined together under standardized technology and specific rules that enable application and data portability. "The cloud infrastructure is shared by several organizations and supports a specific community that has shared concerns (e.g., mission, security requirements, policy, and compliance considerations). It may be managed by the organizations or a third party and may exist on premise or off premise" (CISCO 2012). Schubert et al. (2010) believe that generally cloud systems are restricted to the local infrastructure; for instance, public cloud service providers offer their own computing infrastructure to users. 2.3 Current Status of Cloud Computing Development in China According to the research report from BAS Global Cloud Computing Scorecard, China has shown enthusiasm for ICT development and improvement compared with other countries, and China was ranked in 19th among 24 countries that account for 80% of the global ICT market in 2013. Moreover, China has made critical progress regarding broadband coverage, and in June 2012 carried out a magnificent national broadband arrangement to meet the anticipated 800 million web clients in China in 2015 (2013). As for the education area, believe that there is an immense shortfall in educational information among different districts, between urban and rural areas and among various schools (Wang and Xing, 2011, Wang, 2002, Mundial, 2013). Because of the dense population and vast territory of China, some areas of public education, assets allocation and utilization are not adequately supervised. 334 International Conferences ITS, ICEduTech and STE 2016 2.4 Research Gap Governance involves the strategic task of establishing an organisation’s goals, direction, limitations and accountability frameworks. It is necessary to set up the governance strategy up front if universities or institutions consider adopting the cloud computing technology. Once cloud computing has been adopted, performance management is required to ensure that the system operates as planned. Moreover, sustainable green IT attracts more attention nowadays. Environmental sustainability has been defined as “development that meets the needs and aspirations of the present without compromising the ability of future generations to meet their own needs” (Brundtland, 1987). Thus, governance, sustainability and performance management should be considered together when developing a cloud computing model. To the best of my knowledge, none of the articles which have been reviewed so far has covered these three aspects together, so this study aims to create a cloud computing model that includes cloud computing governance, sustainability and performance management. 3. RESEARCH METHOD AND QUESTION The mixed methods approach has been chosen for this research. Mixed methods research is a methodology for conducting research that involves collecting, analysing, and integrating quantitative and qualitative research in a single study or a longitudinal program of inquiry. The advantage of this form of research is that both qualitative and quantitative research, in combination, provides a better understanding of a research problem or issue than either research approach alone. This research contains online survey and semi-structured interviews. In this research, all the data will serve to resolve the research questions, and the online survey will contain both close-ended and open-ended questions. Thirty universities from top 500 universities in China have been selected as the target participants of this research, and data of interviews and questionnaires will be mainly gathered from these 30 universities. This research aims to develop and evaluate a new cloud computing model for the higher education sector (universities) in China, and would answer the following question: What are the perceptions and attitudes of students, academic staff and IT department personnel towards the new sustainable cloud computing model in Chinese universities? Certainly target participants would have different expectations as their needs are different, various information would be received from participants, thus software like Nvivo will be utilised with the purpose of analysing and combining the useful information to develop a sustainable cloud computing model for Chinese universities. 4. RESEARCH OUTCOME This research will provide a detailed description and new perspective on the cloud computing in Chinese universities. Based on the literature review, an initial model was developed and it consists of three components namely: governance, sustainability and performance management. The proposed model aims to provide a broader view of the cloud technology by combining all these three elements together. Internal stakeholders such as students’ staff and IT personnel will be the users of the new model, and external stakeholders’ service provider, researchers, software developers, government, research partners, etc. could also be effected by this model. This research will review the current cloud computing models. A series of solutions and standards regarding cloud computing will be generated in this research. The outcome of this research is a new cloud computing model which can be applied to universities in China in the future. It is anticipated that this model will encourage Chinese universities to adopt the cloud computing technology in line to become more sustainable. For those universities who already using the cloud technology, this model will provide some valuable information to improve their cloud strategy. Furthermore, with certain modifications, this cloud model could be adapted for other universities in other countries. The new model will be evaluated by using mixed methods approach. The new cloud computing model will be developed to support a great number of potential cloud users who need to clearly understand the principles for cloud-related governance; enterprise architects, business analysts and software developers who are willing to adopt newer approaches to develop and deploy cloud services and infrastructures based on a new cloud computing model; cloud computing field researchers who would like to further increase their understanding of the governance, sustainability and performance management aspects of cloud computing; and students and lecturers who are interested in further enhancing their cloud-related knowledge. 335 ISBN: 978-989-8533-58-6 © 2016 5. CONCLUSION In conclusion, this research provides an initial description regarding the cloud computing model for the Chinese universities. The proposed model aims to improve the environmental sustainability and efficiency of the use of resources in China, especially in the higher education sector. Also, this research will review the current cloud computing models. A series of solutions and standards regarding cloud computing will be generated. The research outcome will benefit potential cloud computing users and institutions in China and globally simultaneously. As time limited, only a few aspects and components from cloud computing have been examined to form this new model in this paper, however, further discussion will be carried out in the future to discuss the assessment, examination and feedback from stakeholders. REFERENCE 2013. BSA Global Cloud Computing Scorecard. Available: http://cloudscorecard.bsa.org/2013/assets/PDFs/country_reports/Country_Report_China.pdf. Armbrust, M., Fox, A., Griffith, R., Joseph, A. D., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A. & Stoica, I. 2010. A view of cloud computing. Communications of the ACM, 53, 50-58. Bhardwaj, S., Jain, L. & Jain, S. 2010. Cloud computing: A study of infrastructure as a service (IAAS). International Journal of Engineering and Information Technology, 2, 60-63. Brundtland, G. H. 1987. Our common future: World Commission on Environment and Development, Oxford, Oxford : Oxford University Press. Chang, V., Wills, G. & De Roure, D. A review of cloud business models and sustainability. Cloud Computing (CLOUD), 2010 IEEE 3rd International Conference on, 2010. IEEE, 43-50. Cheng, H. K., Li, Z. & Naranjo, A. 2016. Research Note—Cloud Computing Spot Pricing Dynamics: Latency and Limits to Arbitrage. Information Systems Research, 27, 145-165. Chi, C. & Gao, F. 2011. The Trend of Cloud Computing in China. Journal of Software, 6, 1230-1234. Cusumano, M. 2010. Cloud computing and SaaS as new computing platforms. Communications of the ACM, 53, 27-29. Jaeger, P. T., Lin, J. & Grimes, J. M. 2008. Cloud computing and information policy: Computing in a policy cloud? Journal of Information Technology & Politics, 5, 269-283. Metz, R. 2011. Understanding the Cloud: An Introduction the the Cloud. In: CORRADO, E. M. & MOULAISON, H. L. (eds.) Getting Starded with Cloud Computing. 1st ed. London: Facet Publishing. Mundial, B. 2013. China 2030-Building a Modern, Harmonious, and Creative Society. The World Bank Development Research Center of the State Council, the People’s Republic of China, 17. Qayyum, J., Khan, F., Lal, M., Gul, F., Sohaib, M. & Masood, F. 2011. Implementing and Managing framework for PaaS in Cloud Computing. IJCSI International Journal of Computer Science Issues, 8, 474-479. Schubert, L., Jeffery, K. G. & Neidecker-Lutz, B. 2010. The Future of Cloud Computing: Opportunities for European Cloud Computing Beyond 2010:--expert Group Report, European Commission, Information Society and Media. Vouk, M. A. 2008. Cloud computing–issues, research and implementations. CIT. Journal of Computing and Information Technology, 16, 235-246. Wang, B. & Xing, H. 2011. The application of cloud computing in education informatization. Wang, X. 2002. Education in China since 1976, McFarland. Wyld, D. C. 2010. The Cloudy future of government IT: Cloud computing and the public sector around the world. International Journal of Web & Semantic Technology, 1, 1-20. Yu, J., Xiao, X. & Zhang, Y. 2016. From concept to implementation: The development of the emerging cloud computing industry in China. Telecommunications Policy, 40, 130-146. 336
British Journal of Educational Technology doi:10.1111/bjet.12208 Vol 46 No 6 2015 1367–1377 Construction of a digital learning environment based on cloud computing Jihong Ding, Caiping Xiong and Huazhong Liu Jihong Ding is a PhD candidate at School of Educational Information Technology of Central China Normal University. Her main research interests are technology-enhanced learning and automatic recommendation. Caiping Xiong is a professor at School of Educational Information Technology of Central China Normal University. His main research interests are technology enriched education, education resources optimal allocation and ubiquitous learning. Huazhong Liu is an on-job PhD candidate at Huazhong University of Science and Technology, and he is also a lecturer of Jiujiang University. His research interests are cloud computing and big data. Address for correspondence: Dr Caiping Xiong, School of Educational Information Technology, Room 730, No. 9 Building, Central China Normal University, No. 152 Luoyu Road, Wuhan 430079, China. Email: junruding@gmail.com Abstract Constructing the digital learning environment for ubiquitous learning and asynchronous distributed learning has opened up immense amounts of concrete research. However, current digital learning environments do not fully fulfill the expectations on supporting interactive group learning, shared understanding and social construction of knowledge. This paper introduces cloud computing to the construction of the digital learning environment for its on-demand services with high reliability, scalability and availability in the distributed environment. Then a digital learning environment based on cloud computing (DLECC) is proposed, including the architecture, co-construction and sharing model, and incentive mechanism of DLECC. Finally, an Educational Technology Space (ETS) platform under the concept of DLECC is constructed and applied to the educational technology training for 110 teachers from primary and secondary schools. The experimental results demonstrate that the co-construction and sharing model and incentive mechanism of DLECC may provide meaningful learning support and interactive communities and promote the co-construction of befitting educational resources. Introduction The construction of digital educational resources is the focus of lifelong learning in the new age. According to the Sloan Consortium’s report on online education in USA, online courses are increasingly becoming a common experience for students (Allen & Seaman, 2010). The digital learning environment is a cooperative and investigative learning system based on Internet resources. It is an open-learning space that contains abundant, diverse resources and interactive and nonlinear organization information resources in line with human cognitive characteristics (Kadne, 2010). In such an environment, learners can decide when to learn, where to learn and what to learn. Scilicet, learners can choose learning tasks and determine learning contents, learning objectives and learning time. Meanwhile, they can customize their own personalized learning tasks according to their own cognitive styles, learning ability and personality characteristics. Besides, learning feedback can be obtained through network examination, assignment submission, group evaluation or teacher evaluation. © 2014 British Educational Research Association 1368 British Journal of Educational Technology Vol 46 No 6 2015 Practitioner Notes What is already known about this topic • Cloud computing technology is widely spread and is integrated with education. • Current digital learning environments based on cloud computing seldom consider designing the incentive mechanism to motivate learners’ learning initiative. • Few empirical studies have shown the concrete design, implementation, evaluation of a digital learning environment based on cloud computing. What this paper adds • Introduced cloud computing to construct the digital learning environment due to its on-demand services with high reliability, scalability and availability. • Proposed a digital learning environment based on cloud computing, including the architecture, co-construction and sharing model, and incentive mechanism. • Constructed the co-construction and sharing model to promote the knowledge aggregation, knowledge regeneration and collaborative editing. • Designed the incentive mechanism to motivate learners’ learning initiative and strengthens community interaction. Implications for practice and/or policy • Co-construction and sharing model may enrich the types and quantity of educational resources, thus radically reform the static resource construction pattern. • Incentive mechanisms may motivate students’ learning initiative, strengthen community interaction and promote the aggregation of collective intelligence. • Ubiquitous learning and adaptive learning is realized due to abundant cloud services and the accessibility of different terminals, which may meet different users’ individual preferences. There is amount of positive research on digital learning environments. However, contemporary digital learning environments are hard to fulfill expectations of fully supporting interactive group learning, shared understanding, social construction of knowledge and acquisition of competencies. The existing teaching platforms have abundant teaching resources and interactive tools but are deficient in information flow control and coordination mechanisms to ensure that learners would have a balanced information access opportunity (Guo, 2011). Thereby, Yang and Yu (2013) built ubiquitous learning ecosystem by integrating the whole elements of learning environments from the perspective of ecology. Although Yang refers to using a kind of mechanism to ensure that the ubiquitous learning environments run effectively, no detailed measures are proposed. Oliver (2013) holds that technology can be used in learning. With the appearance of new technologies such as web 2.0, Internet of Things and cloud computing in succession, cloud computing has greatly triggered educators’ interests in applying cloud computing to education. Kadne (2010) argues that constructing digital learning environments under cloud computing may be an economical way for resources co-construction and knowledge sharing. Cloud computing systems fundamentally provide access to large pools of data and computational resources (Kreijns, Kirschner & Jochems, 2002). Cloud computing has been applied to the field of education since 2009, and concepts such as “cloud computing assisted teaching” and “education based on cloud computing” appear in succession (Zhu & Guan, 2011). © 2014 British Educational Research Association Digital learning environment based on cloud computing 1369 This study applies cloud computing to the construction of digital learning environments, because it can provide on-demand services with high reliability, scalability and availability in the distributed environments. The main objective of this study is to design a digital learning environment based on cloud computing (DLECC), and the research issues can be stated as follows: (1) the architecture of DLECC, (2) the co-construction and sharing model of DLECC, (3) the incentive mechanism of DLECC, and (4) the effect of applying DLECC into practice. Theoretical foundations of constructing DLECC In the construction of DLECC, many disciplinary approaches are involved, such as social constructivism theory, knowledge management and collective intelligence theory and complex learning theory, which also constitute the theoretical foundations of constructing DLECC. Social constructivism Social constructivism emphasizes the importance of culture and context in understanding what occurs in society and constructing knowledge based on this understanding (Ernest, 1999; McMahon, 1997). Knowledge is deemed to a human product and is socially and culturally constructed (Bloom, 2006). The social constructivist Ernest (1999) views learning as a social process, which takes place not only within an individual, nor is a passive development of behaviors that can be shaped by external forces. Learning is a social process in which learners collaboratively construct knowledge through interactive processes of information sharing, negotiation and modification (Wang, 2009). Therefore, the acquisition of knowledge is self-constructed in the process of interacting with the surroundings rather than passively accepted from teachers. Learning is closely connected with cognitive activities, and valuable learning activities and meaningful social interactions play a fundamental role in the learning process. In DLECC, various available learning resources and partners are provided to support learners’ self-directed learning and collaborative exploration in the learning process. Ultimately, learners can create knowledge through their surroundings and their interactions with each other. Knowledge management (KM) and collective intelligence KM is the process of capturing, developing, sharing and effectively using organizational knowledge (Davenport, 1994). It refers to a multidisciplined approach to achieving organizational objectives by making the best use of knowledge (Groff & Jones, 2003). KM may result in improved communication, better decision making, greater creativity and innovation (Gurteen, 2012). Frappaolo (1998) argues that KM with collective intelligence can enhance the innovation capacity and emergency ability of enterprises. Collective intelligence is groups of individuals doing things collectively that seem intelligent (Malone, 2008). It is the capacity of networked Information Communication Technology (ICT) to enhance the collective pool of social knowledge by simultaneously expanding the extent of human interactions (Flew, 2005). In the construction of DLECC, ICT, KM and collective intelligence are integrated to achieve a maximum range of resource sharing and knowledge regeneration and promote the transfer, exchange and sharing of tacit knowledge. All the participants co-construct knowledge in a “shared intelligence space.” Valuable views are generated through discussions, exchanges, debates, analysis and negotiations. In such a collaborative learning environment with massive resources and barrier-free communication, learners’ group thinking and wisdom can be shared by the entire group. Complex learning Complex learning is always involved with achieving integrated sets of learning goals—multiple performance objectives (Van Merriënboer, Clark & De Croock, 2002). It aims at: (1) the integration © 2014 British Educational Research Association 1370 British Journal of Educational Technology Vol 46 No 6 2015 of knowledge, skills and attitudes; (2) the coordination of different skills; (3) the transfer of what is learned to daily life or work settings (Van Merriënboer, Kirschner & Kester, 2003). Van Merriënboer and Sweller (2005) state that complex learning means that students must learn how to deal with materials incorporating an enormous number of interacting elements. DLECC would provide a favorable atmosphere for students and teachers to realize the educational objective of “knowledge and skills, processes and methods, emotional attitudes and the values.” DLECC provides student-centered learning experiences in which learners acquire knowledge, skills and attitudes through practice and reflection. Construction of DLECC Architecture of DLECC The architecture of DLECC is composed of three layers: cloud equipment, cloud learning environment components and cloud services, as shown in Figure 1. The cloud equipment layer mainly consists of physical hardware, system software and network devices. The layer locates at the bottom of the model, and it should ensure the security of DLECC. The cloud learning environment components layer provides students with abundant learning resources, such as learning content, learning support and learning community, and these components can be combined according to students’ imagination. The cloud services layer mainly provides public or individual on-demand services. Users can utilize these available services just expend lower upfront costs, capital expenses and operating expenses. They need not to possess their own infrastructure, software and platform, nor are they concerned as to how servers and networks run in the cloud. Co-construction and sharing model of DLECC The aggregation of the collective wisdom is seldom considered in most paradigms of resources co-construction model. Each institution and university develops respective educational resources, and the lack of complementary advantages leads to the repeated development of some lowquality resources. Worse still, many resources libraries are seldom updated and optimized after construction. In contrast, DLECC may co-construct and share these resources across time and space, as shown in Figure 2. Teachers, students and experts can upload, construct and share various educational resources, they can also download, utilize and evaluate these resources, the evaluation and feedback can impel the revision and evolution of these resources. The co-construction of Figure 1: Architecture of DLECC © 2014 British Educational Research Association Digital learning environment based on cloud computing Teachers Coconstruct Mechanism of construction and sharing Experts Educational resources base Students Cloud platform Resources co-construction Revise Platform of coconstruction and sharing 1371 Teachers Share Experts Students Evaluate Resources sharing Figure 2: Co-construction and sharing model of DLECC resources emphasizes collaborative learning because it may promote the coordinated development of students’ learning ability, team cooperation, emotion and cognition. Different students involved in the collaborative learning possess different cognitive styles, thinking patterns and personal values; these individual differences may arouse reciprocal thinking and collisions through communication and cooperation. Obviously, the resources provided by different people are various, and the diverse resources may generate diverse cultures. Accordingly, creativity will be sparked through the thinking collisions from different cultures. The co-construction and sharing model promote knowledge sharing and knowledge regeneration. For example, the high-quality multimedia coursewares shared on the platform can be transformed into different versions and become more adaptable to different teaching modes after participants’ collaborative editing. Compared with single-user editing, the collaborative editing may shorten editing time, reduce editing cost, extend resource types and thus improve resource quality. The goal of the model is to enable every user to consume and construct high-quality resources. Mechanism of DLECC Most online communities suffer from insufficient user participation in their initial phase of development, and effective incentive mechanism is very important to encourage participation (Cheng & Vassileva, 2006). In DLECC, virtual credits (VC) is exploited to motivate participants’ initiative. VC can be acquired from the following modules: (1) resources co-construction and sharing, (2) questions and answers, and (3) learning activities. First, in the resources co-construction and sharing module, if the contributor successfully uploads a resource, his or her VC would be increased by two. In addition, if the resource is given accurate annotation and passes a quality audit by means of some control parameters such as format, size and readability, the contributor’s VC would be increased by two. If the resource is downloaded by others once, then the contributor’s VC would also be increased by one. The VC would be increased by two if the resource is given a positive comment. Meanwhile, the evaluator’s VC would be increased by one if he or she rates other’s resource once, but it is limited to five every day. Second, in questions and answers module, if the user initiates a discussion, his or her VC would be increased by two, and every participant’s VC in the discussion group would be increased by one. Meanwhile, the initiator’s VC would be added by one every five followers participating in the discussion, but the upper threshold is limited to ten in every discussion. If the participant’s answer is considered as the best in the discussion, his or her VC would be increased by ten. © 2014 British Educational Research Association 1372 British Journal of Educational Technology Vol 46 No 6 2015 Table 1: Description of notations in equation 1 Symbol Description Symbol Description Weight of part i (i = 1 . . . 5, Σwi = 1), set by teachers Total topics posted in DLECC Total online discussions in DLECC Total replies made in DLECC Total resources contributed in DLECC Accumulative total online time of all students ADi Active degree of student i wi Ti Di Ri RSi TOi Total topics posted by student i Total discussions participated in by student i Total replies made by student i Total resources contributed by student i Accumulative online time of student i T D R RS TO Third, in learning activities module, if the user finishes learning the resource or the learning time exceeds the preset threshold, his or her VC would be increased by two if the user passes an online examination. If his or her work is posted as a demonstration, his or her VC would be increased by 20. Meanwhile, active degree (AD) is used in DLECC to evaluate students’ learning initiative. For every student i, their AD can be expressed as ADi and calculated according to equation 1. The explanation of notations in the equation is shown in Table 1. Finally, every student’s total VC and AD would account for a certain proportion in final grades, and the respective proportion could be set by teachers according to different situations. ADi = w1 × Di D + w2 × Ti T + w3 × Ri R + w4 × RSi RS + w5 × TOi TO (1) Application of DLECC: Educational Technology Space (ETS) In accordance with the architecture and mechanism of DLECC, and integrated with Gleasy cloud services platform and full-time cloud conference system, we construct ETS platform, as shown in Figure 3. The Gleasy cloud services platform can support cloud storage, and the full-time cloud conference system can assist the conference to be held ubiquitously. The ETS consists of five main components: learning resources, learning support, learning terminals, learning communities and cloud computing platform. Learning resources include texts, images, audios, videos, animations or their combination, which can be accessed and recombined according to users’ locations and social context. Learning support, such as learning tools, interactive tools, evaluation strategies and recommendation services, are available online. They can be recombined according to users’ different situations and requirements to support efficient and instant services. Learning terminals vary from PC to iPad to smartphone. Learning communities can be established on demands, and corresponding learning communities would be recommended to users according to their learning context and learning preferences. The cloud computing platform is composed of cloud hardware, cloud software as well as numerous ready-made cloud services, and it should guarantee system and data security. In ETS, every registered user can upload, utilize and download various resources, initiate online discussions, join in interactive communities, etc. As learning is relaxed, engaged, exciting and effective, students have greater courage to express themselves in the virtual space. Therefore, formal learning and informal learning, school situations and social situations are integrated organically. Research design The ETS platform could be used for different projects, such as some professional courses learning during regular teaching process, the online training for on-job teachers and blended learning for © 2014 British Educational Research Association Digital learning environment based on cloud computing 1373 Figure 3: Construction of ETS college students, and so forth. In this study, we took the summer courses for teachers from primary and secondary schools from Jiujiang city in China as a case to illustrate the study and validate ETS. Context and participants Training in educational technology is an important part of continuing education for primary and secondary school teachers, and its purpose is to improve teachers’ information literacy and the ability to integrate ICT into curricula. Previously, the training had been conducted by a traditional face-to-face approach without online learning, and training effect demonstrated that trainees had low enthusiasm in traditional approach. Since 2013, ETS had just been published and used as the online learning platform, and the training was renewed by blended learning. Faceto-face learning focused on instructional design and project-based learning, whereas online interactive learning is concerned with pedagogical theory and ICT application. In 2013 summer, 110 primary and secondary school teachers from Jiujiang city participated in the training at Jiujiang University from July 11th to 30th. They came from different schools and various majors, including 67 females and 43 males, their age was between 22 and 45, and average age was about 28. Meanwhile, five professional teachers and two experts from the educational technology major in Jiujiang University were invited to provide professional guidance. Research procedure The research was carried out on the ETS platform, and the procedure was divided into four stages: (1) preparation stage: trainees’ accounts had been created by system automatically before the first lesson, and trainees could log into ETS and perfect their detailed information. Meanwhile, guides could upload some basic instructional materials, tools and activities related to the training course in advance. (2) Utilization stage: trainees began to learn on ETS; they could utilize various services on ETS, for instance, upload and download learning resources, select and study recommended content. They could also take part in the learning activities and launch or © 2014 British Educational Research Association 1374 British Journal of Educational Technology Vol 46 No 6 2015 Table 2: Description of evaluation indexes Index Abbreviation Average learning time on ETS ALTETS Average interaction AITETS time on ETS Total participations TPETS on ETS Total quantities of TQSRETS shared resources on ETS Definition Divide the total learning time by the number of participants per day Divide the total interaction time by the number of participants per day The number of participants on ETS per day The total storage of resources on ETS Unit Description Minute To analyze participants’ on-line time on ETS per day Minute To analyze interaction intensity among participants on ETS per day Person To analyze the degree of participation on ETS MB To measure the participants’ enthusiasm to co-construct and share resources participate in the online discussions through full-time cloud conference system. Certainly, tutors could observe trainees’ learning status at any time. (3) Evaluation stage: in order to evaluate the effect of ETS platform, a survey was conducted, and every trainee should answer some questions carefully before completing the training. (4) Data analysis stage: quantitatively analyzed these relevant data recorded in backend database and data log files and discovered the hidden learning patterns. At the beginning, trainees were informed that online learning process on ETS would be tracked and evaluated, but the trainees could not adapt to ETS. Whereas, with the help of the tutors, they would experience more pleasure from ETS and actively participate in the learning. For instance, trainees might feel “a sense of being taken seriously” when the educators gave individual instruction through video conversation. Besides, online discussion closely linked the trainees and provided abundant expression opportunities for every trainee, so that they could know more about each other. Measurement To evaluate and validate ETS based on DLECC, some evaluation indexes are taken into consideration. These are shown in Table 2. Results and discussion Data collection Every user’s access information was recorded in the backend database and log data files of ETS, including access time, access frequency, duration of learning, records of online discussion and quantities of shared resources, etc, which could be tracked daily. In this study, we sampled some statistical data every day from July 11th to 30th concerning the number of participants, participants’ online learning time and interaction time and the size of total shared resources. Findings In this study, quantitative result was collected through data analysis under the data tracking mechanism. Figure 4 shows the relationship between average learning time on ETS (ALTETS)/ average interaction time on ETS (AITETS) and the dates. It demonstrates that ALTETS/AITETS has increased quickly since the opening of ETS, and then ALTETS maintains a stable growth after about 1 week but grows again before they finish the training, whereas AITETS still keeps relative stable. Because it takes time for trainees to accept ETS, when the online learning became a habit for them, the length of learning time become fixed gradually. The social interactions between trainees on ETS develop gradually and become more intense as they become more familiar with each other daily. © 2014 British Educational Research Association Digital learning environment based on cloud computing 1375 Figure 4: Average learning/interactive time on ETS Figure 5: Total participations on ETS Figure 6: Total quantities of shared resources on ETS Figure 5 shows the relationship between total participations on ETS and the dates. It indicates that the number of participants increases rapidly as time goes on. Only a few users attempt to use the space in the initial phase, but then more and more participants emerge, which is consistent with the innovation diffusion theory. Figure 6 shows the relationship between total quantities of shared resources on ETS and the dates. It illustrates that the amount of shared resources reaches breakneck speed. Because an increasing number of users are inclined to share resources after they are familiar with the platform, especially, a large number of resources are uploaded at the end of the training, such as final assignments, learning notes and reviewing materials. Discussion and implications The above data analysis only reflects trainees’ learning initiative and the quantity of shared resources. In order to explore the quality of educational resources, pedagogical affordance, social © 2014 British Educational Research Association 1376 British Journal of Educational Technology Vol 46 No 6 2015 Table 3: Statistical table The number of people for each point Question Q1 Q2 Q3 Q4 Q5 5 (points) 4 3 2 1 Average (points) 18 (people) 14 21 13 17 59 47 61 48 56 31 38 25 37 36 2 9 3 10 1 0 2 0 2 0 3.85 3.56 3.91 3.55 3.81 affordance and technical affordance of ETS, a survey was also conducted by using 5-point Likert scale items. Every trainee was required to answer five questions carefully before completing the training. The survey aimed to find out: (1) the degree of trainees’ satisfaction with the resources; (2) the usefulness of the incentive mechanism; (3) the enhancement of trainees’ knowledge and ability; (4) interactivity; and (5) usability. The statistical data are shown in Table 3. It seems that the resources on ETS platform substantially meet trainees’ requirement; the incentive mechanism may motivate their initiative of sharing resources. Interaction among trainees is sufficient, and collaborative learning may improve trainees’ knowledge and ability to some extent. Compared with traditional face-to-face training, their social interaction becomes wider and relationship becomes closer. The results of the above study trigger our deep reflection, and some enlightenment is discussed as follows: (1) ubiquitous learning is realized because of the implementation of cloud services and the accessibility of different terminals. (2) The richness and diversity of learning resources and presentation styles basically meet different users’ individual preferences. (3) The collaborative communities and the incentive mechanism may facilitate the construction of collective intelligence, interpersonal interaction, collaborative editing and knowledge regeneration. (4) Various learning support enables adaptive learning. Resources and communities can be recommended, and immediate online services are afforded on demand. Conclusion In this paper, we present DLECC, a digital learning environment based on cloud computing, including the architecture, co-construction and sharing model, incentive mechanism and the effect analysis. The analytical results show that the implementation of DLECC may (1) provide participants with befitting educational resources, meaningful learning support and interactive communities, (2) enrich the types and quantities of educational resources, thus radically reform the static resource construction pattern and (3) strengthen interpersonal interaction. It implies that the co-construction and sharing model and incentive mechanism of VC is helpful. However, DLECC could continue to be improved. We will further strengthen recommendation services and personalized services. We also plan to validate the proposed platform across more large-scale participants. Acknowledgements This work was supported by the National Natural Science Foundation of China (project number: 71273108). The authors would like to thank Dr Qiyun Wang for his help during the study. References Allen, I. E. & Seaman, J. (2010). Learning on demand: online education in the United States. Sloan Consortium: ERIC. Bloom, J. W. (2006). Creating a classroom community of young scientists. New York: Routledge. © 2014 British Educational Research Association Digital learning environment based on cloud computing 1377 Cheng, R. & Vassileva, J. (2006). Design and evaluation of an adaptive incentive mechanism for sustained educational online communities. User Modeling and User-adapted Interaction, 16, 3–4, 321–348. Davenport, T. H. (1994). Saving IT’s soul: human-centered information management. Harvard Business Review, 72, 2, 119–131. Ernest, P. (1999). Forms of knowledge in mathematics and mathematics education: philosophical and rhetorical perspectives. In author (Ed.), Forms of mathematical knowledge (pp. 67–83). The Netherlands: Springer. Flew, T. (2005). New media: an introduction. London: Oxford University Press. Frappaolo, C. (1998). Defining knowledge management: four basic functions. Computerworld, 32, 8, 80. Groff, T. R. & Jones, T. (2003). Introduction to knowledge management. London: Routledge. Guo, Y. Q. (2011). Social information aggregation and pushing mechanisms for social learning in online learning community. Shanghai: East China Normal University. Gurteen, D. (Ed.) (2012). Leading issues in social knowledge management. London: Academic Conferences Limited. Kadne, A. (2010). vLab: a cloud based resource and service sharing platform for computer and network security education (Doctoral dissertation, Arizona State University). Kreijns, K., Kirschner, P. A. & Jochems, W. (2002). The sociability of computer-supported collaborative learning environments. Educational Technology & Society, 5, 1, 8–22. Malone, T. W. (2008). What is collective intelligence and what will we do about it. Oakton, VA: Collective Intelligence: Creating a Prosperous World at Peace, Earth Intelligence Network. McMahon, M. (1997). Social constructivism and the World Wide Web—a paradigm for learning. In ASCILITE conference. Perth, Australia. Oliver, M. (2013). Learning technology. Theorising the tools we study. British Journal of Educational Technology, 44, 1, 31–43. Van Merriënboer, J. J. & Sweller, J. (2005). Cognitive load theory and complex learning: recent developments and future directions. Educational Psychology Review, 17, 2, 147–177. Van Merriënboer, J. J., Clark, R. E. & De Croock, M. B. (2002). Blueprints for complex learning: the 4C/ID-model. Educational Technology Research and Development, 50, 2, 39–61. Van Merriënboer, J. J., Kirschner, P. A. & Kester, L. (2003). Taking the load off a learner’s mind: instructional design for complex learning. Educational Psychologist, 38, 1, 5–13. Wang, Q. (2009). Designing a web-based constructivist learning environments. Interactive Learning Environments, 17, 1, 1–13. Yang, X. M. & Yu, S. Q. (2013). The design of ubiquitous learning environments from the perspective of ecology. Education Research, 3, 98–105. Zhu, Z. T. & Guan, J. (2011). New development of basic education informatization in China: from “Class Access to ICTs” to “education cloud”. Journal of China Education Informatization, 14, 4–8. © 2014 British Educational Research Association Copyright of British Journal of Educational Technology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
Shin, S., Brush, T., Glazewski, K. (2017). Designing and Implementing Web-based Scaffolding Tools for TechnologyEnhanced Socioscientific Inquiry. Educational Technology & Society, 20 (1), 1–12. Designing and Implementing Web-based Scaffolding Tools for TechnologyEnhanced Socioscientific Inquiry Suhkyung Shin*, Thomas A. Brush and Krista D. Glazewski Department of Instructional Systems Technology, Indiana University Bloomington, Indiana, USA // suhkshin@indiana.edu // tbrush@indiana.edu // glaze@indiana.edu * Corresponding author (Submitted September 2, 2015; Revised February 12, 2016; Accepted February 28, 2016) ABSTRACT This study explores how web-based scaffolding tools provide instructional support while implementing a socio-scientific inquiry (SSI) unit in a science classroom. This case study focused on how students used web-based scaffolding tools during SSI activities, and how students perceived the SSI unit and the scaffolding tools embedded in the SSI activities. A web-based SSI unit was developed and utilized in a technology-enhanced science classroom, and included three types of embedded annotations (definition, background information, thinking questions). The findings of this study suggest that students benefitted from web-based annotated scaffoldings in their individual reading and group discussions. The effective use of hard scaffolding may have contributed positively to students’ engagement in the SSI activities and allowed students to easily explore a variety of context-related hyperlinked resources. In addition, the hard scaffolding tools allowed the teacher greater flexibility to effectively monitor students’ learning progress, evaluate students’ understanding of the topic, and provide guidance as needed through questioning. A holistic and dynamic approach is recommended when teachers and instructional designers consider how web-based hard scaffolding tools might function to assist students’ learning in SSI. Keywords Inquiry-based learning, Socioscientific inquiry, Scaffolding, Annotations, Technology-enhanced environments Introduction Inquiry-based learning (IBL) has long been considered important for promoting the understanding and retention of concepts, skills and attitudes that are required for solving ill-structured problems. Recently, socioscientific inquiry (SSI) has been emphasized as a curricular model that engages students in scientific topics while considering associated ethical or social issues. In SSI, students develop their understanding of fundamental aspects of science through a question-driven and open-ended process, which includes inquiry activities, planning and managing investigations, and analyzing results (Edelson, Gordin, & Pea, 1999). Specifically, SSI processes include authentic activities designed to motivate learners to acquire and apply new knowledge. Despite the learning benefits of SSI, students often feel frustrated due to a lack of certain assets, such as (1) domain specific knowledge (Bell, Blair, Crawford, & Lederman, 2003), (2) analysis and argumentation skills (Krajcik et al., 1998), (3) the ability to manage information and determine relevance (Hogan, 2002), and (4) the ability to monitor and reflect on their own learning processes (Quintana et al., 2004). Many researchers have argued that scaffolding provides the framework for assisting students with these challenges. Scaffolds are tools, strategies, and guides that help individual learners to accomplish tasks that are beyond their ability to complete alone (Vygotsky, 1980). Scaffolding can appear in multiple forms depending on the various types of support provided to engage students in an inquiry-based learning activity. Saye and Brush (2002) conceptualized two forms of support: hard and soft. Hard scaffolds are static supports that can be planned in advance in anticipation of potential difficulties with a task. These support structures can be embedded within learning environments to provide students with support while they are actively engaged with a problem (Krajcik et al., 1998; Simons & Klein, 2007). For instance, prompts designed to give definitions or background information for concepts can help students better understand a specific issue during the problem-solving process (Simons & Klein, 2007). In contrast, soft scaffolds are dynamic, situation-specific supports provided by a teacher to help with the learning process. This includes teachers’ clarification of tasks or monitoring of students’ progress (Kim & Hannafin, 2011a), which requires teachers to continuously diagnose learners and provide timely support based on student responses. This type of assistance is generally provided “on-the-fly,” where the teacher monitors students’ progress while engaged in a learning activity and intervenes when support is needed (Saye & Brush, 2002). Given that hard and soft scaffolds interact in dynamic ways in a classroom context (Kim & Hannafin, 2011a), it is essential to investigate what supports can be provided by scaffolding tools and what supports can be offered by the teacher to optimally facilitate problem-solving among students. For example, as students generate problem ISSN 1436-4522 (online) and 1176-3647 (print). This article of the Journal of Educational Technology & Society is available under Creative Commons CC-BY-ND-NC 3.0 license (https://creativecommons.org/licenses/by-nc-nd/3.0/). For further queries, please contact Journal Editors at ets-editors@ifets.info. 1 solutions, opportunities to assist students with integrating discrete fragments of evidence into a broader problem context may be incorporated into an inquiry-based unit via additional small-group discussion sessions with the teacher (Saye & Brush, 2004), which would be difficult to provide as a “hard” scaffold. Scaffolding research typically has focused on certain features and affordances of technology in various settings rather than on the holistic use of scaffolds to support the overall learning experience (Kim & Hannafin, 2011a). Little is known regarding how students experience different types of scaffolding in SSI classrooms. Furthermore, as a relatively new curricular model, few studies have documented the roles of soft and hard scaffolding during SSI activities in classroom practice. Therefore, investigating different types of scaffolding and how they function in different contexts may expand our understanding of how to support and facilitate learning during SSI instruction. Literature review Web-based scaffolding tools for inquiry-based learning Web-based resources have been widely developed and utilized to support students during IBL activities (Lee & Calandra, 2004; Oliver & Hannafin, 2000). For instance, web-based multimedia resources in multiple formats (i.e., audio, text, visual) can represent various perspectives and enable the presentation of authentic examples, thus promoting learners’ cognitive flexibility (Jacobsen & Spiro, 1995). Despite these potential benefits, it has been reported that learners sometimes feel confused and overwhelmed when utilizing web-based multimedia (Jonassen, 1989; Romiszowki, 1990). In order to relieve learners’ cognitive burden without excluding the potential advantages of web-based learning environments, researchers have highlighted the importance of scaffolding and the benefits of web-based scaffolding tools incorporated into IBL activities (Lee & Calandra, 2004). Some researchers have reported that web-based scaffolding tools are effective in promoting students’ scientific reasoning skills (Lee & Calandra, 2004; Walker & Zeidler, 2007). For example, Lee and Calandra (2004) reported that annotations embedded in web-based resources encouraged students to access prior knowledge which is essential in understanding contextual information and generating their own explanations during problem-solving. Walker and Zeidler (2007) studied SSI instruction which utilized the Web-based Science Environment (WISE) and found that the environment facilitated students’ exploration of multiple perspectives with various resources. Findings also suggested that engaging in SSI instruction using WISE was not sufficient to promote their understanding of topics as well as acquire scientific skills. Without any guidance in SSI, students produced hasty conclusions or generalizations, or did not make explicit references to a conceptual understanding of the nature of science during classroom debate. However, researchers did find that guiding questions embedded within the WISE environment may have assisted students in recognizing potential bias in information presented to them on-line. This suggests that hard scaffolding tools embedded in web-based instruction may facilitate learner’s scientific inquiry skills in SSI. As a result of the increased use of IBL, researchers have expanded the classifications of hard scaffolding and guidance about how to integrate hard scaffolds into IBL activities to support students’ learning (Linn, Clark, & Slotta, 2003; Raes, Schellens, Wever, & Vanderhoven, 2012; Williams & Linn, 2002). Hard scaffolding tools include conceptual scaffolds that provide definitions of new terms or web-based resources (Hannafin, Land, & Oliver, 1999), strategic scaffolds that embed expert advice as text-based responses (Simons & Klein, 2007) or video clips to assist students in evaluating alternative approaches to address problems (Pedersen & Liu, 2002), and metacognitive scaffolds that provide evaluation criteria or thinking questions to help students in monitoring and evaluating their progress in completing specific learning activities (Davis & Linn, 2000; Shin & Song, 2015; Wesiak et al., 2014). Researchers have investigated how learners use web-based scaffolding tools and resources through IBL activities (Belland, 2010; Kim & Hannafin, 2011b). For example, Kim and Hannafin (2011b) explored how 6th graders use peer-, teacher-, and technology-enhanced scaffolds in their classroom during their scientific inquiry activity on WISE, which was used to promote students’ knowledge integration of science topics. Embedded scaffolding, including inquiry maps, hints, and prompts helped learners monitor and reflect on their progress while engaged in inquiry activities. The researchers found that students perceived the embedded scaffolds as useful in helping them focus on important resources to organize evidence needed to support their argumentation. In Belland’s (2010) study, the Connection Log was utilized in a web-based environment, allowing students to respond to prompts and collaborate with peers. Students used the Connection Log to organize information, share their work, 2 and manage group work throughout the problem-solving process. Results found that scaffolds may assist students in articulating their thoughts and facilitate their thinking processes during problem-solving activities. Purpose of the current study Although some studies have investigated how scaffolding tools are utilized through IBL, most research has emphasized the effectiveness of hard scaffolding tools in increasing student performance (Kim & Hannafin, 2011a). While measuring students’ achievement has value, there has been relatively little research on how those scaffolds are utilized to support inquiry-based learning strategies such as SSI in a typical classroom. Thus, the purpose of this study was to explore how scaffolding tools can be implemented to support students’ SSI activities in a science classroom. Specifically, this study addressed the following questions:  How do students use hard scaffolding tools during their SSI activities?  How do students perceive hard scaffoldings embedded in the SSI unit?  How do hard scaffolding tools support teacher’s soft scaffolding during SSI activities? Method Research design This study examined how students utilized and experienced scaffolds integrated into instructional activities, rather than how they evaluated the technology-enhanced classroom itself, by way of an instrumental case study with multiple forms of data (Yin, 2003). Such case studies are used to discover new understandings toward an event, possibly leading toward re-thinking a trend, design, or approach (Marshall & Rossman, 1995). Participants A 9th grade biology teacher and his 71 students were involved in the present study. Sixty-two students, including 32 males (51.6%) and 30 females (48.4%), completed the reflection survey, and 12 students participated in focus group interviews. The teacher had nine years of experience teaching science and math, and was recruited from among the recipients of a nationwide award program that recognizes expert teachers of inquiry-based approaches with technology. Research context The context for this study was a high school biology course, comprised of four classes taught by the same teacher, offered in a high school in a rural community in the Midwestern United States. The classes met daily for 50 minutes. This course was selected because this case allows for an in-depth examination of teacher-led development of a science inquiry unit that embedded scaffolding in a technology-enhanced classroom. The course aimed to offer students a unique opportunity to advance their inquiry skills through addressing socioscientific issues. Scaffolding sesign: Socio-Scientific Inquiry Network System The teacher developed a unit in a web-based learning environment, the Socio-Scientific Inquiry Network (SSINet), in which students explored authentic socioscientific issues in the classroom. SSINet supports science teachers in their design and implementation of SSI curriculum with web-based curriculum design tools that easily allow them to link to and sequence a wide variety of web-based resources for delivery to students. Teachers can use the “Activity Creator” tool to organize resources and hard scaffolds via a web-based “viewer.” In this activity, the teacher embedded color-coded hard scaffolding to provide students with guidance. Using the SSINet tools, the teacher was able to embed “definitions (green)” and “background information (blue)” for difficult concepts and “thinking questions (red)” to focus attention on important concepts and issues relevant to the unit (see Figure 1). Students were able to access this information via the activity viewer (see Figure 2). 3 Figure 1. Annotation tool in SSINet Annotation:    Definitions (green) Background information (blue) Thinking questions (red) Activity direction panel: On the left side panel, teacher provides a description and direction of activities. A number of resources are embedded with the hyperlinks. Figure 2. Activity viewer as it appears on students’ mobile devices Teacher-developed inquiry activity The teacher collaborated with the researchers in developing the SSI unit, which was guided by the following driving question: “When should we use personal genetic information to make decisions?” Students completed a sequence of four SSI activities: Entry event, Jigsaw, Whiteboard, and Culminating activity (see Figure 3). 4 Figure 3. The SSI Unit activity Data collection Classroom observations Two researchers observed classes and recorded field notes during each day of the unit to examine how the teacher used scaffolding to support student progress and how students interacted with resources and tools. Video recordings of the entire classroom and student group activities were also collected. Screencasts of student screens Eight students’ laptop screens were recorded using QuickTime Player to determine which resources were viewed and used during hands-on activities. Focus group interviews The authors followed a purposive sampling strategy to select 12 students for focus group interviews (Creswell, 2012). Four groups of students participated focus group interviews. Each group had three students selected by the teacher to maximize diversity of gender, ability, and motivation in the subject area. The interviews explored students’ perceptions of resources and tools that were embedded in the activities. The interviews took place in a classroom, and were audiotaped and transcribed. Reflection survey A student reflection survey was administered at the end of the unit and examined students’ perceptions about the tools, resources, and inquiry activities. The questionnaire included 10 close-ended and seven open-ended questions. Cronbach’s alpha was used to test the attitude items of the survey and the reliability coefficient was 0.75. 5 Teacher’s post-unit interview and debriefings During the unit, daily debriefings were conducted with the teacher, as well as a post-unit interview. Interview/debriefing questions were related to impressions of the class, including the use of resources and tools in his teaching, perceptions about the strengths and weaknesses of this unit, students’ issues or problems, and an assessment of his management of the unit activities. Procedure The unit was implemented for eight class sessions. At the beginning of each session, the teacher explained the purpose of the SSI unit and how to access it on the laptops and iPads. The overarching issue of the unit was introduced with an entry event activity through a case about a woman who had cancer genes. The next six class sessions focused on inquiry activities including: (1) learning about the potential uses of genomic information, (2) examining genetic predetermination and its relation to the environmental influence continuum, (3) investigating when it is legal and illegal to use genetic information, (4) building student opinions, and (5) discussing what laws should govern the use of genetic information. On the last day of instruction, a reflection survey was administered to students and focus group interviews were conducted. While the class was completing the survey and posttest, students participating in focus group interviews were asked move to another classroom for their interview. Two researchers conducted the focus group interviews based on a semi-structured protocol and asked six to ten questions based on in-class activities. Students were asked to reflect on unit activities (e.g., How do you think that these activities for the unit were different from other activities you have done in this class?), and provide their perceptions of the web-based tools and resources embedded into the SSI unit (e.g., Do you think the tools and resources which are embedded in the activities were useful to you?). Once they completed the interview, students returned their classroom to complete the remaining group activities and reflection survey. Each group interview lasted 10 to 15 minutes, totalling 50 minutes to complete all four group interviews. Data analysis Quantitative and qualitative data were collected from multiple data sources to confirm and interpret conclusions (Creswell, 2012). Screencast data were used as a primary data source in order to measure the frequency of usage of color-coded annotations. The total number of visits and amount of time spent using annotations were calculated. Forty-eight annotations were embedded into the SSI unit: 18 as Definitions, 12 as Background Information, and 18 as Thinking Questions. To investigate students’ perception of the SSI unit, the reflection survey was analyzed with descriptive statistics. Data from students’ and teacher’s interviews, screencasts, and observations were coded by researchers and grouped into conceptual categories related to possible factors affecting student inquiry learning. For the third research question, the teacher’s post-unit interview and observations were analysed and triangulated using comparative analysis to identify reliable themes (Creswell, 2012). Results Students’ use of the SSI unit and scaffolding tools Students frequently used embedded color-coded annotations to explore, find and solve problems using resources that were embedded in the SSI unit. Table 1 summarizes the number of visits to annotations and time spent on each while students interactive the resources that embedded into the SSI unit. The analysis of screen-cast data demonstrated that students accessed annotations that provided thinking questions more often and for longer periods of time than definitions or background information. Screen-casting data showed that students first skimmed an article by clicking most annotations then later focused on specific annotations when revisiting the resources, particularly the “thinking questions” designed to focus students’ attention on key aspects of a resource. In focus group interviews, four students highlighted benefits of using color-coded annotations, particularly as a starting point for understanding the genetic issues. Most groups 6 mentioned that they skimmed through resources, went back to annotations and tried to focus on the important aspects of the content, as the following comment suggests: “…that’s where I really started skimming through it and picking out key points which helped because I could figure out where the key points were by what he highlighted…” (Focus group 1) Overall, the findings suggested that students perceived annotations as important and used thinking questions to direct their focus. Table 1. Usage of color-coded annotations (n = 8) Definitions Background information M Total M Total Number of visits 20 180 30 270 Time spenta 29.94 152.46 43.66 212.96 (Per annotation) (1.76) (2.46) Note. a = Measured in seconds. Thinking questions M Total 45 315 60.28 452.54 (3.35) The annotations were also useful when facilitating group discussion. The use of embedded thinking questions helped students to deepen their understanding and analysis during the group activity. In student interviews, one student stated, “…sometimes you click on the red highlighter that gives you questions and when you give it to your partners you discuss them. So, it was kind of interesting, the different questions that they had and how we are giving our opinion on them (Focus group 2).” In addition, data from observations revealed that the activity directions embedded within the activity viewer such as what procedure to follow, what topics to deal with, and what aspects to consider, may have provided strategic scaffolding to assist students as they progressed through the SSI activities. During group activities, the students checked the procedure and key points of group activities by following the prompts with limited guidance from the teacher. In sum, the findings suggested that students perceived the technology-enhanced environments, which facilitated the use of hard scaffolding, as beneficial for helping them focus on the SSI task. Students’ perceptions of the scaffolding tools and resources Quantitative findings Students perceived that scaffolding tools helped engage them with the SSI unit by allowing them to learn more about the presented problem and facilitating group work. Table 2 summarizes the descriptive statistics for the students’ reflection survey. Results showed that students perceived that the activities helped them learn more about genetics (M = 4.03, SD = .97) and that their experience with group work promoted greater learning (M = 4.21, SD = 1.04). Specifically, students indicated that using mobile devices, such as iPads and laptops, was a positive component in their access to the resources for the unit (M = 4.47, SD = .78). Qualitative findings Two themes emerged from analysis of qualitative data: (1) authentic resources facilitated student engagement with IBL and may have helped increase their understanding of content, and (2) students struggled with understanding multiple perspectives and providing evidence to support their positions. The students believed that the resources and materials embedded in the SSI unit were useful and helpful in terms of increasing their understanding and strengthening their grasp of concepts. Specifically, four groups mentioned in the focus group interviews that various materials, such as video clips, annotated articles, and other media, were authentic and context-based resources related to their real life, which helped them connect with and understand the material: “My favorite thing was reading the articles. I liked learning about other people’s lives, how genome sequencing affected them…” (Focus group 3) “I just liked like reading the articles, and watching some of the videos. It helped me understand it better.” (Focus group 2) However, observation and interview data indicated that some students found it difficult to support their position using evidence provided in the culminating activity. Specifically, when asked to identify the most difficult 7 activity in the SSI unit, most of the students mentioned the challenges involved in developing their group presentations. During the focus group interview, one student discussed the challenges associated with this activity, particularly with respect to supporting her opinion with evidence: “Sometimes just agreeing with the rest of the group because you know somebody would put down something and you would be you didn’t all really decide on that. And sometimes coming with the reasons, it's like you know what you want to say but you don’t know how to back it up.” (Focus group 4) In addition, observation data revealed that some of the groups failed to provide evidence to support their position on the use of personal genetic information. The groups were able to discuss their chosen position on the issue, but the evidence they used to support their position was weak or missing altogether. Table 2. Students’ reflection survey (n = 62) Item I enjoy science class. I do well in science class. I would like to learn more about how genetic information is used to make decisions. I enjoyed using the iPad/laptop to access the resources for this unit. The activities I completed in this unit helped me learn more about genetics. I enjoyed the group work I completed in this unit. I think working in a group helped me do better on the activities for this unit. I enjoyed completing the final project for the unit. I wish the teacher had provided more guidance to my group and myself during the unit. I would like to study other science topics the same way we studied genetics in this unit. Note. 1 = strongly disagree, 5 = strongly agree. M 3.90 4.19 3.23 4.47 4.03 4.30 4.21 3.82 2.22 4.14 SD 1.04 .90 1.16 .78 .87 .98 1.04 .97 1.00 1.07 The Role of hard scaffolding tools and soft scaffolding Supporting self-directed learning Analysis of student data obtained from focus group interviews and open-ended survey questions revealed that scaffolding tools and resources may have enabled students to conduct their own research more independently. For example, comments made by students during focus group interviews suggested that by clicking the hyperlinks, the students easily accessed necessary information and resources to successfully complete specific activities. One student stated, “it was really organized, and you could easily find things with simple instructions, you can find stuff, it was all set up for you, so you didn’t have to spend half the class finding it (Focus group 1).” In addition, interview data suggested that hard scaffolds embedded in the activities may have provided more opportunities for independent individual learning. Six students (50%) mentioned in the interviews that utilizing the hard scaffolding allowed them to better manage their learning. For instance, one student explained: “Something that I like personally was you have a lot more freedom …and you can work on your own pace as long as you got it done. You didn’t have to try rushing through it or miss things but you also didn’t have to get through, stop, and wait for half an hour until the rest of the class catches up (Focus group 4)”. The teacher also mentioned in the post-unit interview that hard scaffolds (such as embedded annotations) were useful for his students in terms of exploring the learning content without his direct support: “…. They (students) were able to click on certain words, find out the definitions of the words without me having to explain them, or using a cumbersome dictionary tool. I thought it was useful for that.” Although hard scaffolding was provided while students were in the process of discussing and developing their presentations, observation of the class suggested that some students still struggled with solving problems. In such cases, soft scaffolding by the teacher may have supported the students by providing modeling and questioning. While conducting the culminating activity, the students experienced challenges to developing their presentation, and the teacher provided specific examples and asked questions to shape their thinking and guide them through the activities. Specifically, survey data showed that the teacher provided sufficient soft scaffolding, which might influence students’ satisfaction with their learning experience (see Table 1). In response to the question “I wish the teacher had provided more guidance to myself and my group during the unit,” only 10% of students indicated that they felt they needed more guidance. In response to the question, “I would like to study other science topics the same way we studied genetics in this unit,” over 75% of students indicated that they enjoyed the experience. 8 Enabling the provision of timely soft scaffolding Providing hard scaffolding may have allowed the teacher to assist other students who needed help. In a focus group interview, one student noted: “If he thinks you understand it, then he’ll just let you do it by yourself, he spends more time with kids that need help with…things (Focus group 3).” The data from observations, and the teacher’s debriefings and interview support this student’s assertion. While observing the class, researchers found that the teacher was able to monitor students’ progress through the activities, and assess their level of understanding of the content. The teacher moved through the classroom and periodically asked questions of students to both facilitate their understanding and to determine which students may be having difficulty with the content. The teacher’s comments in debriefings and interviews also suggested that hard scaffolding enabled him to secure time for providing soft scaffolding. As he stated, “… [the annotations] allowed me to go around and ask questions as they are reading, because I could kind of see where a student was at, and ask a pertinent question based on that.” The teacher also noted that he was able to have more interaction with his students and assess their progress, which in turn allowed him to both adjust the support he provided to some students while in turn giving other students greater independence. Discussion The purpose of this study was to examine how learners used the resources and scaffolding tools embedded in an SSI unit to support their learning, and how hard scaffolding tools could support teacher soft scaffolding. The first research question examined students’ use of resources and hard scaffolding during their SSI activities. In this study, students benefitted from color-coded annotated scaffoldings in their individual reading and group discussion, specifically as they were identifying SSI issues, exploring background information, and researching evidence. We found that students considered the annotations as supports that the teacher intentionally provided for additional information on reading materials. Analysis of data suggested that students used the annotations as a starting point for helping them better understanding the content and assisting them with their reading comprehension. In addition, based on students’ interviews and observations, we identified three benefits of webbased color-coded annotations that may play an important role in promoting greater student engagement in inquiry activities: (1) directing attention to important information, (2) providing structured guidance that enhances learners’ interpretation and analysis of problems, and (3) facilitating questions that highlights critical aspects of the problem. As previous studies have suggested, different hard scaffoldings, which were provided in this study as conceptual, strategic and metacognitive scaffolds, can be utilized to alleviate learners’ difficulties and facilitate the problem solving process (Shin & Song, 2015; Simons & Klein, 2007). However, the present findings attempt to address the limitations of past studies that investigated the effects of scaffolding on student achievement by identifying how students recognize and use scaffolds to acquire content knowledge or background information during IBL activities. Another important finding was that students preferred to use strategic scaffolds (e.g., thinking questions, activity guides) while investigating content and participating in activities and group discussion. As a strategic scaffold, thinking questions may help students develop and refine their reflective thinking because question prompts may serve as a cue or guide to focus their attention and continually monitor their learning as they explore the content (Davis & Linn, 2000; Ge & Land, 2003). In SSI, learners deal with problems that accommodate multiple perspectives and incorporate theory or principles in evaluating and supporting their arguments. Research suggests that learners struggle to conduct disciplined SSI with substantial learning loads when simultaneously managing the necessary reasoning skills and new content, and strategic scaffolding may relieve their cognitive burden and promote their problem-solving processes (Walker & Zeidler, 2007). The second research question investigated learners’ perceptions of the SSI unit and scaffolding tools. The findings suggest that the effective use of hard scaffolding may have contributed positively to students’ engagement in the SSI activities, especially through the activity viewer which allowed students to easily explore a variety of context-related hyperlinked resources. In SSINet, the activity viewer presented resources with embedded hyperlinks on the left side, which enabled students to explore the resources on the right side of panel by clicking the hyperlinks. This structure also facilitates the navigation of other resources (i.e., review the guidelines of activities, revisit resources from the left panel). This SSINet tool feature may promote learners’ cognitive abilities to investigate essential information without eliminating the benefits of non-liner features found in hypermedia learning environments. In addition, in this study, the students indicated that the resources related to their own life experience were helpful for understanding multiple perspectives and increasing their 9 understanding of actual social problems. These different interactive scaffolds may positively impact students’ satisfaction with the SSI unit and acquisition of content knowledge. While the rich and numerous resources seemed to play a positive role in the students’ initial engagement, these resources and scaffolds may also have sustained effects as students build and contextualize new knowledge in meaningful ways (Schank, 1999). However, students encountered challenges while conducting the culminating group activities, suggesting that additional hard scaffolds may be needed to support their learning throughout the entire process. Specifically, student feedback indicated that learners sought additional annotations, including examples or expert explanations, for help with representing the central issue from multiple perspectives and modelling problemsolving processes such as developing claims and evidence. Students’ difficulties with linking evidence to specific problem contexts might be due to their lack of experience in making arguments and limited opportunities to develop and support knowledge claims with evidence (Kim & Hannafin, 2011b; Krajcik et al., 1998; Zeidler, Walker, Ackett, & Simmons, 2002). For example, Kim and Hannafin (2011b) found that 6th grade students failed to examine evidence during a science inquiry activity. They reported that learners’ difficulty in generating their arguments with supporting evidence was influenced by their limited inquiry strategies and understanding. The results of this study suggest that additional hard scaffolding, such as strategic scaffolds that guide students while building arguments, might be needed to facilitate more effective decision- making processes among student groups while developing their group presentations. The third research question focused on the role of soft and hard scaffolding. The findings suggest that hard scaffolding may play a significant role in increasing teachers’ ability to provide timely soft scaffolding to students. While interacting with the resources and scaffolding tools embedded in the SSI unit, some students were able to independently identify problems, investigate resources and content, and construct their own arguments. This in turn allowed the teacher greater flexibility to effectively monitor students’ learning progress, evaluate their level of the understanding, and provide guidance as needed through questioning. Since individual learners frame their arguments around their own experiences and prior knowledge (Kim & Hannafin, 2011b; von Aufschnaiter, Erduran, Osborne & Simons, 2008), they may need specific and differential support to complete various tasks required of them during an SSI unit. However, a teacher may not be able to provide appropriate guidance to facilitate problem solving processes to individual students in K-12 classroom environments because of limited time and resources (Hmelo-Silver, 2004). Similar to previous studies on hard scaffolding in classroom environments (Saye & Brush, 2001; Simons & Klein, 2007), the results of this study suggest that providing differential hard scaffolds can create more time for teachers to provide soft scaffolds when necessary. In this study, hard scaffolds helped guide some students through the process of solving socioscientific problems by themselves, which allowed the teacher to prioritize other students’ needs for additional support. The teacher was able to provide timely soft scaffolding by questioning and modelling while monitoring and evaluating all of his students’ progress through the SSI activities. Implications and suggestions for future research Although this study has allowed us to explore the role of hard and soft scaffoldings in a typical science classroom environment, the findings cannot be generalized, and should be articulated and expanded with further research in different settings. Nonetheless, the results of this study do contribute a clearer and more nuanced perspective of teachers’ and students’ experiences with scaffolding in technology-enhanced classroom environments, and help to refine conceptions of hard and soft scaffolding related to inquiry-based learning activities. First, hard scaffolds embedded into the SSI unit might support learners in overcoming barriers to dealing with ill-structured problems, which are central to SSI activities. Given that students focused more on the annotated elements, instructional designers should consider carefully how students perceive scaffolding tools and how and what condition they used it. Practically, utilizing scaffolding tools interacted with complexed and dynamic situations in an actual classroom. Considering that students’ prior knowledge and experiences may affect their use of scaffolding tools, further research is needed to investigate learners who experienced challenges during the inquiry processes in order to gain additional insight regarding improved scaffolding design to support those learners. Secondly, providing authentic and relevant resources that directly link the problem to authentic situations may have been helpful in terms of building students’ background knowledge and provoking their initial motivation. Most students reported that the resources and scaffolding embedded in the SSI unit were interesting and meaningful due to their realistic relationship to real-world problems. In order to enhance the impact that 10 scaffolding has on learners’ engagement, it is crucial to provide authentic resources and tasks that students can meaningfully relate to their own experiences. Finally, it is important to understand and clarify the teacher’s role during disciplined inquiry in technologyenhanced classroom environments. Although the hard scaffolds embedded in the unit activities did assist leaners’ inquiry activities, the teachers’ soft scaffolding, in the form of questioning or modelling, remains essential for monitoring student progress and promoting greater understanding. However, results of this study did suggest that the hard scaffolds (particularly the annotations and the linked resources) assisted the teacher with targeting additional soft scaffolding to students who were struggling with specific SSI activities. To better support IBL activities in technology-enhanced environments, researchers should further explore the relationship between hard and soft scaffolding, and consider how to best align scaffolding supports with different elements of the learning environment. To accomplish this, further research is needed to investigate in more depth the relationships and outcomes of employing different types of soft scaffolding in tandem with hard scaffolding in classroom environments. References Bell, R. L., Blair, L. M., Crawford, B. A., & Lederman, N. G. (2003). Just do it? Impact of a science apprenticeship program on high school students’ understandings of the nature of science and scientific inquiry. Journal of Research in Science Teaching, 40(5), 487-509. Belland, B. R. (2010). Portraits of middle school students constructing evidence-based arguments during problem-based learning: The Impact of computer-based scaffolds. Educational Technology Research and Development, 58(3), 285-309. Creswell, J. W. (2012). Qualitative inquiry and research design: Choosing among five approaches. (3rd ed.). Thousand Oaks, CA: Sage. Davis, E. A., & Linn, M. C. (2000). Scaffolding students’ knowledge integration: Prompts for reflection in KIE. International Journal of Science Education, 22, 819-837. Edelson, D. C., Gordin, D. N., & Pea, R. D. (1999). Addressing the challenges of inquiry-based learning through technology and curriculum design. The Journal of The Sciences, 8(3&4), 391-450. Ge, X., & Land, S. M. (2003). Scaffolding students’ problem-solving processes in an ill-structured task using question prompts and peer interactions. Educational Technology Research and Development, 51(1), 21-38. Hannafin, M., Land, S., & Oliver, K. (1999). Open learning environments: Foundations, methods, and models. In C. Reigeluth (Ed.), Instructional design theories and models: A New paradigm of instructional theory (Vol. 2, pp. 115-140). Mahway, NJ: Erlbaum. Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do students learn? Educational Psychology Review, 16(3), 235-266. Hogan, K. (2002). Small groups’ ecological reasoning while making an environmental management decision. Journal of Research In Science Teaching, 39, 341-368. Jacobsen, M. J., & Spiro, R. J. (1995). Hypertext learning environments, cognitive flexibility, and the transfer of complex knowledge: An Empirical investigation. Journal of Educational Computing Research, 12(4), 301-333. Jonassen, D. H. (1989). Hypertext/hypermedia. Englewood Cliffs, NJ: Educational Technology Publications Inc. Kim, M. C., & Hannafin, M. J. (2011a). Scaffolding problem solving in technology-enhanced learning environments (TELEs): Bridging research and theory with practice. Computers & Education, 56(2), 403-417. Kim, M. C., & Hannafin, M. J. (2011b). Scaffolding 6th graders’ problem solving in technology-enhanced science classrooms: A Qualitative case study. Instructional Science, 39(3), 255-282. Krajcik, J., Blumenfeld, P. C., Marx, R. W., Bass, K. M. Fredricks, J., & Soloway, E. (1998). Inquiry in project-based science classroom: Initial attempts by middle school students. Journal of the Learning Sciences, 7, 313-350. Lee, J., & Calandra, B. (2004). Can embedded annotations help high school students perform problem solving tasks using a web-based historical document? Journal of Research on Technology in Education, 37(1), 65-84. Linn, M. C., Clark, D., & Slotta, J. D. (2003). WISE design for knowledge integration. Science Education, 87, 517-538. Marshall, C., & Rossman, G. B. (1995). Designing qualitative research. London, UK: Sage Publications. Oliver, K., & Hannafin, M. J. (2000). Student management of web-based hypermedia resources during open-ended problem solving. The Journal of Educational Research, 94(2). 75-92. 11 Pedersen, S., & Liu, M. (2002). The Effects of modeling expert cognitive strategies during problem-based learning. Journal of Educational Computing Research, 26(4), 353-380. Quintana, C., Reiser, B. J., Davis, E. A., Krajcik, J., Fretz, E., Duncan, R. G., Kyza, E., Edelson, D., & Soloway, E. (2004). A Scaffolding design framework for software to support science inquiry. Journal of The Learning Sciences, 13(3), 337-386. Raes, A., Schellens, T., Wever, B. D., & Vanderhoven, E. (2012). Scaffolding information problem solving in web-based collaborative inquiry learning. Computers & Education, 59(1), 82-94. Romiszowski, A. J. (1990). The Hypertext/hypermedia solution-but what is exactly the problem? In D. H. Jonassen & H. Mandl (Eds.), Designing hypermedia for learning (pp. 321-354). Heidelberg, Germany: Springer. Saye, J., & Brush, T. (2001). The Use of embedded scaffolds with hypermedia-supported student-centered learning. Journal of Educational Multimedia and Hypermedia, 10, 333-356. Saye, J. W., & Brush, T. (2002). Scaffolding critical reasoning about history and social issues in multimedia-supported learning environments. Educational Technology Research and Development, 50(3), 77-96. Saye, J. W., & Brush, T. (2004). Promoting civic competence through problem-based history learning experiments. In G. E. Hamot, J. J. Patrick, & R. S. Leming (Eds.), Civic learning in teacher education (Vol. 3, pp. 123-145). Bloomington, IN: The Social Studies Development Center. Schank, R. C. (1999). Dynamic memory revisited. New York, NY: Cambridge University Press. Shin, S., & Song, H. (2015). Finding the optimal scaffoldings for learners’ epistemological beliefs during ill-structured problem solving. Interactive Learning Environments, 1-16. doi:10.1080/10494820.2015.1073749 Simons, K. D., & Klein, J. D. (2007). The Impact of scaffolding and student achievement levels in a problem-based learning environment. Instructional Science, 35, 41-72. von Aufschnaiter, C., Erduran, S., Osborne, J., & Simon, S. (2008). Arguing to learn and learning to argue: Case studies of how students’ argumentation relates to their scientific knowledge. Journal of Research in Science Teaching, 45(1), 101-131. Vygotsky, L. S. (1980). Mind in society: The Development of higher psychological processes. Cambridge, MA: Harvard university press. Walker, K. A., & Zeidler, D. L. (2007). Promoting discourse about socioscientific issues through scaffolded inquiry. International Journal of Science Education, 29, 1387- 1410. Wesiak, G., Steiner, C. M., Moore, A., Dagger, D., Power, G., Berthold, M., Albert, D., & Conlan, O. (2014). Iterative augmentation of a medical training simulator: effects of affective metacognitive scaffolding. Computers & Education, 76, 1329. Williams, M., & Linn, M. C. (2002). WISE inquiry in fifth grade biology. Research in Science Education, 32, 415-436. Yin, R. K. (2003). Case study research: Design and methods. Thousand Oaks, CA: Sage. Zeidler, D. L., Walker, K. A., Ackett, W. A., & Simmons, M. L. (2002). Tangled up in views: Beliefs in the nature of science and responses to socioscientific dilemmas. Science Education, 86(3), 343-367. 12 Copyright of Journal of Educational Technology & Society is the property of International Forum of Educational Technology & Society (IFETS) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
D US-China Education Review A 6 (2012) 613-618 Earlier title: US-China Education Review, ISSN 1548-6613 DAVID PUBLISHING Exploring the Influences of Elementary School Students’ Learning Motivation on Web-Based Collaborative Learning Huang Chin-Fei, Liu Chia-Ju National Kaohsiung Normal University, Kaohsiung, Taiwan  The purpose of this study is to explore the influences of students’ learning motivation on Web-based collaborative learning. This study conducted learning materials of Web pages about science and collaborative learning, a motivation questionnaire and interviews were used for data collection. Eighty Grade 5 students and a science teacher were recruited in this study. The controlled group involved 40 students who need to learn the dissolve concept on the Web pages, and complete the homework which was assigned by the Web pages by themselves. The experimental group involved the other 40 students and every four students were grouped in a team. The experimental group students not only need to learn the dissolve concept on Web pages, but also need to complete the homework which was assigned by the Web pages with team members. Besides, the experimental group students need to present their homework to other teams and provide feedbacks and suggestions to other teams. The results showed that experimental group significantly promoted their science learning motivation by using Web-based collaborative learning. Keywords: collaborative learning, learning motivation, Web-based learning Introduction Job, Dweck, and Walton (2010) mentioned that the motivation could provide the unlimited willpower for people to do what they want to do. In other words, no matter what goals people want to reach, the motivation would be the most important factor to lead people to go. In the same way, the key point to promote students’ active learning and learning achievement is learning motivation (Hynd, Holschuh, & Nist, 2000; Pintrich, 2003; Polich, Ehlers, Otis, Mandell, & Bloom, 1986). Therefore, to find the learning strategies to promote students’ learning motivation and provide students’ extensive willpower to learn science is a core issue in science education. According to technical changes with each passing day, the Web-based learning is more important in these few years (Berge, 1999; Jin, 2005). Previous studies indicated that the Web-based learning could have significantly improved students’ engagement and motivation in learning (Lo, Chan, & Yeh, 2012). Although the Web-based learning environment could help students to learn more quickly and conveniently, it is better for elementary school students to learn science with peer relationship(Wentzel & Watkins, 2002). Collaborative learning requires students in small groups to solve ill-structured problems, such as real-life situation problems, with peer relationship (Slavin, 1997). The concept of collaborative learning is suitable for Huanga Chin-Fei, Graduate Institute of Science Education, National Kaohsiung Normal University. Liu Chia-Ju, Graduate Institute of Science Education, National Kaohsiung Normal University. 614 STUDENTS’ LEARNING MOTIVATION ON WEB-BASED COLLABORATIVE LEARNING elementary school students to learn with their team members and try to solve problems which were connected with their real-life situations. Due to these reasons, the purpose of this study is to combine the Web-based science learning environment with collaborative learning as a new style of learning strategy for elementary school students, and to explore the influences of students’ learning motivation on this new learning strategy. The research question is based on the purpose of this study. Research Design Participants Eighty Grade 5 grade students (n = 80, mean age ± SD = 11.20 ± 0.40 years) and a science teacher (female, age = 37 years old, teaching science of elementary school for five years) were recruited in this study. The controlled group involved 40 students (n = 40, mean age ± SD = 11.25 ± 0.44 years) who need to learn the dissolve concept on the Web pages and complete the homework which was assigned by the Web pages by themselves. The experimental group involved the other 40 students (n = 40, mean age ± SD = 11.15 ± 0.4436 years), and every four students were grouped in a team. The experimental group students need to learn the dissolve concept on Web pages as same as the controlled group, and also need to complete the homework which was assigned by the Web pages with team members. Furthermore, the experimental group students need to present their homework to other teams and provide feedbacks and suggestions to other teams. The science teacher was responsible for choosing the science Web pages about dissolve concept and answer students’ questions after they learned the concepts from Web pages by themselves completely. Although the science teacher had taught science in elementary school for five years, she did not teach the students in this study before. Instruments The Web pages about dissolve concept. The Web pages about dissolve concept were chosen by the science teacher in this study and determined by the other two experts to reach consensus. The expert panel was made up of one science educator and one science teacher who had taught science in elementary school for 12 years. At the beginning of this study, the science teacher chosen eight Web pages about dissolve concept, and all of the experts discussed the appropriateness of the Web pages. At last, one Web page about dissolve concept (see Figure 1) was been chosen until all the experts reached consensus. Figure 1. The examples of the Web page about dissolve concept in this study. Retrieved from http://science.edu.tw/index.jsp STUDENTS’ LEARNING MOTIVATION ON WEB-BASED COLLABORATIVE LEARNING 615 The Web page about dissolve concept in this study included teaching module, conceptual teaching with animation, virtual experiments, multiple assessments on line and the illustrations of scientific histories. The participants need to learn the dissolve concept on this Web page for three weeks (45 minutes per week, total: 135 minutes) (see Figure 2). If they had any questions, they could ask the science teacher in this study. The learning motivation scale. All of the students needed to write down the learning motivation scale (Likert scale) which was developed by this study (α = 0.86; total items = 7 items; total scores = 120 scores) before and after the employment of different learning strategies (see Figure 2). There are four dimensions in the learning motivation scale which involved self-efficacy, goals of performance, the values of learning and the sense of achievements. Each dimension included six items, and there were 24 total items in the learning motivation scale. Figure 2. The research design of this study. Data Collection and Analysis The scores of learning motivation scale were collected for analysis. The extracted data were analyzed using paired-sample t-test, ANCOVA (analysis of covariance) analysis SPSS (Statistical Package for Social Science) version 17.0. Results and Discussion As well known for the influences of students’ learning motivation on Web-based collaborative learning, 80 students were divided into two groups (a controlled group and an experimental group). All students need to write down the learning motivation scales after and before the employment of different learning strategies. The scores of learning motivation scales were collected and analyzed by using paired-sample t-test and ANCOVA. Table 1 showed the paired sample t-test of the pre-test and post-test learning motivation from the controlled and the experimental groups. The results indicated that students in both two groups significantly 616 STUDENTS’ LEARNING MOTIVATION ON WEB-BASED COLLABORATIVE LEARNING promote their learning motivations after learning on the Web page in this study. This finding was consistent with previous studies which suggested that the Web-based learning could help students to learn more quickly and conveniently, and have significantly improved students’ engagement and motivation in learning (Lo, Chan, & Yeh, 2012; Wentzel & Watkins, 2002). Table 1 The Paired Sample t-Test of the Pre-test and Post-test Learning Motivation From Controlled and Experimental Groups (n =80) Group Controlled group (n = 40) Experimental group (n = 40) Score Pre-test Post-test Pre-test Post-test Mean ± SD 87.78 ± 10.81 95.63 ± 9.20 88.53 ± 10.02 100.28 ± 10.12 t p Cohen’s d -9.006*** 0.000 -1.167 -8.151*** 0.000 -0.782 Notes. *** p < 0.001; t means t value from t-test; p means the significance probability. The result in Table 1 illustrated that the Web-based learning could help to promote elementary school students’ learning motivation. For further understanding the influences of elementary school students’ learning motivation on collaborative learning of the Web-based environment, this study analyzed the data by using ANCOVA. Table 2 showed that the experimental group revealed significant higher scores of learning motivation than that of the controlled group after performing learning strategies in this study. In other words, combining Web-based learning environment with collaborative learning strategy could promote elementary school students’ learning motivation, which is better than only building the Web-based learning environment. The finding in this study was supported by the result of Wentzel and Watkins’ research which suggested that it is better for elementary school students to learn science with collaborative learning. Table 2 The ANCOVA Analysis of Learning Motivation Between Controlled and Experimental Groups (Covariance Factor: The Scores of Learning Motivation Before Learning Treatment) Group Controlled group Experimental group Notes. ** Mean scores ± SD 100.28 ± 10.12 95.63 ± 9.20 SS df F-value η2 343.657 1 7.559** .089 p < 0.01; SS means sum of square of deviation from the mean; df means the degree of freedom; η2 means the eta-squared. According to the data from the interviews (the examples are as below), the experimental group students in this study indicated that the collaborative learning could help them to think about the different opinions, and they will learn some knowledge from peers through discussion. S66: Originally, I thought… but S80 (the code name of one of her team members) said… Maybe he is right. S72: … I do not know. My team member told me. He said that he had read the dissolve concept in other books… Yes. I thought he is very smart. I learn a lot from him. (S66, S72 are the case students) Furthermore, Slavin (1997) mentioned that collaborative learning will be useful for students to solve problems in real-life situation. In this study, we selected “dissolve” concept, since the concept is related to the real-life situation. However, many elementary students could not understand the dissolve concept. By observing STUDENTS’ LEARNING MOTIVATION ON WEB-BASED COLLABORATIVE LEARNING 617 the macro-phenomenon, elementary school students thought the sugar “disappears” after dissolving (Johnstone, 1991). Because the micro-phenomenon is difficult to display in the real world environment, the misconception of “Dissolve is the meaning of something disappear in water” are existing in students’ mind. The misconceptions of dissolve from elementary school students are also shown according to interview data of this study. S07: The dissolve means disappear… I cannot see the sugar anymore. S29: I am not sure. I cannot see the sugar in water, but if I put a lot of sugar, it will appear in the bottom of cup. S63: No! The sugar disappeared after it dissolves in water. (S07, S29 and S63 are the case students) As same as interview data, at the beginning of this study, there are 73.7% (59 participants/80 participants) of students who mentioned about “dissolve is the meaning of sugar disappear in water”. However, after learning on the Web page which the experts selected, a lot of students in this study understood the true meaning of dissolve. The students pointed out a key virtual animation in the Web page (see Figure 3) which performed that the sugars disperse in water. That is to say, the students could learn the micro-phenomenon of dissolving through media or Web-based environment. Figure 3. The virtual animation of micro-phenomenon of dissolving. Conclusions The most important key point to promote students’ active learning and learning achievement is learning motivation (Hynd, Holschuh, & Nist, 2000; Pintrich, 2003; Polich, Ehlers, Otis, Mandell, & Bloom, 1986). The purpose of this study is to explore the influences of students’ learning motivation on Web-based collaborative learning. The results of this study proved that the Web-based collaborative learning could promote elementary school students’ science learning motivation. Besides, combining Web-based learning environment with collaborative learning strategy could promote elementary school students’ learning motivation, which is better than only building the Web-based learning environment. Further, the students could learn the micro-phenomenon of dissolve concept through Web-based environment and change their misconceptions. We suggested that Web-based learning should be a good learning strategy for students, especially in illustrating the micro-phenomenon. But it might be better to improve elementary school students’ learning motivation by using a Web-based collaborative learning strategy to share their opinions and discuss with peers 618 STUDENTS’ LEARNING MOTIVATION ON WEB-BASED COLLABORATIVE LEARNING than that only to construct a Web-based learning environment. References Berge, Z. L. (1999). Interaction in post-secondary web-based learning. Educational Technology, 39(1), 5-11. Hynd, C., Holschuh, J., & Nist, S. (2000). Learning complex scientific information: Motivation theory and its relation to student perceptions. Reading and Writing Quarterly, 16(1), 23-57. Jin, S. H. (2005). Analyzing student-student and student-instructor interaction through multiple communication tools in web-based learning. International Journal of Instructional Media, 32(1), 59-67. Job, V., Dweck, C. S., & Walton, G. M. (2010). Ego depletion—Is it all in your head? Implicit theories about willpower affect self-refulation. Psychological Science, 21(11), 1686-1693. Johnstone, A. H. (1991). Why is science difficult to learn? Things are seldom what they seem. Journal of Computer Assisted Learning, 7(2), 75-83. Lo, J. J., Chan, Y. C., & Yeh, S. W. (2012). Designing an adaptive Web-based learning system based on students’ cognitive styles identified online. Computers & Education, 58(1), 209-222. Pintrich, P. R. (2003). A motivational science perspective on the role of student motivation in learning and teaching contexts. Journal of Educational Psychology, 95(4), 667-686. Polich, J., Ehlers, C. L., Otis, S., Mandell, A. J., & Bloom, F. E. (1986). P300 latency reflects the degree of cognitive decline in dementing illness. Electroencephalography and Clinical Neurophysiology, 63(2), 138-144. Slavin, R. E. (1997). Educational psychology: Theory and practice (5th ed.). Needham Heights: M. A.: Allyn & Bacon. Wentzel, K. R., & Watkins, D. E. (2002). Peer relationships and collaborative learning as contexts for academic enablers. School Psychology Review, 31(3), 366-377.

Tutor Answer

School: Carnegie Mellon University



The Different Computation
Student’s Name
Institutional Affiliation




The Different Computation
Cloud computing is generally considered as the new frontier in the ground of computing,
and its operation technology comprises of hardware, network, and software (Duan, 2016). The
nature of software, network and hardware are what is called clouds. Web computing refers to as
use of browser applications to handle the computation task. The chance of doing web computing
started in the year 1997 but was well described in the year 2000. This browser application which
was used by web users was called web workers. The use of web computing and cloud computing
has enhanced the development of computation in the organizations (Wang et al., 2016). Both
web computing and cloud computing seemed to be similar since they have a common type of
setups and mostly offered the same results. However, there is a lot of difference between web
computing and cloud computing based on the technical definition of each. Therefore, the central
role of this research paper is to examine and explain the differences between cloud computations
and web computing.
Differences in Attention, Availability and Competition
Web computing has attracted more attention compared to cloud computing. This is
because many research groups have diverted their concentration toward web computing and
particularly Europe has explicitly proposed for web computing. Also, some industries that are
growing globally have started development with the interest of using web computing to enhance
efficiency in their organizations. Additionally, the primary objective of why industries prefer
web computing is to add value to their customer and also to maintain and create customers
loyalty to outweigh level of competence in marketing. Web computing technology is not only
significant in an open field like web but also a close field like industrial setting (Breslin et al.,



2010). The technologies fitted in web computing can be deployed for domains, for instance,
knowledge E-Commerce and management, Web Services and enterprise application.
Nowadays, cloud computing is the resource which is readily available and attractive in
comparison with web computing (Zhang et al., 2010). The thing that has made cloud computing
resources readily available is because more companies are improving the number of
employment, thus increasing and the figures of department too. Therefore, the more department
is increasing; the more cloud computing is needed to accomplish their goals. Especially to the
small scale businesses, cloud computing delivers technology gadgets that are beneficial to the
business. Further, to all businesses that want to create the foundation of competence the internet
services offer opportunities for competing at a higher level of marketing. Cloud computing also
assists business to adjust their concentration on developing and establishing business application
that increases business figures. These computations serve as instruments of business
improvement that led to business innovation. However, cloud computing be should be
considered when to be applied.
To improve the high level of competition in the market industries, cloud computing
technologies play a significant role in improving the level of business than web computing.
Many companies globally prefer the use of cloud computation in several manners. The reason
why many prefer cloud computations to curb the menace of competition is that the technology
that is created by the cloud is not required for personal gain, but the Infrastructure cloud
organization offers it. Although cloud computation provides an innovative foundation for
increasing the productivity of the business, technology services can only be useful to those with
access to the network. This means that offline workers cannot use this service since it is



undividedly offered online. Therefore, to u...

flag Report DMCA

Thanks, good work

Similar Questions
Hot Questions
Related Tags
Study Guides

Brown University

1271 Tutors

California Institute of Technology

2131 Tutors

Carnegie Mellon University

982 Tutors

Columbia University

1256 Tutors

Dartmouth University

2113 Tutors

Emory University

2279 Tutors

Harvard University

599 Tutors

Massachusetts Institute of Technology

2319 Tutors

New York University

1645 Tutors

Notre Dam University

1911 Tutors

Oklahoma University

2122 Tutors

Pennsylvania State University

932 Tutors

Princeton University

1211 Tutors

Stanford University

983 Tutors

University of California

1282 Tutors

Oxford University

123 Tutors

Yale University

2325 Tutors