construction of a digital learning environment based on cloud computing
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Construction of a digital learning environment based oncloud computing
Jihong Ding, Caiping Xiong and Huazhong Liu
Jihong Ding is a PhD candidate at School of Educational Information Technology of Central China Normal Univer-sity. Her main research interests are technology-enhanced learning and automatic recommendation. Caiping Xiongis a professor at School of Educational Information Technology of Central China Normal University. His mainresearch 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 lecturerof Jiujiang University. His research interests are cloud computing and big data. Address for correspondence: DrCaiping Xiong, School of Educational Information Technology, Room 730, No. 9 Building, Central China NormalUniversity, No. 152 Luoyu Road, Wuhan 430079, China. Email: email@example.com
AbstractConstructing the digital learning environment for ubiquitous learning and asynchro-nous distributed learning has opened up immense amounts of concrete research.However, current digital learning environments do not fully fulfill the expectations onsupporting interactive group learning, shared understanding and social construction ofknowledge. This paper introduces cloud computing to the construction of the digitallearning environment for its on-demand services with high reliability, scalability andavailability in the distributed environment. Then a digital learning environment basedon cloud computing (DLECC) is proposed, including the architecture, co-constructionand sharing model, and incentive mechanism of DLECC. Finally, an Educational Tech-nology Space (ETS) platform under the concept of DLECC is constructed and applied tothe educational technology training for 110 teachers from primary and secondaryschools. The experimental results demonstrate that the co-construction and sharingmodel and incentive mechanism of DLECC may provide meaningful learning supportand interactive communities and promote the co-construction of befitting educationalresources.
IntroductionThe construction of digital educational resources is the focus of lifelong learning in the new age.According to the Sloan Consortiums report on online education in USA, online courses areincreasingly becoming a common experience for students (Allen & Seaman, 2010).
The digital learning environment is a cooperative and investigative learning system based onInternet resources. It is an open-learning space that contains abundant, diverse resources andinteractive and nonlinear organization information resources in line with human cognitive char-acteristics (Kadne, 2010). In such an environment, learners can decide when to learn, where tolearn and what to learn. Scilicet, learners can choose learning tasks and determine learningcontents, learning objectives and learning time. Meanwhile, they can customize their own per-sonalized learning tasks according to their own cognitive styles, learning ability and personalitycharacteristics. Besides, learning feedback can be obtained through network examination,assignment submission, group evaluation or teacher evaluation.
British Journal of Educational Technology (2014)doi:10.1111/bjet.12208
2014 British Educational Research Association
There is amount of positive research on digital learning environments. However, contemporarydigital learning environments are hard to fulfill expectations of fully supporting interactive grouplearning, shared understanding, social construction of knowledge and acquisition of competen-cies. The existing teaching platforms have abundant teaching resources and interactive tools butare deficient in information flow control and coordination mechanisms to ensure that learnerswould have a balanced information access opportunity (Guo, 2011).
Thereby, Yang and Yu (2013) built ubiquitous learning ecosystem by integrating the wholeelements of learning environments from the perspective of ecology. Although Yang refers to usinga kind of mechanism to ensure that the ubiquitous learning environments run effectively, nodetailed measures are proposed.
Oliver (2013) holds that technology can be used in learning. With the appearance of newtechnologies such as web 2.0, Internet of Things and cloud computing in succession, cloudcomputing has greatly triggered educators interests in applying cloud computing to education.Kadne (2010) argues that constructing digital learning environments under cloud computingmay be an economical way for resources co-construction and knowledge sharing. Cloud com-puting 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 educationsince 2009, and concepts such as cloud computing assisted teaching and education based oncloud computing appear in succession (Zhu & Guan, 2011).
Practitioner NotesWhat 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 itson-demand services with high reliability, scalability and availability.
Proposed a digital learning environment based on cloud computing, including thearchitecture, co-construction and sharing model, and incentive mechanism.
Constructed the co-construction and sharing model to promote the knowledge aggre-gation, knowledge regeneration and collaborative editing.
Designed the incentive mechanism to motivate learners learning initiative andstrengthens community interaction.
Implications for practice and/or policy
Co-construction and sharing model may enrich the types and quantity of educationalresources, thus radically reform the static resource construction pattern.
Incentive mechanisms may motivate students learning initiative, strengthen commu-nity interaction and promote the aggregation of collective intelligence.
Ubiquitous learning and adaptive learning is realized due to abundant cloud servicesand the accessibility of different terminals, which may meet different users individualpreferences.
2 British Journal of Educational Technology
2014 British Educational Research Association
This study applies cloud computing to the construction of digital learning environments, becauseit can provide on-demand services with high reliability, scalability and availability in the distrib-uted environments. The main objective of this study is to design a digital learning environmentbased on cloud computing (DLECC), and the research issues can be stated as follows: (1) thearchitecture of DLECC, (2) the co-construction and sharing model of DLECC, (3) the incentivemechanism of DLECC, and (4) the effect of applying DLECC into practice.
Theoretical foundations of constructing DLECCIn the construction of DLECC, many disciplinary approaches are involved, such as social con-structivism theory, knowledge management and collective intelligence theory and complex learn-ing theory, which also constitute the theoretical foundations of constructing DLECC.
Social constructivismSocial constructivism emphasizes the importance of culture and context in understandingwhat 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 culturallyconstructed (Bloom, 2006). The social constructivist Ernest (1999) views learning as a socialprocess, which takes place not only within an individual, nor is a passive development ofbehaviors that can be shaped by external forces. Learning is a social process in which learnerscollaboratively construct knowledge through interactive processes of information sharing, nego-tiation and modification (Wang, 2009).
Therefore, the acquisition of knowledge is self-constructed in the process of interacting with thesurroundings rather than passively accepted from teachers. Learning is closely connected withcognitive activities, and valuable learning activities and meaningful social interactions play afundamental role in the learning process. In DLECC, various available learning resources andpartners are provided to support learners self-directed learning and collaborative exploration inthe learning process. Ultimately, learners can create knowledge through their surroundings andtheir interactions with each other.
Knowledge management (KM) and collective intelligenceKM is the process of capturing, developing, sharing and effectively using organizational knowl-edge (Davenport, 1994). It refers to a multidisciplined approach to achieving organizationalobjectives by making the best use of knowledge (Groff & Jones, 2003). KM may result in improvedcommunication, better decision making, greater creativity and innovation (Gurteen, 2012).Frappaolo (1998) argues that KM with collective intelligence can enhance the innovation capac-ity and emergency ability of enterprises. Collective intelligence is groups of individuals doingthings collectively that seem intelligent (Malone, 2008). It is the capacity of networked Informa-tion Communication Technology (ICT) to enhance the collective pool of social knowledge bysimultaneously expanding the extent of human interactions (Flew, 2005).
In the construction of DLECC, ICT, KM and collective intelligence ar