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Advances in E-learning-Experiences and Methodologies

Knowledge Discovery from

Knowledge Discovery from E-Learning Activities Scott, D.W., & Sain, S.R. (2004). Multi-dimensional density estimation. In C. R. Rao, E. J. Wegman & J. L. Solka (Eds.), Handbook of Statistics, Data Mining and Computational Statistics, Vol. 24, (pp. 229-261). Elsevier. Selim, H. (2007). Critical success factors for e- learning acceptance: Confirmatory factor models. Computers & Education, 49(2), 396-413. Shee, D., & Wang, Y. (in press). Multi-criteria evaluation of the Web-based e-learning system: A methodology based on learner satisfaction and its applications. Computers & Education. Shin, N., & Kim, J. (1999). An exploration of learner progress and dropout in Korea National Open University. Distance Education an International Journal, 20, 81-97. Silvescu, A., Reinoso-Castillo, J., & Honavar, V. (2001). Ontology-driven information extraction and knowledge acquisition from heterogeneous, distributed, autonomous biological data sources. In International Joint Conferences on Artificial Intelligence (IJCAI) (pp. 1-10). Sowa, J.F. (2000). Knowledge representation: Logical, philosophical and computational foundations. Pacific Grove, CA: Brooks Cole. Srivastava, J., Cooley, R., Deshpande, M., & Tan, P. (2000). Web usage mining: Discovery and applications of usage patterns from web data. In SIGKDD Explorations (pp. 12-23). Stephenson, J.E., Brown, C., & Griffin, D.K. (in press). Electronic delivery of lectures in the university environment: An empirical comparasion of three delivery styles. Computers & Education. Sun, P., Tsai, R., Finger, G., Chen, Y., & Yeh, D. (in press). What drives a successful e-learning? An empirical investigation of the critical factors influencing learner satisfaction. Computers & Education. Uschold, M., King, M., Morales, S., & Zorgios, Y. (1998). The enterprise ontology. Knowledge Engineering Review, 13, 32-89. Weigand, H. (1997). Multilingual ontology-based lexicon for news filtering. In IJCAI Workshop on Multilingual Ontologies (pp. 138-159). Xenos, M. (2004). Prediction and assessment of student behaviour in open and distance education in computers using Bayesian networks. Computers & Education, 43(4), 345-359. Zang, W., & Lin, F. (2003). Investigation of Web-based teaching and learning by boosting algorithms. In IEEE International Conference on Information Technology: Research and Education (pp. 445-449). Ziehe, A., & Müller, K.R. (1998). TDSEP-an efficient algorithm for blind separation using time structure. In 8th International Conference on Artificial Neural Networks (pp. 675-680). AddItIonAL reAdIng data mining and knowledge Discovery Chi, X., & Spedding, T.A. (2006). A Web-based intelligent virtual learning environment for industrial continous improvement. In IEEE 4 th International Conference on Industrial Informatics (pp. 1102-1107). Hammouda, K., & Kamel, M. (2006). Data mining in e-learning. In S. Pierre (Ed.), E-learning networked environments and architectures: A knowledge processing perspective. Springer Book Series: Advanced Information and Knowledge Processing. Han, J., & Kamber, M. (2001). Data mining concepts and techniques. Academic Press.

Knowledge Discovery from E-Learning Activities Markou, M., & Singh, S. (2003). Novelty detection: A review. Part 1: Statistical approaches. Signal Processing, 83(12), 2481-2497. Yang, Y., Wu, X., & Zhu, X. (2006). Mining in anticipation for concept change: Proactive-reactive prediction in data streams. Data Mining and Knowledge Discovery, 13(3), 261-289. ontologies Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The semantic Web: A new form of Web content that is meaningful to computers will unleash a revolution of new possibilities. Scientific American Magazine, 284(5), 34-43. Cardoso, J., & Sheth, A. (2002). Semantic e- workflow composition. Journal of Intelligent Information Systems, 21(3), 191-225. Ceccaroni, L., & Ribiere, M. (2002). Experiences in modeling agentcities utility-ontologies with a collaborative approach. Paper presented at the Ontologies in Agent Systems Workshop, Autonomous Agents and Multi-Agent Systems Conference. Davies, J., Studer, R., & Warren, P. (2006). Semantic Web technologies: Trends and research in ontology-based systems. Wiley. Sowa, J.F. (2006). Categorization in cognitive computer science. In H. Cohen & C. Lefebvre (Eds.), Handbook of categorization in cognitive science (pp. 141-163). Elsevier. Sowa, J.F. (2006). A dynamic theory of ontology. In B. Bennett & C. Fellbaum (Eds.), Formal ontology in information systems (pp. 204-213). IOS Press. Pattern recognition Langseth, H., & Nielsen T.D. (2005). Latent classification models. Machine Learning, 59(3), 237-265. Lee T.W., Lewicki, M.S., & Sejnowski, T.J. (2000). ICA mixture models for unsupervised classification of non-gaussian classes and automatic context switching in blind signal separation. IEEE Transactions on Pattern Analysis & Machine Intelligence, 22(10), 1078-1089. Salazar, A., Igual, J., Vergara, L., & Serrano, A. (in press). Learning hierarchies from ICA mixtures. Paper presented at the International Joint Conference on Neural Networks. Vergara, L., Salazar, A., Igual, J., & Serrano, A. (2006). Data clustering methods based on mixture of independent component analyzers. Paper presented at the ICA Research Network International Workshop, ICArn (pp. 127-130). Webb, A.R. (2002). Statistical pattern recognition. John Wiley and Sons. education Butler, K.A. (1990). Learning and teaching style: In theory and practice (2 nd ed.). Gregorc Associates, Incorporated. Entwistle, N. (1990). Styles of learning and teaching - an integrated outline of educational psychology for students, teachers, and lecturers. Fulton, David Publishers. Entwistle, N., & Peterson, E. (2004). Conceptions of learning and knowledge in higher education: Relationships with study behaviour and influences of learning environments. International Journal of Educational Research, 41(6), 407-428.

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    Advances in E-Learning: Experiences

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    Table of Contents Preface .........

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    Chapter XIV Open Source LMS Customi

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    Chapter III Philosophical and Epist

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    of constructive and cooperative met

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    Chapter XIV Open Source LMS Customi

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    contents, learning contexts, proces

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    xv these organizations do not get a

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    xvii QuALIty In e-LeArnIng Before t

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    allow that the teachers in training

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    xxi ISO. (1986). Quality-Vocabulary

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    Chapter I RAPAD: A Reflective and P

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    RAPAD in fields such as law, engine

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    RAPAD mystery to the new student. B

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    RAPAD example, whereas Laurillard h

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    RAPAD Ontologically, systems philos

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    RAPAD information related processes

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    RAPAD methods and techniques accord

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    RAPAD 2. An introduction to learnin

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    RAPAD then asked to reflect on and

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    RAPAD Figure 4. A rich picture to h

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    RAPAD Again using techniques from t

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    RAPAD university preparation course

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    RAPAD The third interface is at the

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    RAPAD Knight, P.T., & Trowler, P. (

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    RAPAD AddItIonAL reAdIngs Goodyear,

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    A Heideggerian View on E-Learning t

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    A Heideggerian View on E-Learning (

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    A Heideggerian View on E-Learning s

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    A Heideggerian View on E-Learning r

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    A Heideggerian View on E-Learning o

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    A Heideggerian View on E-Learning n

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    A Heideggerian View on E-Learning M

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    A Heideggerian View on E-Learning W

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    Philisophical and Epistemological B

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    Philisophical and Epistemological B

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    Philisophical and Epistemological B

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    Philisophical and Epistemological B

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    Philisophical and Epistemological B

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    Philisophical and Epistemological B

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    Philisophical and Epistemological B

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    Chapter IV E-Mentoring: An Extended

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    E-Mentoring However, what is unders

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    E-Mentoring baugh, & Williams, 2004

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    E-Mentoring Table 2. Contact. Diffe

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    E-Mentoring Table 10. Ethical impli

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    E-Mentoring Table 15. Technology st

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    E-Mentoring Table 21. Coaching. Bes

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    E-Mentoring Table 27. Moment. Best

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    E-Mentoring Moreover, existing rese

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    E-Mentoring Kasprisin, C. A., Singl

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    E-Mentoring Ensher, E. A., Heun, C.

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    Chapter V Training Teachers for E-L

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    Training Teachers for E-Learning FL

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    Training Teachers for E-Learning ne

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    Training Teachers for E-Learning A

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    Training Teachers for E-Learning yo

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    Training Teachers for E-Learning Di

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    Training Teachers for E-Learning ht

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    The Role of Institutional Factors i

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    The Role of Institutional Factors i

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    The Role of Institutional Factors i

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    The Role of Institutional Factors i

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    The Role of Institutional Factors i

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    The Role of Institutional Factors i

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    The Role of Institutional Factors i

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    The Role of Institutional Factors i

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    E-Learning Value and Student Experi

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    E-Learning Value and Student Experi

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    E-Learning Value and Student Experi

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    E-Learning Value and Student Experi

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    E-Learning Value and Student Experi

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    E-Learning Value and Student Experi

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    E-Learning Value and Student Experi

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    E-Learning Value and Student Experi

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    E-Learning Value and Student Experi

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    E-Learning Value and Student Experi

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    Integrating Technology and Research

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    Integrating Technology and Research

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    Integrating Technology and Research

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    Integrating Technology and Research

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    Integrating Technology and Research

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    Integrating Technology and Research

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  • Page 196 and 197: Chapter X Knowledge Discovery from
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  • Page 222 and 223: Chapter XI Swarm-Based Techniques i
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  • Page 236 and 237: Chapter XII E-Learning 2.0: The Lea
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  • Page 252 and 253: E-Learning 2.0 McPherson, K. (2006)
  • Page 254 and 255: E-Learning 2.0 Rosen, A. (2006). Te
  • Page 256 and 257: Telematic Environments and Competit
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    Telematic Environments and Competit

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    Telematic Environments and Competit

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    Telematic Environments and Competit

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    Open Source LMS Customization Intro

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    Open Source LMS Customization or ev

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    Open Source LMS Customization compa

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    Open Source LMS Customization Figur

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    Open Source LMS Customization Figur

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    Open Source LMS Customization Figur

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    Open Source LMS Customization Haina

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    Evaluation and Effective Learning p

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    Evaluation and Effective Learning r

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    Evaluation and Effective Learning t

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    Evaluation and Effective Learning p

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    Evaluation and Effective Learning m

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    Evaluation and Effective Learning c

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    Evaluation and Effective Learning H

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    Chapter XVI Formative Online Assess

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    Formative Online Assessment in E-Le

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    Formative Online Assessment in E-Le

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    Formative Online Assessment in E-Le

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    Formative Online Assessment in E-Le

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    Formative Online Assessment in E-Le

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    Formative Online Assessment in E-Le

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    Formative Online Assessment in E-Le

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    Formative Online Assessment in E-Le

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    Formative Online Assessment in E-Le

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    Formative Online Assessment in E-Le

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    0 Chapter XVII Designing an Online

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    Designing an Online Assessment in E

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    Designing an Online Assessment in E

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    Designing an Online Assessment in E

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    Designing an Online Assessment in E

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    Designing an Online Assessment in E

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    Designing an Online Assessment in E

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    Designing an Online Assessment in E

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    Designing an Online Assessment in E

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    Quality Assessment of E-Facilitator

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    Quality Assessment of E-Facilitator

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    Quality Assessment of E-Facilitator

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    Quality Assessment of E-Facilitator

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    Quality Assessment of E-Facilitator

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    Chapter XIX E-QUAL: A Proposal to M

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    E-QUAL is proposed to evaluate the

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    E-QUAL provide competent, service-o

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    E-QUAL 2004; Scalan, 2003) and qual

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    E-QUAL benchmarks address technolog

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    E-QUAL E-learning added two differe

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    E-QUAL Table 6. Application of the

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    E-QUAL Future trends The future of

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    E-QUAL (EQO) co-located to the 4 th

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    E-QUAL SMEs: An analysis of e-learn

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    E-QUAL Meyer, K. A. (2002). Quality

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    Compilation of References Argyris,

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    Compilation of References Biggs, J.

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    Compilation of References Cabero, J

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    Compilation of References Comezaña

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    Compilation of References Downes, S

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    Compilation of References Fandos, M

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    Compilation of References national

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    Compilation of References Hudson, B

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    Compilation of References Harbour.

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    Compilation of References Little, J

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    Compilation of References Metros, S

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    Compilation of References ONeill, K

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    Compilation of References Preece, J

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    Compilation of References Sadler, D

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    Compilation of References Shin, N.,

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    Compilation of References tional Co

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    Compilation of References Vermetten

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    Compilation of References Yu, F. Y.

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    About the Contributors Juan Pablo d

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    About the Contributors part: “An

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    About the Contributors María D. R-

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    About the Contributors Applications

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    Index e-learning tools, automated p

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    Socrates 55 Sophists 55 student-foc

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