Considerando-se as limitações citadas na seção anterior e oportunidades relacionadas de pesquisas interessantes, a seguir são listados trabalhos futuros que podem melhorar e evoluir as contribuições desta tese:
Promover uma utilização maior e analisar os ganhos de aprendizagem das aplicações geradas. Uma questão mais relacionada à área educacional diz respeito ao ganho de aprendizagem proporcionado pelo uso de uma aplicação gerada pelo UFC- Inventor. Este é um aspecto complexo e está associado ao desempenho do professor no uso do ambiente. Entretanto, trata-se de uma pesquisa interessante no momento em que os resultados positivos podem promover o uso das tecnologias ubíquas em aulas
de campo. Para isso, são necessários mais experimentos com aplicações distintas, inclusive em domínios de conhecimento diferentes.
Analisar a corretude dos modelos elaborados. No momento em que se considera um uso maior do ambiente, surge a necessidade de se verificar se os modelos que estão sendo elaborados estão consistentes. Esta não é uma tarefa simples porque envolve a verificação tanto de aspectos pedagógicos, como os objetivos de aprendizagem da aula de campo projetada, quanto de questões tecnológica, como a validade das regras contextuais especificadas.
Integrar o ambiente UFC-Inventor com as tecnologias da Internet das Coisas. Uma tecnologia que tem ganhado a atenção dos pesquisadores nos últimos anos e tem muitos pontos em comum com a computação ubíqua é o paradigma Internet das Coisas. Sendo assim, a integração do UFC-Inventor com as soluções de desse paradigma mostra-se como uma alternativa de pesquisa interessante ao possibilitar o uso do ambiente em cenários não previstos inicialmente.
Automatizar a visualização dos dados transmitidos. Como demonstrado no estudo de caso desta tese, foi necessário o desenvolvimento de um sistema específico para possibilitar o acesso aos dados registrados durante a aula de campo. Portanto, apresenta-se como uma possibilidade de pesquisa futura interessante a implementação de uma solução para permitir que os dados registrados em campo pelas aplicações possam ser visualizados. Esta não é uma tarefa trivial principalmente porque duas informações essenciais variam de projeto para projeto: o modelo de dados da aplicação de coleta e o formato de saída dos dados esperado pelo professor.
Aperfeiçoar o processo de incorporação de novos recursos de computação ubíqua. Atualmente, para se incorporar novos elementos da ML4UL na UFC-GLM é necessário alterar o código-fonte da ferramenta e gerar uma nova versão. Portanto, para tornar a ferramenta de modelagem e, consequentemente, o ambiente UFC- Inventor, mais flexível, uma possibilidade seria desenvolver uma forma para aperfeiçoar a adição de novos recursos ao ambiente sem ter que mudar o seu código- fonte. Para isso, uma solução seria a utilização de documentos templates que já teriam uma estrutura padrão que fosse reconhecida automaticamente pela ferramenta, através da utilização de atributos como: nome do recurso, propriedades, valores aceitáveis, entre outros. Porém, para criação desses templates, o usuário necessita ter conhecimentos técnicos sobre o funcionamento do recurso que está sendo adicionado. Desenvolver e experimentar novos layouts de interface. Nesta tese de Doutorado foram implementados apenas dois tipos diferentes de layouts de interface, que
variavam pouco e tinham como objetivo principal demonstrar o funcionamento da proposta. Portanto, essa é uma área que apresenta várias possibilidades de investigação, como a geração de layouts mais intuitivos e que facilitem o uso.
Migrar a ferramenta de modelagem para uma plataforma colaborativa e na Web. Essa é uma oportunidade mais focada em implementação, que está relacionada à dificuldade de uso de um software desktop por várias pessoas dispersas geograficamente, com a possibilidade de visualizar a evolução da interface. Ao mesmo tempo em que produziria benefícios importantes, como evitar a necessidade de instalação, essa possibilidade de trabalho futuro impõe questões que devem ser consideradas, como controle de acesso, permissões dos usuários/grupos, versionamento do projeto de aula, entre outras.
REFERÊNCIAS
ABOWD, Gregory D.; MYNATT, Elizabeth D. Charting past, present, and future research in ubiquitous computing.ACM Transactions on Computer-Human Interaction (TOCHI), v. 7, n. 1, p. 29-58, 2000.
AINSWORTH, Shaaron; GRIMSHAW, Shirley. Evaluating the REDEEM authoring tool: can teachers create effective learning environments?. IJ Artificial Intelligence in Education, v. 14, n. 3-4, p. 279-312, 2004.
AKMAN, Ibrahim; TURHAN, Cigdem. User acceptance of social learning systems in higher education: an application of the extended Technology Acceptance Model. Innovations in Education and Teaching International, p. 1-9, 2015.
ALAMER, Reem A.; AL-OTAIBI, Hind M.; AL-KHALIFA, Hend S. L3MS: A Lightweight Language Learning Management System Using Mobile Web Technologies. In: Advanced
Learning Technologies (ICALT), 2015 IEEE 15th International Conference on. IEEE,
2015. p. 326-327.
ALLWIHAN, Regad; BRAILSFORD, Tim; COBB, Sue. Capturing experience in the field trip: a comparison study of using mobile devices between geography and architecture students.INTED2013 Proceedings, p. 1550-1556, 2013.
ATOJI, Rodolpho Iemini. Bluetooth e NFC: estudo de caso. Universidade de São Paulo
Instituto de Matemática e Estatística, São Paulo, 2010.
ATZORI, Luigi; IERA, Antonio; MORABITO, Giacomo. The internet of things: A survey.Computer networks, v. 54, n. 15, p. 2787-2805, 2010.
BALASUBRAMANIAN, Krishnakumar et al. Component-based system integration via (meta) model composition. In:Engineering of Computer-Based Systems, 2007. ECBS'07. 14th Annual IEEE International Conference and Workshops on the. IEEE, 2007. p. 93- 102.
BANGOR, Aaron; KORTUM, Philip; MILLER, James. Determining what individual SUS scores mean: Adding an adjective rating scale. Journal of usability studies, v. 4, n. 3, p. 114- 123, 2009.
BARAKI, Harun et al.Towards Interdisciplinary Design Patterns for Ubiquitous Computing Aplications. kassel university press GmbH, 2014.
BARKER, Phil. What is IEEE learning object metadata/IMS learning resource metadata?.cetis standards briefings series, 2005.
BATTISTELLA, Paulo Eduardo; VON WANGENHEIM, Aldo. Avaliação de Ferramentas de Autoria Gratuitas para produção de Objetos de Aprendizagem no padrão SCORM. Revista Brasileira de Informática na Educação, v. 19, n. 3, p. 16-28, 2011.
BEHRENDT, Marc; FRANKLIN, Teresa. A Review of Research on School Field Trips and Their Value in Education. International Journal of Environmental and Science Education, v. 9, n. 3, p. 235-245, 2014.
BELLAVISTA, Paolo et al. A survey of context data distribution for mobile ubiquitous systems.ACM Computing Surveys (CSUR), v. 44, n. 4, p. 24, 2012.
BERTRAN, Benjamin et al. DiaSuite: A tool suite to develop Sense/Compute/Control applications.Science of Computer Programming, v. 79, p. 39-51, 2014.
BEZERRA, Carla et al. Challenges for usability testing in ubiquitous systems. In:Proceedings of the 26th Conference on l'Interaction Homme-Machine. ACM, 2014. p. 183-188.
BONETT, Douglas G.; WRIGHT, Thomas A. Cronbach's alpha reliability: Interval estimation, hypothesis testing, and sample size planning. Journal of Organizational Behavior, v. 36, n. 1, p. 3-15, 2015.
BOYINBODE, O. K.; AKINTOLA, K. G. Effecting E-Learning with U-learning Technology in Nigerian Educational System.E-LEARNING, v. 1, p. 1, 2009.
BOYLE, Robin; INGHAM, Joanne M. Suggestions on How to Conduct Empirical Research: A Behind-the-Scenes View. Perspectives: Teaching Legal Research and Writing, v. 15, n. 3, p. 176, 2007.
BRAMBILLA, Marco; CABOT, Jordi; WIMMER, Manuel. Model-driven software engineering in practice.Synthesis Lectures on Software Engineering, v. 1, n. 1, p. 1-182, 2012.
BRITAIN, Sandy. A review of learning design: concept, specifications and tools.A report for the JISC E-learning Pedagogy Programme, v. 2006, 2004.
BROOKE, John. SUS-A quick and dirty usability scale. Usability evaluation in industry, v. 189, n. 194, p. 4-7, 1996.
BURGOS, Daniel; TATTERSALL, Colin; KOPER, Rob. Re-purposing existing generic games and simulations for e-learning.Computers in Human Behavior, v. 23, n. 6, p. 2656- 2667, 2007.
And Rec-ommendations.LWA 2010, p. 281, 2010.
BURGOS, Daniel. How to use IMS LD to support eLearning in an effective way (invited talk). In:Computers in Education (SIIE), 2012 International Symposium on. IEEE, 2012. p. 1-1.
BURSZTYN, Natalie et al. Utilizing geo-referenced mobile game technology for universally accessible virtual geology field trips. International Journal of Education in Mathematics, Science and Technology, v. 3, n. 2, p. 93-100, 2015.
CARVALHO, Windson et al. Towards context-aware and mobile e-learning applications. 2011. In: TISE 2011, Congreso Internacional de Informática Educativa, 2011, Santiago, Chile.
CASSOU, Damien et al. A generative programming approach to developing pervasive computing systems. In:ACM Sigplan Notices. ACM, 2009. p. 137-146.
CASSOU, Damien et al. Toward a tool-based development methodology for pervasive computing applications. Software Engineering, IEEE Transactions on, v. 38, n. 6, p. 1445- 1463, 2012.
CHANG, En-Chi; HUANG, Chia-Yin. Technology Acceptance Model, Consumser Personality and Smartphone Users’ Satisfaction. In: Marketing Dynamism & Sustainability: Things Change, Things Stay the Same…. Springer International Publishing, 2015. p. 710-712.
CHEN, Baiyun; DENOYELLES, Aimee. Exploring students' mobile learning practices in higher education.Educause Review. Disponível em http://www. educause. edu/ero/article/exploring-students-mobile-learning-practices-higher-education, 2013.
CHEN, Chia-Chen; HUANG, Tien-Chi. Learning in a u-Museum: Developing a context- aware ubiquitous learning environment.Computers & Education, v. 59, n. 3, p. 873-883, 2012.
CHEN, Chih‐Hung; LIU, Guan‐Zhi; HWANG, Gwo‐Jen. Interaction between gaming and multistage guiding strategies on students' field trip mobile learning performance and motivation. British Journal of Educational Technology, 2015.
CHIANG, Tosti HC; YANG, Stephen JH; HWANG, Gwo-Jen. Students' online interactive patterns in augmented reality-based inquiry activities.Computers & Education, v. 78, p. 97- 108, 2014.
CHIN, Kai-Yi; CHEN, Yen-Lin. A mobile learning support system for ubiquitous learning environments.Procedia-Social and Behavioral Sciences, v. 73, p. 14-21, 2013.
CHUNG, Hsin-Hui; CHEN, Shu-Chu; KUO, Min-Hsiu. A Study of EFL College Students’ Acceptance of Mobile Learning. Procedia-Social and Behavioral Sciences, v. 176, p. 333- 339, 2015.
COHEN, Eli; NYCZ, Malgorzata. Learning objects and e-learning: An informing science perspective.Interdisciplinary Journal of E-Learning and Learning Objects, v. 2, n. 1, p. 23-34, 2006.
COHEN, Philip R. et al. Sketch-Thru-Plan: a multimodal interface for command and control. Communications of the ACM, v. 58, n. 4, p. 56-65, 2015.
CONOLE, Gráinne et al. Visualising learning design to foster and support good practice and creativity.Educational Media International, v. 45, n. 3, p. 177-194, 2008.
COPE, Bill; KALANTZIS, Mary. Ubiquitous learning: An agenda for educational transformation.Proceedings of the 6th Networked Learning, Greece, 2008.
CUADRADO, Jesus Sanchez; IZQUIERDO, Javier Luis Cánovas; MOLINA, Jesus Garcia. Applying model-driven engineering in small software enterprises.Science of Computer Programming, v. 89, p. 176-198, 2014.
DAVIES, Sarah-Jane et al. Enabling remote activity: using mobile technology for remote participation in geoscience fieldwork.Proceedings of the European Geosciences Union General Assembly, 2010.
DAVIS, Fred D. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, p. 319-340, 1989.
DE-LA-FUENTE-VALENTÍN, Luis; PARDO, Abelardo; KLOOS, Carlos Delgado. Generic service integration in adaptive learning experiences using IMS learning design. Computers & Education, v. 57, n. 1, p. 1160-1170, 2011.
DEN HAAN, Johann. MDE-Model Driven Engineering-reference guide. URL: http://www.theenterprisearchitect.eu/blog/2009/01/15/mde-model-driven-engineering-
reference-guide/, 2009. Último acesso em 15 de maio de 2015.
DERNTL, Michael et al. The conceptual structure of IMS Learning Design does not impede its use for authoring.Learning Technologies, IEEE Transactions on, v. 5, n. 1, p. 74-86, 2012.
DIRENE, Alexandre et al. Acquiring expertise in medical radiology through long-term interactions. In:Computer-Based Medical Systems, 2008. CBMS'08. 21st IEEE International Symposium on. IEEE, 2008. p. 403-408.
DLUDLA, Angeline G. et al. System architecture for ubiquitous live video streaming in university network environment. In:AFRICON, 2013. IEEE, 2013. p. 1-5.
DONOHOO, Brad K.; OHLSEN, Chris; PASRICHA, Sudeep. AURA: An application and user interaction aware middleware framework for energy optimization in mobile devices. In:Computer Design (ICCD), 2011 IEEE 29th International Conference on. IEEE, 2011. p. 168-174.
FAVRE, Jean-Marie. Foundations of model (driven)(reverse) engineering: Models. In: Proceedings of the International Seminar on Language Engineering for Model- Driven Software Development, Dagstuhl Seminar 04101. 2004.
FIGUEIREDO, Vânia Santos; SILVA, Geane Suelí Castro. A importância da aula de campo na prática em geografia. 10º Encontro Nacional de Pratica de Ensino em Geografia. Campo Grande: UFCG, 2009.
FLÔRES, Maria Lucia Pozzatti; TAROUCO, Liane Margarida Rockenbach; REATEGUI, Eliseo Berni. Funcionalidades da ferramenta de autoria para apoiar a construção de objetos de aprendizagem. In: Anais do Simpósio Brasileiro de Informática na Educação. 2011.
GARCÍA, Cristian González et al. Midgar: Generation of heterogeneous objects interconnecting applications. A Domain Specific Language proposal for Internet of Things scenarios.Computer Networks, v. 64, p. 143-158, 2014.
GARCÍA-MAGARIÑO, Iván; PALACIOS-NAVARRO, Guillermo. A model-driven approach for constructing ambient assisted-living multi-agent systems customized for Parkinson patients. Journal of Systems and Software, v. 111, p. 34-48, 2016.
GIEMZA, Adam; BOLLEN, Lars; HOPPE, H. Ulrich. LEMONADE: field-trip authoring and classroom reporting for integrated mobile learning scenarios with intelligent agent support.International Journal of Mobile learning and Organization, v. 5, n. 1, p. 96-114, 2011.
GÓMEZ, S. Learning Design Implementation in Context-Aware and Adaptive Mobile Learning (Ph. D. Thesis). 2013.
GÓMEZ, Sergio et al. Context-aware adaptive and personalized mobile learning delivery supported by UoLmP.Journal of King Saud University-Computer and Information Sciences, v. 26, n. 1, p. 47-61, 2014.
GREat. Grupo de Redes de Computadores, Engenharia de Software e Sistemas (GREat). Disponível em: http://great.ufc.br/. Acesso em: 20 de janeiro 2016.
GRANT, Wayne C. Wireless coyote: A computer-supported field trip.Commun. ACM, v. 36, n. 5, p. 57-59, 1993.
GUO, Bin; ZHANG, Daqing; IMAI, Michita. Toward a cooperative programming framework for context-aware applications.Personal and ubiquitous computing, v. 15, n. 3, p. 221-233, 2011.
HAILPERN, Brent; TARR, Peri. Model-driven development: The good, the bad, and the ugly. IBM systems journal, v. 45, n. 3, p. 451-461, 2006.
HERMIDA, Jesús M. et al. Applying model-driven engineering to the development of Rich Internet Applications for Business Intelligence.Information Systems Frontiers, v. 15, n. 3, p. 411-431, 2013.
HOPPE, H. Ulrich; GAßNER, Katrin. Integrating collaborative concept mapping tools with group memory and retrieval functions. In:Proceedings of the Conference on Computer Support for Collaborative Learning: Foundations for a CSCL Community. International Society of the Learning Sciences, 2002. p. 716-725
HWANG, Gwo-Jen; TSAI, Chin-Chung; YANG, Stephen JH. Criteria, strategies and research issues of context-aware ubiquitous learning. Journal of Educational Technology & Society, v. 11, n. 2, p. 81-91, 2008.
HUNG, Pi-Hsia et al. Seamless connection between learning and assessment-applying progressive learning tasks in mobile ecology inquiry.Journal of Educational Technology & Society, v. 16, n. 1, p. 194-205, 2013.
IMS GLOBAL LEARNING CONSORTIUM, Inc et al. IMS learning design information model. IMS LD version v. 1, 2003. Disponível em: http://www.imsglobal.org/learningdesign/ ldv1p0/imsld_infov1p0.html. Último acesso em 15 de maio de 2015.
IVANOV, Rosen. NFC-based pervasive learning service for children. In:Proceedings of the 14th International Conference on Computer Systems and Technologies. ACM, 2013. p. 329-336.
JEONG, Chang-Won; JOO, Su-Chong; JEONG, Young Sik. Sleeping situation monitoring system in ubiquitous environments.Personal and ubiquitous computing, v. 17, n. 7, p. 1357-1364, 2013.
JOUAULT, Frédéric et al. ATL: A model transformation tool.Science of computer programming, v. 72, n. 1, p. 31-39, 2008.
KELLY, Steven; TOLVANEN, Juha-Pekka.Domain-specific modeling: enabling full code generation. John Wiley & Sons, 2008.
KINDBERG, Tim; FOX, Armando. System software for ubiquitous computing.IEEE pervasive computing, v. 1, n. 1, p. 70-81, 2002.
Koper, Rob; Miao, Yongwu. (2007). Using the IMS LD standard to describe learning designs. Disponível em http://lnx-hrl-075v.web.pwo.ou.nl/handle/1820/927. Último acesso em 15 de maio de 2015.
KORTUEM, Gerd et al. Smart objects as building blocks for the internet of things.Internet Computing, IEEE, v. 14, n. 1, p. 44-51, 2010.
KOPER, Rob; MIAO, Yongwu. Using the IMS LD standard to describe learning designs. 2007. Disponível em http://lnx-hrl-075v.web.pwo.ou.nl/handle/1820/927. Último acesso em 15 de maio de 2015.
KRAVCIK, Milos et al. Mobile collector for field trips.Journal of educational technology & society, v. 7, n. 2, p. 25-33, 2004.
LEE, JongSuk Ruth et al. A ubiquitous smart learning platform for the 21st smart learners in an advanced science and engineering education. In:Network-Based Information Systems (NBiS), 2012 15th International Conference on. IEEE, 2012. p. 733-738.
LEWIS, James R.; SAURO, Jeff. The factor structure of the system usability scale. In: Human Centered Design. Springer Berlin Heidelberg, 2009. p. 94-103.
LIMA, Edmilson et al. GREat Tour: Um Guia de Visitas Móvel e Sensível ao Contexto. In: XII Workshop on Tools and Applications, 19th Brazilian Symposium on Multimedia and the Web, Brasil, 2013.
LIMA, Luciana de; MARÇAL, Edgar; RIBEIRO, Júlio; ANDRADE, Rossana; VIANA, Windson, e MELO JÚNIOR, Antonio. A Guide for the Development and Use of M-learning Applications in Mathematics.IEEE Technology and Engineering Education (ITEE), v. 6, n. 2, p. 1-12, 2011.
LO, Wan-Tzu; QUINTANA, Chris. Students' use of mobile technology to collect data in guided inquiry on field trips. In:Proceedings of the 12th International Conference on Interaction Design and Children. ACM, 2013. p. 297-300.
MACHADO, C. et al. Architectural elements of ubiquitous systems: A systematic review. In: ICSEA 2013, The Eighth International Conference on Software Engineering Advances. 2013. p. 208-213.
MACIEL, Cristiano et al. A Multi-agent Architecture to Support Ubiquitous Applications in Smart Environments. In:Agent Technology for Intelligent Mobile Services and Smart
Societies. Springer Berlin Heidelberg, 2015. p. 106-116.
MADANI, Halima Hebiri et al. Towards accessible and personalized mobile learning for learners with disabilities. In:Information and Communication Technology and Accessibility (ICTA), 2013 Fourth International Conference on. IEEE, 2013. p. 1-6.
MARÇAL, Edgar; ANDRADE, Rossana; RIOS, Riverson. Aprendizagem utilizando dispositivos móveis com sistemas de realidade virtual.RENOTE, v. 3, n. 1, 2005.
MARÇAL, Edgar et al. Geomóvel: Um Aplicativo para Auxílio a Aulas de Campo de Geologia. In: Anais do Simpósio Brasileiro de Informática na Educação. 2013.
MARÇAL, Edgar et al. A mobile learning system to enhance field trips in geology. In: Frontiers in Education Conference (FIE), 2014 IEEE. IEEE, p. 1-8, 2014.
MARINHO, Fabiana G. et al. MobiLine: A Nested Software Product Line for the domain of mobile and context-aware applications. Science of Computer Programming, v. 78, n. 12, p. 2381-2398, 2013.
MARTÍNEZ-ORTIZ, Iván; SIERRA, José Luis; FERNÁNDEZ-MANJÓN, Baltasar. Enhancing IMS LD Units of Learning Comprehension. In:Internet and Web Applications and Services, 2009. ICIW'09. Fourth International Conference on. IEEE, 2009. p. 561- 566.
MAVROUDI, Anna; HADZILACOS, Thanasis. Implementation of adaptive learning designs.Annals of the University of Craiova, Series: Automation, Computers, Electronics and Mechatronics, v. 9, n. 2, 2012.
MAYER, Richard E. Multimedia learning. Psychology of learning and motivation, v. 41, p. 85-139, 2002.
MEDZINI, Arnon; MEISHAR-TAL, Hagit; SNEH, Yael. Use of mobile technologies as support tools for geography field trips. International Research in Geographical and Environmental Education, v. 24, n. 1, p. 13-23, 2015.
MEEK, S., FITZGERALD, E., PRIESTNALL, G., SHARPLES, M. Field Trip Learning. In: Kinuthia, W. & Marshall, S. (eds). On the Move: Mobile Learning for Development. Information Age Publishing Inc., Charlotte, NC, 2013.
MERCADAL, Julien et al. A domain-specific approach to architecturing error handling in pervasive computing.ACM Sigplan Notices, v. 45, n. 10, p. 47-61, 2010.
MEDEIROS, Flávio Mota; DE ALMEIDA, Eduardo Santana; DE LEMOS MEIRA, Silvio Romero. Towards an approach for service-oriented product line architectures. In:Proceedings
of the Workshop on Service-oriented Architectures and Software Product Lines. 2009. p. 1-7.
MIT, Massachusetts Institute of Technology. App Inventor. 2012. Disponível em: http://appinventor.mit.edu/.
MOHAGHEGHI, Parastoo et al. MDE adoption in industry: challenges and success criteria. In: Models in Software Engineering. Springer Berlin Heidelberg, 2009. p. 54-59.
MORAIS, Nídia Salomé et al. Uma Revisão de Literatura sobre o Uso das Tecnologias da Comunicação no Ensino Superior. Revista PRISMA.COM, n. 24, 2014.
MOURA, César.Conceiving and Implementing a language-oriented approach for the design of automated learning scenarios. 2007. Tese de Doutorado. Université des Sciences et Technologie de Lille-Lille I.
MUGWANYA, Raymond; MARSDEN, Gary. Mobile learning content authoring tools (MLCATs): a systematic review. In: E-Infrastructures and E-Services on Developing Countries. Springer Berlin Heidelberg, 2010. p. 20-31.
MUK, Alexander; CHUNG, Christina. Applying the technology acceptance model in a two- country study of SMS advertising. Journal of Business Research, v. 68, n. 1, p. 1-6, 2015. MUNNELLY, Jennifer; FRITSCH, Serena; CLARKE, Siobhan. An aspect-oriented approach to the modularisation of context. In: Pervasive Computing and Communications, 2007. PerCom'07. Fifth Annual IEEE International Conference on. IEEE, 2007. p. 114-124.
MYERS, Bruce Leigh; SCHROEDER, Trevor. An Application of the Technology Acceptance Model to Intended Adoption of Digital Printing Technology in the Label Industry. Refereed Articles, p. 10, 2014.
NABORS, Martha L.; EDWARDS, Linda Carol; MURRAY, R. Kent. Making the case for field trips: What research tells us and what site coordinators have to say. Education, v. 129, n. 4, p. 661-667, 2009.
NIELSEN, Jakob; MOLICH, Rolf. Heuristic evaluation of user interfaces. In: Proceedings of the SIGCHI conference on Human factors in computing systems. ACM, 1990. p. 249-256.
NIEUWDORP, Eva. The pervasive discourse: an analysis.Computers in Entertainment (CIE), v. 5, n. 2, p. 13, 2007.
OGATA, Hiroaki; YANO, Yoneo. Context-aware support for computer-supported ubiquitous
IEEE International Workshop on. IEEE, 2004. p. 27-34.
OKERLUND, Johanna; TURBAK, Franklyn. A Preliminary Analysis of App Inventor Blocks Programs. Poster presented at Visual Languages and Human Centric Computing (VLHCC), Sept, p. 15-19, 2013.
OLIVEIRA, Francisco Hélio; SALVADOR, Laís; NOVAIS, Renato. Uma Análise do Uso da Ontologia IMS LD na Construção de Modelos Conceituais para E-learning. In: Anais do Simpósio Brasileiro de Informática na Educação. 2014. p. 1213-1222.
OLSEN, Gøran K.; OLDEVIK, Jon. Scenarios of traceability in model to text transformations. In:Model Driven Architecture-Foundations and Applications. Springer