Skip to main content
SpringerLink
Log in

Facilitating Complex Learning by Mobile Augmented Reality Learning Environments

  • Chapter
Book cover Reshaping Learning

Part of the book series: New Frontiers of Educational Research ((NFER))

Abstract

The widespread ownership of mobile devices has lead to an increased interest to ubiquitous learning that is supported by a wide range of mobile devices. Mobile learning (m-learning) is referred to as when the process of learning and teaching occurs with the use of mobile devices anywhere and anytime. These developments have led to new research challenges in integrating formal and informal learning opportunities in technological supported environments. Therefore, this chapter is intended to provide an overview on how complex learning may be facilitated by mobile augmented reality learning environments and discuss technological, theoretical, and assessment challenges that must be addressed by future research for mobile augmented reality learning environments to fulfill its potential.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Abas H, Badioze Zaman H (2011) Visual learning through augmented reality storybook for remedial student. In: Zaman H, Robinson P, Petrou M, Olivier P, Shih T, Velastin S, Nyström I (eds) Visual informatics: sustaining research and innovations, vol 7067. Springer, Berlin, pp 157–167

    Chapter  Google Scholar 

  • Albrecht U-V, von Jan U, Krückelberg J, Behrends M, Matthies HK (2011) Medical students experience the mobile augmented reality blended learning environment (MARBLE)—an attractive concept for the net-generation? In: Sampson DG, Spector JM, Ifenthaler D, Isaias P (eds) Proceedings of the IADIS international conference on cognition and exploratory learning in the digital age. IADIS Press, Rio de Janeiro, pp 263–266

    Google Scholar 

  • Axelrod R (ed) (1976) Structure of decision: the cognitive maps of political elites. Princeton University Press, Princeton

    Google Scholar 

  • Azuma R (1997) A survey of augmented reality presence. Teleoperators Virtual Environ 6(4):355–385

    Article  Google Scholar 

  • Bechtel Power Corporation. (n.d.) (2011) Watts bar completion. Retrieved 13 Nov 2011 from http://www.bechtel.com/watts-bar-completion.html

  • Bimber O, Raskar R (2005) Spatial augmented reality. merging real and virtual worlds. A K Peters, Wellesley

    Book  Google Scholar 

  • Bransford JD, Brown AL, Cocking RR (2000) How people learn: brain, mind, experience, and school. National Academy Press, Washington

    Google Scholar 

  • Brehmer B (1980) In one word: not from experience. Acta Psychol 45:223–241

    Article  Google Scholar 

  • Brown JS, Collins A, Duguid P (1989) Situated cognition and the culture of learning. Educ Res 18(1):32–42

    Article  Google Scholar 

  • Cavalli-Sforza V, Weiner A, Lesgold A (1994) Software support for students engaging in scientific activity and scientific controversy. Sci Educ 78:577–599

    Article  Google Scholar 

  • Chinn C, Malhotra B (2002) Epistemologically authentic inquiry in schools: a theoretical framework for evaluating inquiry tasks. Sci Educ 82(2):175–218

    Article  Google Scholar 

  • Clarke J, Dede C (2007) MUVEs as a powerful means to study situated learning. In: Chinn CA, Erkens G, Putambekar S (eds) Proceedings of the 2007 computer-supported collaborative learning (CSCL) conference, New Brunswick, pp 141–144

    Google Scholar 

  • Dana SK, Roy PK, Kurth J (eds) (2009) Complex dynamics in physiological systems: from heart to brain. Springer, New York

    Google Scholar 

  • de Jong T, van Joolingen WR (1998) Scientific discovery learning with computer simulations of conceptual domains. Rev Educ Res 68(2):179–202

    Article  Google Scholar 

  • Dede C (2009) Immersive interfaces for engagement and learning. Science 323(66):66–69

    Article  Google Scholar 

  • Dewey J (1938) Context and thought. In: Bernstein R (ed) On experience, nature and freedom. Library of Liberal Arts, New York, pp 88–110

    Google Scholar 

  • Dörner D (1980) On the difficulties people have in dealing with complexity. Simul Games 11:87–106

    Google Scholar 

  • Dörner D (1987) On the difficulties people have in dealing with complexity. In: Rasmussen J, Duncker K, Leplat J (eds) New technology and human error. Wiley, Chichester, pp 97–109

    Google Scholar 

  • Dörner D (1996) The logic of failure: Why things go wrong and what can we do to make them right (trans: Kimber R, Kimber R). Metropolitan Books, New York

    Google Scholar 

  • Dörner D, Wearing AJ (1995) Complex problem solving: toward a (computer-simulated) theory. In: Frensch PA, Funke J (eds) Complex problem solving: the European perspective. Lawrence Erlbaum Associates, Inc, Hillsdale, pp 65–99

    Google Scholar 

  • Dunleavy M, Dede C, Mitchell R (2009) Affordances and limitations of immersive participatory augmented reality simulations for teaching and learning. J Sci Educ Technol 18(1):7–22

    Article  Google Scholar 

  • Eisenhart M, Finkel E, Marion S (1996) Creating the conditions for scientific literacy: A re-examination. Am Educ Res J 33:261–295

    Article  Google Scholar 

  • Ellaway R (2010) eMedical teacher. Med Teach 32:798–800

    Article  Google Scholar 

  • Eseryel D, Law V (2010) Promoting learning in complex systems: effect of question prompts versus system dynamics model progressions as a cognitive-regulation scaffold in a simulation-based inquiry-learning environment. In: Proceedings of the 9th international conference of the learning sciences, Chicago, IL

    Google Scholar 

  • Eseryel D, Ge X, Ifenthaler D, Law V (2011) Dynamic modeling as a cognitive regulation scaffold for complex problem solving skill acquisition in an educational massively multiplayer online game environment. J Educ Comput Res 45(3):265–287

    Article  Google Scholar 

  • Fjeld M, Voegtli BM (2002) Augmented chemistry: an interactive educational workbench. In: Proceedings of international symposium on mixed and augmented reality, IEEE Computer Society

    Google Scholar 

  • Frederiksen J, White BY (1992) Mental models and understanding: a problem for science education. In: Scanlon E, O’Shea T (eds) New directions in educational technology. Springer, New York, pp 211–226

    Chapter  Google Scholar 

  • Freitas R, Campos P (2008) SMART: a system of augmented reality for teaching 2nd grade students. In: Proceedings of the 22nd British CHI group annual conference on HCI 2008: people and computers XXII: culture, creativity, interaction. Liverpool, UK

    Google Scholar 

  • Frensch PA, Funke J (1995) Definitions, traditions, and a general framework for understanding complex problem solving. In: Frensch PA, Funke J (eds) Complex problem solving: the European perspective. Lawrence Erlbaum Associates, Inc, Hillsdale, pp 3–26

    Google Scholar 

  • Funke J (1991) Solving complex problems: exploration and control of complex systems. In: Sternberg RJ, Frensch PA (eds) Complex problem solving: principles and mechanisms. Lawrence Erlbaum Associates, Inc, Hillsdale, pp 185–222

    Google Scholar 

  • Gee JP (2003) What video games have to teach us about learning and literacy. Palgrave-Macmillan, New York

    Google Scholar 

  • Gillet A, Sanner M, Stoffler D, Goodsell D, Olson A (2004) Augmented reality with tangible auto-fabricated models for molecular biology applications. IEEE Vis 235–241

    Google Scholar 

  • Glenberg AM (1997) What memory is for. Behav Brain Sci 20(1):1–19

    Google Scholar 

  • Goodwin C (1994) Professional vision. Am Anthropologist 96(3):606–633

    Article  Google Scholar 

  • Greeno JG (1989) Situations, mental models and generative knowledge. In: Klahr D, Kotovsky K (eds) Complex information processing. Lawrence Erlbaum, Hillsdale, pp 285–318

    Google Scholar 

  • Greeno JG (1998) The situativity of knowing, learning, and research. Am Psychol 53:5–26

    Article  Google Scholar 

  • Griffin MM (1995) You can’t get there from here: situated learning, transfer, and map skills. Contemp Educ Psychol 20:65–87

    Article  Google Scholar 

  • Haller M, Billinghurst M, Thomas BH (2007) Emerging technologies of augmented reality: interfaces and design. Idea Group, Inc., Hershey

    Book  Google Scholar 

  • Harris M, Cullen R (2007) Learner-centered leadership: an agenda for action. Innovative High Educ 33(1):21–28

    Article  Google Scholar 

  • Hatano G, Inagaki K (1986) Two courses of expertise. In: Stevenson HAH, Hakuta K (eds) Child development and education in Japan. Freeman, New York, pp 262–272

    Google Scholar 

  • Hatano G, Oura Y (2003) Commentary: reconceptualizing school learning using insights from expertise research. Educ Res 32(8):26–29

    Article  Google Scholar 

  • Heinecke WF, Milman NB, Washington LA, Blasi L (2001) New directions in the evaluation of the effectiveness of educational technology. Comput Schools 18(2/3):97–110

    Article  Google Scholar 

  • Hendricks CC (2001) Teaching causal reasoning through cognitive apprenticeship: what are results from situated learning? J Educ Res 94(5):302–311

    Article  Google Scholar 

  • Hogan K, Thomas D (2001) Cognitive comparisons of students systems modeling in ecology. J Sci Educ Technol 10(10):75–96

    Google Scholar 

  • Hung W (2011) Team-based problem solving: the role of collective cognition. Paper presented at the international convention of the association for educational communications and technology (AECT), Jacksonville, FL

    Google Scholar 

  • Ifenthaler D (2009) Bridging the gap between expert-novice differences: the model-based feedback approach. In: Kinshuk D, Sampson DG, Spector JM, Isaias P, Ifenthaler D (eds) In: Proceedings of the IADIS international conference on cognition and exploratory learning in the digital age, IADIS Press, Rome, pp 49–60

    Google Scholar 

  • Ifenthaler D (2010) Learning and instruction in the digital age. In: Spector JM, Ifenthaler D, Isaías P, Kinshuk, Sampson DG (eds) Learning and instruction in the digital age: making a difference through cognitive approaches, technology-facilitated collaboration and assessment, and personalized communications. Springer, New York, pp 3–10

    Google Scholar 

  • Ifenthaler D (2011a) Identifying cross-domain distinguishing features of cognitive structures. Educ Tech Res Dev 59(6):817–840. doi:10.1007/s11423-011-9207-4

    Article  Google Scholar 

  • Ifenthaler D (2011b) MaTS—mannheimer tablet-PC schulen. Lehrstuhl für Erziehungswissenschaft, Mannheim

    Google Scholar 

  • Ifenthaler D (2012) Is Web 3.0 changing learning and instruction? In: Isaias P, Ifenthaler D, Kinshuk D, Sampson DG, Spector JM (eds) Towards learning and instruction in Web 3.0. advances in cognitive and educational psychology. Springer, New York, pp 11–16

    Google Scholar 

  • Ifenthaler D, Seel NM (2005) The measurement of change: learning-dependent progression of mental models. Technol, Instr, Cogn Learn 2(4):317–336

    Google Scholar 

  • Ifenthaler D, Seel NM (2011) A longitudinal perspective on inductive reasoning tasks. Illuminating the probability of change. Learn Instr 21(4):538–549. doi:10.1016/j.learninstruc.2010.08.004

    Article  Google Scholar 

  • Ifenthaler D, Pirnay-Dummer P, Seel NM (2007) The role of cognitive learning strategies and intellectual abilities in mental model building processes. Technol, Instr, Cogn Learn 5(4):353–366

    Google Scholar 

  • Ifenthaler D, Masduki I, Seel NM (2011) The mystery of cognitive structure and how we can detect it. Tracking the development of cognitive structures over time. Instr Sci 39(1):41–61. doi:10.1007/s11251-009-9097-6

    Article  Google Scholar 

  • Ifenthaler D, Eseryel D, Ge X (eds) (2012) Assessment in game-based learning: foundations, innovations, and perspectives. Springer, New York

    Google Scholar 

  • Ifenthaler D, Schweinbenz V (in press) The acceptance of tablet-PCs in classroom instruction: The teacher’s perspectives. Computer in Human Behavior

    Google Scholar 

  • Jacobson MJ (2000) Problem solving about complex systems: difference between experts and novices. In: Fishman B, O’Connor-Divelbiss S (eds) Fourth international conference of the learning sciences. Lawrence Erlbaum Associates, Inc, Mahwah, pp 14–21

    Google Scholar 

  • Jonassen DH (1997) Instructional design models for well-structured and ill-structured problem-solving learning outcomes. Educ Tech Res Dev 45(1):65–94

    Article  Google Scholar 

  • Jonassen DH (2000) Toward a design theory of problem solving. Educ Tech Res Dev 48(4):63–85. doi:10.1007/BF02300500

    Article  Google Scholar 

  • Jonassen DH (2004) Learning to solve problems: an instructional design guide. Pfeiffer, San Francisco

    Google Scholar 

  • Jonassen DH (2011) Learning to solve problems. A handbook for designing problem-solving learning environments. Routledge, New York

    Google Scholar 

  • Kelso JAS (2009) Understanding complex systems. In: Dana SK, Roy PK, Kurth J (eds) Complex dynamics in physiological systems: from heart to brain. Springer, New York, pp 9–11

    Google Scholar 

  • Kirschner PA, Sweller J, Clark RE (2006) Why minimal guidance during instruction does not work: an analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educ Psychol 41(2):75–86

    Article  Google Scholar 

  • Kohn LT, Corrigan JM, Donaldson MS (1999) To err is human: building a safer health system. Institute of Medicine: Committee on Quality of Health Care in America, Washington

    Google Scholar 

  • Lassila O, Hendler J (2007) Embracing “Web 3.0”. Internet Comput 11(3):90–93

    Article  Google Scholar 

  • Lave J, Wenger E (1991) Situated learning: legitimate periperal participation. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Law V, Eseryel D (2011) Cognitive regulation in a simulation-based inquiry learning environment. Paper presented at the annual convention of association for educational communications and technology (AECT), Jacksonville, FL

    Google Scholar 

  • Law V, Ge X, Eseryel D (2011) An investigation of the development of a reflective virtual learning community in an ill-structured domain of instructional design. Knowl Manag E-Learn: An Int J 3(4):513–533

    Google Scholar 

  • Ma JY, Choi JS (2007) The virtuality and reality of augmented reality. J Multimedia 2(1):32–37

    Article  Google Scholar 

  • Mackinnon AJ, Wearing AJ (1980) Complexity and decision-making. Behav Sci 25:285–296

    Article  Google Scholar 

  • Martín-Gutiérrez J, Contero M, Alcañiz M (2010) Evaluating the usability of an augmented reality based educational application. In: Aleven V, Kay J, Mostow J (eds) Intelligent tutoring systems, vol 6094. Springer, Berlin, pp 296–306

    Chapter  Google Scholar 

  • Mayer RE, Wittrock MC (1996) Problem-solving transfer. In: Berlinert DC, Calfee RC (eds) Handbook of educational psychology. Macmillan, New York, pp 47–62

    Google Scholar 

  • McGinn M, Roth W (1999) Preparing students for competent scientific practice: implications of recent research in science and technology studies. Educ Res 28:14–24

    Article  Google Scholar 

  • Means B, Haertel GD (2004) Using technology evaluation to enhance student learning. Teachers College Press, New York

    Google Scholar 

  • Mehler-Bicher A, Reiß M, Steiger L (2011) Augmented reality: Theorie und Praxis. Oldenbourg, München

    Book  Google Scholar 

  • Milgram P, Takemura H, Utsumi A, Kishino F (1994) Augmented reality: a class of displays on the reality-virtuality continuum. SPIE proceedings: telemanipulator and telepresence technologies, Boston, MA

    Google Scholar 

  • Miller GA (1956) The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychol Rev 63(2):81–97

    Article  Google Scholar 

  • Naylor JC, Briggs GE (1963) Effects of task complexity and task organization on the relative efficiency of part and whole training methods. J Expe Psychol 65:217–224

    Article  Google Scholar 

  • Nischelwitzer A, Lenz F-J, Searle G, Holzinger A (2007) Some aspects of the development of low-cost augmented reality learning environments as examples for future interfaces in technology enhanced learning. In: Stephanidis C (ed) Universal access in human-computer interaction. Applications and services, vol 4556. Springer, Berlin, pp 728–737

    Google Scholar 

  • Palincsar AS, Magnusson SJ (2001) The interplay of first-hand and text-based investigations to model and support the development of scientific knowledge and reasoning. In: Carver S, Klahr D (eds) Cognition and instruction: twenty five years of progress. Lawrence Erlbaum, Mahwah, pp 151–194

    Google Scholar 

  • Peirce CS (1992) Questions concerning faculties claimed for man. In: Houser N, Kloesel C (eds) The essential peirce, vol 1. Indiana University Press, Bloomington, pp 11–27

    Google Scholar 

  • Perkins DN, Grotzer TA (1997) Teaching intelligence. Am Psychol 52:1125–1133

    Article  Google Scholar 

  • Plous S (1993) The psychology of judgment and decision making. McGraw-Hill, New York

    Google Scholar 

  • Putz-Osterloh W, Lemme M (1987) Knowledge and its intelligent application to problem solving. Ger J Psychol 11:286–303

    Google Scholar 

  • Rumelhart DE, Smolensky P, McClelland JL, Hinton GE (1986) Schemata and sequential thought processes in PDP models. In: McClelland JL, Rumelhart DE (eds) Parallel distributed processing. Explorations in the microstructure of cognition, vol 2: psychological and biological models. MIT Press, Cambridge, pp 7–57

    Google Scholar 

  • Sabelli NH (2006) Complexity, technology, science, and education. J Learn Sci 15:5–9

    Article  Google Scholar 

  • Saforrudin N, Badioze Zaman H, Ahmad A (2011) Technical skills in developing augmented reality application: teachers’ readiness. In: Zaman H, Robinson P, Petrou M, Olivier P, Shih T, Velastin S, Nyström I (eds) Visual informatics: sustaining research and innovations, vol 7067. Springer, Berlin, pp 360–370

    Chapter  Google Scholar 

  • Salomon G (ed) (1993) Distributed cognitions: psychological and educational considerations. Cambridge University Press, New York

    Google Scholar 

  • Scardamalia M, Bereiter C (1994) Computer support for knowledge-building communities. J Learn Sci 3(3):265–283

    Article  Google Scholar 

  • Schwartz DL, Bransford JD, Sears D (2005) Efficiency and innovation in transfer. In: Mestre J (ed) Transfer of learning from a modern multidisciplinary perspective. Information Age Publishing, Greenwich, pp 1–51

    Google Scholar 

  • Seel NM (1999) Educational diagnosis of mental models: Assessment problems and technology-based solutions. J Struct Learning Int Sys 14(2):153–185

    Google Scholar 

  • Seel NM (2001) Epistemology, situated cognition, and mental models: Like a bridge over troubled water. Instr Sci 29(4–5):403–427

    Article  Google Scholar 

  • Seel NM (2006) Mental models and complex problem solving. In: Elen J, Clark RE (eds) Handling complexity in learning environments: theory and research. Elsevier Ltd, Amsterdam, pp 43–66

    Google Scholar 

  • Seel NM, Ifenthaler D, Pirnay-Dummer P (2009) Mental models and problem solving: technological solutions for measurement and assessment of the development of expertise. In: Blumschein P, Hung W, Jonassen DH, Strobel J (eds) Model-based approaches to learning: using systems models and simulations to improve understanding and problem solving in complex domains. Sense Publishers, Rotterdam, pp 17–40

    Google Scholar 

  • Shaffer DW (2006) Epistemic frames for epistemic games. Comput Educ 46(13):223–234

    Article  Google Scholar 

  • Shelton BE (2003) How augmented reality helps students learn dynamic spatial relationships. University of Washington, Seattle

    Google Scholar 

  • Sin A, Badioze Zaman H (2009) Tangible interaction in learning astronomy through augmented reality book-based educational tool. In: Badioze Zaman H, Robinson P, Petrou M, Olivier P, Schröder H, Shih T (eds) Visual informatics: bridging research and practice, vol 5857. Springer, Berlin, pp 302–313

    Chapter  Google Scholar 

  • Snow RE (1990) New approaches to cognitive and conative assessment in education. Int J Educ Res 14(5):455–473

    Google Scholar 

  • Spector JM (2010) Mental representations and their analysis: an epestimological perspective. In: Ifenthaler D, Pirnay-Dummer P, Seel NM (eds) Computer-based diagnostics and systematic analysis of knowledge. Springer, New York, pp 27–40

    Chapter  Google Scholar 

  • Spector JM, Anderson TM (eds) (2000) Integrated and holistic perspectives on learning, instruction, and technology: understanding complexity. Kluwer Academic Publishers, Dordrecht

    Google Scholar 

  • Spector JM, Christensen DL, Sioutine AV, McCormack D (2001) Models and simulations for learning in complex domains: using causal loop diagrams for assessment and evaluation. Comput Hum Behav 17(5–6):517–545

    Article  Google Scholar 

  • Traxler J (2009) Current state of mobile learning. In: Ally M (ed) Mobile learning: transforming the delivery of education and training. Athabasca University Press, Edmonton, pp 9–24

    Google Scholar 

  • van Merriënboer JJG (1997) Training complex cognitive skills: a four-component instructional design model for technical training. Educational Technology Publications, Englewood Cliffs

    Google Scholar 

  • van Merriënboer JJG, Clark RE, de Croock MBM (2002) Blueprints for complex learning: the 4C/ID-model. Educ Tech Res Dev 50(2):39–64

    Article  Google Scholar 

  • Vygotsky LS (1978) Mind in society: the development of higher psychological processes (trans: Cole M, John-Steiner V, Scribner S, Souberman E (eds)). Harvard University Press, Cambridge

    Google Scholar 

  • Wenger E (1998) Communities of practice: learning, meaning, and identity. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Wertsch J (1998) Mind as action. Oxford University Press, New York

    Google Scholar 

  • Wightman DC, Lintern G (1985) Part-task training for tracking and manual control. Hum Factors 27:267–284

    Google Scholar 

  • Winn WD (2003) Learning in artificial environments: embodiment, embeddedness and dynamic adaption. Technol, Instr, Cognition Learn 1(1):87–114

    Google Scholar 

  • Yu L (2007) Introduction to the semantic web and semantic web services. Chapman and Hall, Boca Raton

    Book  Google Scholar 

  • Zimmerman BJ, Schunk D (2001) Theories of self-regulated learning and academic achievement: an overview and analysis. In: Zimmerman BJ, Schunk D (eds) Self-regulated learning and academic achievement. Theoretical perspectives. Lawrence Erlbaum Associates, Mahawah, pp 1–37

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of Oklahoma, Oklahoma, USA

    Dirk Ifenthaler & Deniz Eseryel

Authors
  1. Dirk Ifenthaler
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Deniz Eseryel
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dirk Ifenthaler .

Editor information

Editors and Affiliations

  1. Faculty of Education, Beijing Normal University, Beijing, People’s Republic of China

    Ronghuai Huang

  2. Faculty of Science and Technology, Athabasca University, Athabasca, AB, Canada

    Kinshuk

  3. College of Information, University of North Texas, Denton, TX, USA

    J. Michael Spector

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Ifenthaler, D., Eseryel, D. (2013). Facilitating Complex Learning by Mobile Augmented Reality Learning Environments. In: Huang, R., Kinshuk, Spector, J.M. (eds) Reshaping Learning. New Frontiers of Educational Research. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32301-0_18

Download citation

Publish with us

Policies and ethics

Search

Navigation