ISSN 2083-6473
ISSN 2083-6481 (electronic version)




Associate Editor
Tomasz Neumann

Published by
TransNav, Faculty of Navigation
Gdynia Maritime University
3, John Paul II Avenue
81-345 Gdynia, POLAND
www http://www.transnav.eu
e-mail transnav@am.gdynia.pl
Experimental Research with Neuroscience Tool in Maritime Education and Training (MET)
1 University of the Aegean, Chios, Greece
ABSTRACT: The paper argues for the necessity to combine MMR methods (questionnaire, interview), gaze tracking as neuroscience tool and sentiment/opinion techniques for personal satisfaction analysis at the maritime and training education (MET) and proposes a practical research approach for this purpose. The purpose of this paper is to compare the results from gaze tracker (Face analysis tool) of three experiments & sentiment analysis of two experiments for satisfaction evaluation of the students-users? (subjective) satisfaction of the maritime education via user interface evaluation of several types of educational software (i.e. engine simulator, ECDIS, MATLAB). The experimental procedure presented here is a primary effort to research the emotion analysis (satisfaction) of the users-students in MET. The gaze tracking & sentiment analysis methodology appears to be one sufficient as evaluation tool. Finally, the ultimate goal of this research is to find and test the critical factors that influence the educational practice and user?s satisfaction of MET modern educational tools (simulators, ECDIS etc.).
Akpan, J. P. 2001. Issues associated with inserting computer simulations into biology instruction: a review of the literature. Electronic Journal of Science Education, 5(3), Retrieved from: http://ejse.southwestern.edu/article/viewArticle/7656/5423.
Arpan, S., 2009. “CSCI 8810 A report on Gaze Tracking”, Retrieved from: http://www.docstoc.com/docs/80403505/CSCI-8810-C-Gaze-Tracking
Asteriadis, S. Tzouveli, P. Karpouzis, K. Kollias, S. 2009. Estimation of behavioral user state based on eye gaze and head pose—application in an e-learning environment, Multimedia Tools and Applications, Springer 2009;41:3:469-493.
Blake, C., and Scanlon, E. (2007). Reconsidering simulations in science education at a distance:features of effective use. Journal of Computer Assisted Learning, 23(6), 491–502.
Brannen, J. 1995. Combining qualitative and quantitative ap-proaches: An overview, J. Brannen (ed.), Mixing Methods: Qualitative and Quantitative Research. UK:Avebury, 3-38.
Bryman, J. 1995. Quantitative and qualitative research:further reflections on their integration, Mixing Methods: Qualita-tive and Quantitative Research. UK:Avebury, 57-80.
Borg, W.R. and Gall, M.D. (1979) Educational Research: an Introduction (6th edition). NY: Longman.
Brooke, J. 1996. SUS: A “quick and dirty” usability scale. In: Jordan, P. W., Thomas, B., Weerdmeester, B. A., McClelland (eds.) Usability Evaluation in Industry, Taylor & Francis, London, UK pp. 189-194.
Cheng, D. Zhao, Z. Lu, J. Tu, D. 2010. A Kind of Modelling and Simulating Method for Eye Gaze Tracking HCI System, Proceedings of 3rd International Congress on Image and Signal Processing (CISP2010), IEEE, EMB, pp. 511-514.
Cohen, L. Manion, L. Morrison, K. 2008. Research Methods in Education (5th edtion). London: Routledge Falmer.
Conati, C. and Merten, C. 2007. Eye-tracking for user modelling in exploratory learning environments: An empirical evaluation. Knowledge-Based Systems;20:557-74.
Crook, C. 1994. Computers and the collaborative experience of learning. London, Routledge.
de Jong, T., and van Joolingen, W. R. (1998). Scientific discovery learning with computer simulations of conceptual domains. Review of Educational Research, 68(2), 179–201.
Dix, A. Finlay, J. Abowd, G. D. Beale, R. 2004. Human-Computer Interaction, UK:Pearson Education Limited.
Duchowski, A. T. 2007. Eye tracking methodology: Theory and practice, Springer, New York.
Fidel, R. 2008. Are we there yet?: Mixed methods research in library and information science, Library & Information Science Research, pp. 265-72.
Fotopoulou, A. Mini, M. Pantazara, M. Moustaki,A. 2009. “La combinatoire lexicale des noms de sentiments en grec moderne”, in Le lexique des emotions, I. Navacova and A. Tutin, Eds. Grenoble: ELLUG.
Galin, D. and Ornstein, R. 1974. “Individual Differences in Cognitive Style—I. Reflective Eye Movements,” Neuropsychologia, vol. 12, pp. 367-376.
Goswami. U. 2007. Neuroscience and education: from research to practice? Nature Review Neuroscience, 7:406-413.
Hagerty M, Just M A. 1993. Constructing mental models of machines from text and diagrams. Journal of Memory and Language; 32:71-42.
Hansen, D.W. Qiang, Ji 2010. In the Eye of the Beholder: A Survey of Models for Eyes and Gaze Pattern Analysis and Machine Intelligence, IEEE Transactions on, Vol.32, Is.3, pp.478-500.
Holsanova, J. Holmberg, N. Holmqvist, K. 2009. Reading information graphics: the role of spatial contiguity and dual attentional guidance. Applied Cognitive Psychology 2009; 23:1215-26.
Hyona J, Niemi P. 1990.Eye movements during repeated reading of a text. Acta Psychologica; 73: 259-80.
IMO-International, Maritime Organization, 2003. Issues for training seafarers resulting from the implementation on board technology, STW 34/INF.6.
IMO, 2012. “Development of an e-Navigation strategy implementation plan”, NAV 58/INF.13, 27 April 2012.
Just M A, Carpenter P A. A. 1980. Theory of reading: From eye fixations to comprehension. Psychological Review 1980;87: 329-55.
Kluj, S. 2002. Relationship between learning goals and proper simulator, ICERRS5 Paper.
Kotzabasis, P. 2011. Human-Computer Interaction: Principles, methods and examples, Athens, Kleidarithmos (in Greek).
Lambov, D. Pais, S. Dias, G. 2011. Merged Agreement Algorithms for Domain Independent Sentiment Analysis, Pacific Association, For Computational Linguistics (PACLING 2011), Procedia - Socila and Behavioural Sciences, 27, pp. 248-257.
Maks, I. and Vossen, P. 2012. A lexicon model for deep sentiment analysis and opinion mining applications, Decision Support Systems 53, pp. 680-88.
Mueller, S.C. Jackson, C. P. T. and Skelton, R.W. 2008. “Sex Differences in a Virtual Water Maze: An Eye Tracking and Pupillometry Study”. Behavioural Brain Research, vol. 193, pp. 209-215.
Nacke L.E. Stellmach, S. Sasse, D. Niesenhaus, J. Dachselt, R. 2011. LAIF: A logging and interaction framework for gaze-based interfaces in virtual entertainment environments, Entertainment Computing 2, pp. 265–273.
Nielsen, J. 1994. Usability Engineering, Academic Press Inc.
Nielsen, J, and Mack, R.L. (eds.) 1994. Usability Inspection Methods, New York, John Wiley.
Norman, K.l. 2006. Levels of Automation and User Participation in Usability Testing, Interacting with computers, Elsevier.
Papachristos D, Nikitakos N. 2010. Application Methods and Tools of Neuroscience, in Marine Education. Conference Proceedings “Marine Education & Marine Technology” (ELINT), 1 December 2010, Athens, Greece.
Papachristos, D. Koutsabasis, P. Nikitakos, N. 2012. Usability Evaluation at the Ship’s Bridge: A Multi-Method Approach, In Proceedings of 4th International Symposium on “Ships Operation, Management and Economics”-SOME12, The Greek Section (SNAME), 8-9 November 2012, Eygenideio Foundation, Athens.
Papachristos, D. and Nikitakos, N., 2013a. Human Factor Evaluation for Marine Education by using Neuroscience Tools, In Proceedings 4th International Symposium of Maritime Safety Security and Environmental Protection, 30-31 May 2013, Athens, http://www.massep.gr/sponsorship-opportunities/.
Papachristos, D. Alafodimos, K. Lambrou, M. Kalogiannakis, M. Nikitakos, N. 2013b. Gaze tracking Method Use in the Satisfaction Evaluation (Matlab Environment) in Maritime Education. Information & IT Today, ISSN: 1339-147X, Vol.1, Issue 1, pp.11-18.
Papachristos, D. Alafodimos, K. Lambrou, M. 2013c. Marine e-Learning Evaluation: A Neuroscience Approach. International Journal of Marine Navigation and Safety of Sea Transportation, Volume 7, (3), Sept. 2013, DOI: 10.12716/10001.07.03.XX.
Papachristos, D. Alafodimos, K. Lambrou, M. Kalogiannakis, M. Nikitakos, N. 2013d. Sentiment Analysis in the Satisfaction Evaluation for Maritime Education. Proceeding of ICELW 2013, June 12th – 14th , New York, NY, USA.
Patton, M. Q. 1990. Qualitative Evaluation and Research Methods. CA:Sage Publications.
Petersen, E.S. Dittman, K. Lützhöft, M. 2010. Making the Phantom Real: A Case of Applied Maritime Human Factors, Proceedings of SNAME SOME 2010,http://publications.lib.chalmers.se/cpl/record/I ndex.xsql?pubid=133364 (last access 18 November 2014).
Pinker, S. and Jackendorff, R. 2005. The faculty of language: what’s special about it?, Cognition, 95, pp. 201-236.
Rayner, K. Xingshan, L. Williams, C.C. Kyle, R. C. and Arnold, W. D. 2007. “Eye Movements during Information Processing Tasks: Individual Differences and Cultural Effects,” Vision Research, vol. 47, pp. 2714-2726.
Retalis, S. (eds.), 2005. Educational Technology. The advanced internet technologies in learning service, Ath-ens:Kastaniotis Editions (in greek).
Rutten, N. Van Joolingen, W. R. Van de Veen, J. T. 2012. The learning effects of computer simulations in science education, Computers & Education 58, pp. 136-153.
Ryu, Y.S. 2005.Development of Usabilities Questionnaires for Electronic mobile Products and Decision Making Methods, Phd Thesis, Blacksburg, Virginia, USA, retrieving from http://scholar.lib.vt.edu/theses/available/etd- 08212005-234205/unrestricted/ETD_Ryu_Final.pdf (last access 19 November 2014).
Shanahan, J. Qu, Y. Wiebe, J. 2006. Computing Attitude and Affect in Text: Theory and Application, Springer.
Solomonidou, X. 2001. Modern Educational Technology. Saloniki, Kodikas (in Greek).
Tsianos, N., Lekkas, Z., Germanakos, P., Mourlas, C., Samaras, G 2009. An Experimental Assessment of the Use of Cognitive and Affective Factors in Adaptive Educational Hypermedia, IEEE Transactions on Learning Technologies, Vol. 2, No. 3, July-September 2009, pp. 249-258.
Tsoukalas, V. Papachristos, D. Mattheu, E. Tsoumas, N. 2008. Marine Engineers’ Training: Educational Assessment of Engine Room Simulators, WMU Journal of Maritime Affairs, Vol.7, No.2, pp.429-448, ISSN 1651-436X, Current Awareness Bulletin, Vol. XX-No.10, Dec. 2008, IMO Maritime Knowledge Centre, pp.7.
Tsoumas, N. Papachristos, D. Matheou, E. Tsoukalas, V. 2004. Pedagogical Evaluation of the Ship’s Engine Room Simulator, used in apprentice marine engineers’ Instruction, 1st International Conference IT, Athens.
Tullis, T. and Albert, B. 2008. Measuring the User Experience: Collecting Analysing and Presenting Usability Metrics, Morgan Kaufmann.
Torner, M. Almstrom, C. Karlsson, R. Kadefors, R. 1994. Working on a moving surface—a biomechanical analysis of musculoskeletal load due to ship motions in combination with work, Ergonomics, Vol. 37.
van Berkum, J. J. A., and de Jong, T. 1991. Instructional environments for simulations. Education & Computing, 6, 305–358.
Van Gog T, Scheiter K. 2010. Eye tracking as a tool to study and enhance multimedia learning. Learning and Instruction; 20:95-99.
Verschaffel L, De Corte E, Pauwels A. 1992. Solving compare word problems: An eye movement test of Lewis and Mayer’s consistency hypothesis. Journal of Educational Psychology; 84:85-94.
Vostanjoglou, Th. 1998. ANTILEXICON (Greek Lexicon), 2nd edition revised, Athens.
Wang, J. 2001. The current status and future aspects in formal ship safety assessment, Safety Sciences 38, pp. 19-30.
Windschitl, M., and Andre, T. 1998. Using computer simulations to enhance conceptual change: the roles of constructivist instruction and student epistemological beliefs. Journal of Research in Science Teaching, 35(2), 145–160
Citation note:
Papachristos D., Nikitakos N.: Experimental Research with Neuroscience Tool in Maritime Education and Training (MET). TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 10, No. 2, doi:10.12716/1001.10.02.17, pp. 341-349, 2016
Authors in other databases:
Dimitris Papachristos:

Other publications of authors:

File downloaded 388 times

Important: TransNav.eu cookie usage
The TransNav.eu website uses certain cookies. A cookie is a text-only string of information that the TransNav.EU website transfers to the cookie file of the browser on your computer. Cookies allow the TransNav.eu website to perform properly and remember your browsing history. Cookies also help a website to arrange content to match your preferred interests more quickly. Cookies alone cannot be used to identify you.
Akceptuję pliki cookies z tej strony