A novel sensor-based methodology for learner's motivation analysis in game-based learning

Interacting with Computers

Volumn 26, Issue 4, 2014, Pages 305-320

  Ghergulescu, Ioana ^a   Muntean, Cristina Hava ^a  

^a NATIONAL COLLEGE OF IRELAND   (Ireland)

Author keywords

cognitive science; electroencephalography; game based learning; motivation assessment; novel interaction paradigms; user studies

Indexed keywords

ELECTROENCEPHALOGRAPHY; ELECTROPHYSIOLOGY; MOTIVATION; SURVEYS;

COGNITIVE SCIENCE; GAME-BASED LEARNING; INTERACTION PARADIGM; MOTIVATION ASSESSMENTS; USER STUDY;

LEARNING SYSTEMS;

EID: 84901436399     PISSN: 09535438     EISSN: None     Source Type: Journal    
DOI: 10.1093/iwc/iwu013     Document Type: Article

References (58)

1. Bandura, A. (1994). Self-Efficacy. In Ra machandran,V.S. (ed.), Encyclopedia of Human Behavior. Academic Press Inc., San Diego, California. http://www.uky.edu/eushe2/Bandura/Bandura1994EHB.pdf.
2. Bandura, A. (2006). Guide for Constructing Self-Efficacy Scales. In Pajares, F. and Urdan, T.C. (eds) Self-Efficacy Beliefs of Adolescents, Vol. 5, pp. 307-337. Information Age Publishing. http://books.google.com/bookshl= en&lr=&id=Cj97DKKRE7AC &oi=fnd&pg=PA307&dq=Guide+for+C onstructing+Self-efficacy +Scales&ots=cF-zVtHm9&sig=oduipbAiFyz- PCMb4Z2aN9- EwMQ.
3. Bandura A., Caprara G.V., Barbaranelli C., Gerbino M., Pastorelli C. 2003. Role of affective self-regulatory effica cy in diverse spheres of psychosocial functioning Child Dev. 74 769-782. http://onlinelibrary.wiley.com/ doi/10.1111/1467-8624.00567/abstract. (Pubitemid 37244639)
4. Belle, A., Hobson, R. and Najarian, K. (2011). A physio logical signal processing system for optimal engagement and attention detection. In 2011 IEEE Int. Conf. on Bioinformatics and Biomedicine Workshops (BIBMW), Atlanta, Georgia, USA, pp. 555-561. doi:10.1109/BIBMW.2011.6112429.
5. Betsch, T., Plessner, H., Schwieren, C. and Gütig, R. (2001). I like it but I don?t know why: A value-account approach to implicit attitude formation. Pers. Soc. Psychol. Bull., 27, 242-253. http://psp.sag epub.com/content/27/2/242.short.
6. Bixler, B. (2006). Motivation and its Relationship to the Design of Educational Games. Technical Report, New Media Consortium. http://hrast.pef.uni- lj.si/docs/research/Serious%20games/Moti vation%20in%20Educ%20Games.pdf.
7. Bonnefond, A., Doignon-Camus, N., Hoeft, A. and Dufour,A. (2011). Impact of motivation on cognitive control in the context of vigilance lowering: An ERP study. Brain Cogn., 77, 46 4-471. http://www.sciencedirect.com/science/article/ pii/S0278262611001370.
8. Cernea, D., Kerren, A. and Ebert, A. (2011a). Detecting Insight and Emotion in Visualization Applications with a Commercial EEG Headset. In P roc. SIGRAD 2011 Conf. on Evaluations of Graphics and Visualization. http://www.ep.liu.se/ecp/065/008/ecp11065008.pdf.
9. Cernea, D., Olech, P.-S., Ebert, A. and Kerren, A. (2011b). EEGBased Measurement of Subjective Parameters in Evaluations. In Stephanidis, C. (ed.), HCI International 2011-Posters? Extended Abstracts, Communications in Computer and Information Science, Vol. 174, pp. 279-283. Springer, Berlin, Heidelberg. http: //www.springerlink.com/content/u9058000231rq020/abstract/.
10. Cernea, D., Olech, P.-S., Ebert, A. and Kerren, A. (2012). Measuring Subjectivity. Künstliche Intelligenz, 26, 177-182. http://www.springerlink. com/content/j102g8gk50p96762/abstract/.
11. Chanel, G., Rebetez, C., Bé trancourt, M. and Pun, T. (2008). Boredom, Engagement and Anxiety as Indicators for Adaptation to Difficulty in Games. MindTrek?08, pp. 13-17 . ACM, New York, NY, USA. http://doi.acm.org/10. 1145/1457199.1457203.
12. Chanel, G., Rebetez, C., Betrancourt, M. and Pun, T. (2011). Emotion assessment from physiological signals for adaptation of game difficulty. IEEE Trans. Syst. Man Cybern. Part A: Syst. Hum., 41, 1052-1063.
13. Chaouachi, M. and Frasson, C. (2010). Exploring the Relationship between Learner EEG Mental Engagement and Affect. In Aleven, V., Kay, J. and Mos tow, J. (eds) Intelligent Tutoring Systems, Lecture Notes in Computer Science, Vol. 6095, pp. 291-293.Springer, Berlin/Heidelberg. http://www.springerlink.com/ content/n5345157m178r258/abstract/.
14. Chaouachi, M., Chal foun, P., Jraidi, I. and Frasson, C. (2010). Affect and mental engagement: Towards adaptability for intelligent systems. http://citeseerx.ist.psu.edu/viewdoc/downloaddoi=10.1.1.161.7222&rep= rep1&type=pdf.
15. Chen, Z.-H. and Chan, T.-W. (2008). Learning by Substitutive Competition: Nurturing My-Pet for Game Competition Based on Open Learner Model. In 2008 2nd IEEE Int. Conf. on Digital Games and Intelligent Toys Based Educat ion, Banff, BC, Canada, pp. 124-131. doi:10.1109/DIGITEL.2008.36.
16. Cowley, B., Charles, D., Black, M. and Hickey, R. (2008). Toward an understanding of flow in video games. Comput. Entertain., 6, 20:1-20:27. http://doi.acm.org/10.1145/1371216.1371223.
17. Csikszentmihalyi, M. (2000). Beyond Boredom and Anxiety. Jossey-Bass, San Francisco, CA, USA. http://www.amazon.com/dp/0787951404.
18. Derbali, L. and Frasson, C. (2010). Prediction of Players Motivational States Using Electrophysiological Measures during Serious Game Play. In 2010 IEEE 10th Int. Conf. on Advanced Learning Technologies (ICALT), Sousse, Tunisia, pp. 498-502. doi:10.1109/ICALT.2010.143.
19. Derbali, L. and Frasson, C. (2011). Physiological Evaluation of Attention Getting Strategies During Serious Game Play. In The 15th Int. Conf. on Artificial Intelligence in Education, pp. 447-449. Springer, Berlin, Heidelberg, Auckland, NewZealand. http://www.springerlink.com/index/UK4R5R2R527 N7415.pdf.
20. Easterday, M., Aleven, V., Scheines, R. and Carver, S. (2011). Using Tutors to Improve Educational Games. In Artificial Intelligence in Education, pp. 63-71. http://www.springerlink.com/index/P1321423258N254P.pdf.
21. Emotiv (2013). Emotiv-EEG System-Electroencephalography. http://www.emotiv.com/.
22. Fairclough, S.H., Gilleade, K., Ewing, K.C. and Roberts, J. (2010). Capturing user engagement via psychophysiology: Measures and mechanisms for biocybernetic adaptation. Int. J. Autonomous Adaptive Commun. Syst. http://web.mac .com/shfairclough/Step hen-Fairclough-Research/Publications- physiological-computing -mental-effort-stephen-fairclough-files/IJAACS-2010-Fair clough.pdf.
23. Ghergulescu, I. (2013). Automatic Non-Disturbing Motivation Monitoring in Game-based E-learning through Player Behaviour and EEG. PhD Thesis, National College of Ireland, Dublin, Ireland.
24. Ghergulescu, I. and Muntean, C.H. (2011). Learner Motivation Assessment with -e-Adventure- G ame Platform. In World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2011, pp. 1212-1221. AACE, Chesapeake, VA. http://editlib.org/p/38880.
25. In Ifenthaler D., Eseryel, D. and Ge, X. (eds), Assessment in Game-Based Learning Springer, New York, NY.
26. Ghinea, G. and Thomas, J. (1999). An Approach Towards Mapping Quality of Perception to Quality of Service in Multimedia Communications. In 1999 IEEE 3rd Workshop on Multi media Signal Processing, Copenhagen, Denmark, pp. 497-501. doi:10.1109/MMSP.1999.793898.
27. Gonzalez-Sanchez, J., Chavez-Echeagaray, M.E., Atkinson, R. and Burleson, W. (2011). ABE: An Agent-Based Software Architec ture for a Multimodal Emotion Recognition Framework. In 2011 9th Working IEEE/IFIP Conf. on Software Architecture (WICSA), Boulder, CO, USA, pp. 187-193. doi:10.1109/WICSA.2011.32.
28. Harmon-Jones, E., Gable, P.A . and Price, T.F. (2011). Leaning embodies desire: Evidence that leaning forward increases relative left frontal cortical activation to appetitive stimuli. Biol. Psychol., 87, 311-313. http://www.sciencedirect.com/science/article/ pii/S0301051111000810.
29. Hwang, G.-J. andWu, P.-H. (2012).Advancements and trends in digital game-based learning research: A review of publications in selected journals from 2001 to 2010. Br. J. Educ. Technol., 43, E6-E10. http://onlinelibrary.wiley. com/doi/10.1111/j.1467-8535.2011.01242.x/abstract.
30. IJsselsteijn, W., De Kort, Y., Poels, K., Jurgelionis, A. and Bellotti, F. (2007). Characterising and Measuring User Experiences in Digital Games. In Proc. ACE Conf. ? 07. Salzburg, Austria. http://lrcm.com.umontreal.ca/Dufresne/ COM6535/IJsselsteijn% 20et%20al%202007%20Characterising%20and%20Measuring %20User%20Experiences%20ACE%202007%20workshop.pdf.
31. IMI ( 2008). Intrinsic Motivation Inventory Description. http://www.psych.rochester.edu/SDT/measures/IMI-description.php.
32. Inventado, P.S., Legaspi, R., Suarez, M. and Numao, M. (2011). Predicting student emotions r esulting from appraisal of ITS feedback. Res. Pract. Technol. Enhanced Learning, 6, 107-133. http://www.apsce.net/RPTEL/ RPTEL2011JulIssue-Article3- pp107-133.pdf.
33. Karapanos, E., Martens, J.-B. and Hassenzahl, M. (2010). On the Retrospective Assessment of Users? Experiences Over Time: Memory or Actuality In CHI ?10 Extended Abstracts on Human Factors in Computing Systems, CHI EA? 10, pp. 4075-4080.ACM, NewYork, NY, USA. http://doi.acm.org/10.1145/1753846.1754105.
34. Karimi, A. and Lim, Y.P. (2010). Children, Engagement and Enjoyment in Digital Narrative. In Proc. of Ascilite, pp. 475-483. http://cms.ascilite.org. au/conferences/sydney10/procs/Karimifull.pdf. Keller, J.M. (1987). Development and use of the ARCS model of instructional design. J. Instr. Dev., 10, 2-10. http://link.springer. com/article/10.1007/BF02905780.
35. Keller, J.M. (1987). Development and use of the ARCS model of instructional design. J. Instr. Dev., 10, 2-10. http://link.springer. com/article/10.1007/BF02905780
36. Kleih, S., Nijboer, F., Halder, S. and Kübler, A. (2010). Motivation modulates the P300 amplitude during brain-computer interface use. Clin. Neurophys., 121, 1023- 1031. http://www.sciencedirect.com/science/article/pii/ S13882457100 00775.
37. Kuber, R. and Wright, F.P. (2013). Augmenting the instant messaging experience through the use of BCI and gestural technologies. Int. J. Hum.-Comput. Interact., 29, 178-191. http://www.tandfonline.com/doi/abs/10.1080/ 1044 7318.2012.702635.
38. Liu, M., Horton, L., Olmanson, J. and Toprac, P. (2011). A study of learning and motivation in a new media enriched environment for middle school science. Educ. Technol. Res. Dev., 59, 249- 265. http://link.springer.com/ article/10.1007/s11423-011-9192-7.
39. Lopez-Duran, N.L., Nusslock, R., George, C. and Kovacs, M. (2012). Frontal EEG asymmetry moderates the effects of stressful life events on internalizing symptoms in children at familial risk for depression. Psychophysiology. http://onlinelibrary. wiley.com/doi/10.1111/j.1469-8986.2011. 01332.x/full.
40. Mampusti, E.T., Ng, J.S., Quinto, J.J.I., Teng, G.L., Suarez, M.T.C. and Trogo, R.S. (2011). Measuring Academic Affective States of Students via Brainwave Signals. In 2011 3rd Int. Conf. on Knowledge and Systems Engineering (KSE), Hanoi, Vietnam, pp. 226-231. doi:10.1109/KS E.2011.43.
41. McQuiggan, S.W., Mott, B.W. and Lester, J.C. (2007). Modeling self-efficacy in intelligent tutoring systems: An inductive approach. User Model. User-Adapt. Interact., 18, 81-123. http://www.sprin gerlink.com/index/10. 1007/s11257-007-9040-y.
42. Miller, L.M., Chang, C.-I., Wang, S., Beier, M.E. and Klisch, Y. (2011). Learning and motivational impacts of a multimedia science game. Comput. Educ., 57, 1425-1 433. http://www.sciencedirect.com/science/article/pii/ S0360131511000339.
43. Moreno-Ger, P. (2012). Fire protocol. http://e-adventure.e-ucm.es/course/ view.phpid=29.
44. Nash, K., Mcgregor, I. and Inzlicht, M . (2010). Line bisection as a neural marker of approach motivation. Psychophysiology, 47, 979-983. http://onlinelibrary.wiley.com/doi/10.1111/j.1469-8986.2010.00999.x/abstract.
45. Pope, A.T., Bogart, E.H. and Bartolome, D.S. (1995). Biocybernetic system evaluates indices of operator engagement in automated task. Biol. Psychol., 40, 187-195. http://www.sciencedirect. com/science/article/pii/0301051195051163.
46. Prinzel L. J., Freeman F.G., Scerbo M.W., Mikulka P.J., Pope A.T. 2000 A closed-loop system for examining psychophysiological measures for adaptive task allocation Int. J. Aviat. Psychol. 10. 393-410. http://www.tandfonline.com/doi/ abs/10.1207/S15327108IJAP1004-6
47. Rebolledo-Mendez, G., de Freitas, S., Rojano-Caceres, J.R. and Garcia-Gaona, A.R. (2010). An Empirical Examination of the Relation Between Attention and Motivation in Computer-Based Education: A Modeling Approach. In Twenty-Third International Florida Artificial Intelligence Research Society Conference. Daytona Beach, FL, AAAI Press. http://www.aaai.org/ocs/index.php/ FLAIRS/2010/paper/view/1304.
48. Renshaw, T., Stevens, R. and Denton, P.D. (2009). Towards understanding engagement in games: An eye-tracking study. Horizon, 17, 408-420. http://www.emeraldinsight.com/journals.htmarticleid=1817161.
49. Ryan, R.M. and Deci, E.L. (2000 a ). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemp. Educ. Psychol., 25, 54-67. http://www.sciencedirect.com/science/article/pii/S0361476X99910202.
50. Ryan, R.M. and Deci, E.L. (2000 b ). Self-determination theory and the facilitation of intrinsic motivation, social development, and wellbeing. Am. Psychol., 55, 68-78.
51. Shen, L., Wang, M. and Shen, R. (2009). Affective e-learning: Using ?emotional? data to improve learning in pervasive learning environment. Educ. Technol. Soc., 12, 176-189. http://www.ifets.info/others/download-pdf.phpj-id= 43&a-id=939.
52. Stamps, K. and Hamam, Y. (2010). Towards Inexpensive BCI Control for Wheelchair Navigation in the Enabled Environment-A Hardware Survey. In Yao, Y., Sun, R., Poggio, T., Liu, J., Zhong, N. and Huang, J. (eds) Brain Informatics, Lec ture Notes in Computer Science,Vol. 6334, pp. 336-345. Springer, Berlin/Heidelberg. http://www.springerlink.com/content/l683157470640344/ abstract/.
53. Syufagi, M.A., Hariadi, M. and Purnomo, M.H. (2013). Petr i net model for serious games based on motivation behavior classification. Int. J. Comput. Games Technol., 2013, 1-12. http://www.hindawi.com/journals/ijcgt/2013/851287/ abs/.
54. Torrente, J., del Blanco, A., Marchiori, E.J., Moreno-Ger, P. and Fernandez-Manjon, B. (2010). e-Adventure: Introducing Educational Games in the Learning Process. In 2010 IEEE Education Engineering (EDUCON), Madrid, Spain, pp. 1121-1126. doi:10.1109/EDUCON .2010.5493056.
55. Tüzü n, H., Ylmaz-Soylu, M., Karaku̧s, T., Inal, Y. and Kzlkaya, G. (2009). The effects of computer games on primary school students? achievement and motivation in geography learning. Comput. Educ., 52, 68-77. http://www.sciencedirect.com/science/article/pii/S0360131508000985.
56. Vansteenkiste, M., Lens, W. and Deci, E.L. (2006). Intrinsic versus extrinsic goal contents in self-determination theory: Another look a t the quality of academic motivation. Educ. Psychol., 41, 19-31. http://www. tandfonline.com/doi/abs/10.1207/s153269 85ep4101-4. (Pubitemid 43500304)
57. Vos, N., van der Meijden, H. and Denessen, E. (2011). Effects of constructing vers us playing an educational game on student motivation and deep learning strategy use. Comput. Educ., 56, 127-137. http://www.sciencedirect.com/ science/article/pii/S0360131510002344.
58. Weiss, P.L.T., Gal, E., Eden, S., Zancanaro, M. and Telch, F. (2011). Usability of a Multi-Touch Tabletop Surface to Enhance Social CompetenceTraining for Children withAutism Spectrum Disorder. In Proc. Chais Conf. on Instructional Technologies Research 2011: Learning in the Technological Era, pp. 71-78. http://chais.openu.ac.il/research-center/chais2011/download/weiss-92- eng.pdf.