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  • 1.
    Ekanayake, Hiran B.
    et al.
    Stockholm University, Forum 100, 164 40 Kista, Sweden / University of Colombo, School of Computing, 35 Reid Avenue, 00700 Colombo 7, Western Province, Sri Lanka.
    Backlund, Per
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Ziemke, Tom
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Ramberg, Robert
    Stockholm University, Forum 100, 164 40 Kista, Sweden.
    Hewagamage, Kamalanath P.
    University of Colombo, School of Computing, 35 Reid Avenue, 00700 Colombo 7, Western Province, Sri Lanka.
    Lebram, Mikael
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Comparing expert driving behavior in real world and simulator contexts2013In: International Journal of Computer Games Technology, ISSN 1687-7047, E-ISSN 1687-7055, article id 891431Article in journal (Refereed)
    Abstract [en]

    Computer games are increasingly used for purposes beyond mere entertainment, and current hi-tech simulators can provide quite, naturalistic contexts for purposes such as traffic education. One of the critical concerns in this area is the validity or transferability of acquired skills from a simulator to the real world context. In this paper, we present our work in which we compared driving in the real world with that in the simulator at two levels, that is, by using performance measures alone, and by combining psychophysiological measures with performance measures. For our study, we gathered data using questionnaires as well as by logging vehicle dynamics, environmental conditions, video data, and users' psychophysiological measurements. For the analysis, we used several novel approaches such as scatter plots to visualize driving tasks of different contexts and to obtain vigilance estimators from electroencephalographic (EEG) data in order to obtain important results about the differences between the driving in the two contexts. Our belief is that both experimental procedures and findings of our experiment are very important to the field of serious games concerning how to evaluate the fitness of driving simulators and measure driving performance. © 2013 Hiran B. Ekanayake et al.

  • 2.
    Ekanayake, Hiran B.
    et al.
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre. Stockholm University, Sweden & Department of Computation and Intelligent Systems, University of Colombo School of Computing, Colombo, Sri Lanka.
    Fors, Uno
    Department of Computer and Systems Sciences, Stockholm University, Stockholm, Sweden.
    Ramberg, Robert
    Department of Computer and Systems Sciences, Stockholm University, Stockholm, Sweden.
    Ziemke, Tom
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Backlund, Per
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Hewagamage, Kamalanath P.
    University of Colombo School of Computing, Colombo, Sri Lanka.
    Affective Realism of Animated Films in the Development of Simulation-Based Tutoring Systems2013In: International Journal of Distance Education Technologies, ISSN 1539-3100, E-ISSN 1539-3119, Vol. 11, no 2, p. 96-109Article in journal (Refereed)
    Abstract [en]

    This paper presents a study focused on comparing real actors based scenarios and animated characters based scenarios with respect to their similarity in evoking psychophysiological activity for certain events by measuring galvanic skin response (GSR). In the experiment, one group (n=11) watched the real actors’ film whereas another group (n=7) watched the animated film, which had the same story and dialogue as the real actors’ film. The results have shown that there is no significant difference in the skin conductance response (SCR) scores between the two groups; however, responses significantly differ when SCR amplitudes are taken into account. Moreover, Pearson’s correlation reported as high as over 80% correlation between the two groups’ SCRs for certain time intervals. The authors believe that this finding is of general importance for the domain of simulation-based tutoring systems in development of and decisions regarding use of animated characters based scenarios.

  • 3.
    Ekanayake, Hiran
    et al.
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre. Stockholm University, Kista, Sweden / School of Computing, University of Colombo, Colombo, Sri Lanka.
    Backlund, Per
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Ziemke, Tom
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Ramberg, Robert
    Stockholm University, Kista, Sweden.
    Hewagamage, Kamalanath
    School of Computing, University of Colombo, Colombo, Sri Lanka.
    Assessing Performance Competence in Training Games2011In: Affective Computing and Intelligent Interaction: Fourth International Conference, ACII 2011, Memphis, TN, USA, October 9–12, 2011, Proceedings, Part II / [ed] Sidney D’Mello, Arthur Graesser, Björn Schuller, Jean-Claude Martin, Springer Berlin/Heidelberg, 2011, p. 518-527Conference paper (Refereed)
    Abstract [en]

    In-process assessment of trainee learners in game-based simulators is a challenging activity. This typically involves human instructor time and cost, and does not scale to the one tutor per learner vision of computer-based learning. Moreover, evaluation from a human instructor is often subjective and comparisons between learners are not accurate. Therefore, in this paper, we propose an automated, formula-driven quantitative evaluation method for assessing performance competence in serious training games. Our proposed method has been empirically validated in a game-based driving simulator using 7 subjects and 13 sessions, and accuracy up to 90.25% has been achieved when compared to an existing qualitative method. We believe that by incorporating quantitative evaluation methods like these future training games could be enriched with more meaningful feedback and adaptive game-play so as to better monitor and support player motivation, engagement and learning performance.

  • 4.
    Ekanayake, Hiran
    et al.
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Backlund, Per
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Ziemke, Tom
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Ramberg, Robert
    Stockholm University, Sweden.
    Hewagamage, Kamalanath
    University of Colombo School of Computing, Sri Lanka.
    Game Interaction State Graphs for Evaluation of User Engagement in Explorative and Experience-based Training Games2010In: 2010 International Conference on Advances in ICT for Emerging Regions (ICTer 2010), IEEE conference proceedings, 2010, p. 40-44Conference paper (Refereed)
    Abstract [en]

    There is an increasing interest to use computer games for non-traditional education, such as for training purposes. For training education, simulators are considered as offering more realistic learning environments to experience situations that are similar to real world. This type of learning is more beneficial for practicing critical situations which are difficult or impossible in real world training, for instance experience the consequences of unsafe driving. However, the effectiveness of simulation-based learning of this nature is dependent upon the learner’s engagement and explorative behaviour. Most current learner evaluation systems are unable to capture this type of learning. Therefore, in this paper we introduce the concept of game interaction state graphs (GISGs) to capture the engagement in explorative and experience-based training tasks. These graphs are constructed based on rules which capture psychologically significant learner behaviours and situations. Simple variables reflecting game state and learner’s controller actions provide the ingredients to the rules. This approach eliminates the complexity involved with other similar approaches, such as constructing a full-fledged cognitive model for the learner. GISGs, at minimum, can be used to evaluate the explorative behaviour, the training performance and personal preferences of a learner.

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