Crystallized intelligence affects hedonic and epistemic values to continue playing a game with saliency-based design

The purpose of most educational games is to generate students' interest to learn or apply their knowledge. This study designed a new type of human-computer interaction for players to "blow away" the sand shown on the smartphone screen by physically blowing into the smartphone's sound channel. A saliency model was used to examine whether crystallized intelligence (Gc) is correlated to players' experiential value and willingness to play. Data from 200 university students were collected for confirmatory factor analysis with structural equation modeling. The results revealed that Gc was an antecedent of hedonic and epistemic values, and these two types of experiential values could predict an individual's continuance intention to play. The implication of this study suggests that Gc is an essential factor in playing an App game involving object feature identification, as it encourages students to learn and to gain a variety of knowledge. Crystallized intelligence (Gc) was an antecedent of hedonic and epistemic values.Hedonic and epistemic values could predict continuance intention to play.Gc is an essential factor in playing an game involving object feature identification.

[1]  Garry Falloon,et al.  Young students using iPads: App design and content influences on their learning pathways , 2013, Comput. Educ..

[2]  Jeffrey A. Greene,et al.  Modeling and measuring epistemic cognition: A qualitative re-investigation , 2014 .

[3]  Arthur F Kramer,et al.  Selling points: What cognitive abilities are tapped by casual video games? , 2013, Acta psychologica.

[4]  J. Steenkamp,et al.  The Role of Optimum Stimulation Level in Exploratory Consumer Behavior , 1992 .

[5]  Moez Limayem,et al.  User switching of information technology: A theoretical synthesis and empirical test , 2012, Inf. Manag..

[6]  Marcel Zeelenberg,et al.  Option Attachment: When Deliberating Makes Choosing Feel Like Losing. , 2003 .

[7]  Gang Hua,et al.  Automatic salient object extraction with contextual cue and its applications to recognition and alpha matting , 2013, Pattern Recognit..

[8]  M. Corbetta,et al.  The Reorienting System of the Human Brain: From Environment to Theory of Mind , 2008, Neuron.

[9]  Gregory R. Hancock,et al.  Structural equation modeling: A second course, 2nd ed. , 2013 .

[10]  Ulrich Schroeders,et al.  On the nature of crystallized intelligence: the relationship between verbal ability and factual knowledge☆ , 2014 .

[11]  Mark D. Griffiths,et al.  The Structural Characteristics of Video Games: A Psycho-Structural Analysis , 2004, Cyberpsychology Behav. Soc. Netw..

[12]  B. Thompson,et al.  EFFECTS OF SAMPLE SIZE, ESTIMATION METHODS, AND MODEL SPECIFICATION ON STRUCTURAL EQUATION MODELING FIT INDEXES , 1999 .

[13]  Roberto Colom,et al.  Video-games: Do they require general intelligence? , 2009, Comput. Educ..

[14]  Detmar W. Straub,et al.  Effective website design for experience-influenced environments: The case of high culture museums , 2014, Inf. Manag..

[15]  L. McEvoy,et al.  Neurophysiological indices of strategy development and skill acquisition. , 1999, Brain research. Cognitive brain research.

[16]  Gregory J. Brush,et al.  Comparing the Perceived Value of Information and Entertainment Mobile Services , 2008 .

[17]  Mark Colgate,et al.  Customer Value Creation: A Practical Framework , 2007 .

[18]  J. Alba,et al.  Pleasure principles: A review of research on hedonic consumption , 2013 .

[19]  J. Cacioppo,et al.  The need for cognition. , 1982 .

[20]  Neil Salkind,et al.  Using SPSS for the MacIntosh and Windows: Analyzing and Understanding Data , 2002 .

[21]  Jitendra Malik,et al.  Shape matching and object recognition using shape contexts , 2010, 2010 3rd International Conference on Computer Science and Information Technology.

[22]  Yong Liu,et al.  Please stay with me! An empirical investigation on hedonic IS continuance model for social network games , 2013, ICIS.

[23]  Yu-Ju Chen,et al.  Using the saliency-based model to design a digital archaeological game to motivate players' intention to visit the digital archives of Taiwan's natural science museum , 2013, Comput. Educ..

[24]  P. Ackerman,et al.  Investment and intellect: a review and meta-analysis. , 2013, Psychological bulletin.

[25]  Robert W. Zmud,et al.  A Comprehensive Conceptualization of Post-Adoptive Behaviors Associated with Information Technology Enabled Work Systems , 2005, MIS Q..

[26]  Levin,et al.  Information Processing at Successive Stages of Decision Making: Need for Cognition and Inclusion-Exclusion Effects. , 2000, Organizational behavior and human decision processes.

[27]  Chris S. Hulleman,et al.  Achievement Goal Theory at the Crossroads: Old Controversies, Current Challenges, and New Directions , 2011 .

[28]  Neil Salkind,et al.  Using SPSS for Windows and Macintosh : Analyzing and Understanding Data , 2004 .

[29]  Young-Gul Kim,et al.  Extending the TAM for a World-Wide-Web context , 2000, Inf. Manag..

[30]  Georg W. Oesterdiekhoff,et al.  Was pre-modern man a child? The quintessence of the psychometric and developmental approaches , 2012 .

[31]  Chin-Lung Hsu,et al.  Consumer behavior in online game communities: A motivational factor perspective , 2007, Comput. Hum. Behav..

[32]  Edward E. Rigdon,et al.  The effect of dynamic retail experiences on experiential perceptions of value: an Internet and catalog comparison , 2002 .

[33]  Kar Yan Tam,et al.  Mobile data service fuels the desire for uniqueness , 2006, CACM.

[34]  R. Cattell,et al.  Abilities : Their Structure , Growth , and Action , 2015 .

[35]  Ian J. Deary,et al.  Intelligence and inspection time: Achievements, prospects, and problems. , 1996 .

[36]  Lazar Stankov,et al.  Age differences in the realism of confidence judgements: A calibration study using tests of fluid and crystallized intelligence , 1996 .

[37]  C. Fornell,et al.  Evaluating structural equation models with unobservable variables and measurement error. , 1981 .

[38]  Lieven De Marez,et al.  Cognitive abilities, digital games and arithmetic performance enhancement: A study comparing the effects of a math game and paper exercises , 2015, Comput. Educ..

[39]  Kamel Rouibah,et al.  Effect of management support, training, and user involvement on system usage and satisfaction in Kuwait , 2009, Ind. Manag. Data Syst..

[40]  Ian J. Deary,et al.  Simple information processing and intelligence , 2000 .

[41]  Jinwoo Kim,et al.  Why People Continue to Play Online Games: In Search of Critical Design Factors to Increase Customer Loyalty to Online Contents , 2004, Cyberpsychology Behav. Soc. Netw..

[42]  Morris B. Holbrook,et al.  Customer value and autoethnography: subjective personal introspection and the meanings of a photograph collection , 2005 .

[43]  J. Rutter,et al.  Gender dynamics and the social and spatial organization of computer gaming , 2003 .

[44]  Carsten K. W. De Dreu,et al.  Social Decision Making in Fuzzy Situations: Motivated Information Processing and Strategic Choice. , 2006 .

[45]  Yu-Ying Huang,et al.  Service Backstage Visibility and the Corresponding Perceived Values in the Process of Service Delivery , 2012 .

[46]  George R. Mangun,et al.  Right temporoparietal junction activation by a salient contextual cue facilitates target discrimination , 2011, NeuroImage.

[47]  J. Hair.  Multivariate data analysis , 1972 .

[48]  Hamdan Said,et al.  Confirmatory factor analysis (CFA) for testing validity and reliability instrument in the study of education , 2011 .

[49]  Antonia E. E. Baumeister,et al.  Cognitive ability and epistemic rationality: A study in Nigeria and Germany , 2014 .

[50]  Dong-Mo Koo,et al.  The moderating role of locus of control on the links between experiential motives and intention to play online games , 2009, Comput. Hum. Behav..

[51]  Rex B. Kline,et al.  Principles and Practice of Structural Equation Modeling , 1998 .

[52]  Alain Van Hiel,et al.  Effects of Ambiguity and Need for Closure on the Acquisition of Information , 2002 .

[53]  Mu Wu,et al.  No One Likes to Lose , 2014, J. Media Psychol. Theor. Methods Appl..

[54]  Chiao-Chen Chang,et al.  Examining users′ intention to continue using social network games: A flow experience perspective , 2013, Telematics Informatics.

[55]  M. Holbrook.  Consumer Value: A Framework for Analysis and Research , 1999 .

[56]  Anol Bhattacherjee,et al.  Understanding Information Systems Continuance: An Expectation-Confirmation Model , 2001, MIS Q..

[57]  Phillip L. Ackerman,et al.  Knowledge and Cognitive Aging , 2007 .

[58]  Wen-Bin Chiou,et al.  Psychological Motives and Online Games Addiction: ATest of Flow Theory and Humanistic Needs Theory for Taiwanese Adolescents , 2006, Cyberpsychology Behav. Soc. Netw..

[59]  Elizabeth R. Peterson,et al.  “I think I can, I think I can …”: The interrelationships among self-assessed intelligence, self-concept, self-efficacy and the personality trait intellect in university students in Scotland and New Zealand , 2007 .

[60]  Jordan Litman.  Interest and deprivation factors of epistemic curiosity , 2008 .

[61]  D. Larcker,et al.  STRUCTURAL EQUATION MODELS WITH UNOBSERVABLE VARIABLES AND MEASUREMENT ERROR , 1981 .

[62]  R. MacCallum,et al.  Power Analysis in Covariance Structure Modeling Using GFI and AGFI. , 1997, Multivariate behavioral research.

[63]  P. Mussel.  Epistemic curiosity and related constructs: Lacking evidence of discriminant validity , 2010 .

[64]  R. Cattell.  The measurement of adult intelligence. , 1943 .

[65]  E. Macaluso,et al.  Dissociation of stimulus relevance and saliency factors during shifts of visuospatial attention. , 2007, Cerebral cortex.

[66]  Torsten Schubert,et al.  Video game practice optimizes executive control skills in dual-task and task switching situations. , 2012, Acta psychologica.

[67]  P. Ackerman.  A theory of adult intellectual development: Process, personality, interests, and knowledge , 1996 .

[68]  A. Bandura.  Self-efficacy. I: V. S. Ramachandran (red.), Encyclopedia of human behavior (vol. s. ). New York: Academic Press. , 1994 .

[69]  Terri Gullickson,et al.  Encyclopedia of human behavior , 1995 .

[70]  Shamus P. Smith,et al.  Exploring the effectiveness of commercial and custom-built games for cognitive training , 2013, Comput. Hum. Behav..

[71]  S. Mulaik,et al.  EVALUATION OF GOODNESS-OF-FIT INDICES FOR STRUCTURAL EQUATION MODELS , 1989 .

[72]  Thomas J. Bouchard,et al.  The structure of human intelligence: It is verbal, perceptual, and image rotation (VPR), not fluid and crystallized , 2005 .

[73]  M. Davies,et al.  Online computer gaming: a comparison of adolescent and adult gamers. , 2004, Journal of adolescence.

[74]  P. Bentler,et al.  Cutoff criteria for fit indexes in covariance structure analysis : Conventional criteria versus new alternatives , 1999 .

[75]  Timothy C. Bates,et al.  Crystallized intelligence as a product of speed and drive for experience: the relationship of inspection time and openness to g and Gc , 2003 .

[76]  Yong Liu,et al.  Modeling hedonic is continuance through the uses and gratifications theory: An empirical study in online games , 2015, Comput. Hum. Behav..

[77]  C. S. Green,et al.  Action video game modifies visual selective attention , 2003, Nature.

[78]  Tanya J. McGill,et al.  How students and instructors using a virtual learning environment perceive the fit between technology and task , 2007, J. Comput. Assist. Learn..

[79]  Ulrich Schroeders,et al.  Age-related changes in the mean and covariance structure of fluid and crystallized intelligence in childhood and adolescence☆ , 2015 .