Flow experience and continuance intention toward online learning: An integrated framework

This study integrated the person-artefact-task model (PAT) and value-satisfactionbehavioral intention (V-S-BI) model to examine factors influencing students getting into positive and optimal flow experience in online learning, and flow impacts on students’ continuance intention toward learning online. Results showed that telepresence was a more significant factor getting students into flow experience than clear goals on task, balance between challenges and skills of the task, and perceived ease of use. Concentration on task at hand was found to be the most influential factor of the flow experience, while sense of control was the weakest one. Although flow had a direct impact on satisfaction, the indirect impacts through utilitarian value and hedonic value were stronger. The positive relationship between satisfaction and continuance intention was confirmed in this study. The findings of this study have significant theoretical and practical implications to both researchers and practitioners.

[1]  Susan A. Jackson,et al.  Athletes in flow: A qualitative investigation of flow states in elite figure skaters , 1992 .

[2]  Kirk L. Wakefield,et al.  Can A Retail Web Site be Social? , 2007 .

[3]  VenkateshViswanath Determinants of Perceived Ease of Use , 2000 .

[4]  R. Oliver Satisfaction: A Behavioral Perspective On The Consumer , 1996 .

[5]  Dennis L. Hoffman,et al.  Marketing in Hypermedia Computer-Mediated Environments : Conceptual Foundations 1 ) , 1998 .

[6]  Frank Biocca,et al.  Telepresence via Television: Two Dimensions of Telepresence May Have Different Connections to Memory and Persuasion , 2006, J. Comput. Mediat. Commun..

[7]  Wynne W. Chin,et al.  Extending the technology acceptance model: the influence of perceived user resources , 2001, DATB.

[8]  Ji-Hye Park,et al.  Factors Influencing Adult Learners' Decision to Drop Out or Persist in Online Learning , 2009, J. Educ. Technol. Soc..

[9]  Gian Luca Marzocchi,et al.  Hierarchical representation of satisfactory consumer service experience , 2003 .

[10]  R. B. Woodruff,et al.  Customer value: The next source for competitive advantage , 1997 .

[11]  William R. Darden,et al.  Work and/or Fun: Measuring Hedonic and Utilitarian Shopping Value , 1994 .

[12]  Fred D. Davis Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[13]  David Gefen,et al.  Structural Equation Modeling Techniques and Regression: Guidelines for Research Practice , 2000 .

[14]  Rolf T. Wigand,et al.  Exploring Web users' optimal flow experiences , 2000, Inf. Technol. People.

[15]  Soung Hie Kim,et al.  ERP training with a web-based electronic learning system: The flow theory perspective , 2007, Int. J. Hum. Comput. Stud..

[16]  Steve Howard,et al.  The ebb and flow of online learning , 2005, Comput. Hum. Behav..

[17]  Jeffrey Sam Siekpe,et al.  AN EXAMINATION OF THE MULTIDIMENSIONALITY OF FLOW CONSTRUCT IN A COMPUTER-MEDIATED ENVIRONMENT , 2005 .

[18]  V. Zeithaml,et al.  A Dynamic Process Model of Service Quality: From Expectations to Behavioral Intentions , 1993 .

[19]  Namin Shin,et al.  Online learner's 'flow' experience: an empirical study , 2006, Br. J. Educ. Technol..

[20]  Sang M. Lee,et al.  The Impact of Flow on Online Consumer Behavior , 2010, J. Comput. Inf. Syst..

[21]  Elsevier Sdol International Journal of Human-Computer Studies , 2009 .

[22]  M. Csíkszentmihályi Beyond boredom and anxiety , 1975 .

[23]  Zhilin Yang,et al.  Customer perceived value, satisfaction, and loyalty: The role of switching costs , 2004 .

[24]  Jeffrey J. Martin,et al.  An Exploratory Study of Flow and Motivation in Theater Actors , 2002 .

[25]  Wynne W. Chin Issues and Opinion on Structural Equation Modeling by , 2009 .

[26]  V. Zeithaml Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence: , 1988 .

[27]  Susan Wiedenbeck,et al.  The mediating effects of intrinsic motivation, ease of use and usefulness perceptions on performance in first-time and subsequent computer users , 2001, Interact. Comput..

[28]  Udo Konradt,et al.  Flow experience and positive affect during hypermedia learning , 2003, Br. J. Educ. Technol..

[29]  David Piggott,et al.  A systematic review of the experience, occurrence, and controllability of flow states in elite sport , 2012 .

[30]  Hsiang Chen,et al.  Flow on the net-detecting Web users' positive affects and their flow states , 2006, Comput. Hum. Behav..

[31]  L. Liao A Flow Theory Perspective on Learner Motivation and Behavior in Distance Education , 2006 .

[32]  Szu-Yuan Sun,et al.  An empirical analysis of the antecedents of web-based learning continuance , 2007, Comput. Educ..

[33]  Jari Salo,et al.  Hedonic and Utilitarian Search for Electronic Word-of-Mouth , 2012, 2012 45th Hawaii International Conference on System Sciences.

[34]  Anol Bhattacherjee,et al.  An empirical analysis of the antecedents of electronic commerce service continuance , 2001, Decis. Support Syst..

[35]  F. Nah,et al.  Enhancing%' or paper_id like 'brand equity through flow and telepresence: a comparison of 2D and 3D virtual worlds , 2011 .

[36]  Ephraim R. McLean,et al.  The DeLone and McLean Model of Information Systems Success: A Ten-Year Update , 2003, J. Manag. Inf. Syst..

[37]  Tsung-Hsien Kuo,et al.  How can one amplify the effect of e-learning? An examination of high-tech employees' computer attitude and flow experience , 2010, Comput. Hum. Behav..

[38]  Yongxia Skadberg,et al.  Visitors' flow experience while browsing a Web site: its measurement, contributing factors and consequences , 2004, Comput. Hum. Behav..

[39]  G. Moneta The Flow Model of Intrinsic Motivation in Chinese: Cultural and Personal Moderators , 2004 .

[40]  M. Csíkszentmihályi The flow experience and its significance for human psychology. , 1988 .

[41]  S. Deshpande,et al.  Task Characteristics and the Experience of Optimal Flow in Human—Computer Interaction , 1994 .

[42]  J. Webster,et al.  The Dimensionality and Correlates of Flow in Human-Computer Interactions. , 1993 .

[43]  Ping Zhang,et al.  Flow in Computer-Mediated Environments: Promises and Challenges , 2005, Commun. Assoc. Inf. Syst..

[44]  K. Seltman Marketing for management. , 2004, Marketing health services.

[45]  Fiona Fui-Hoon Nah,et al.  Enhancing Brand Equity Through Flow and Telepresence: A Comparison of 2D and 3D Virtual Worlds , 2011, MIS Q..

[46]  Elena Karahanna,et al.  Time Flies When You're Having Fun: Cognitive Absorption and Beliefs About Information Technology Usage , 2000, MIS Q..

[47]  Gavin McArdle,et al.  Virtual reality for collaborative e-learning , 2008, Comput. Educ..

[48]  Marios Koufaris,et al.  Applying the Technology Acceptance Model and Flow Theory to Online Consumer Behavior , 2002, Inf. Syst. Res..

[49]  Charlie C. Chen,et al.  An Integrative Model to Predict the Continuance Use of Electronic Learning Systems: Hints for Teaching , 2006 .

[50]  G. Piessen,et al.  Indications de la chirurgie digestive et endocrinienne pratiquée en ambulatoire chez l’adulte ☆ ☆☆ , 2011 .

[51]  Rolf T. Wigand,et al.  Optimal experience of Web activities , 1999 .

[52]  S. Green,et al.  The effects of three social decision schemes on decision group process , 1980 .

[53]  Jonathan Steuer,et al.  Defining virtual reality: dimensions determining telepresence , 1992 .

[54]  Shu-Sheng Liaw,et al.  Investigating learners' attitudes toward virtual reality learning environments: Based on a constructivist approach , 2010, Comput. Educ..

[55]  Raafat George Saadé,et al.  The impact of cognitive absorption on perceived usefulness and perceived ease of use in on-line learning: an extension of the technology acceptance model , 2005, Inf. Manag..

[56]  Shu-Sheng Liaw,et al.  Investigating students' perceived satisfaction, behavioral intention, and effectiveness of e-learning: A case study of the Blackboard system , 2008, Comput. Educ..

[57]  C. Fornell,et al.  Evaluating Structural Equation Models with Unobservable Variables and Measurement Error , 1981 .

[58]  Susan M. Keaveney,et al.  Customer Switching Behavior in Service Industries: An Exploratory Study , 1995 .

[59]  I. Ajzen,et al.  Understanding Attitudes and Predicting Social Behavior , 1980 .

[60]  Jawaid A. Ghani,et al.  The Experience Of Flow In Computer-Mediated And In Face-To-Face Groups , 1991, ICIS.

[61]  Wynne W. Chin The partial least squares approach for structural equation modeling. , 1998 .

[62]  Donna L. Hoffman,et al.  Flow Online: Lessons Learned and Future Prospects , 2009 .

[63]  Philip H. Mirvis Flow: The Psychology of Optimal Experience , 1991 .

[64]  Marshall Scott Poole,et al.  Antecedents of flow in online shopping: a test of alternative models , 2009, Inf. Syst. J..

[65]  R. Batra,et al.  Measuring the hedonic and utilitarian sources of consumer attitudes , 1991 .

[66]  Murugan Anandarajan,et al.  Experiencing flow with instant messaging and its facilitating role on creative behaviors , 2010, Comput. Hum. Behav..

[67]  Bartholomäus Wissmath,et al.  Playing online games against computer- vs. human-controlled opponents: Effects on presence, flow, and enjoyment , 2008, Comput. Hum. Behav..

[68]  M. Holbrook,et al.  The value of value: Further excursions on the meaning and role of customer value , 2011 .

[69]  Charles D. Barrett Understanding Attitudes and Predicting Social Behavior , 1980 .

[70]  A. Parasuraman,et al.  The Behavioral Consequences of Service Quality , 1996 .

[71]  M. Csíkszentmihályi Flow. The Psychology of Optimal Experience. New York (HarperPerennial) 1990. , 1990 .

[72]  M. Csíkszentmihályi,et al.  Optimal experience in work and leisure. , 1989, Journal of personality and social psychology.

[73]  George P. Schell,et al.  Universities marginalize online courses , 2004, CACM.

[74]  Donna L. Hoffman,et al.  Measuring the Customer Experience in Online Environments: A Structural Modeling Approach , 2000 .

[75]  Frank Biocca,et al.  The Cyborg's Dilemma: Progressive Embodiment in Virtual Environments , 2006, J. Comput. Mediat. Commun..

[76]  Allan Bird,et al.  ORGANIZATIONAL DEMOGRAPHY IN JAPANESE FIRMS: GROUP HETEROGENEITY, INDIVIDUAL DISSIMILARITY, AND TOP MANAGEMENT TEAM TURNOVER , 1993 .

[77]  Kieran Mathieson,et al.  Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior , 1991, Inf. Syst. Res..

[78]  Laurie P. Dringus,et al.  Temporal transitions in participation flow in an asynchronous discussion forum , 2010, Comput. Educ..

[79]  G. Stein,et al.  Examining flow experiences in sport contexts: Conceptual issues and methodological concerns , 1992 .

[80]  Glenn J. Browne,et al.  The Role of Need for Cognition and Mood in Online Flow Experience , 2006, J. Comput. Inf. Syst..

[81]  Ping Zhang,et al.  A person-artefact-task (PAT) model of flow antecedents in computer-mediated environments , 2003, Int. J. Hum. Comput. Stud..

[82]  Bong Gyou Lee,et al.  Measuring the Quality of the u-Learning Service Using the Zone of Tolerance SERVQUAL , 2010 .

[83]  H. Marsh,et al.  Development and Validation of a Scale to Measure Optimal Experience: The Flow State Scale , 1996 .

[84]  M. Bassi,et al.  Psychological Selection and Optimal Experience Across Cultures: Social Empowerment through Personal Growth , 2010 .

[85]  Matthew Lombard,et al.  At the Heart of It All: The Concept of Presence , 2006 .