Investigating e-learning system usage outcomes in the university context

This paper investigates the outcomes of e-learning systems adoption and use by conceptualizing three e-learning systems adoption outcome constructs namely perceived learning assistance, perceived community building assistance and perceived academic performance. Utilizing these constructs, the paper proposes a research model for assessing the possible outcomes of e-learning systems adoption and use. The study collected longitudinal survey data from 249 university students participating in hybrid courses using a popular learning management system, Moodle. Partial least squares (PLS) approach was then used to test the research model. The findings suggest that beliefs about perceived usefulness and perceived ease of use, and how an e-learning system is used influence students' perceived learning assistance and perceived community building assistance. In turn, perceived learning assistance and perceived community building assistance influence the students' perceived academic performance.

[1]  Alan R. Dennis,et al.  Rethinking media richness: towards a theory of media synchronicity , 1999, Proceedings of the 32nd Annual Hawaii International Conference on Systems Sciences. 1999. HICSS-32. Abstracts and CD-ROM of Full Papers.

[2]  Cliff Lampe,et al.  The Benefits of Facebook "Friends: " Social Capital and College Students' Use of Online Social Network Sites , 2007, J. Comput. Mediat. Commun..

[3]  Steven Hornik,et al.  An empirical examination of factors contributing to the creation of successful e-learning environments , 2008, Int. J. Hum. Comput. Stud..

[4]  Younghwa Lee,et al.  The Technology Acceptance Model: Past, Present, and Future , 2003, Commun. Assoc. Inf. Syst..

[5]  H W Marsh,et al.  Is More Ever Too Much? The Number of Indicators per Factor in Confirmatory Factor Analysis. , 1998, Multivariate behavioral research.

[6]  Hsiu-Ju Chen,et al.  Linking employees' e-learning system use to their overall job outcomes: An empirical study based on the IS success model , 2010, Comput. Educ..

[7]  Yi-Shun Wang,et al.  Multi-criteria evaluation of the web-based e-learning system: A methodology based on learner satisfaction and its applications , 2008, Comput. Educ..

[8]  Geraldine Clarebout,et al.  Can instruction as such affect learning? The case of learner control , 2011, Comput. Educ..

[9]  Confirmation Model.  UNDERSTANDING INFORMATION SYSTEMS CONTINUANCE: AN EXPECTATION- , 2001 .

[10]  Wynne W. Chin,et al.  Structural equation modeling analysis with small samples using partial least squares , 1999 .

[11]  Detmar W. Straub,et al.  A Practical Guide To Factorial Validity Using PLS-Graph: Tutorial And Annotated Example , 2005, Commun. Assoc. Inf. Syst..

[12]  Keenan A. Pituch,et al.  The influence of system characteristics on e-learning use , 2006, Comput. Educ..

[13]  Jason D. Baker,et al.  Hybrid structures: Faculty use and perception of web-based courseware as a supplement to face-to-face instruction , 2004, Internet High. Educ..

[14]  Nian-Shing Chen,et al.  Effects of matching teaching strategy to thinking style on learner's quality of reflection in an online learning environment , 2011, Comput. Educ..

[15]  Timothy Teo,et al.  Modelling technology acceptance in education: A study of pre-service teachers , 2009, Comput. Educ..

[16]  Hock-Hai Teo,et al.  Evaluating information accessibility and community adaptivity features for sustaining virtual learning communities , 2003, Int. J. Hum. Comput. Stud..

[17]  Tor J. Larsen,et al.  The role of task-technology fit as users' motivation to continue information system use , 2009, Comput. Hum. Behav..

[18]  Woong-Kyu Lee,et al.  The relationship of e-Learner's self-regulatory efficacy and perception of e-Learning environmental quality , 2008, Comput. Hum. Behav..

[19]  Maite Urretavizcaya,et al.  Blending traditional teaching methods with learning environments: Experience, cyclical evaluation process and impact with MAgAdI , 2013, Comput. Educ..

[20]  Jane E. Klobas,et al.  A task-technology fit view of learning management system impact , 2009, Comput. Educ..

[21]  Sang-Gun Lee,et al.  Validating E-learning factors affecting training effectiveness , 2007, Int. J. Inf. Manag..

[22]  F. Heider.  The psychology of interpersonal relations , 1958 .

[23]  A. K. M. Najmul Islam,et al.  The Role of Perceived System Quality as Educators’ Motivation to Continue E-learning System Use , 2012 .

[24]  Kar Yan Tam,et al.  Understanding Continued Information Technology Usage Behavior: A Comparison of Three Models in the Context of Mobile Internet , 2006, Decis. Support Syst..

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

[26]  Teemu Valtonen,et al.  Pre-Service Teachers' Experiences of Using Social Software Applications Questionnaire , 2014 .

[27]  Liping Deng,et al.  From Moodle to Facebook: Exploring students' motivation and experiences in online communities , 2013, Comput. Educ..

[28]  J. Coleman,et al.  Social Capital in the Creation of Human Capital , 1988, American Journal of Sociology.

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

[30]  Alireza Hassanzadeh,et al.  A model for measuring e-learning systems success in universities , 2012, Expert Syst. Appl..

[31]  Sirkka L. Jarvenpaa,et al.  The Use of Information Technology to Enhance Management School Education: A Theoretical View , 1995, MIS Q..

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

[33]  Fred D. Davis,et al.  Extension of the Technology Acceptance Model: Four Longitudinal Field : . , 2000 .

[34]  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..

[35]  Patrick Y. K. Chau,et al.  Cultivating the sense of belonging and motivating user participation in virtual communities: A social capital perspective , 2012, Int. J. Inf. Manag..

[36]  Dov Te'eni,et al.  Review: A Cognitive-Affective Model of Organizational Communication for Designing IT , 2001, MIS Q..

[37]  Siti Salwah Salim,et al.  Effects of Collaborative Web Based Vocational Education and Training (VET) on Learning Outcomes , 2013, Comput. Educ..

[38]  Kan-Min Lin,et al.  e-Learning continuance intention: Moderating effects of user e-learning experience , 2011, Comput. Educ..

[39]  Moez Limayem,et al.  How Habit Limits the Predictive Power of Intention: The Case of Information Systems Continuance , 2007, MIS Q..

[40]  Ephraim R. McLean,et al.  Information Systems Success: The Quest for the Dependent Variable , 1992, Inf. Syst. Res..

[41]  T. C. Edwin Cheng,et al.  The role of perceived user-interface design in continued usage intention of self-paced e-learning tools , 2009, Comput. Educ..

[42]  A. K. M. Najmul Islam,et al.  Understanding E-Learning System Usage Outcomes in Hybrid Courses , 2012, 2012 45th Hawaii International Conference on System Sciences.

[43]  Zeying Wan,et al.  Why people benefit from e-learning differently: The effects of psychological processes on e-learning outcomes , 2008, Inf. Manag..

[44]  María Guadalupe Ramírez Ortiz,et al.  The social networks of academic performance in a student context of poverty in Mexico , 2004, Soc. Networks.

[45]  D. H. Zhu,et al.  Adoption of Social Networking Sites , 2012 .

[46]  Alexander Hars,et al.  Web Based Knowledge Infrastructures for the Sciences: An Adaptive Document , 2000, Commun. Assoc. Inf. Syst..

[47]  Marylène Gagné,et al.  Understanding e-learning continuance intention in the workplace: A self-determination theory perspective , 2008, Comput. Hum. Behav..

[48]  Marjan Hericko,et al.  A meta-analysis of e-learning technology acceptance: The role of user types and e-learning technology types , 2011, Comput. Hum. Behav..

[49]  Dale Goodhue,et al.  Task-Technology Fit and Individual Performance , 1995, MIS Q..

[50]  Gwo-Dong Chen,et al.  An activity-theoretical approach to investigate learners' factors toward e-learning systems , 2007, Comput. Hum. Behav..

[51]  Alan R. Dennis,et al.  Media, Tasks, and Communication Processes: A Theory of Media Synchronicity , 2008, MIS Q..

[52]  Yuan Sun,et al.  Extending technology usage to work settings: The role of perceived work compatibility in ERP implementation , 2009, Inf. Manag..

[53]  Vincent Cho,et al.  Comparing e-Learning tools' success: The case of instructor-student interactive vs. self-paced tools , 2011, Comput. Educ..

[54]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[55]  Matthew K. O. Lee,et al.  Acceptance of Internet-based learning medium: the role of extrinsic and intrinsic motivation , 2005, Inf. Manag..

[56]  Jungjoo Kim,et al.  Investigating factors that influence social presence and learning outcomes in distance higher education , 2011, Comput. Educ..

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

[58]  Peter B. Seddon.  A Respecification and Extension of the DeLone and McLean Model of IS Success , 1997, Inf. Syst. Res..

[59]  Minjuan Wang,et al.  Cybergogy for Engaged Learning: A Framework for Creating Learner Engagement through Information and Communication Technology , 2006 .

[60]  Carmel McNaught,et al.  Understanding the ways in which design features of educational websites impact upon student learning outcomes in blended learning environments , 2010, Comput. Educ..

[61]  Detmar W. Straub,et al.  Structural Equation Modeling and Regression: Guidelines for Research Practice , 2000, Commun. Assoc. Inf. Syst..

[62]  Christer Carlsson,et al.  Factors driving the adoption of m-learning: An empirical study , 2010, Comput. Educ..

[63]  Carol T. Kulik,et al.  Individual and corporate dispute resolution: Using procedural fairness as a decision heuristic. , 1993 .

[64]  Barry D. Davidson,et al.  Social networks, communication styles, and learning performance in a CSCL community , 2007, Comput. Educ..

[65]  Chao-Min Chiu,et al.  Understanding e-learning continuance intention: An extension of the Technology Acceptance Model , 2006, Int. J. Hum. Comput. Stud..

[66]  E. Deci,et al.  Human autonomy: The basis for true self-esteem. , 1995 .

[67]  Brigitte Maier,et al.  Students' expectations of, and experiences in e-learning: Their relation to learning achievements and course satisfaction , 2010, Comput. Educ..

[68]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[69]  I. Ajzen.  The theory of planned behavior , 1991 .

[70]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[71]  Alain Pinsonneault,et al.  Survey Research Methodology in Management Information Systems: An Assessment , 1993, J. Manag. Inf. Syst..

[72]  Teemu Valtonen,et al.  Pre-service teachers' experiences of using social software applications for collaborative inquiry , 2013, Comput. Educ..

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

[74]  Wei Wang,et al.  ScholarWorks @ Georgia State University , 2022 .

[75]  A. K. M. Najmul Islam,et al.  The Determinants of the Post-Adoption Satisfaction of Educators with an E-Learning System , 2011, J. Inf. Syst. Educ..