Pre-Service Teachers' Intention to Use MUVEs as Practitioners - A Structural Equation Modeling Approach

[1]  Philip M. Sadler,et al.  Conceptualizing astronomical scale: Virtual simulations on handheld tablet computers reverse misconceptions , 2014, Comput. Educ..

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

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

[4]  Peggy A. Ertmer,et al.  Behaviorism, Cognitivism, Constructivism: Comparing Critical Features From an Instructional Design Perspective , 2008 .

[5]  R. O’Brien,et al.  A Caution Regarding Rules of Thumb for Variance Inflation Factors , 2007 .

[6]  Paul Benjamin Lowry,et al.  Partial Least Squares (PLS) Structural Equation Modeling (SEM) for Building and Testing Behavioral Causal Theory: When to Choose It and How to Use It , 2014, IEEE Transactions on Professional Communication.

[7]  Kristopher J Preacher,et al.  Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models , 2008, Behavior research methods.

[8]  Timothy Teo Explaining the Intention to Use Technology among Volitional Users in Education: An Evaluation of the Technology Acceptance Model (TAM) Using Structural Equation Modeling , 2010 .

[9]  Timothy Teo,et al.  Factors influencing teachers' intention to use technology: Model development and test , 2011, Comput. Educ..

[10]  Tassos A. Mikropoulos,et al.  Educational virtual environments: A ten-year review of empirical research (1999-2009) , 2011, Comput. Educ..

[11]  Yoav Yair,et al.  3D-Virtual Reality in Science Education: An Implication for Astronomy Teaching , 2001 .

[12]  R. P. McDonald,et al.  Principles and practice in reporting structural equation analyses. , 2002, Psychological methods.

[13]  Neil Selwyn,et al.  Students' attitudes toward computers: Validation of a computer attitude scale for 16-19 education , 1997, Comput. Educ..

[14]  Michael Barnett,et al.  Electromagnetism Supercharged! Learning Physics with Digital Simulation Games , 2004, ICLS.

[15]  Jason W. Osborne,et al.  Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis. , 2005 .

[16]  P. Bentler,et al.  Significance Tests and Goodness of Fit in the Analysis of Covariance Structures , 1980 .

[17]  Allison Littlejohn,et al.  Are digital natives a myth or reality? University students' use of digital technologies , 2011, Comput. Educ..

[18]  Jiejie Zhu,et al.  Virtual Reality and Mixed Reality for Virtual Learning Environments , 2006, Edutainment.

[19]  Wynne W. Chin,et al.  A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo Simulation Study and an Electronic - Mail Emotion/Adoption Study , 2003, Inf. Syst. Res..

[20]  Denise Tolhurst,et al.  Organisational factors affecting teachers' use and perception of information & communications technology , 2005 .

[21]  William Sugar,et al.  Examining Teachers' Decisions To Adopt New Technology , 2004, J. Educ. Technol. Soc..

[22]  Timothy Teo,et al.  Examining the intention to use technology among pre-service teachers: an integration of the Technology Acceptance Model and Theory of Planned Behavior , 2012, Interact. Learn. Environ..

[23]  Geoffrey A. Moore,et al.  Crossing the Chasm , 1991 .

[24]  Elizabeth M. Weiss,et al.  Computer self-efficacy and anxiety scales for an Internet sample: testing measurement equivalence of existing measures and development of new scales , 2004, Comput. Hum. Behav..

[25]  Timothy Teo,et al.  An Assessment of Pre-Service Teachers’ Technology Acceptance in Turkey: A Structural Equation Modeling Approach , 2012 .

[26]  Khe Foon Hew,et al.  Use of three-dimensional (3-D) immersive virtual worlds in K-12 and higher education settings: A review of the research , 2010, Br. J. Educ. Technol..

[27]  B. Tabachnick,et al.  Using Multivariate Statistics , 1983 .

[28]  Xiaofeng Guo,et al.  Meeting the "Digital Natives": Understanding the Acceptance of Technology in Classrooms , 2013, J. Educ. Technol. Soc..

[29]  Kamariah Abu Bakar,et al.  Using a student‐centred learning approach to teach a discrete information technology course: the effects on Malaysian pre‐service teachers’ attitudes toward information technology , 2006 .

[30]  Maxwell K. Hsu,et al.  Computer attitude, statistics anxiety and self-efficacy on statistical software adoption behavior: An empirical study of online MBA learners , 2009, Comput. Hum. Behav..

[31]  Manuel Castro,et al.  New technology trends in education: Seven years of forecasts and convergence , 2011, Comput. Educ..

[32]  Emmanuel Fokides,et al.  Pre-Service Teachers, Computers, and ICT Courses: A Troubled Relationship , 2016, Int. J. Inf. Commun. Technol. Educ..

[33]  Dongping Zheng,et al.  Rethinking Language Learning: Virtual Worlds as a Catalyst for Change , 2011 .

[34]  Michele D. Dickey Brave new (interactive) worlds: A review of the design affordances and constraints of two 3D virtual worlds as interactive learning environments , 2005, Interact. Learn. Environ..

[35]  Terrence J Sejnowski,et al.  Foundations for a New Science of Learning , 2009, Science.

[36]  Lynette L. Ralph,et al.  Information Literacy and Doctoral Students: Avatars and Educators Collaborate for Online Distance Learning , 2010 .

[37]  Timothy Teo,et al.  Assessing the intention to use technology among pre-service teachers in Singapore and Malaysia: A multigroup invariance analysis of the Technology Acceptance Model (TAM) , 2009, Comput. Educ..

[38]  Issues in Informing Science and Information Technology Volume 5 , 2008 Teaching in Virtual Worlds : Opportunities and Challenges , 2008 .

[39]  Boleslaw K. Szymanski,et al.  Social consensus through the influence of committed minorities , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[40]  Jimmy Macharia,et al.  Key factors that influence the diffusion and infusion of information and communication technologies in Kenyan higher education , 2014 .

[41]  Emmanuel Fokides,et al.  Content and language integrated learning in OpenSimulator project. Results of a pilot implementation in Greece , 2017, Education and Information Technologies.

[42]  Peggy A. Ertmer,et al.  Teacher value beliefs associated with using technology: Addressing professional and student needs , 2010, Comput. Educ..

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

[44]  Scott B. MacKenzie,et al.  Common method biases in behavioral research: a critical review of the literature and recommended remedies. , 2003, The Journal of applied psychology.

[45]  Timothy Teo,et al.  Student Teachers’ Acceptance of Computer Technology , 2011 .

[46]  Shu-Sheng Liaw,et al.  Exploring users' attitudes and intentions toward the web as a survey tool , 2005, Comput. Hum. Behav..

[47]  Jan Stage,et al.  Usability in open source software development: opinions and practice , 2006 .

[48]  I. Ajzen,et al.  Attitude-behavior relations: A theoretical analysis and review of empirical research. , 1977 .

[49]  Fotini Paraskeva,et al.  Individual characteristics and computer self-efficacy in secondary education teachers to integrate technology in educational practice , 2008, Comput. Educ..

[50]  Melissa D. Hartley,et al.  Using Second Life® for Situated and Active Learning in Teacher Education , 2016 .

[51]  David R. Anderson,et al.  Model selection and multimodel inference : a practical information-theoretic approach , 2003 .

[52]  P. M. Podsakoff,et al.  Self-Reports in Organizational Research: Problems and Prospects , 1986 .

[53]  Timothy Teo,et al.  Unpacking teachers' acceptance of technology: Tests of measurement invariance and latent mean differences , 2014, Comput. Educ..

[54]  Igor Titov,et al.  Programming literacy level needed for modern teachers: Fragile border between content creator and a programmer , 2014, 2014 IEEE Global Engineering Education Conference (EDUCON).

[55]  H. O'Neil,et al.  Classification of learning outcomes: evidence from the computer games literature , 2005 .

[56]  Mingming Zhou,et al.  Explaining the intention to use technology among university students: a structural equation modeling approach , 2014, Journal of Computing in Higher Education.

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

[58]  Linda G. Wallace,et al.  The adoption of software measures: A technology acceptance model (TAM) perspective , 2014, Inf. Manag..

[59]  N. Law,et al.  Improving IT training for serving teachers through evaluation , 1999 .

[60]  H. Kaiser The Application of Electronic Computers to Factor Analysis , 1960 .

[61]  A. Bandura Social Foundations of Thought and Action: A Social Cognitive Theory , 1985 .