Modeling the determinants of pre‐service teachers' perceived usefulness of e‐learning

Purpose – The purpose of this paper is to explore the determinants of pre‐service teachers' perceived usefulness of e‐learning for teaching and learning.Design/methodology/approach – A total of 189 pre‐service teachers completed a survey questionnaire measuring their responses to four constructs which explain perceived usefulness in the context of e‐learning: learning environment (LE), course delivery (CD), tutor attribute (TA), and facilitating conditions (FC). These were administered during the teaching term where participants were attending a technology course. Structural equation modeling (SEM) was employed for modeling and data analysis.Findings – Results revealed that 62.5 percent of the total variance in the pre‐service teachers' perceived usefulness of e‐learning was explained by the four variables. Among them, learning environment did not have a significant influence on perceived usefulness. Overall, the data in this study provided evidence to support the notion that perceived usefulness is a mul...

[1]  Susan Powers,et al.  Technology and Teacher Education: A Guide for Educators and Policymakers , 2002 .

[2]  Cher Ping Lim,et al.  Managing Teachers’ Barriers to ICT Integration in Singapore Schools , 2006 .

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

[4]  Mun Y. Yi,et al.  Predicting the use of web-based information systems: self-efficacy, enjoyment, learning goal orientation, and the technology acceptance model , 2003, Int. J. Hum. Comput. Stud..

[5]  Raafat George Saadé,et al.  Web-Based Educational Information System for Enhanced Learning, EISEL: Student Assessment , 2003, J. Inf. Technol. Educ..

[6]  Robert Andersson,et al.  Examining user acceptance of computer technology: an empirical study of student teachers , 2005, J. Comput. Assist. Learn..

[7]  R. Kline.  Principles and practice of structural equation modeling, 2nd ed. , 2005 .

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

[9]  Terry Anderson,et al.  The Theory and Practice of Online Learning , 2009 .

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

[11]  J. Arbaugh,et al.  Technological and Structural Characteristics, Student Learning and Satisfaction with Web-Based Courses , 2002 .

[12]  Judy Drennan,et al.  Factors Affecting Student Attitudes Toward Flexible Online Learning in Management Education , 2005 .

[13]  Ed Smeets,et al.  Does ICT contribute to powerful learning environments in primary education? , 2005, Comput. Educ..

[14]  Karl G. Jöreskog,et al.  Lisrel 8: User's Reference Guide , 1997 .

[15]  Chorng-Shyong Ong,et al.  Gender differences in perceptions and relationships among dominants of e-learning acceptance , 2006, Comput. Hum. Behav..

[16]  James C. Anderson,et al.  STRUCTURAL EQUATION MODELING IN PRACTICE: A REVIEW AND RECOMMENDED TWO-STEP APPROACH , 1988 .

[17]  L. Schrum.  Technology professional development for teachers , 1999 .

[18]  J. Arbaugh.  Managing the on-line classroom , 2002 .

[19]  Shirley Alexander,et al.  Using Students' Experiences to Derive Quality in an e-Learning System: An Institution's Perspective , 2007, J. Educ. Technol. Soc..

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

[21]  D. E. Benson,et al.  Conceptions of Self and the Use of Digital Technologies in a Learning Environment. , 2007 .

[22]  Sue Trinidad,et al.  Development, Validation and Use of the Online Learning Environment Survey. , 2005 .

[23]  Melissa M. Groves,et al.  Instructional Technology Adoption in Higher Education: An Action Research Case Study , 2000 .

[24]  Frank Biocca,et al.  INTERNET USE IN LOW-INCOME FAMILIES: IMPLICATIONS FOR THE DIGITAL DIVIDE , 2003 .

[25]  G. A. Marcoulides,et al.  An Introduction to Applied Multivariate Analysis , 2008 .

[26]  V. A. Thurmond,et al.  Evaluation of Student Satisfaction: Determining the Impact of a Web-Based Environment by Controlling for Student Characteristics , 2002 .

[27]  D. Bolliger.  Key Factors for Determining Student Satisfaction in Online Courses , 2004 .

[28]  Daniel W. Surry,et al.  A model for integrating instructional technology into higher education , 2005, Br. J. Educ. Technol..

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

[30]  Yaacov J. Katz.  The Comparative Suitability Of Three ICT Distance Learning Methodologies For College Level Instruction , 2000 .

[31]  R. Henson.  Understanding Internal Consistency Reliability Estimates: A Conceptual Primer on Coefficient Alpha , 2001 .

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

[33]  Waiman Cheung,et al.  Proposing a framework to assess Internet usage in university education: an empirical investigation from a student's perspective , 2005, Br. J. Educ. Technol..

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

[36]  Barry J. Fraser,et al.  Teacher-Student Interaction and Gifted Students' Attitudes Toward Chemistry in Laboratory Classrooms in Singapore , 2005 .

[37]  Blake Ives,et al.  Web-based Virtual Learning Environments: a Research Framework and a Preliminary Assessment of Effectiveness in Basic It Skills Training Author(s): Piccoli Et Al./web-based Virtual Learning Environments Web-based Virtual Learning Environments: a Research Framework and a Preliminary Assessment of Effe , 2022 .

[38]  J. Laffey,et al.  Social Influence for Perceived Usefulness and Ease-of-Use of Course Delivery Systems. , 2006 .

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

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