Using simulation system for collaborative learning to enhance learner’s performance

Abstract This study focuses on adoption of simulation system in rapidly changing technology and information flow. Given the prevalent popularity of simulation system, it is important to understand and adopt simulation system to develop future educational plans. This paper addresses how simulation system enhances student collaborative learning and learner performance using Technology Acceptance Model. Results were analyzed using Structure Equation Modeling technique; this study established that perceived usefulness, perceived ease of use, and perceived enjoyment all have a significant positive relationship with simulation system. The results indicate that simulation system serves as a dynamic tool to accelerate the progress of learning environments by encouraging collaboration and communication among students which strengthen their learning abilities and increase performance because students practically perform all the theories in a risk-free environment. In the competitive world, simulation system should be implementing at education level so that students can learn more before entering into a real-life career.

[1]  H. Hasan,et al.  Toward a model for the acceptance of Internet banking in developing countries , 2005 .

[2]  Chien-Hung Liu,et al.  An empirical investigation of computer simulation technology acceptance to explore the factors that affect user intention , 2015, Universal Access in the Information Society.

[3]  Jonathan D. Moizer,et al.  Simulations and games , 2009 .

[4]  Sawsen Lakhal,et al.  The AACSB Assurance of Learning process: An assessment of current practices within the perspective of the unified view of validity , 2015 .

[5]  S. Bossert,et al.  Cooperative Activities in the Classroom , 1988 .

[6]  Richard,et al.  Extrinsic and Intrinsic Motivation to Use Computers in the Workplace , 2022 .

[7]  Margaret E. Gredler,et al.  Games and Simulations and Their Relationships to Learning , 2013 .

[8]  Miltiadis D. Lytras,et al.  A recommender agent based on learning styles for better virtual collaborative learning experiences , 2015, Comput. Hum. Behav..

[9]  Edythe Johnson Holubec,et al.  Cooperation in the Classroom , 1993 .

[10]  Qun Zhao,et al.  The effects of psychological ownership and TAM on social media loyalty: An integrated model , 2016, Telematics Informatics.

[11]  Precha Thavikulwat,et al.  The Architecture of Computerized Business Gaming Simulations , 2004 .

[12]  E. Cohen Restructuring the Classroom: Conditions for Productive Small Groups , 1994 .

[13]  Mike Hart,et al.  The Impact of Cognitive and other Factors on the Perceived Usefulness of OLAP , 2004, J. Comput. Inf. Syst..

[14]  Viswanath Venkatesh,et al.  Creating an effective training environment for enhancing telework , 2000, Int. J. Hum. Comput. Stud..

[15]  Robert E. Wood,et al.  Simulations, learning and real world capabilities , 2009 .

[16]  Diana Adler,et al.  Using Multivariate Statistics , 2016 .

[17]  Henry Adobor,et al.  Management simulations: determining their effectiveness , 2006 .

[18]  Michael R. Mullen,et al.  Structural equation modelling: guidelines for determining model fit , 2008 .

[19]  Wan Salihin Wong Abdullah,et al.  The Effects of Perceived Usefulness and Perceived Ease of Use on Continuance Intention to Use E-Government , 2016 .

[20]  Luca Chittaro,et al.  Serious games for emergency preparedness: Evaluation of an interactive vs. a non-interactive simulation of a terror attack , 2015, Comput. Hum. Behav..

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

[22]  D. Kolb Experiential Learning: Experience as the Source of Learning and Development , 1983 .

[23]  Ken Jones Simulations as Examinations , 1982 .

[24]  KimYoung-Gul,et al.  Extending the TAM for a World-Wide-Web context , 2001 .

[25]  David H. Jonassen,et al.  Handbook of Research on Educational Communications and Technology : A Project of the Association for Educational Communications and Technology , 1996 .

[26]  James E. Driskell,et al.  Games, Motivation, and Learning: A Research and Practice Model , 2002 .

[27]  Chin-Lung Hsu,et al.  Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation , 2008, Inf. Manag..

[28]  Renaud Marlet,et al.  Education and experience. , 1989, Nursing standard (Royal College of Nursing (Great Britain) : 1987).

[29]  Per E. Pedersen,et al.  Intentions to use mobile services: Antecedents and cross-service comparisons , 2005 .

[30]  Deborah Ambrosio Mawhirter,et al.  Expect the Unexpected: Simulation Games as a Teaching Strategy , 2016 .

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

[32]  Shaun McQuitty,et al.  Statistical power and structural equation models in business research , 2004 .

[33]  F. Lateef Simulation-based learning: Just like the real thing , 2010, Journal of emergencies, trauma, and shock.

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

[35]  Varun Rai,et al.  Agent-Based Modeling of Energy Technology Adoption: Empirical Integration of Social, Behavioral, Economic, and Environmental Factors , 2014, Environ. Model. Softw..

[36]  Suzaan Hughes,et al.  Increasing the impact of a business simulation: The role of reflection , 2015 .

[37]  Martin Ebner,et al.  Successful implementation of user-centered game based learning in higher education: An example from civil engineering , 2007, Comput. Educ..

[38]  B. Tabachnick,et al.  Using multivariate statistics, 5th ed. , 2007 .

[39]  P. Barrett Structural equation modelling : Adjudging model fit , 2007 .

[40]  Zelimir Dulcic,et al.  Evaluating the Intended Use of Decision Support System (DSS) by Applying Technology Acceptance Model (TAM) in Business Organizations in Croatia , 2012 .

[41]  Chris D. Nugent,et al.  Modelling assistive technology adoption for people with dementia , 2016, J. Biomed. Informatics.

[42]  J. Meek,et al.  Facebook, social integration and informal learning at university: ‘It is more for socialising and talking to friends about work than for actually doing work’ , 2009 .

[43]  J. Miles,et al.  A time and a place for incremental fit indices , 2007 .

[44]  V. Pandey,et al.  Exploring the adoption of a virtual reality simulation: The role of perceived ease of use, perceived usefulness and personal innovativeness , 2012 .

[45]  Fengfeng Ke,et al.  Collaborative science learning in an immersive flight simulation , 2016, Comput. Educ..

[46]  BARBAROS BOSTAN,et al.  Player motivations: A psychological perspective , 2009, CIE.

[47]  Timo Lainema,et al.  Applying an authentic, dynamic learning environment in real world business , 2006, Comput. Educ..

[48]  Tieju Ma,et al.  Optimizing systematic technology adoption with heterogeneous agents , 2017, Eur. J. Oper. Res..

[49]  Shin-Yuan Hung,et al.  Decomposing perceived playfulness: A contextual examination of two social networking sites , 2016, Inf. Manag..

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

[51]  Gordon C. Bruner,et al.  Explaining consumer acceptance of handheld Internet devices , 2005 .

[52]  T. Grantcharov,et al.  Randomized clinical trial of virtual reality simulation for laparoscopic skills training , 2004, The British journal of surgery.

[53]  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..

[54]  Hock Chuan Chan,et al.  The Moderating Effects of Utilitarian and Hedonic Values on Information Technology Continuance , 2012, TCHI.

[55]  Robert Davis,et al.  Modeling game usage, purchase behavior and ease of use , 2012, Entertain. Comput..

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

[57]  Declan Doyle,et al.  Using a business simulation to teach applied skills – the benefits and the challenges of using student teams from multiple countries , 2000 .

[58]  Kathleen R Rosen,et al.  The history of medical simulation. , 2008, Journal of critical care.

[59]  Simon Cooper,et al.  Use of educational games in the health professions: a mixed-methods study of educators' perspectives in the UK. , 2010, Nursing & health sciences.

[60]  David F. Treagust,et al.  Validity and use of an instrument for assessing classroom psychosocial environment in higher education , 1986 .

[61]  Eric T. G. Wang,et al.  Understanding Web-based learning continuance intention: The role of subjective task value , 2008, Inf. Manag..

[62]  Inna Popil,et al.  A game-based strategy for the staff development of home health care nurses. , 2015, Journal of continuing education in nursing.

[63]  Barbara B. Flynn,et al.  Empirical research methods in operations management , 1990 .

[64]  Peter B. Barr,et al.  An exploratory look at the use of importance‐performance analysis as a curricular assessment tool in a school of business , 2000 .

[65]  James H. Steiger,et al.  Understanding the limitations of global fit assessment in structural equation modeling , 2007 .

[66]  J. Charterina,et al.  Business simulation games with and without supervision: An analysis based on the TAM model , 2016 .

[67]  Hans van der Heijden,et al.  Factors influencing the usage of websites: the case of a generic portal in The Netherlands , 2003, Inf. Manag..

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

[69]  Hamid Sadeghi,et al.  A novel justice-based linear model for optimal learner group formation in computer-supported collaborative learning environments , 2015, Comput. Hum. Behav..

[70]  Miltiadis D. Lytras,et al.  An emerging - Social and emerging computing enabled philosophical paradigm for collaborative learning systems: Toward high effective next generation learning systems for the knowledge society , 2015, Comput. Hum. Behav..

[71]  Miltiadis D. Lytras,et al.  The impact of Social Multimedia Systems on cyberlearners , 2013, Comput. Hum. Behav..

[72]  M. Csíkszentmihályi Play and Intrinsic Rewards , 2014 .

[73]  Thurasamy Ramayah,et al.  Wearable technologies: The role of usefulness and visibility in smartwatch adoption , 2016, Comput. Hum. Behav..

[74]  John C. Morey,et al.  Simulation based teamwork training for emergency department staff: does it improve clinical team performance when added to an existing didactic teamwork curriculum? , 2004, Quality and Safety in Health Care.

[75]  Fred D. Davis,et al.  Extrinsic and Intrinsic Motivation to Use Computers in the Workplace1 , 1992 .

[76]  Rajiv Kishore Editorial Preface - JAIS Special Issue on Ontologies in the Context of Information Systems , 2007, J. Assoc. Inf. Syst..

[77]  Z. Arifin,et al.  The Effect of Dynamic Capability to Technology Adoption and its Determinant Factors for Improving Firm's Performance; Toward a Conceptual Model , 2015 .

[78]  Reynol Junco,et al.  The effect of Twitter on college student engagement and grades , 2011, J. Comput. Assist. Learn..

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

[80]  Carol K. K. Chan,et al.  The international handbook of collaborative learning , 2013 .

[81]  Izak Benbasat,et al.  Quo vadis TAM? , 2007, J. Assoc. Inf. Syst..

[82]  W. Gijselaers,et al.  International Hospitality Management Students' Epistemological Beliefs and Conceptions of Teaching and Learning , 2009 .

[83]  S. Bossert,et al.  Chapter 6: Cooperative Activities in the Classroom , 1988 .

[84]  Brian Miller,et al.  Students’ Perceptions of the Usefulness of a Virtual Simulation in Post-Secondary Hospitality Education , 2008 .

[85]  Hans van Buuren,et al.  Measuring perceived sociability of computer-supported collaborative learning environments , 2007, Comput. Educ..

[86]  Richard Newman,et al.  Evaluating business simulation software: approach, tools and pedagogy , 2009 .

[87]  Lei Zhu,et al.  Optimal timing of technology adoption under the changeable abatement coefficient through R&D , 2016, Comput. Ind. Eng..

[88]  M. Loon,et al.  The impact of critical thinking disposition on learning using business simulations , 2015 .

[89]  Marlene A. Pratt,et al.  Enhancing hospitality student learning through the use of a business simulation , 2016 .

[90]  Douglas R. Vogel,et al.  Designing Web 2.0 Collaboration Tools to Support Project-Based Learning: An Activity-Oriented Approach , 2012, Int. J. Syst. Serv. Oriented Eng..

[91]  Nasriah Zakaria,et al.  Understanding Technology and People Issues in Hospital Information System (HIS) Adoption: Case study of a tertiary hospital in Malaysia. , 2016, Journal of infection and public health.

[92]  Chei Sian Lee,et al.  Making work fun: Investigating antecedents of perceived enjoyment in human computation games for information sharing , 2014, Comput. Hum. Behav..

[93]  David M. Gaba,et al.  Simulation-Based Training in Anesthesia Crisis Resource Management (ACRM): A Decade of Experience , 2001 .

[94]  Na Na,et al.  Simulations and games , 1985 .

[95]  John Fripp,et al.  A future for business simulations , 1997 .

[96]  Kar Yan Tam,et al.  The Effects of Post-Adoption Beliefs on the Expectation-Confirmation Model for Information Technology Continuance , 2006, Int. J. Hum. Comput. Stud..

[97]  Anton Strahilov,et al.  Simulation of the behavior of pneumatic drives for virtual commissioning of automated assembly systems , 2015 .

[98]  Xianggui Qu,et al.  Multivariate Data Analysis , 2007, Technometrics.

[99]  A. S. Getchell,et al.  Agent-based Modeling , 2008 .

[100]  Roy Radner,et al.  On the allocation of effort , 1975 .

[101]  Margaret Meiling Luo,et al.  Post-Adoption Behaviors of E-Service Customers: The Interplay of Cognition and Emotion , 2008, Int. J. Electron. Commer..