Examining the roles of students' beliefs and security concerns for using smartwatches in higher education

PurposeDespite the increased use of wearables in education, little attention has been paid to why some students are more likely to adopt smartwatches than others. The question of what impacts the adoption of smartwatches in educational activities is still neglected. In addition, the question of how security determinants can affect the adoption of smartwatches by students has not been addressed yet. Hence, this research develops a theoretical model by integrating the technology acceptance model (TAM) and protection motivation theory (PMT) to study students’ adoption of smartwatches for educational purposes. Design/methodology/approachQuestionnaires were distributed to university students in Malaysia. A total of 679 valid responses were collected. The collected data were analyzed using partial least squares-structural equation modeling (PLS-SEM). FindingsThe results of data analysis provide support for the proposed model. Furthermore, the findings indicated that perceived vulnerability, self-efficacy, response efficacy, response cost, ease of use, and perceived usefulness have significant effects on students’ behavioral intention to use smartwatches for educational purposes. In addition, perceived ease of use of smartwatches for educational purposes helps students to realize the benefits of this technology. Originality/valueThis is an original study that develops a new holistic theoretical model by combining the PMT and TAM to study the effects of ease of use, usefulness, and security-related factors on the adoption of smartwatches for educational purposes. The study offers practical implications for universities and higher education institutions to improve students’ learning experiences to ensure their sustainability using new and innovative ways by exploiting new technologies such as smartwatches.

[1]  M. Sarstedt,et al.  A new criterion for assessing discriminant validity in variance-based structural equation modeling , 2015 .

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

[3]  Vitaliy Mezhuyev,et al.  Technology Acceptance Model in M-learning context: A systematic review , 2018, Comput. Educ..

[4]  Kim-Kwang Raymond Choo,et al.  Factors Influencing the Adoption of Cloud Incident Handling Strategy: A Preliminary Study in Malaysia , 2015, AMCIS.

[5]  May O Lwin,et al.  Can Exergames Impart Health Messages? Game Play, Framing, and Drivers of Physical Activity Among Children , 2014, Journal of health communication.

[6]  Norman Shaw,et al.  Improving Healthcare with Wearables: Overcoming the Barriers to Adoption , 2017, HCI.

[7]  Judit T. Nagy,et al.  Evaluation of Online Video Usage and Learning Satisfaction: An Extension of the Technology Acceptance Model , 2018 .

[8]  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..

[9]  R. W. Rogers,et al.  A Protection Motivation Theory of Fear Appeals and Attitude Change1. , 1975, The Journal of psychology.

[10]  Kuo-Lun Hsiao,et al.  What drives smartwatch adoption intention? Comparing Apple and non-Apple watches , 2017, Libr. Hi Tech.

[11]  Mostafa Al-Emran,et al.  Do knowledge acquisition and knowledge sharing really affect e-learning adoption? An empirical study , 2019, Education and Information Technologies.

[12]  Vivian Genaro Motti.  Wearable Technologies in Education: A Design Space , 2019, HCI.

[13]  Jon-Chao Hong,et al.  The effect of consumer innovativeness on perceived value and continuance intention to use smartwatch , 2017, Comput. Hum. Behav..

[14]  Mohammad Nazir Ahmad,et al.  The effects of transformational leadership and ERP system self-efficacy on ERP system usage , 2014, J. Enterp. Inf. Manag..

[15]  U. Sekaran.  Research Methods for Business , 1999 .

[16]  Robert LaRose,et al.  Understanding online safety behaviors: A protection motivation theory perspective , 2016, Comput. Secur..

[17]  L. Ghahremani,et al.  Effect of Health Education Based on the Protection Motivation Theory on Malaria Preventive Behaviors in Rural Households of Kerman, Iran , 2014, International journal of preventive medicine.

[18]  Siddhi Pittayachawan,et al.  Comparing intention to avoid malware across contexts in a BYOD-enabled Australian university: A Protection Motivation Theory approach , 2015, Comput. Secur..

[19]  Ari Yair Barrera-Animas,et al.  Monitoring Student Activities with Smartwatches: On the Academic Performance Enhancement , 2019, Sensors.

[20]  Jun-ichi Takada,et al.  Persuasive content development: application of protection motivation theory in promoting heritage site preservation awareness , 2014, CHI Extended Abstracts.

[21]  Esteban Romero-Frías,et al.  Personal Learning Environments Acceptance Model: The Role of Need for Cognition, e-Learning Satisfaction and Students. Perceptions , 2015, J. Educ. Technol. Soc..

[22]  Francisco J. Martínez-López,et al.  An extension of the technology acceptance model for online learning environments , 2018, Interact. Learn. Environ..

[23]  Layla Safwat Jamil.  ASSESSING THE BEHAVIOURAL INTENTION OF STUDENTS TOWARDS LEARNING MANAGEMENT SYSTEM , THROUGH TECHNOLOGY ACCEPTANCE MODEL-CASE OF IRAQI UNIVERSITIES , 2017 .

[24]  Stephanie Hui-Wen Chuah.  You inspire me and make my life better: Investigating a multiple sequential mediation model of smartwatch continuance intention , 2019, Telematics Informatics.

[25]  Muhammad Imtiaz Shafiq,et al.  Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM) , 2020, Technology in Society.

[26]  Cheryl Burke Jarvis,et al.  The problem of measurement model misspecification in behavioral and organizational research and some recommended solutions. , 2005, The Journal of applied psychology.

[27]  Ronny Scherer,et al.  The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers' adoption of digital technology in education , 2019, Comput. Educ..

[28]  P. Sheeran,et al.  Prediction and Intervention in Health-Related Behavior: A Meta-Analytic Review of Protection Motivation Theory , 2000 .

[29]  Eylem Kiliç,et al.  Learning with interactive whiteboards: Determining the factors on promoting interactive whiteboards to students by Technology Acceptance Model , 2015, Interact. Technol. Smart Educ..

[30]  Bongwon Suh,et al.  Leveraging Smartwatches to Estimate Students' Perceived Difficulty and Interest in Online Video Lectures , 2019, ICETC.

[31]  John Orwat,et al.  A Protection Motivation Theory application to date rape education , 2011, Psychology, health & medicine.

[32]  Merrill Warkentin,et al.  Fear Appeals and Information Security Behaviors: An Empirical Study , 2010, MIS Q..

[33]  Hyeon Woo Lee,et al.  Integrating user interface and personal innovativeness into the TAM for mobile learning in Cyber University , 2014, J. Comput. High. Educ..

[34]  H. Moed,et al.  Business Research , 1938, Nature.

[35]  Khaled Shaalan,et al.  Exploring Students’ Acceptance of E-Learning Through the Development of a Comprehensive Technology Acceptance Model , 2019, IEEE Access.

[36]  B. Berg.  Qualitative Research Methods for the Social Sciences , 1989 .

[37]  Marko Sarstedt,et al.  Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research , 2014 .

[38]  Robert Willis,et al.  Towards closing the gender gap in Iraq: understanding gender differences in smartphone adoption and use , 2019, Inf. Technol. Dev..

[39]  L. Kaljee,et al.  Evaluation of Three Adolescent Sexual Health Programs in Ha Noi and Khanh Hoa Province, Vietnam , 2012, AIDS research and treatment.

[40]  Andrina Granic,et al.  Technology acceptance model: a literature review from 1986 to 2013 , 2014, Universal Access in the Information Society.

[41]  Gerjo Kok,et al.  Evaluating traffic informers: testing the behavioral and social-cognitive effects of an adolescent bicycle safety education program. , 2014, Accident Analysis and Prevention.

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

[43]  Mahmood Shah,et al.  Employees' behavioural intention to smartphone security: A gender-based, cross-national study , 2020, Comput. Hum. Behav..

[44]  Chung-Hung Tsai,et al.  A Study of Personal Health Record User’s Behavioral Model Based on the PMT and UTAUT Integrative Perspective , 2016, International journal of environmental research and public health.

[45]  Imran A. Zualkernan,et al.  Smartwatches for Context-Aware Ubiquitous Learning , 2019, Project and Design Literacy as Cornerstones of Smart Education.

[46]  Manuel Caeiro,et al.  Towards the use of commercial wrist wearables in education , 2017, 2017 4th Experiment@International Conference (exp.at'17).

[47]  Rupert Ward,et al.  Developing a General Extended Technology Acceptance Model for E-Learning (GETAMEL) by analysing commonly used external factors , 2016, Comput. Hum. Behav..

[48]  Alain Yee-Loong Chong,et al.  An updated and expanded assessment of PLS-SEM in information systems research , 2017, Ind. Manag. Data Syst..

[49]  Mikko T. Siponen,et al.  Which Factors Explain Employees' Adherence to Information Security Policies? An Empirical Study , 2007, PACIS.

[50]  Marko Sarstedt,et al.  PLS-SEM: Indeed a Silver Bullet , 2011 .

[51]  Ali Tarhini,et al.  Towards the Acceptance of RSS to Support Learning: An Empirical Study to Validate the Technology Acceptance Model in Lebanon. , 2015 .

[52]  S. Kong,et al.  Investigating Students’ Acceptance of a Statistics Learning Platform Using Technology Acceptance Model , 2017 .

[53]  Jun-ichi Takada,et al.  IMPACT OF LEARNING CONTENT ON WORLD HERITAGE SITE PRESERVATION AWARENESS IN TOWN OF LUANG PRABANG, LAO PDR: APPLICATION OF PROTECTION MOTIVATION THEORY , 2015 .

[54]  James B. Wilcox,et al.  The Pretest in Survey Research: Issues and Preliminary Findings: , 1982 .

[55]  Mehmet Cem Bölen.  Exploring the determinants of users’ continuance intention in smartwatches , 2020 .

[56]  Silas Formunyuy Verkijika,et al.  Understanding smartphone security behaviors: An extension of the protection motivation theory with anticipated regret , 2018, Comput. Secur..

[57]  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.

[58]  Nikola Marangunic,et al.  Technology acceptance model in educational context: A systematic literature review , 2019, Br. J. Educ. Technol..

[59]  Li-Chiou Chen,et al.  A security risk perception model for the adoption of mobile devices in the healthcare industry , 2019, Security Journal.

[60]  E. Seydel,et al.  Protection Motivation Theory , 2022 .

[61]  Younghwa Lee,et al.  Threat or coping appraisal: determinants of SMB executives’ decision to adopt anti-malware software , 2009, Eur. J. Inf. Syst..

[62]  Deborah Compeau,et al.  Computer Self-Efficacy: Development of a Measure and Initial Test , 1995, MIS Q..

[63]  Wu-Yuin Hwang,et al.  A Study of the Use of Wearable Devices for Healthy and Enjoyable English as a Foreign Language Learning in Authentic Contexts , 2018, J. Educ. Technol. Soc..

[64]  Sureni Weerasinghe Mrs,et al.  Technology Acceptance Model in the Domains of LIS and Education: A Review of Selected Literature , 2017 .

[65]  Viswanath Venkatesh,et al.  Technology Acceptance Model 3 and a Research Agenda on Interventions , 2008, Decis. Sci..

[66]  Nisreen Ameen.  Arab users' acceptance and use of mobile phones : a case of young users in Iraq, Jordan and UAE , 2017 .

[67]  Natalie Gerhart,et al.  Watch It! Factors Driving Continued Feature Use of the Smartwatch , 2018, Int. J. Hum. Comput. Interact..

[68]  Rastislav Metruk,et al.  DEVELOPING ENGLISH SKILLS BY MEANS OF MOBILE APPLICATIONS , 2018 .

[69]  Dong-Hee Shin,et al.  An acceptance model for smart watches: Implications for the adoption of future wearable technology , 2015, Internet Res..

[70]  Ali Kashif Bashir,et al.  Investigating the Acceptance of Mobile Library Applications with an Extended Technology Acceptance Model (TAM) , 2020, Comput. Educ..

[71]  Michael Foth,et al.  Technology acceptance as an influencing factor of hospital employees’ compliance with data‐protection standards in Germany , 2012, Journal of Public Health.

[72]  Mohammed Amin Almaiah,et al.  Extending the TAM to examine the effects of quality features on mobile learning acceptance , 2016, Journal of Computers in Education.

[73]  Thad Starner,et al.  Towards haptic learning on a smartwatch , 2018, UbiComp.

[74]  M. Katz,et al.  Development of an Educational Video to Improve Patient Knowledge and Communication with Their Healthcare Providers about Colorectal Cancer Screening , 2009, American journal of health education.

[75]  Rudy Hirschheim,et al.  A paradigmatic and methodological examination of information systems research from 1991 to 2001 , 2004, Inf. Syst. J..

[76]  Riaan Rudman,et al.  Addressing the incremental risks associated with adopting Bring Your Own Device , 2018 .

[77]  Xinguang Chen,et al.  Effects Through 24 Months of an HIV/AIDS Prevention Intervention Program Based on Protection Motivation Theory Among Preadolescents in the Bahamas , 2009, Pediatrics.

[78]  Philip E. T. Lewis,et al.  Research Methods for Business Students , 2006 .

[79]  Robert P. Minch,et al.  Application of Protection Motivation Theory to Adoption of Protective Technologies , 2009, 2009 42nd Hawaii International Conference on System Sciences.

[80]  Nils Urbach,et al.  Structural Equation Modeling in Information Systems Research Using Partial Least Squares , 2010 .

[81]  Robert P. Minch,et al.  Application of Protection Motivation Theory to Adoption of Protective Technologies , 2009 .

[82]  Irene Woon,et al.  A Protection Motivation Theory Approach to Home Wireless Security , 2005, ICIS.

[83]  Chiyoung Cha,et al.  The effects of STI education on Korean adolescents using smartphone applications , 2017 .

[84]  Yiwen Gao,et al.  An empirical study of wearable technology acceptance in healthcare , 2015, Ind. Manag. Data Syst..

[85]  Vincent Dutot,et al.  Applying the technology acceptance model in a three-countries study of smartwatch adoption , 2019, The Journal of High Technology Management Research.

[86]  L. Goldenhar,et al.  Operationalizing Theoretical Constructs in Bloodborne Pathogens Training Curriculum , 1996, Health education quarterly.

[87]  Said A. Salloum,et al.  An empirical examination of continuous intention to use m-learning: An integrated model , 2020, Education and Information Technologies.

[88]  J. Wilcox,et al.  The Pretest in Survey Research: Issues and Preliminary Findings , 1982 .

[89]  Younghwa Lee,et al.  Understanding anti-plagiarism software adoption: An extended protection motivation theory perspective , 2011, Decis. Support Syst..

[90]  Mostafa Al-Emran,et al.  What impacts learning with wearables? An integrated theoretical model , 2020, Interact. Learn. Environ..

[91]  Bum Soo Chon,et al.  Determinants of the Intention to Protect Personal Information among Facebook Users , 2018 .

[92]  Kevin Ashford-Rowe,et al.  EDUCAUSE Horizon Report: 2019 Higher Education Edition. , 2019 .

[93]  Keng Siau,et al.  Factors Influencing the Adoption of Smart Wearable Devices , 2018, Int. J. Hum. Comput. Interact..

[94]  J. Hair.  Multivariate data analysis : a global perspective , 2010 .

[95]  Carman Neustaedter,et al.  Assessing the usability of smartwatches for academic cheating during exams , 2017, MobileHCI.

[96]  AbdullahFazil,et al.  Developing a General Extended Technology Acceptance Model for E-Learning (GETAMEL) by analysing commonly used external factors , 2016 .

[97]  S. Prentice-Dunn,et al.  Psychosocial predictors of intentions to comply with bariatric surgery guidelines , 2010, Psychology, health & medicine.

[98]  E. Mohammadi,et al.  Barriers and facilitators related to the implementation of a physiological track and trigger system: A systematic review of the qualitative evidence , 2017, International journal for quality in health care : journal of the International Society for Quality in Health Care.