Mobile devices (m-devices) are transforming the global landscape of education. These handheld gadgets enhance medical students’ learning simultaneously. This study looked into the behavioral intentions of Pakistani medical students toward learning through m-devices.
Methods
Uses & gratifications theory and theory of planned behavior were adopted as conceptual frameworks. Data were collected from 310 medical students from 1st year to 5th year. The study used structural equation modeling to assess its hypotheses.
Results and Discussion
The results of this empirical investigation indicated that medical students opted for m-learning with the motivation of information-seeking and trust. Moreover, medical students perceived behavioral control is affected by information-seeking, trust, attitude, and subjective norms. Whereas, attitude, perceived behavioral control, information-seeking, and trust are positively associated with the behavioral intentions of medical students when they use their m-devices for academic purposes.
Practical implications
This study will shed light on several of practical implications for concerned policymakers to create strategies that will directly leverage m-learning in medical education from the eyes of less-resourced country (Pakistan). Moreover, this proposed conceptual model could increase the awareness of medical institutions and facilitate dealing with the impacts of these factors on students’ behavior.
Significance of the Study
To the best of our knowledge, this study is among a few attempts to understand medical students’ motivational factors behind their behavioral intentions while using m-devices academically. Resultantly, this study adds to the theoretical understanding of the variables influencing Pakistani medical students’ m-learning behavioral intention in this setting. Secondly, this proposed conceptual model could increase the awareness of medical institutions and facilitate dealing with the impacts of these factors on students’ behavior.
AbdusalomovSMannopO (2022) Mobile-Assisted Language Learning. In Advances in Educational Technologies and Instructional Design Book Series. USA: IGI Global DOI: https://doi.org/10.4018/978-1-6684-5400-8.ch003.
2.
AhadADAnshariM (2017) Smartphone habits among youth. International Journal of Cyber Behavior,Psychology and Learning7(1): 65–75. doi: 10.4018/IJCBPL.2017010105.
3.
AjzenI (2011) The theory of planned behavior: Reactions and reflections. Psychology & Health26(9): 1113–1127.
4.
Al-SousNAlmajaliDDahalinZ (2022) Understanding the role of the bring-your-own-device policy in m-learning behavioral usage. International Journal of Data and Network Science6(4): 1187–1194.
5.
AlkhalifahTde VriesDRampersadG (2017, December) Mobile learning adoption in developing countries. In: Proceedings of the 9th international conference on education technology and computers, pp.89–93.
6.
AlkhwaldiAF (2024) Investigating the social sustainability of immersive virtual technologies in higher educational institutions: Students’ perceptions toward metaverse technology. Sustainability16(2): 934.
7.
AmjadNWoodAM (2009) Identifying and changing the normative beliefs about aggression that lead young Muslim adults to join extremist anti-Semitic groups in Pakistan. Aggressive Behavior35(6): 514–519.
8.
AndersonJCGerbingDW (1988) Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin103(3): 411.
9.
AziziSMKhatonyA (2019) Investigating factors affecting medical sciences students’ intention to adopt m-learning. BMC Medical Education19(1): 1–10.
10.
AzraNSameerNKulsoomG (2022) The outcomes of a mobile just-in-time-learning intervention for teaching bioethics in Pakistan. BMC Medical Education22(1). doi: https://doi.org/10.1186/s12909-022-03698-9.
11.
BaoZShangB (2021). Self-efficacy and continuance intention of Web 2.0 platforms: a meta-analysis. Data Technologies and Applications55(4): 511–526.
12.
BasakSKWottoMBélangerP (2020) International students’ gender impact to use Mobile learning in tertiary education. In: Inventive Communication and Computational Technologies: Proceedings of ICICCT 2019, pp.1179–1190: Springer Singapore.
13.
BlumlerJGKatzE (eds.) (1974) The Uses of Mass Communications: Current Perspectives on Gratifications Research. Beverly Hills: Sage Publications, Canada, pp.19–31.
14.
BoruffJTStorieD (2014) Mobile devices in medicine: A survey of how medical students, residents, and faculty use smartphones and other mobile devices to find information. Journal of the Medical Library Association: JMLA102(1): 22–30.
15.
Briz-PonceLPereiraACarvalhoL, et al. (2017) Learning with mobile technologies–students’ behavior. Computers in Human Behavior72: 612–620.
16.
ChahalJBaberH (2024) University or personal sustainability—what shapes sustainable entrepreneurship intentions of students?Journal of Entrepreneurship and Innovation in Emerging Economies23939575241237940.
17.
ChandranVPBalakrishnanARashidM, et al. (2022) Mobile applications in medical education: A systematic review and meta-analysis. PLoS ONE17(3): e0265927.
18.
ChaseTJJuliusAChandanJS, et al. (2018) Mobile learning in medicine: an evaluation of attitudes and behaviours of medical students. BMC medical education18(1): –8.
19.
ChenGM (2011) Tweet this: A uses and gratifications perspective on how active twitter use gratifies a need to connect with others. Computers in Human Behavior27(2): 755–762.
20.
CheonJLeeSCrooksSM, et al. (2012) An investigation of m-learning readiness in higher education based on the theory of planned behavior. Computers & Education59(3): 1054–1064.
21.
ConnerMArmitageCJ (1998) Extending the theory of planned behavior: A review and avenues for further research. Journal of Applied Social Psychology28(1): 1429–1464.
22.
de JongeLPMestersIGovaertsMJ, et al. (2020) Supervisors’ intention to observe clinical task performance: An exploratory study using the theory of planned behaviour during postgraduate medical training. BMC medical Education20: 1–10.
23.
EllawayRHFinkPGravesL, et al. (2014) Left to their own devices: Medical learners’ use of mobile technologies. Medical Teacher36(2): 130–138.
24.
EomS (2023) The effects of the use of mobile devices on the E-learning process and perceived learning outcomes in university online education. E-learning and Digital media20(1): 80–101.
25.
FarooqFRathoreFAMansoorSN (2020) Challenges of online medical education in Pakistan during COVID-19 pandemic. Journal of the College of Physicians and Surgeons Pakistan30(6): 67–69.
26.
FishbeinMAjzenI (1975) Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Reading, MA: Addison-Wesley.
27.
FlorenthalB (2019) Students’ motivation to participate via Mobile technology in the classroom: A uses and gratifications approach. Journal of Marketing Education41(3): 234–253.
28.
GaoXZhangYCaiX (2019) Status seeking and conspicuous consumption: A systematic review and meta-analysis. International Journal of Consumer Studies43(1): 15–26.
29.
GaskinJLimJ (2016) “Model Fit Measures”, AMOS Plugin. Gaskination's StatWiki.
30.
GerlichRNDrumhellerKBabbJ, et al. (2015) App consumption: An exploratory analysis of the uses & gratifications of mobile apps. Academy of Marketing Studies Journal19(1): 69.
31.
GormleyGJCollinsKBoohanM, et al. (2009) Is there a place for e-learning in clinical skills? A survey of undergraduate medical students’ experiences and attitudes. Medical Teacher31(1): e6–e12.
32.
GreenBLKennedyIHassanzadehH, et al. (2015) A semi-quantitative and thematic analysis of medical student attitudes towards M-L earning. Journal of Evaluation in Clinical Practice21(5): 925–930.
33.
GuoZTanFBCheungK (2010) Students’ uses and gratifications for using computer-mediated communication media in learning contexts. Communications of the Association for Information Systems27: 339–378.
34.
HarrietKLRichardB (2017) Mobile learning in developing countries: A synthesis of the past to define the future. World Academy of Science, Engineering and Technology, International Journal of Educational and Pedagogical Sciences11(2): 448–455. DOI: https://doi.org/10.5281/ZENODO.1129069.
35.
HashmiFSSoroyaSHMahmoodK (2023) Knowledge sharing through social networking sites (SNSs): A study of Pakistani research students. Information Development39(4): 853–865.
36.
HashimKFTanFBRashidA (2015) Adult learners’ intention to adopt mobile learning: A motivational perspective. British Journal of Educational Technology46(2): 381–390.
37.
HayatAAKeshavarziMHZareS, et al. (2021) Challenges and opportunities from the COVID-19 pandemic in medical education: A qualitative study. BMC Medical Education21(1): 247.
38.
HsiaoCHChenCC (2015) Critical factors influencing physicians’ intention to use computerized clinical practice guidelines: An integration of decision-making theory and technology acceptance model. Computers in Human Behavior43: 125–137.
39.
HuLTBentlerPM (1999) Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal6(1): 1–55.
40.
ImtiazMFarooqRMunirMA (2021) Problems of medical education in Pakistan. Pakistan Journal of Medical and Health Sciences15(11): 3476–3478.
41.
ImtinanUChangVIssaT (2012) Characteristics of mobile learning environments in developing countries. The International Journal of Learning18(5): 163–173.
42.
IqbalSQureshiIA (2012) M-learning adoption: A perspective from a developing country. International Review of Research in Open and Distributed Learning13(3): 147–164.
43.
IslamTMahmoodKSadiqM, et al. (2020) Understanding knowledgeable workers’ behavior toward COVID-19 information sharing through WhatsApp in Pakistan. Frontiers in Psychology11: 572526.
44.
JamalATemsahMHKhanSA, et al. (2016) Mobile phone use among medical residents: A cross-sectional multicenter survey in Saudi Arabia. JMIR mHealth and UHealth4(2): e61.
45.
JamilA (2023) An empirical study on academic sustainability of mobile learning at university level. Pakistan journal of educational research6(2). doi: https://doi.org/10.52337/pjer.v6i2.788.
46.
KhanHMalikA (2021) Academic use of smartphones among medical students in Pakistan. Information Development38(2) 299–309.
47.
KucukSBaydas OnluOKapakinS (2020) A model for medical students’ behavioral intention to use m-learning. Journal of Medical Education and Curricular Development7: 2382120520973222.
48.
LatifMZHussainISaeedR, et al. (2019) Use of smartphones and social media in medical education: Trends, advantages, challenges, and barriers. Acta Informatica medica27(2): 133.
49.
LeungLWeiR (2000) More than just talk on the move: Uses and gratifications of the cellular phone. Journalism and Mass Communication Quarterly77(2): 308–320.
50.
LiawSSHuangHM (2015) How factors of personal attitudes and learning environments affect gender difference toward mobile learning acceptance. The International Review of Research in Open and Distributed Learning16(4).
51.
LinCA (1998) Exploring personal computer adoption dynamics. Journal of Broadcasting & Electronic Media42(1): 95–112.
52.
LinYHHsuCLChenMF, et al. (2017) New gratifications for social word-of-mouth spread via mobile SNSs: Uses and gratifications approach with a perspective of media technology. Telematics and Informatics34(4): 382–397.
53.
MaassenOFritschSGantnerJ, et al. (2020) Future mobile device usage, requirements, and expectations of physicians in German university hospitals: Web-based survey. Journal of Medical Internet Research22(12): e23955.
54.
MalikAIslamTAhmadM, et al. (2023) Health information-seeking and sharing behavior of young adults on social media in Pakistan. Journal of Librarianship and Information Science55(3): 579–595.
55.
MickanSAthertonHRobertsNW, et al. (2014) Use of handheld computers in clinical practice: A systematic review. BMC Medical Informatics and Decision Making14(1): 1–10.
56.
MinZ (2023) Mobile technology-powered education in developing countries. Science Insights Education Frontiers15(1): 2147–2148.
57.
MohanVNAlexanderT (2022) Mobile cloud computing in healthcare. In: Industry 4.0 Technologies for Education. USA: Auerbach Publications, pp. 381–391.
58.
NaqviAMHJiangYMiaoM, et al. (2020) The effect of social influence, trust, and entertainment value on social media use: Evidence from Pakistan. Cogent Business & Management7(1): 1723825.
59.
NaseemANizamuddinSGhiasK (2022) The outcomes of a mobile just-in-time-learning intervention for teaching bioethics in Pakistan. BMC Medical Education22(1): 674.
60.
PavlouPAFygensonM (2006) Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS Quarterly30(1): 115–143.
61.
PerksLGTurnerJSTollisonAC (2019) Podcast uses and gratifications scale development. Journal of Broadcasting & Electronic media63(4): 617–634.
62.
RazaSAUmerAQaziW, et al. (2018) The effects of attitudinal, normative, and control beliefs on m-learning adoption among the students of higher education in Pakistan. Journal of Educational Computing Research56(4): 563–588.
63.
ReychavIMcHaneyR (2017) The relationship between gender and mobile technology use in collaborative learning settings: An empirical investigation. Computers & Education113: 61–74.
64.
RichAMedisauskaiteAPottsHW, et al. (2020) A theory-based study of doctors’ intentions to engage in professional behaviors. BMC Medical Education20(1): 1–10.
65.
RobinsonR (2015) Spectrum of tablet computer use by medical students and residents at an academic medical center. PeerJ3: e1133.
66.
SaeedSShahBAliAB, et al. (2021) E-learning experience of medical and dental students from private colleges of Karachi, during COVID-19. Journal of Bahria University Medical and Dental College11(2): 76–80.
67.
ShahJHaqUBashirA, et al. (2016) Awareness of academic use of smartphones and medical apps among medical students in a private medical college. Journal of Pakistan Medical Association66(2): 184–186.
68.
ShiueYM (2007) Investigating the sources of teachers’ instructional technology use through the decomposed theory of planned behavior. Journal of Educational Computing Research36(4): 425–453.
69.
SoaresD and Nursalam (2023) The use of digital technology in health learning during the COVID-19 pandemic: A systematic review. Journal of the Pakistan Medical Association73(02): S135–S139.
70.
TagoeMAAbakahE (2014) Determining distance education Students’ readiness for M-learning at university of Ghana using the theory of planned behavior. International Journal of Education and Development Using Information and Communication Technology10(1): 91–106.
71.
VenkateshVDavisFD (2000) A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science46(2): 186–204.
72.
WangYLiMLiZ (2019) Understanding user behavior in mobile health applications: A meta-analysis. International Journal of Human-Computer Interaction35(1): 33–43.
WittREKebaetseMBHolmesJH, et al. (2016) The role of tablets in accessing information throughout undergraduate medical education in Botswana. International Journal of Medical Informatics88: 71–77.
75.
YamaneT.LamolaA. A. (1967). Sensitized photodimerization of thymine in DNA. Proceedings of the National Academy of Sciences, 58(2), 443–446.
76.
YamaneTLamolaAA (1967) Sensitized photodimerization of thymine in DNA. Proceedings of the National Academy of Sciences58(2): 443–446.
77.
ZhangYZhaoJLiZ (2018) Understanding user experience in mobile apps: A systematic review. International Journal of Human-Computer Interaction34(1): 23–35.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
