Abstract
The databases’ information and associated analytical approaches are gaining an ever-greater role in making business decisions, thus increasing the need for highly educated employees with good expertise of statistical support software that provides support for analysis of complex databases. This article presents a cross-national analysis regarding the adoption and use of statistical support software SPSS in higher education among students from Slovenia, Malaysia and Turkey. We present a conceptual model, based on TAM (Technology Acceptance Model) and we compared it in different national contexts. The conceptual model was tested using SEM (structural equation modeling). Despite different cultural and geographical differences, we found that the three models as a whole do not significantly differ, however, vary considerable differences between individual constructs by countries were identified. Students from Malaysia and Turkey are perceiving greater benefits of using of SPSS in future, show greater compatibility of SPSS with the academic needs, and have more positive attitude towards the use of SPSS as well as higher perceived usefulness of statistics as students from Slovenia.
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References
Abbas, T.: Social factors affecting students’ acceptance of e-learning environments in developing and developed countries: a structural equation modeling approach. J. Hosp. Tour. Technol. 7(2), 200–212 (2016)
Abbasi, M.S., Tarhini, A., Elyas, T., Shah, F.: Impact of individualism and collectivism over the individual’s technology acceptance behaviour: a multi-group analysis between Pakistan and Turkey. J. Enterp. Inf. Manag. 28(6), 747–768 (2015)
Abbass, R., Mesch, G.S.: Cultural values and facebook use among palestinian youth in Israel. Comput. Hum. Behav. 48, 644–653 (2015)
Adam, W.C., Infeld, D.L., Wulff, C.M.: Statistical software for curriculum and careers. J. Public Aff. Educ. 18(1), 173–188 (2018)
Aguilera-Hermida, A.P., Quiroga-Garza, A., Gómez-Mendoza, S., Del Río Villanueva, C.A., AvolioAlecchi, B., Avci, D.: Comparison of students’ use and acceptance of emergency online learning due to COVID-19 in the USA, Mexico, Peru, and Turkey. Educ. Inf. Technol. 26, 6823–6845 (2021)
Al-Khateeb, F.B.: Predicting internet usage in two emerging economies using an extended technology acceptance model (TAM). Proceedings of the 2007 International Symposium on Collaborative Technologies and Systems, CTS (2007)
Alshare, K.A., Mesak, H.I., Grandon, E.E., Badri, M.A.: Examining the moderating role of national culture on an extended technology acceptance model. J. Glob. Inf. Technol. Manag. 14(3), 27–53 (2011)
Alzaidi, M.S., Shehawy, Y.M.: Cross-national differences in mobile learning adoption during COVID-19. Educ. + Train. 64(3), 305–328 (2022)
Anders, D.O., Lindberg, O.J., Fransson, G.: Students’ voices about information and communication technology in upper secondary schools. Int. J. Inf. Learn. Technol. 35(2), 82–92 (2018)
Arenas-Gaitán, J., Ramírez-Correa, P.E., Rondán-Cataluña, F.J.: Cross cultural analysis of the use and perceptions of web based learning systems. Comput. Educ. 57(2), 1762–1774 (2011)
Bagozzi, R.P., Yi, Y.: On the evaluation of structural equation model. J. Acad. Mark. Sci. 16(1), 74–94 (1998)
Bayliss, L.: Demystifying data: a constructivist approach to teaching statistical concepts using SPSS. J. Public Relat. Educ. 6(1), 58–84 (2020)
Brezavšček, A., Šparl, P., Žnidaršič, A.: Factors influencing the behavioural intention to use statistical software: the perspective of the slovenian students of social sciences. EURASIA J. Math. Sci. Technol. Educ. 13(3), 953–986 (2017)
Campbell, D.T.: Recommendations for APA test standards regarding construct, trait, or discriminant validity. Am. Psychol. 15(8), 546–553 (1960)
Campbell, S.W.: A cross-cultural comparison of perceptions and uses of mobile telephony. New Media Soc. 9(2), 343–363 (2007)
Chiang, D., Brooks, C., Chen, H.: Cross-cultural social contexts: a comparison of Chinese and US students’ experiences in active learning classrooms. Interact. Learn. Environ. (2020). https://doi.org/10.1080/10494820.2020.1855206
Cho, J.H., Erin, L., Quinlan, M.: Cross-national comparisons of college students’ attitudes toward diet/fitness apps on smartphones. J. Am. Coll. Health 65(7), 437–449 (2017)
Choi, J., Geistfeld, L.V.: A cross-cultural investigation of consumer e-shopping adoption. J. Econ. Psychol. 25(6), 821–838 (2004)
Choi, K.S., Im, I., Hofstede, G.J.: A cross-cultural comparative analysis of small group collaboration using mobile twitter. Comput. Hum. Behav. 65, 308–318 (2016)
Cox, T.H., Lobel, S.A., McLeod, P.L.: Effects of ethnic group cultural differences on cooperative and competitive behavior on a group task. Acad. Manag. J. 34(4), 827–847 (1991)
Davis, F.D., Bagozzi, R.P., Warshaw, P.R.: User acceptance of computer technology: a comparison of two theoretical models. Manag. Sci. 35(8), 982–1002 (1989)
Dutot, V., Bhatiasevi, V., Bellallahom, N.: Applying the technology acceptance model in a three-countries study of smartwatch adoption. J. High Technol. Manag. Res. 30(2), 1–14 (2019)
Farinosi, M., Lim, C., Roll, J.: Book or screen, pen or keyboard? A cross-cultural sociological analysis of writing and reading habits basing on Germany, Italy and the UK. Telemat. Inform. 33(2), 410–421 (2016)
Field, A.: Discovering Statistics Using SPSS. Sage, London (2009)
Forbush, E., Foucault-Welles, B.: Social media use and adaptation among Chinese students beginning to study in the United States. Int. J. Intercult. Relat. 50, 1–12 (2016)
Fusilier, M., Durlabhji, S., Cucchi, A.: An investigation of the integrated model of user technology acceptance: internet user samples in four countries. J. Educ. Comput. Res. 38(2), 155–182 (2008)
Geisser, S.: A predictive approach to the random effect model. Biometrika 61(1), 101–107 (1974)
Gonulal, T.: Statistical knowledge and training in second language acquisition. The case of doctoral students. ITL Int. J. Appl. Linguistics 171(1), 62–89 (2020)
Grandon, E.E., Alshare, K., Kwun, O.: Factors influencing student intention to adopt online classes: a cross-cultural study. J. Comput. Sci. Coll. 20(4), 46–56 (2005)
Grant, C.A., Sleeter, C.E.: Race, class, gender, and disability in the classroom. In: Multicultural Education Issues and Perspectives. John Wiley & Sons, Hoboken (2010)
Gray, C.D., Kunnear, P.R.: IBM SPSS Statistics 19 Made Simple. Taylor & Francis Group, New York (2011)
Grimes, P.W.: Dishonesty in academics and business: a cross-cultural evaluation of student attitudes. J. Bus. Ethics 49(3), 273–290 (2004)
Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E.: Multivariate Data Analysis. Prentice Hall, New Jersey (2010)
Hartzel, K.S., Marley, K.A., Spangler, W.E.: Online social network adoption: a cross-cultural study. J. Comput. Inf. Syst. 56(2), 87–96 (2016)
Hsu, M.K., Wang, S.W., Chin, K.K.: Computer attitude, statistics anxiety and selfefficacy on statistical software adoption behavior: an empirical study of online MBA learners. Comput. Hum. Behav. 25(2), 412–420 (2009)
Huang, F., Teo, T., Sánchez-Prieto, J.C., García-Peñalvo, F.J., Olmos-Migueláñez, S.: Cultural values and technology adoption: a model comparison with university teachers from China and Spain. Comput. Educ. 133, 69–81 (2019)
Im, I., Hing, S., Kang, M.S.: An international comparison of technology adoption Testing the UTAUT model. Inf. Manag. 48, 1–8 (2011)
Keil, M., Tan, B.C.Y., Wei, K.K., Saarinen, T., Tuunainen, V., Wassenaar, A.: A cross-cultural study on escalation of commitment behavior in software projects. MIS Q. 24(2), 299–325 (2000)
Kim, Y., Sohn, D., Choi, S.M.: Cultural difference in motivations for using social network sites: a comparative study of American and Korean college students. Comput. Hum. Behav. 27(1), 365–372 (2011)
Kock, N.: WarpPLS 5.0 User Manual. ScriptWarp Systems Laredo, Texas (2015)
Kurt, O.E., Tingöy, O.: The acceptance and use of a virtual learning environment in higher education: an empirical study in Turkey, and the UK. Int. J. Educ. Technol. High. Educ. 14, 26 (2017)
Lee, J.-W.: Online support service quality, online learning acceptance, and student satisfaction. Internet High. Educ. 13(4), 277–283 (2010)
Lee, I., Choi, B., Kim, J., Hong, S.-J.: Culture-technology fit: effects of cultural characteristics on the post-adoption beliefs of mobile internet users. Int. J. Electron. Commer. 11(4), 11–51 (2014)
Leidner, D.E., Kayworth, T.K.: Review: a review of culture in information systems research: toward a theory of information technology culture conflict. MIS q. 30(2), 357–399 (2006)
Letchumanan, M., Muniandy, B.: Migrating to e-book: a study on perceived usefulness and ease of use. Library Hi Tech News 30(7), 10–15 (2013)
Li, N., Kirkup, G.: Gender and cultural differences in Internet use: a study of China and the UK. Comput. Educ. 48(2), 301–317 (2007)
Li, N., Kirkup, G., Hodgson, B.: Cross-cultural comparison of women students’ attitudes toward the internet and usage: China and the United Kingdom. Cyberpsychol. Behav. 4(3), 415–426 (2001)
Lin, S.H., Lee, H.-C., Chang, C.-T., Fu, C.J.: Behavioral intention towards mobile learning in Taiwan, China, Indonesia, and Vietnam. Technol. Soc. 63, 1–13 (2020)
Lindberg, J.O., Olofsson, A.D., Fransson, G.: Same but different? An examination of Swedish upper secondary school teachers’ and students’ views and use of ICT in education. Int. J. Inf. Learn. Technol. 34(2), 122–132 (2017)
Liu, X., Liu, S., Lee, S.-H., Magjuka, R.J.: Cultural differences in online learning: international student perceptions. Educ. Technol. Soc. 13(3), 177–188 (2010)
Masood, A., Lodhi, R.N.: Determinants of behavioral intentions to use SPSS among students: application of technology acceptance model (TAM). FWU J. Soc. Sci. 10(2), 146–152 (2016)
McCoy, S., Everard, A., Jones, B.M.: An Examination of the technology acceptance model in uruguay and the US: a focus on culture. J. Glob. Inf. Technol. Manag. 8(2), 27–45 (2005)
Mei, B., Brown, G.T.L., Teo, T.: Toward an understanding of preservice english as a foreign language teachers’ acceptance of computer-assisted language learning 2.0 in the People’s Republic of China. J. Educ. Comput. Res. 56(1), 74–104 (2018)
Muenchen, R. A. (2013). The Popularity of Data Analysis Software. r4stats.com http://immagic.com/eLibrary/ARCHIVES/GENERAL/BLOGS/R130203M.pdf (Accessed 12 July 2016).
Mulyan, R.S., Ridwan, M., Ilona, D.: Statistical software adoption behaviour among Indonesia’s undergraduate students. J. Phys. Conf. Ser. 1339(1), 1–9 (2019)
Nah, F.F., Tan, X., Teh, S.H.: An empirical investigation on end-users’ acceptance of enterprise systems. Inf. Res. Manag. J. 17(3), 32–53 (2004)
Nilsson, D.: A cross-cultural comparison of self-service technology use. Eur. J. Mark. 41(3/4), 367–381 (2007)
Nunnally, J.C.: Psychometric Theory. Mc-Graw-Hill Book Company, New York (1978)
Ozgur, C., Kleckner, M., Li, Y.: Selection of statistical software for solving big data problems: a guide for businesses, students, and Universities. SageOpen (2015). https://doi.org/10.1177/2158244015584379
Peters, A.N., Winschiers-Theophilus, H., Mennecke, B.E.: Cultural influences on facebook practices: a comparative study of college students in Namibia and the United States. Comput. Hum. Behav. 49, 259–271 (2015)
Purdie, N., Hattie, J., Douglas, G.: Student conceptions of learning and their use of self-regulated learning strategies: a cross-cultural comparison. J. Educ. Psychol. 88(1), 87–100 (1996)
Ratten, V.: Factors influencing consumer purchase intention of cloud computing in the United States and Turkey: the role of performance expectancy, ethical awareness and consumer innovation. EuroMed J. Bus. 10(1), 80–97 (2015)
Reisdorf, B.C.: Non-adoption of the internet in Great Britain and Sweden. Inf. Commun. Soc. 14(3), 400–420 (2011)
Saad, R., Bahli, B.: The impact of cognitive absorption on perceived usefulness and perceived ease of use in on-line learning: an extension of the technology acceptance model. Inf. & Manag. 42(2), 317–327 (2005)
Saeed, N., Sinnappan, S.: Multicultural Awareness and Technology in Higher Education: Global Perspectives. Comparing Learning Styles and Technology Acceptance of Two Culturally Different Groups of Students. IGI Global, Hershey (2014)
Sagi, J., Carayannis, E., Dasgupta, S., Thomas, G.: Globalization and e-commerce: a cross-cultural investigation of user attitudes. Adv. Top. Glob. Inf. Manag. 5, 128–148 (2006)
Salloum, S.A., Alhamad, A.Q.M., Al-Emran, M., Monem, A.A., Shaalan, K.: Exploring students’ acceptance of E-learning through the development of a comprehensive technology acceptance model. IEEE Access 7, 128445–128462 (2019)
Schepers, J., Wetzels, M.: A meta-analysis of the technology acceptance model: investigating subjective norm and moderation effects. Inf. Manag. 44, 90–103 (2007)
Schepers, J., Wetzels, M., de Ruyter, R.: Leadership styles in technology acceptance: do followers practice what leaders preach? Manag. Serv. Qual. 15(6), 496–508 (2005)
Šebjan, U., Tominc, P.: Impact of support of teacher and compatibility with needs of study on usefulness of SPSS by students. Comput. Hum. Behav. 53, 354–365 (2015)
Sensales, G., Greenfield, P.M.: Attitudes toward computers, science, and technology a cross-cultural comparison between students in Rome and los angeles. J. Cross Cult. Psychol. 26(3), 229–242 (1995)
Šerić, M.: Have social media made their way in classrooms? a study at three European universities. J. Int. Commun. 25(2), 230–253 (2019)
Shepherd, T.L., Linn, D.: Behavior and Classroom Management in the Multicultural Classroom: Proactive, Active, and Reactive strategies. Sage, Singapore (2015)
Shukla, S., Kumar, R.: Researcher intention to use statistical software: examine the role of statistical anxiety, self-efficacy and enjoyment. Int. J. Technol. Hum. Interact. 16(3), 39–55 (2020)
Singh, N., Fassott, G., Cha, M.C.H., Hoffman, J.A.: Understanding international web site usage a cross-national study of German, Brazilian, and Taiwanese online consumers. Int. Mark. Rev. 23(1), 83–97 (2006)
Song, Y., Kong, S.-C.: Investigating students’ acceptance of a statistics learning platform using technology acceptance model. J. Educ. Comput. Res. 55(6), 865–897 (2017)
Srite, M.: Culture as an explanation of technology acceptance differences: an empirical investigation of Chinese and US users. Australas. J. Inf. Syst. 14(1), 5–26 (2006)
Stone, M.: Cross-validatory choice and assessment of statistical predictions. J. r. Stat. Soc. 36(2), 111–133 (1974)
Straub, D., Keil, M., Brenner, W.: Testing the technology acceptance model across cultures: a three country study. Inf. Manag. 33(1), 1–11 (1997)
Sukendro, S., Habibi, A., Khaeruddin, K., Indrayana, B., Syahruddin, S., Makadada, F.A., Hakim, H.: Using an extended technology acceptance model to understand students’ use of e-learning during Covid-19: Indonesian sport science education context. Heliyon 6(11), 1–9 (2020)
Sung, R., Mayer, R.E.: Students’ beliefs about mobile devices versus desktop computers in South Korea and the United States. Comput. Educ. 59(4), 1328–1338 (2012)
Tarhini, A., Hone, K., Liu, X.: A cross-cultural examination of the impact of social, organisational and individual factors on educational technology acceptance between British and Lebanese university students. Br. J. Edu. Technol. 46(4), 739–755 (2015a)
Tarhini, A., Scott, M.J., Sharma, S.K., Abbasi, M.S.: Differences in intention to use educational RSS feeds between Lebanese and British students: a multi-group analysis based on the technology acceptance model. Electron. J. e-Learn. 13(1), 14–29 (2015b)
Tenenhaus, M., Vinzi, V.E., Chatelin, Y.-M., Lauro, C.: PLS path modeling. Comput. Stat. Data Anal. 48(1), 159–205 (2005)
Teo, T., Luan, W.S., Sing, C.C.: A cross-cultural examination of the intention to use technology between Singaporean and Malaysian pre-service teachers: an application of the technology acceptance model (TAM). J. Educ. Technol. Soc. 11(4), 265–280 (2008)
Teo, T., Lee, C.B., Wong, S.L.: Assessing the intention to use technology among pre-service teachers in Singapore and Malaysia: a multigroup invariance analysis of the technology acceptance model (TAM). Comput. Educ. 53(3), 1000–1009 (2009)
Terzis, V., Moridis, C.N., Economides, A.A., Mendez, G.R.: Computer based assessment acceptance: a cross-cultural study in Greece and Mexico. Educ. Technol. Soc. 16(3), 411–424 (2013)
Tham, Y.: Trade in higher education services in Malaysia: key policy challenges. High Educ. Pol. 23(1), 99–122 (2010)
Tham, S.Y., Kam, A.J.: Internationalising higher education: comparing the challenges of different higher education institutions in Malaysia. Asia Pacific J. Educ. 28, 353 (2008)
Unesco. (2015). Education for all 2000-2015: Achievements and challenges. United Nations Educational, Scientific and Cultural Organization, Paris
Venkatesh, V., Davis, F.D.: A model of the antecedents of perceived ease of use: development and test. Decis. Sci. 27(3), 451–481 (1996)
Viberg, O., Grönlund, A.: Cross-cultural analysis of users’ attitudes toward the use of mobile devices in second and foreign language learning in higher education: a case from Sweden and China. Comput. Educ. 69, 169–180 (2013)
Wong, S.L., Teo, T. (2009). Determinants of the intention to use technology: comparison between Malaysian and Singaporean female student teachers. Proceedings of the 17th International Conference on Computers in Education, ICCE.
Yi, M.Y., Fiedler, K.D., Park, J.S.: Understanding the role of individual innovativeness in the acceptance of IT-based innovations: comparative analyses of models and measures. Decis. Sci. 37(3), 393–426 (2006)
Yoo, S.J., Huang, W.-H.D.: Comparison of web 2.0 technology acceptance level based on cultural differences. Educ. Technol. Soc. 14(4), 241–252 (2011)
Zeqiri, J., Alserhan, B.A.: University student satisfaction with blended learning: a cross-national study between North Macedonia and Jordan. Int. J. Technol. Enhanc. Learn. 13(3), 325–337 (2021)
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Appendix A: Measurement scale for conceptual research model
Appendix A: Measurement scale for conceptual research model
Attitude toward using SPSS |
---|
1. [AT1]: Overall, I have a positive opinion about the use of SPSS |
2. [AT2]: I believe it is a good idea to use SPSS in while studying |
3. [AT3]: I like the idea about the use of SPSS |
4. [AT4]: I support the use of SPSS |
Perceived compatibility with needs of study |
1. [C1]: SPSS is appropriate in all aspects of my study program |
2. [C2]: Working with SPSS fits well with my field of study |
3. [C3]: Usage of SPSS complies with my study and work habits |
Perceived usefulness of statistics (US) |
1. [US1]: Use of expertise in statistics enables me to accomplish learning activities and obligations more quickly |
2. [US2]: Use of expertise in statistics is improving my study grade average |
3. [US3]: Use of expertise in statistics improves my study efficiency |
4. [US4]: Expertise in statistics is useful |
5. [US5]: Expertise in statistics makes my study obligations simple |
6. [US6]: In my opinion is expertise in statistics useful in general |
Perceived usefulness of SPSS (U) |
1. [U1]: Using SPSS enables me to accomplish learning activities and obligations more quickly |
2. [U2]: Using SPSS helps me accomplish my studying effectively |
3. [U3]: Using SPSS enables me to accomplish learning obligations more easily |
4. [U4]: In my opinion is expertise obtained of SPSS at faculty useful in general |
5. [U5]: In my opinion usage of SPSS should be learned in all schools of higher education |
Perceived SPSS ease of use (EU) |
1. [EU1]: Using SPSS is simple and easy to understand |
2. [EU2]: Learning SPSS is simple |
3. [EU3]: Working with SPSS does not require much thinking |
4. [EU4]: I think it is easy to get SPSS to do what I want it to do |
5. [EU5]: General using SPSS is simple in understand |
Intention to use SPSS in the future (IU) |
1. [IU1]: I intend to use SPSS more in the future |
2. [IU2]: I will use SPSS for analysis more than other statistical information support |
3. [IU3]: I will share my knowledge of SPSS and recommend others to use the SPSS |
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Sebian, B., Ghaviferkr, S. & Yildirim, A. Adoption and use of statistical software support in higher education: a cross-national analysis. Qual Quant 57, 4633–4656 (2023). https://doi.org/10.1007/s11135-022-01571-x
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DOI: https://doi.org/10.1007/s11135-022-01571-x