Abstract
The emergence of new technologies changes how students’ study and learn. This project investigated relationships between voice assistants and students’ study efficacy, effectiveness, and efficiency. A questionnaire was designed to probe students’ self-assessed study practices. A total of 50 students responded. The results confirm significant differences between students that use voice assistants and those that do not. Study-efficacy, effectiveness, and efficiency were positively connected to the use of voice assistants. The results also revealed that voice assistants influenced issues related to personal study but not activities relating to other people such as group work and interaction with the teacher. Future work could investigate if curiosity and endorsement of new technologies in context of study is an indicator of study efficacy, effectiveness, efficiency, and ambition, while a lack of interest in such tools are connected to a lower interest in their own study process.
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References
Minder, B., Wolf, P., Baldauf, M., Verma, S.: Voice assistants in private households: a conceptual framework for future research in an interdisciplinary field. Human. Soc. Sci. Commun. 10(1), 173 (2023). https://doi.org/10.1057/s41599-023-01615-z
Winkler, R., Söllner, M., Leimeister, J.M.: Enhancing problem-solving skills with smart personal assistant technology. Comput. Educ. 165, 104148 (2021). https://doi.org/10.1016/j.compedu.2021.104148
Dutsinma, F.L.I., Pal, D., Funilkul, S., Chan, J.H.: A systematic review of voice assistant usability: an ISO 9241–11 approach. SN Comput. Sci. 3(4), 267 (2022). https://doi.org/10.1007/s42979-022-01172-3
Terzopoulos, G., Satratzemi, M.: Voice assistants and smart speakers in everyday life and in education. Inform. Educ. 19, 473–490 (2020). https://doi.org/10.15388/infedu.2020.21
Zharikova, D., et al.: DeepPavlov dream: platform for building generative AI assistants. In: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, pp. 599–607. Association for Computational Linguistics (2023)
Babic, S., Orehovacki, T., Etinger, D.: Perceived user experience and performance of voice assistants employed in higher education settings. In: 2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), pp. 0830–0834. IEEE (2018)
Todorov, J., Valkanov, V., Stoyanov, S., Daskalov, B., Popchev, I., Orozova, D.: Personal assistants in a virtual education space. Pract. Issues Intell. Innov. 140, 131–153 (2018). https://doi.org/10.1007/978-3-319-78437-3_6
Tsourakas, T., Terzopoulos, G., Goumas, S.: Educational use of voice assistants and smart speakers. J. Eng. Sci. Technol. Rev. 14(4) (2021)
Balci, E.: Overview of voice assistants. Acta Infologica 3(1), 22–33 (2019). https://doi.org/10.26650/acin.454522
Huang, Y.: Research on the development of voice assistants in the era of artificial intelligence. In: SHS Web of Conferences, vol. 155 (2023). https://doi.org/10.1051/shsconf/202315503019
Benbya, H., Davenport, T. H., Pachidi, S.: Artificial intelligence in organizations: Current state and future opportunities. MIS Q. Executive 19(4) (2020)
Marikyan, D., Papagiannidis, S., Rana, O.F., Ranjan, R., Morgan, G.: “Alexa, let’s talk about my productivity”: The impact of digital assistants on work productivity. J. Bus. Res. 142, 572–584 (2022). https://doi.org/10.1016/j.jbusres.2022.01.015
Trivedi, N.: ProblemPal: generating autonomous practice content in real-time with voice commands and amazon alexa. In: E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, pp. 80–82. Association for the Advancement of Computing in Education (2018). https://www.learntechlib.org/primary/p/184950/
Terzopoulos, G., Satratzemi, M.: Voice assistants and artificial intelligence in education. In: Proceedings of the 9th Balkan Conference on Informatics, pp. 1–6. ACM (2019). https://doi.org/10.1145/3351556.3351588
Wilson, R., Joiner, K., Abbasi, A.: Improving students’ performance with time management skills. J. Univ. Teach. Learn. Pract. 18(4), 230–250 (2021). https://doi.org/10.53761/1.18.4.16
Bräuer, P., Mazarakis, A.: How to design audio-gamification for language learning with Amazon Alexa?—A long-term field experiment. Int. J. Human-Comput. Interact. 40, 1–18 (2022)
Rahman, A., Tomy, P. Voice assistant as a modern contrivance to acquire oral fluency: an acoustical and computational analysis. World J. English Lang. 13(1) (2023)
Rahman, A., Tomy, P.: Voice assistant-an interlocutor to mollify foreign language speaking anxiety. Interact. Learn. Environ. 1–18 (2023)
Tai, T.Y.: Comparing the effects of voice assistant-human and human-human interactions on EFL learners’ willingness to communicate beyond the classroom. Comput. Educ. 210, 104965 (2024)
Winkler, R., Weingart, P., Söllner, M.: Using smart personal assistants for online learning activities: what benefits can we expect? In: Gronau, N., Heine, M., Krasnova, H., Pousttchi, K. (Hrsg.) Entwicklungen, Chancen und Herausforderungen der Digitalisierung. Band 1: Proceedings der 15. Internationalen Tagung Wirtschaftsinformatik 2020, pp. 465–479. GITO Verlag, Berlin (2020). https://doi.org/10.17170/kobra-202010231996
Jian, H.L., Sandnes, F.E., Huang, Y.P., Cai, L., Law, K.M.: On students’ strategy-preferences for managing difficult course work. IEEE Trans. Educ. 51(2), 157–165 (2008)
Jian, H.L., Sandnes, F.E., Huang, Y.P., Huang, Y.M., Hagen, S.: Studies or leisure? A cross-cultural comparison of Taiwanese and Norwegian engineering students’ preferences for university life. Int. J. Eng. Educ. 26(1), 227–335 (2010)
Sandnes, F.E., Örtenblad, A., Bøhn, E.D.: For or against equal pay? A study of common perceptions. Compens. Benefits Rev. 55(3), 87–110 (2023)
Eika, E., Sandnes, F.E.: Starstruck by journal prestige and citation counts? On students’ bias and perceptions of trustworthiness according to clues in publication references. Scientometrics 127(11), 6363–6390 (2022). https://doi.org/10.1007/s11192-022-04521-4
Panofsky, C.P.: The relations of learning and student social class: toward re-“socializing” sociocultural learning theory. In: Vygotsky’s Educational Theory in Cultural Context, pp. 411–431 (2003)
Wang, L.: Sociocultural learning theories and information literacy teaching activities in higher education. In: Reference & User Services Quarterly, pp. 149–158 (2007)
Law, K.M., Sandnes, F.E., Jian, H.L., Huang, Y.P.: A comparative study of learning motivation among engineering students in South East Asia and beyond. Int. J. Eng. Educ. 25(1), 144 (2009)
Jian, H.L., Sandnes, F.E., Law, K.M., Huang, Y.P., Huang, Y.M.: The role of electronic pocket dictionaries as an English learning tool among Chinese students. J. Comput. Assist. Learn. 25(6), 503–514 (2009)
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Devkota, A., Gupta, S., Shrestha, R., Sandnes, F.E. (2024). Students’ Perceptions of Study Efficacy, Effectiveness, and Efficiency: Effects of Voice Assistant Use. In: Cheng, YP., Pedaste, M., Bardone, E., Huang, YM. (eds) Innovative Technologies and Learning. ICITL 2024. Lecture Notes in Computer Science, vol 14786. Springer, Cham. https://doi.org/10.1007/978-3-031-65884-6_15
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