Factors influence students' attitudes toward AI-based innovative solutions
Anh-Binh Le, My-Trinh Bui, Bao-Dat Le
Citation: Proceedings of the 2022 International Conference on Research in Management & Technovation, Viet Ha Hoang, Vijender Kumar Solanki, Nguyen Thi Hong Nga, Shivani Agarwal (eds). ACSIS, Vol. 34, pages 21–26 (2022)
Abstract. As technology improves, it appears that academic machine instructors will be used in many jobs in future of education. Despite the fact that the existing research does not clearly define the idea of machine lecturers. Nonetheless, given the current era of education, it appears to be critical to begin thinking about this concept. Machine units are technologies with a specific level of agency, suggesting that they will play a specific function in communication. Lecturers are frequently thought of as those who encourage and help others to improve their emotional and learning behavior via data collecting, advancement, and moral shaping. The machine teacher model may be broadly characterized as a technological design that helps and interacts with a person in boosting affective and learning behavior through numerous techniques, as supported by these two notions. In this paper, different factors will be examined to determine whether these will have certain effects on college students attiudes toward AI teaching assistants.
- Abdullah, F., & Ward, R. Developing a General Extended Technology Acceptance Model for E- Learning (GETAMEL) by analysing commonly used external factors. Computers in Human Behavior, 56, 238–256, 2016.
- Bervell, B., Umar, I.N. and Kamilin, M.H. Towards a model for online learning satisfaction (MOLS): re-considering non-linear relationships among personal innovativeness and modes of online interaction. Open Learning: The Journal of Open, Distance and e-Learning, 35(3), pp.236- 259, 2020.
- Bloom, B. S.. Taxonomy of educational objectives: The classification of educational goals. New York: David McKay Company, 1956.
- Burgoon, J. K., Bonito, J. A., Bengtsson, B., Cederberg, C., Lundeberg, M., & Allspach, L . Interactivity in human–com-puter interaction: A study of credibility, understanding, and influence. Computers in Human Behavior, 16(6), 553–574, 2000.
- Carvalho, S.W. and de Oliveira Mota, M. The role of trust in creating value and student loyalty in relational exchanges between higher education institutions and their students. Journal of marketing for higher education, 20(1), pp.145-165, 2010.
- Chandler, J., & Schwarz, N. (2010). Use does not wear ragged the fabric of friendship: Thinking of objects as alive makes people less willing to replace them. Journal of Consumer Psychology, 20(2), 138–145, 2010.
- Cheng, Y. and Jiang, H., 2020. How do AI- driven chatbots impact user experience? Examining gratifications, perceived privacy risk, satisfaction, loyalty, and continued use. Journal of Broadcasting & Electronic Media, 64(4), pp.592-614, 2020.
- Coeckelbergh, M . Virtual moral agency, virtual moral responsibility: on the moral significance of the appearance, perception, and performance of artificial agents. AI & society, 24(2), 181-189, 2009.
- Davis, F. D. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340, 1989.
- Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982– 1003, 1989.
- De Visser, E. J., Monfort, S. S., Goodyear, K., Lu, L., O’Hara, M., Lee, M. R., & Parasuraman, K.F. A little anthropomorphism goes a long way. Human Factors: The Journal of the Human Factors and Ergonomics Society, 59(1), 116–133, 2017.
- Edwards, A., Edwards, C., Spence, P.R., Harris, C. and Gambino, A. Robots in the classroom: Differences in students’ perceptions of credibility and learning between "teacher as robot" and "robot as teacher". Computers in Human Behavior,65pp. 627–634, 2016.
- Edwards, C., Edwards, A., Spence, P.R. and Lin, X. I, teacher: using artificial intelligence (AI) and social robots in communication and instruction. Communication Education, 67(4), pp.473-480, 2018.
- Fischer, G. Communication requirements for cooperative problem solving systems. Information Systems, 15(1), 21–36, 1990.
- Fogel, A. L., & Kvedar, J. C. Artificial intelligence powers digital medicine. NPJ digital medicine, 1(1), 1-4, 2008.
- Garcia, R. and Calantone, . A critical look at technological innovation typology and innovativeness terminology: a literature review. Journal of Product Innovation Management: An international publication of the product development & management association, 19(2), pp.110- 132, 2002.
- Goetz, J., & Kiesler, S. Cooperation with a robotic assistant [Paper presentation]. CHI02: Human Factors in Computing Systems. Minneapolis, Minnesota, 2002.
- Gul, R. The relationship between reputation, customer satisfaction, trust, and loyalty. Journal of Public Administration and Governance, 4(3), pp.368- 387, 2014.
- Guthrie, S. E. Anthropomorphism: A definition and a theory. In R. W. Mitchell, 1997.
- N. S. Thompson, & H. L. Miles (Eds.), SUNY series in philosophy and biology. Anthropomorphism, anecdotes, and animals (pp. 50–58). State University of New York Press.
- Han, J.H., Jo, M.H., Jones, V. and Jo, J.H . Comparative study on the educational use of home robots for children. Journal of Information Processing Systems, 4(4), pp.159- 168, 2008.
- Joshi, A., Kale, S., Chandel, S. and Pal, D.K. Likert scale: Explored and explained. British journal of applied science & technology, 7(4), p.396, 2015.
- Kim, J., Merrill, K., Xu, K. and Sellnow, D.D . My teacher is a machine: Understanding students’ perceptions of AI teaching assistants in online education. International Journal of Human–Computer Interaction, 36(20), pp.1902-1911, 2020.
- Kim, K.J. and Frick, T.W. Changes in student motivation during online learning. Journal of Educational Computing Research, 44(1), pp.1-23, 2021.
- Kirienko, M., Sollini, M., Ninatti, G., Loiacono, D., Giacomello, E., Gozzi, N., Amigoni, F., Mainardi, L., Lanzi, P.L. and Chiti, A., 2021. Distributed learning: a reliable privacy-preserving strategy to change multicenter collaborations using AI. European Journal of Nuclear Medicine and Molecular Imaging, 48(12), pp.3791-3804.
- Krishna Rao, M.R.K . Infusing critical thinking skills into content of AI course. In Proceedings of the 10th annual SIGCSE conference on Innovation and technology in computer science education (pp. 173-177), 2005, June.
- Landwehr, J. R., McGill, A. L., & Herrmann, A. It’s got the look: The effect of friendly and aggressive “facial” expressions on product liking and sales. Journal of Marketing, 75(3), 132– 146, 2011. https://doi.org/10.1509/jmkg.75.3.132.
- Li, J. The benefit of being physically present: A survey of experimental works comparing copresent robots, telepresence robots, and virtual agents. International Journal of Human-computer Studies, 77, 23–37, 2015.
- Li, J., Kizilcec, R., Bailenson, J., & Ju, W. Social robots and virtual agents as lecturers for video instruction. Computers in Human Behavior, 55, 1222–1230, 2015.
- Manheim, K., & Kaplan, L. Artificial intelligence: Risks to privacy and democracy. Yale JL & Tech., 21, 106, 2019.
- McClure, P.K. "You’re fired," says the robot: The rise of automation in the workplace, technophobes, and fears of unemployment. Social Science Computer Review, 36(2), pp.139-156, 2018.
- McKnight, D. H., & Chervany, N. L. What trust means in e-commerce customer relationships: An interdisciplinary conceptual typology. International journal of electronic commerce, 6(2), 35-59, 2001.
- McMullan, R. and Gilmore, A. The conceptual development of customer loyalty measurement: A proposed scale. Journal of Targeting, Measurement and Analysis for Marketing, 11(3), pp.230-243, 2003.
- Midgley, D.F. and Dowling, G.R. Innovativeness: The concept and its measurement. Journal of consumer research, 4(4), pp.229-242, 1978.
- Moreale, E., & Watt, S. An agent- based approach to mailing list knowledge management. In L. van Elst, V. Dignum, & A. Abecker (Eds.), Agent-mediated knowledge management. AMKM 2003. Lecture notes in computer science (Vol. 2926, pp. 118–129), 2004. Springer Berlin, Heidelberg.
- Nind, M. and Hewett, D. Access to communication: Developing the basics of communication with people with severe learning difficulties through intensive interaction, 2012. David Fulton Publishers.
- Park, E., Kim, K.J. and Pobil, A.P.D. The effects of a robot instructor’s positive vs. negative feedbacks on attraction and acceptance towards the robot in classroom. In International conference on social robotics (pp. 135-141), 2011,November Springer. Berlin, Heidelberg.
- Park, Y., & Chen, J. V. Acceptance and adoption of the innovative use of smartphone. Industrial Management & Data Systems, 107 (9), 1349–1365, 2007.
- Petrock, V. US voice assistant users 2019: Who, what, when, where and why. eMarketer, 2019.
- Pfeifer, R., & Scheier, C. Understanding intelligence. The MIT Press. Ramírez-Montoya, M. S., Mena, J., & Rodríguez-Arroyo, J. A. (2017). In-service teachers’ self-perceptions of digital competence and OER use as determined by a xMOOC training course. Computers in Human Behavior, 77, 356–364.
- Rampersad, G. Robot will take your job: Innovation for an era of artificial intelligence. Journal of Business Research, 116, pp.68-74, 2020.
- Redish, E. F., & Smith, K. A. Looking beyond content: Skill development for engineers. Journal of Engineering Education, 97(3), 295-307, 2020.
- Roehrich, G. Consumer innovativeness: Concepts and measurements. Journal of business research, 57(6), pp.671- 677, 2004.
- Selwyn, N. Should robots replace teachers?: AI and the future of education. John Wiley & Sons, 2019.
- Siau, K., & Wang, W. Building trust in artificial intelligence, machine learning, and robotics. Cutter business technology journal, 31(2), 47-53, 2018
- Statista. (2019, February). Number of voice assistants in use worldwide 2019-2023. https://www.statista.com/statistics/973815/wor ldwide-digital-voice-assistant-in-use/
- Täks, M., Tynjälä, P., Toding, M., Kukemelk, H., & Venesaar, U. Engineering students' experiences in studying entrepreneurship. Journal of engineering education, 103(4), 573-598, 2014.
- Vasagar, J. How robots are teaching Singapore’s kids. Financial Times, 2017.
- Waytz, A., Morewedge, C. K., Epley, N., Monteleone, G., Gao, J. H., & Cacioppo, J. T . Making sense by making sentient: Effectance motivation increases anthropomorphism. Journal of Personality and Social Psychology, 99(3), 410–435. https://doi.org/10.1037/a0020240, 2010.
- Winter, P. Coming into the world, uniqueness, and the beautiful risk of education: An interview with Gert Biesta. Studies in Philosophy and Education, 30(5), pp.537-542, 2011.
- World Economic Forum. The future of jobs: Employment, skills and workforce strategy for the fourth industrial revolution. Global Challenge Insight Report, 2016.
- Yuan, L. (Ivy), & Dennis, A. R. Acting likehumans? Anthropomorphism and consumer’s willingness to pay in electronic commerce. Journal of Management Information Systems, 36(2), 450–47, 2019.