Abstract
Artificial intelligence (AI) has the potential to support self-regulated learning (SRL) because of its strong anthropomorphic characteristics. However, most studies of AI in education have focused on cognitive outcomes in higher education, and little research has examined how psychological needs affect SRL with AI in the K–12 setting. SRL is a self-directed process driven by psychological factors that can be explained by the three basic needs of self-determination theory (SDT), i.e., autonomy, competence, and relatedness. This study fills a research gap by examining the moderating effects of need satisfaction and gender in predicting SRL among Grade 9 students. The results indicate that girls perceive more need support than boys. In predicting SRL, satisfaction of the need for autonomy and competence is moderated by both gender and AI knowledge, whereas satisfaction of the need for relatedness is moderated by gender only. Particularly among girls, the effects of autonomy and competence more strongly predict SRL when AI knowledge is low. These findings confirm the gender differences in need satisfaction when predicting SRL with a chatbot. The findings have implications for both teacher instruction and the design and development of intelligent learning environments.





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References
Alowayr, A., & Al-Azawei, A. (2021). Predicting mobile learning acceptance: An integrated model and empirical study based on the perceptions of higher education students. Australasian Journal of Educational Technology, 37(3), 38–55. https://doi.org/10.14742/ajet.6154.
Anthonysamy, L., Koo, A. C., & Hew, S. H. (2020). Self-regulated learning strategies in higher education: Fostering digital literacy for sustainable lifelong learning. Education and Information Technologies, 25(4), 2393–2414. https://doi.org/10.1007/s10639-020-10201-8
Assor, A., Kaplan, H., & Roth, G. (2002). Choice is good, but relevance is excellent: Autonomy-enhancing and suppressing teacher behaviours predicting students’ engagement in schoolwork. British Journal of Educational Psychology, 72(2), 261–278. https://doi.org/10.1348/000709902158883
Audrin, C., & Audrin, B. (2022). Key factors in digital literacy in learning and education: A systematic literature review using text mining. Education and Information Technologies. https://doi.org/10.1007/s10639-021-10832-5
Bao, Y., Xiong, T., Hu, Z., & Kibelloh, M. (2013). Exploring gender differences on general and specific computer self-efficacy in mobile learning adoption. Journal of Educational Computing Research, 49(1), 111–132. https://doi.org/10.2190/EC.49.1.e
Bedenlier, S., Bond, M., Buntins, K., Zawacki-Richter, O., & Kerres, M. (2020). Facilitating student engagement through educational technology in higher education: A systematic review in the field of arts and humanities. Australasian Journal of Educational Technology, 36(4), 126–150. https://doi.org/10.14742/ajet.5477.
Black, A. E., & Deci, E. L. (2000). The effects of instructors’ autonomy support and students’ autonomous motivation on learning organic chemistry: A self-determination theory perspective. Science Education, 84(6), 740–756. https://doi.org/10.1002/1098-237X(200011)84:6%3c740::AID-SCE4%3e3.0.CO;2-3
Blut, M., Wang, C., Wünderlich, N. V., & Brock, C. (2021). Understanding anthropomorphism in service provision: A meta-analysis of physical robots, chatbots, and other AI. Journal of the Academy of Marketing Science, 49(4), 632–658. https://doi.org/10.1007/s11747-020-00762-y
Bru, E., Virtanen, T., Kjetilstad, V., & Niemiec, C. P. (2021). Gender differences in the strength of association between perceived support from teachers and student engagement. Scandinavian Journal of Educational Research, 65(1), 153–168. https://doi.org/10.1080/00313831.2019.1659404
Cai, Z., Fan, X., & Du, J. (2017). Gender and attitudes toward technology use: A meta-analysis. Computers & Education, 105, 1–13. https://doi.org/10.1016/j.compedu.2016.11.003
Cheon, S. H., Reeve, J., & Moon, I. S. (2012). Experimentally based, longitudinally designed, teacher-focused intervention to help physical education teachers be more autonomy supportive toward their students. Journal of Sport and Exercise Psychology, 34(3), 365–396. https://doi.org/10.1123/jsep.34.3.365
Chew, E., & Chua, X. N. (2020). Robotic Chinese language tutor: Personalising progress assessment and feedback or taking over your job? On the Horizon, 28(3), 113–124. https://doi.org/10.1108/OTH-04-2020-0015
Chiu, T. K. F. (2017). Introducing electronic textbooks as daily-use technology in schools: A top-down adoption process. British Journal of Educational Technology, 48(2), 524–537. https://doi.org/10.1111/bjet.12432
Chiu, T. K. F. (2021). Digital support for student engagement in blended learning based on Self-determination Theory. Computers in Human Behavior, 124, 106909. https://doi.org/10.1016/j.chb.2021.106909
Chiu, T. K. F. (2022). Applying the Self-determination Theory (SDT) to explain student engagement in online learning during the COVID-19 pandemic. Journal of Research on Technology in Education, 54(sup1), 14–30. https://doi.org/10.1080/15391523.2021.1891998
Chiu T. K. F., Chai C. S., Williams, J, & Lin T. J. (2021). Teacher professional development on Self-determination Theory-based design thinking in STEM education. Education Technology & Society, 24 (4), 153–165. https://www.jstor.org/stable/48629252.
Chiu, T. K. F., Sun, J. C. Y., & Ismailov, M. (2022). Investigating the relationship of technology learning support to digital literacy from the perspective of Self-Determination Theory. Educational Psychology, Advanced Online Publication,. https://doi.org/10.1080/01443410.2022.2074966
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Routledge. https://doi.org/10.4324/9780203771587.
Colley, A., & Comber, C. (2003). Age and gender differences in computer use and attitudes among secondary school students: What has changed? Educational Research, 45(2), 155–165. https://doi.org/10.1080/0013188032000103235
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
Dawson, J. F., & Richter, A. W. (2006). Probing three-way interactions in moderated multiple regression: Development and application of a slope difference test. Journal of Applied Psychology, 91(4), 917–926. https://doi.org/10.1037/0021-9010.91.4.917
Deci, E. L., & Ryan, R. M. (2002). Handbook of self-determination research. University of Rochester Press.
Flowerday, T., & Schraw, G. (2000). Teacher beliefs about instructional choice: A phenomenological study. Journal of Educational Psychology, 92(4), 634–645. https://doi.org/10.1037/0022-0663.92.4.634
Furrer, C., & Skinner, E. (2003). Sense of relatedness as a factor in children’s academic engagement and performance. Journal of Educational Psychology, 95(1), 148–162. https://doi.org/10.1037/0022-0663.95.1.148
Goodenow, C. (1993). Classroom belonging among early adolescent students: Relationships to motivation and achievement. The Journal of Early Adolescence, 13(1), 21–43. https://doi.org/10.1177/0272431693013001002
Grolnick, W. S., & Raftery-Helmer, J. N. (2015). Contexts supporting self-regulated learning at school transitions. In Self-regulated learning interventions with at-risk youth: Enhancing adaptability, performance, and well-being. (pp. 251–276). American Psychological Association. https://doi.org/10.1037/14641-012.
Hew, T.-S., & Syed Abdul Kadir, S. L. (2016). Understanding cloud-based VLE from the SDT and CET perspectives: Development and validation of a measurement instrument. Computers & Education, 101, 132-149.https://doi.org/10.1016/j.compedu.2016.06.004.
Holzer, J., Luftenegger, M., Kaser, U., Korlat, S., Pelikan, E., Schultze-Krumbholz, A., Spiel, C., Wachs, S., & Schober, B. (2021). Students’ basic needs and well-being during the COVID-19 pandemic: A two-country study of basic psychological need satisfaction, intrinsic learning motivation, positive emotion and the moderating role of self-regulated learning. International Journal of Psychology, 56(6), 843–852. https://doi.org/10.1002/ijop.12763
Hsi, S., & Hoadley, C. M. (1997). Productive discussion in science: Gender equity through electronic discourse. Journal of Science Education and Technology, 6(1), 23–36. https://doi.org/10.1023/A:1022564817713
Hsu, H.-C.K., Wang, C. V., & Levesque-Bristol, C. (2019). Reexamining the impact of self-determination theory on learning outcomes in the online learning environment. Education and Information Technologies, 24(3), 2159–2174. https://doi.org/10.1007/s10639-019-09863-w
Huang, Y. C., Backman, S. J., Backman, K. F., McGuire, F. A., & Moore, D. (2019). An investigation of motivation and experience in virtual learning environments: A self-determination theory. Education and Information Technologies, 24(1), 591–611. https://doi.org/10.1007/s10639-018-9784-5
Hui, E. K. P., Sun, R. C. F., Chow, S. S. Y., & Chu, M. H. T. (2011). Explaining Chinese students’ academic motivation: Filial piety and self-determination. Educational Psychology, 31(3), 377–392. https://doi.org/10.1080/01443410.2011.559309
Hussin, A. A. (2018). Education 4.0 made simple: Ideas for teaching. International Journal of Education and Literacy Studies, 6(3), 92–98. https://doi.org/10.7575/aiac.ijels.v.6n.3p.92.
Iwaniec, J. (2019). Language learning motivation and gender: The case of Poland. International Journal of Applied Linguistics, 29(1), 130–143. https://doi.org/10.1111/ijal.12251
Jang, H., Kim, E. J., & Reeve, J. (2012). Longitudinal test of self-determination theory’s motivation mediation model in a naturally occurring classroom context. Journal of Educational Psychology, 104(4), 1175–1188. https://doi.org/10.1037/a0028089
Jeno, L. M., Dettweiler, U., & Grytnes, J. A. (2020). The effects of a goal-framing and need-supportive app on undergraduates' intentions, effort, and achievement in mobile science learning. Computers & Education, 159, 104022. https://doi.org/10.1016/j.compedu.2020.104022.
Katz, I., & Assor, A. (2007). When choice motivates and when it does not. Educational Psychology Review, 19(4), 429. https://doi.org/10.1007/s10648-006-9027-y
Kim, S., Jang, Y., Kim, W., Choi, S., Jung, H., Kim, S., & Kim, H. (2021). Why and what to teach: AI curriculum for elementary school. Proceedings of the AAAI Conference on Artificial Intelligence, 35(17), 15569–15576. https://ojs.aaai.org/index.php/AAAI/article/view/17833.
Kim, Y.-E., Yu, S. L., & Shin, J. (2022). How temptation changes across time: Effects of self-efficacy for self-regulated learning and autonomy support. Educational Psychology, 42(3), 278–295. https://doi.org/10.1080/01443410.2021.2009774
Kimbrough, A. M., Guadagno, R. E., Muscanell, N. L., & Dill, J. (2013). Gender differences in mediated communication: Women connect more than do men. Computers in Human Behavior, 29(3), 896–900. https://doi.org/10.1016/j.chb.2012.12.005
Kındap-Tepe, Y., & Aktaş, V. (2021). The Mediating role of needs satisfaction for prosocial behavior and autonomy support. Current Psychology, 40(10), 5212–5224. https://doi.org/10.1007/s12144-019-00466-9
Lam, S.-F., Jimerson, S., Kikas, E., Cefai, C., Veiga, F. H., Nelson, B., Hatzichristou, C., Polychroni, F., Basnett, J., Duck, R., Farrell, P., Liu, Y., Negovan, V., Shin, H., Stanculescu, E., Wong, B. P. H., Yang, H., & Zollneritsch, J. (2012). Do girls and boys perceive themselves as equally engaged in school? The results of an international study from 12 countries. Journal of School Psychology, 50(1), 77–94. https://doi.org/10.1016/j.jsp.2011.07.004
Lee, H., & Kim, Y. (2014). Korean adolescents’ longitudinal change of intrinsic motivation in learning English and mathematics during secondary school years: Focusing on gender difference and school characteristics. Learning and Individual Differences, 36, 131–139. https://doi.org/10.1016/j.lindif.2014.07.018
León, J., Núñez, J. L., & Liew, J. (2015). Self-determination and STEM education: Effects of autonomy, motivation, and self-regulated learning on high school math achievement. Learning and Individual Differences, 43, 156–163. https://doi.org/10.1016/j.lindif.2015.08.017
Lietaert, S., Roorda, D., Laevers, F., Verschueren, K., & De Fraine, B. (2015). The gender gap in student engagement: The role of teachers’ autonomy support, structure, and involvement. British Journal of Educational Psychology, 85(4), 498–518. https://doi.org/10.1111/bjep.12095
List, A., Brante, E. W., & Klee, H. L. (2020). A framework of pre-service teachers' conceptions about digital literacy: Comparing the United States and Sweden. Computers & Education, 148, 103788. https://doi.org/10.1016/j.compedu.2019.103788.
Liu, W. C., Wang, C. K. J., Kee, Y. H., Koh, C., Lim, B. S. C., & Chua, L. (2014). College students’ motivation and learning strategies profiles and academic achievement: A self-determination theory approach. Educational Psychology, 34(3), 338–353. https://doi.org/10.1080/01443410.2013.785067
Luor, T., Wu, L.-L., Lu, H.-P., & Tao, Y.-H. (2010). The effect of emoticons in simplex and complex task-oriented communication: An empirical study of instant messaging. Computers in Human Behavior, 26(5), 889–895. https://doi.org/10.1016/j.chb.2010.02.003
Luo, Y., Lin, J., & Yang, Y. (2021). Students’ motivation and continued intention with online self-regulated learning: A self-determination theory perspective. Zeitschrift Für Erziehungswissenschaft, 24(6), 1379–1399. https://doi.org/10.1007/s11618-021-01042-3
Mandigo, J., Holt, N., Anderson, A., & Sheppard, J. (2008). Children’s motivational experiences following autonomy-supportive games lessons. European Physical Education Review, 14(3), 407–425. https://doi.org/10.1177/1356336x08095673
McCormick, M. P., & O’Connor, E. E. (2015). Teacher–child relationship quality and academic achievement in elementary school: Does gender matter? Journal of Educational Psychology, 107(2), 502–516. https://doi.org/10.1037/a0037457
Miller, R. G. (1981). Simultaneous statistical inference (2nd ed.). Springer-Verlag. https://doi.org/10.1007/978-1-4613-8122-8.
Mouratidis, A., Vansteenkiste, M., Michou, A., & Lens, W. (2013). Perceived structure and achievement goals as predictors of students’ self-regulated learning and affect and the mediating role of competence need satisfaction. Learning and Individual Differences, 23, 179–186. https://doi.org/10.1016/j.lindif.2012.09.001
Niemiec, C. P., & Ryan, R. M. (2009). Autonomy, competence, and relatedness in the classroom: Applying self-determination theory to educational practice. Theory and Research in Education, 7(2), 133–144. https://doi.org/10.1177/1477878509104318
Ong, C.-S., & Lai, J.-Y. (2006). Gender differences in perceptions and relationships among dominants of e-learning acceptance. Computers in Human Behavior, 22(5), 816–829. https://doi.org/10.1016/j.chb.2004.03.006
Padilla-Meléndez, A., del Aguila-Obra, A. R., & Garrido-Moreno, A. (2013). Perceived playfulness, gender differences and technology acceptance model in a blended learning scenario. Computers & Education, 63, 306–317. https://doi.org/10.1016/j.compedu.2012.12.014
Palasundram, K., Mohd Sharef, N., Nasharuddin, N. A., Kasmiran, K. A., & Azman, A. (2019). Sequence to sequence model performance for education chatbot. International Journal of Emerging Technologies in Learning (iJET), 14(24), 56–68. https://doi.org/10.3991/ijet.v14i24.12187
Panadero, E., Jonsson, A., & Botella, J. (2017). Effects of self-assessment on self-regulated learning and self efficacy: Four meta-analyses. Educational Research Review, 22, 74–98. https://doi.org/10.1016/j.edurev.2017.08.004
Patall, E. A., Cooper, H., & Wynn, S. R. (2010). The effectiveness and relative importance of choice in the classroom. Journal of Educational Psychology, 102(4), 896–915. https://doi.org/10.1037/a0019545
Pelau, C., Dabija, D.-C., & Ene, I. (2021). What makes an AI device human-like? The role of interaction quality, empathy and perceived psychological anthropomorphic characteristics in the acceptance of artificial intelligence in the service industry. Computers in Human Behavior, 122, 106855. https://doi.org/10.1016/j.chb.2021.106855
Polizzi, G. (2020). Digital literacy and the national curriculum for England: Learning from how the experts engage with and evaluate online content. Computers & Education, 152, 103859. https://doi.org/10.1016/j.compedu.2020.103859.
Prinsen, F. R., Volman, M. L. L., & Terwel, J. (2007). Gender-related differences in computer-mediated communication and computer-supported collaborative learning. Journal of Computer Assisted Learning, 23(5), 393–409. https://doi.org/10.1111/j.1365-2729.2007.00224.x
Radel, R., Pelletier, L., Baxter, D., Fournier, M., & Sarrazin, P. (2014). The paradoxical effect of controlling context on intrinsic motivation in another activity. Learning and Instruction, 29, 95–102. https://doi.org/10.1016/j.learninstruc.2013.09.004
Ratelle, C. F., & Duchesne, S. (2014). Trajectories of psychological need satisfaction from early to late adolescence as a predictor of adjustment in school. Contemporary Educational Psychology, 39(4), 388–400. https://doi.org/10.1016/j.cedpsych.2014.09.003
Reeve, J. (2002). Self-determination theory applied to educational setting. In I. E. L. D. R. M. R. (Eds.) (Ed.), Handbook on self-determination research: Theoretical and applied issues. University of Rochester Press.
Roca, J. C., Chiu, C.-M., & Martínez, F. J. (2006). Understanding e-learning continuance intention: An extension of the Technology Acceptance Model. International Journal of Human-Computer Studies, 64(8), 683–696. https://doi.org/10.1016/j.ijhcs.2006.01.003
Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic Definitions and new directions. Contemporary Educational Psychology, 25(1), 54–67. https://doi.org/10.1006/ceps.1999.1020
Ryan, R. M., & Deci, E. L. (2017). Self-determination theory: Basic psychological needs in motivation, development, and wellness. The Guilford Press.https://doi.org/10.1521/978.14625/28806.
Ryan, R. M., Stiller, J. D., & Lynch, J. H. (1994). Representations of relationships to teachers, parents, and friends as predictors of academic motivation and self-esteem. The Journal of Early Adolescence, 14(2), 226–249. https://doi.org/10.1177/027243169401400207
Salas-Pilco, S. Z. (2020). The impact of AI and Robotics on physical, social-emotional and intellectual learning outcomes: An integrated analytical framework. British Journal of Educational Technology, 51(5), 1808–1825. https://doi.org/10.1111/bjet.12984
Schottenbauer, M. A., Rodriguez, B. F., Glass, C. R., & Arnkoff, D. B. (2004). Computers, anxiety, and gender: An analysis of reactions to the Y2K computer problem. Computers in Human Behavior, 20(1), 67–83. https://doi.org/10.1016/S0747-5632(03)00044-X
Schraw, G., Flowerday, T., & Lehman, S. (2001). Increasing situational interest in the classroom. Educational Psychology Review, 13(3), 211–224. https://doi.org/10.1023/A:1016619705184
Schweder, S., & Raufelder, D. (2021). Needs satisfaction and motivation among adolescent boys and girls during self-directed learning intervention☆. Journal of Adolescence, 88(1), 1–13. https://doi.org/10.1016/j.adolescence.2021.01.007
Sha, L., Looi, C.-K., Chen, W., Seow, P., & Wong, L.-H. (2012). Recognizing and measuring self-regulated learning in a mobile learning environment. Computers in Human Behavior, 28(2), 718–728. https://doi.org/10.1016/j.chb.2011.11.019
Sierens, E., Vansteenkiste, M., Goossens, L., Soenens, B., & Dochy, F. (2009). The synergistic relationship of perceived autonomy support and structure in the prediction of self-regulated learning. British Journal of Educational Psychology, 79(1), 57–68. https://doi.org/10.1348/000709908X304398
Skinner, E., Furrer, C., Marchand, G., & Kindermann, T. (2008). Engagement and disaffection in the classroom: Part of a larger motivational dynamic? Journal of Educational Psychology, 100(4), 765–781. https://doi.org/10.1037/a0012840
Tanaka, M. (2022). Motivation, self-construal, and gender in project-based learning. Innovation in Language Learning and Teaching. https://doi.org/10.1080/17501229.2022.2043870
van Braak, J. P. (2004). Domains and determinants of university students’ self-perceived computer competence. Computers & Education, 43(3), 299–312. https://doi.org/10.1016/j.compedu.2003.09.006
Vansteenkiste, M., Williams, G. C., & Resnicow, K. (2012). Toward systematic integration between self-determination theory and motivational interviewing as examples of top-down and bottom-up intervention development: Autonomy or volition as a fundamental theoretical principle. International Journal of Behavioral Nutrition and Physical Activity, 9(1), 23. https://doi.org/10.1186/1479-5868-9-23
Vantieghem, W., & Van Houtte, M. (2015). Differences in study motivation within and between genders: An examination by gender typicality among early adolescents. Youth & Society, 50(3), 377–404. https://doi.org/10.1177/0044118X15602268
Venkatesh, V., & Morris, M. G. (2000). Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115–139. https://doi.org/10.2307/3250981
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412
Virtanen, P., & Nevgi, A. (2010). Disciplinary and gender differences among higher education students in self-regulated learning strategies. Educational Psychology, 30(3), 323–347. https://doi.org/10.1080/01443411003606391
Wang, H.-Y., & Wang, Y.-S. (2008). Gender differences in the perception and acceptance of online games. British Journal of Educational Technology, 39(5), 787–806. https://doi.org/10.1111/j.1467-8535.2007.00773.x
Xia, Q., Chiu, T. K. F., Lee, M., Temitayo, I., Dai, Y., & Chai, C. S. (2022). A Self-determination theory design approach for inclusive and diverse Artificial Intelligence (AI) K-12 education. Computers & Education, 189, 104582. https://doi.org/10.1016/j.compedu.2022.104582
Xie, K., & Ke, F. (2011). The role of students’ motivation in peer-moderated asynchronous online discussions. British Journal of Educational Technology, 42(6), 916–930. https://doi.org/10.1111/j.1467-8535.2010.01140.x
Yang, T.-C., Chen, M. C., & Chen, S. Y. (2018). The influences of self-regulated learning support and prior knowledge on improving learning performance. Computers & Education, 126, 37–52. https://doi.org/10.1016/j.compedu.2018.06.025
Young-Jones, A., Cara, K. C., & Levesque-Bristol, C. (2014). Verbal and behavioral cues: Creating an autonomy-supportive classroom. Teaching in Higher Education, 19(5), 497–509. https://doi.org/10.1080/13562517.2014.880684
Yukselturk, E., & Bulut, S. (2009). Gender differences in self-regulated online learning environment. Educational Technology & Society, 12(3), 12–22.
Zhou, M. (2016). The roles of social anxiety, autonomy, and learning orientation in second language learning: A structural equation modeling analysis. System, 63, 89–100. https://doi.org/10.1016/j.system.2016.09.001
Zimmerman, B. J. (2006). Development and adaptation of expertise: The role of self-regulatory processes and beliefs. In A. Ericsson, N. Charness, P. Feltovich, & R. Hoffman (Eds.), The Cambridge handbook of expertise and expert performance (pp. 705–722). Cambridge University Press.
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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Thomas K.F. Chiu and Qi Xia. The first draft of the manuscript was written by Qi Xia and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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Appendix
Appendix
Perceived autonomy.
I feel like I can make a lot of input in deciding how I use the chatbot in learning.
I feel a sense of freedom when using the chatbot.
I have many opportunities with the chatbot to decide for myself how to learn.
I have a say regarding what input I want to learn with chatbot.
Perceived competence.
I think I am pretty good at learning with the chatbot.
I have been able to learn interesting new knowledge with the chatbot.
I feel a sense of accomplishment from learning with the chatbot.
I am pretty skillful at learning with the chatbot.
Perceived relatedness.
When I learn with the chatbot, I feel supported.
When I learn with the chatbot, I feel comfortable.
When I learn with the chatbot, I feel important.
When I learn with the chatbot, I feel valued.
Self-regulated learning.
When learning English with the chatbot, I will normally set learning goals for myself so that I can decide how and what I want to learn.
When learning English with the chatbot, I will normally try to identify the knowledge that I do not understand well.
When learning English with the chatbot, I will normally ask myself questions to help me focus on what to study.
When I am not sure about any English language, I will go back and try to figure it out on my own using the chatbot.
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Xia, Q., Chiu, T.K.F. & Chai, C.S. The moderating effects of gender and need satisfaction on self-regulated learning through Artificial Intelligence (AI). Educ Inf Technol 28, 8691–8713 (2023). https://doi.org/10.1007/s10639-022-11547-x
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DOI: https://doi.org/10.1007/s10639-022-11547-x