Exploring the categories of students’ interest and their relationships with deep learning in technology supported environments
Harackiewicz, J. M., Smith, J. L. & Priniski, S. J. Interest matters: The importance of promoting interest in education. Policy Insights Behav. Brain Sci. 3 (2), 220–227. (2016).
Google Scholar
Montazami, A. et al. Why this app? How educators choose a good educational app. Comput. Educ. 184, 104513. (2022).
Google Scholar
Wong, J. T. & Hughes, B. S. Leveraging learning experience design: Digital media approaches to influence motivational traits that support student learning behaviors in undergraduate online courses. J. Comput. High. Educ. 35 (3), 595–632. (2023).
Google Scholar
Sung, H. Y., Hwang, G. J., Chen, C. Y. & Liu, W. X. A contextual learning model for developing interactive e-books to improve students’ performances of learning the analects of Confucius. Interact. Learn. Environs. 30 (3), 470–483. (2022).
Google Scholar
Xu, E. W., Wang, W. & Wang, Q. X. The effectiveness of collaborative problem solving in promoting students’ critical thinking: A meta-analysis based on empirical literature. Hum. Soc. Sci. Commun. 10 (1), 11. (2023).
Google Scholar
Schiefele, U. Interest, learning, and motivation. Educ. Psychol. 26 (3–4), 299–323. (1991).
Google Scholar
Krapp, A. Interest, motivation and learning: An educational-psychological perspective. Eur. J. Psychol. Educ. 14, 23–40. (1999).
Google Scholar
Hidi, S. & Renninger, K. A. The four-phase model of interest development. Educ. Psychol. 41 (2), 111–127. (2006).
Google Scholar
Harackiewicz, J. M., Durik, A. M., Barron, K. E., Linnenbrink-Garcia, L. & Tauer, J. M. The role of achievement goals in the development of interest: Reciprocal relations between achievement goals, interest, and performance. J. Educ. Psychol. 100 (1), 105. (2008).
Google Scholar
Renninger, K. A., Hidi, S. & Krapp, A. The Role of Interest in Learning and Development (Lawrence Erlbaum, 1992).
Hidi, S. Interest and its contribution as a mental resource for learning. Rev. Educ. Res. 60 (4), 549–571. (1990).
Google Scholar
Palmer, D., Dixon, J. & Archer, J. Using situational interest to enhance individual interest and science-related behaviours. Res. Sci. Educ. 47, 731–753. (2017).
Google Scholar
Ainley, M. Interest: Knowns, unknowns, and basic processes. in The Science of Interest (eds. O’Keefe, P., Harackiewicz, J.) (2017). https://doi.org/10.1007/978-3-319-55509-6_1
Zainuddin, Z., Chu, S. K. W., Shujahat, M. & Perera, C. J. The impact of gamification on learning and instruction: A systematic review of empirical evidence. Educ. Res. Rev. 30, 100326. (2020).
Google Scholar
David, L. & Weinstein, N. Using technology to make learning fun: technology use is best made fun and challenging to optimize intrinsic motivation and engagement. Eur. J. Psychol. Educ. 1–23. (2023).
Google Scholar
Wong, J. T., Chen, E., Au-Yeung, N., Lerner, B. S. & Richland, L. E. Fostering engaging online learning experiences: Investigating situational interest and mind-wandering as mediators through learning experience design. Educ. Inf. Technol. 1–27. (2024).
Google Scholar
Vongkulluksn, V. W., Matewos, A. M., Sinatra, G. M. & Marsh, J. A. Motivational factors in makerspaces: A mixed methods study of elementary school students’ situational interest, self-efficacy, and achievement emotions. Int. J. STEM Educ. 5, 1–19. (2018).
Google Scholar
Schraw, G. & Lehman, S. Situational interest: A review of the literature and directions for future research. Educ. Psychol. Rev. 13, 23–52. (2001).
Google Scholar
Nicholas, K. & Fletcher, J. What is happening in the use of ICT mathematics to support young adolescent learners? A new Zealand experience. Educ. Rev. 69 (4), 474–489. (2017).
Google Scholar
Hwang, G. J., Wang, S. Y. & Lai, C. L. Effects of a social regulation-based online learning framework on students’ learning achievements and behaviors in mathematics. Comput. Educ. 160, 104031. (2021).
Google Scholar
Wang, X. et al. What matters in AI-supported learning: A study of human-AI interactions in Language learning using cluster analysis and epistemic network analysis. Comput. Educ. 194, 104703. (2023).
Google Scholar
Marton, F. & Säljö, R. On qualitative differences in learning: I—Outcome and process. Br. J. Educ. Psychol. 6 (1), 4–11. (1976).
Google Scholar
Gijbels, D., Van de Watering, G., Dochy, F. & Van den Bossche, P. The relationship between students’ approaches to learning and the assessment of learning outcomes. Eur. J. Psychol. Educ. 20, 327–341. (2005).
Google Scholar
Trigwell, K., Ellis, R. A. & Han, F. Relations between students’ approaches to learning, experienced emotions and outcomes of learning. Stud. High. Educ. 37 (7), 811–824. (2012).
Google Scholar
Di, W., Danxia, X. & Chun, L. The effects of learner factors on higher-order thinking in the smart classroom environment. J. Comput. Educ. 6 (4), 483–498. (2019).
Google Scholar
Ellis, R. A. & Bliuc, A. M. Exploring new elements of the student approaches to learning framework: The role of online learning technologies in student learning. Act. Learn. High. Educ. 20 (1), 11–24. (2019).
Google Scholar
Han, J. & Geng, X. University students’ approaches to online learning technologies: The roles of perceived support, affect/emotion and self-efficacy in technology-enhanced learning. Comput. Educ. 194, 104695. (2023).
Google Scholar
Yang, Y., Luo, J., Yang, M., Yang, R. & Chen, J. From surface to deep learning approaches with generative AI in higher education: An analytical framework of student agency. Stud. High. Educ.. (2024).
Google Scholar
González, C., López, D., Calle-Arango, L., Montenegro, H. & Clasing, P. Chilean university students’ digital learning technology usage patterns and approaches to learning. ECNU Rev. Educ. 5 (1), 37–64. (2022).
Google Scholar
Biggs, J. Differentiation of learning processes within ability groups. Educ. Psychol. 4 (1), 21–39. (1984).
Google Scholar
Biggs, J., Kember, D. & Leung, D. Y. The revised two-factor study process questionnaire: R-SPQ-2F. Br. J. Educ. Psychol. 71 (1), 133–149. (2001).
Google Scholar
Kember, D., Biggs, J. & Leung, D. Y. Examining the multidimensionality of approaches to learning through the development of a revised version of the learning process questionnaire. Br. J. Educ. Psychol. 74 (2), 261–279. (2004).
Google Scholar
Liu, S., Liu, S., Liu, Z., Peng, X. & Yang, Z. Automated detection of emotional and cognitive engagement in MOOC discussions to predict learning achievement. Comput. Educ. 181, 104461. (2022).
Google Scholar
Brown, J. S., Collins, A. & Duguid, P. Situated cognition and the culture of learning. Educ. Res. 18 (1), 32–42. (1989).
Google Scholar
Li, X. & Chu, S. K. W. Exploring the effects of gamification pedagogy on children’s reading: A mixed-method study on academic performance, reading‐related mentality and behaviors, and sustainability. Br. J. Educ. Technol. 52 (1), 160–178. (2021).
Google Scholar
Dubovi, I. Cognitive and emotional engagement while learning with VR: The perspective of multimodal methodology. Comput. Educ. 183, 104495. (2022).
Google Scholar
Deci, E. L. & Ryan, R. M. Motivation, personality, and development within embedded social contexts: An overview of self-determination theory. Oxf. Handb. Hum. Motivation 18 (6), 85–107 (2012).
Google Scholar
Bureau, J. S., Howard, J. L., Chong, J. X. & Guay, F. Pathways to student motivation: A meta-analysis of antecedents of autonomous and controlled motivations. Rev. Educ. Res. 92 (1), 46–72. (2022).
Google Scholar
Jack, B. M. & Lin, H. S. Warning! Increases in interest without enjoyment May not be trend predictive of genuine interest in learning science. Int. J. Educ. Dev. 62, 136–147. (2018).
Google Scholar
Biggs, J. What do inventories of students’ learning processes really measure? A theoretical review and clarification. Br. J. Educ. Psychol. 63 (1), 3–19. (1993).
Google Scholar
Wu, X. Y. Exploring the effects of digital technology on deep learning: A meta-analysis. Educ. Inf. Technol. 29 (1), 425–458. (2024).
Google Scholar
Dohn, N. B. Students’ interest in scratch coding in lower secondary mathematics. Br. J. Educ. Technol. 51 (1), 71–83. (2020).
Google Scholar
Sugden, N., Brunton, R., MacDonald, J. B., Yeo, M. & Hicks, B. Evaluating student engagement and deep learning in interactive online psychology learning activities. Australas. J. Educ. Technol. 37 (2), 45–65. (2021).
Google Scholar
Rotgans, J. I. & Schmidt, H. G. The role of teachers in facilitating situational interest in an active-learning classroom. Teach. Teach. Educ. 27 (1), 37–42. (2011).
Google Scholar
Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. Multivariate Data Analysis 8th edn (Cengage Learning, 2019).
Chiu, C. M. & Wang, E. T. Understanding Web-based learning continuance intention: The role of subjective task value. Inf. Manag. 45 (3), 194–201. (2008).
Google Scholar
Pastor, D. A., Barron, K. E., Miller, B. J. & Davis, S. L. A latent profile analysis of college students’ achievement goal orientation. Contemp. Educ. Psychol. 32 (1), 8–47. (2007).
Google Scholar
Richardson, H. A., Simmering, M. J. & Sturman, M. C. A Tale of three perspectives: Examining post hoc statistical techniques for detection and correction of common method variance. Organ. Res. Methods 12 (4), 762–800. (2009).
Google Scholar
Tein, J. Y., Coxe, S. & Cham, H. Statistical power to detect the correct number of classes in latent profile analysis. Struct. Equ Model. 20 (4), 640–657. (2013).
Google Scholar
Linnenbrink-Garcia, L. et al. Measuring situational interest in academic domains. Educ. Psychol. Meas. 70 (4), 647–671. (2010).
Google Scholar
Rotgans, J. I. & Schmidt, H. G. Interest development: Arousing situational interest affects the growth trajectory of individual interest. Contemp. Educ. Psychol. 49, 175–184. (2017).
Google Scholar
Yin, J., Goh, T. T., Yang, B. & Yang, X. Conversation technology with micro-learning: The impact of chatbot-based learning on students’ learning motivation and performance. J. Educ. Comput. Res. 59 (1), 154–177. (2021).
Google Scholar
Lu, G., Xie, K. & Liu, Q. What influences student situational engagement in smart classrooms: Perception of the learning environment and students’ motivation. Br. J. Educ. Technol. 53 (6), 1665–1687. (2022).
Google Scholar
Drymiotou, I., Constantinou, C. P. & Avraamidou, L. Enhancing students’ interest in science and understandings of STEM careers: The role of career-based scenarios. Int. J. Sci. Educ. 43 (5), 717–736. (2021).
Google Scholar
Liu, C. C., Liao, M. G., Chang, C. H. & Lin, H. M. An analysis of children’ interaction with an AI chatbot and its impact on their interest in reading. Comput. Educ. 189, 104576. (2022).
Google Scholar
Chen, S. Y. & Liu, S. Y. Using augmented reality to experiment with elements in a chemistry course. Comput. Hum. Behav. 111, 106418. (2020).
Google Scholar
Lai, T. et al. The application of artificial intelligence technology in education influences Chinese adolescent’s emotional perception. Curr. Psychol. 43 (6), 5309–5317. (2024).
Google Scholar
Happe, L., Buhnova, B., Koziolek, A. & Wagner, I. Effective measures to foster girls’ interest in secondary computer science education: A literature review. Educ. Inf. Technol. 26, 2811–2829. (2021).
Google Scholar
Vos, N., Van Der Meijden, H. & Denessen, E. Effects of constructing versus playing an educational game on student motivation and deep learning strategy use. Comput. Educ. 56 (1), 127–137. (2011).
Google Scholar
Takase, M., Niitani, M. & Imai, T. What educators could do to facilitate students’ use of a deep approach to learning: A multisite cross-sectional design. Nurs. Educ. Today 89, 104422. (2020).
Google Scholar
Asikainen, H. & Gijbels, D. Do students develop towards more deep approaches to learning during studies? A systematic review on the development of students’ deep and surface approaches to learning in higher education. Educ. Psychol. Rev. 29, 205–234. (2017).
Google Scholar
Fryer, L. K. & Ainley, M. Supporting interest in a study domain: A longitudinal test of the interplay between interest, utility-value, and competence beliefs. Learn. Instruc. 60, 252–262. (2019).
Google Scholar
Ainley, M. Connecting with learning: Motivation, affect and cognition interest processes. Educ. Psychol. Rev. 18, 391–405. (2006).
Google Scholar
Eccles, J. S. & Wigfield, A. Motivational beliefs, values, and goals. Annu. Rev. Psychol. 53 (1), 109–132. (2002).
Google Scholar
D’Mello, S., Lehman, B., Pekrun, R. & Graesser, A. Confusion can be beneficial for learning. Learn. Instruc. 29, 153–170. (2014).
Google Scholar
Dirk, J. & Nett, U. E. Uncovering the situational impact in educational settings: Studies on motivational and emotional experiences. Learn. Instruc. 81, 101661. (2022).
Google Scholar
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