Ainley, M., & Ainley, J. (2011). Student engagement with science in early adolescence: The contribution of enjoyment to students’ continuing interest in learning about science. Contemporary Educational Psychology, 36(1), 4-12. https://doi.org/10.1016/j.cedpsych.2010.08.001

Anderson, A. E., Justement, L. B., & Bruns, H. A. (2020). Using real-world examples of the COVID-19 pandemic to increase student confidence in their scientific literacy skills. Biochemistry and Molecular Biology Education, 48(6), 678-684. https://doi.org/10.1002/bmb.21474

Anelli, C. (2011). Scientific literacy: What is it, are we teaching it, and does it matter? American Entomologist, 57(4), 235-244. https://doi.org/10.1093/ae/57.4.235 

Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238-246. https://doi.org/10.1037/0033-2909.107.2.238

Berkley, S. (2020). COVID-19 needs a Big Science approach. Science, 367(6485), 1407. https://doi.org/10.1126/science.abb8654

Brown, G., & Susskind, D. (2020). International cooperation during the COVID-19 pandemic. Oxford Review of Economic Policy, 36 (Supplement_1), S64-S76. https://doi.org/10.1093/oxrep/graa025

Chen, F., & Cui, Y. (2020). Investigating the relation of perceived teacher unfairness to science achievement by hierarchical linear modeling in 52 countries and economies. Educational Psychology, 40(3), 273-295. https://doi.org/10.1080/01443410.2019.1652248

Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling: A Multidisciplinary Journal, 14(3), 464-504. https://doi.org/10.1080/10705510701301834

Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling: A Multidisciplinary Journal, 9(2), 233-255. https://doi.org/10.1207/S15328007SEM0902_5

Coccia, M. (2021). Evolution and structure of research fields driven by crises and environmental threats: The COVID-19 research. Scientometrics, 126, 9405-9429. https://doi.org/10.1007/s11192-021-04172-x

Dávila-Acedo, M. A., Cañada, F., Sánchez-Martín, J., Airado-Rodríguez, D., & Mellado, V. (2021). Emotional performance on physics and chemistry learning: The case of Spanish K-9 and K-10 students. International Journal of Science Education, 43(6), 823-843. https://doi.org/10.1080/09500693.2021.1889069

Dewey, J. (1903). Interest as related to will. The University of Chicago Press.

Dimitrov, D. M. (2010). Testing for factorial invariance in the context of construct validation. Measurement and Evaluation in Counseling and Development, 43(2), 121-149. https://doi.org/10.1177/0748175610373459

Dunn, T. J., Baguley, T., & Brunsden, V. (2014). From alpha to omega: A practical solution to the pervasive problem of internal consistency estimation. The British Journal of Psychology, 105(3), 399-412. https://doi.org/10.1111/bjop.12046

Elsner, J. N., Sadler, T. D., Zangori, L., Friedrichsen, P. J., & Ke, L. (2022). Student interest, concerns, and information-seeking behaviors related to COVID-19. Disciplinary and Interdisciplinary Science Education Research, 4, Article 11. https://doi.org/10.1186/s43031-022-00053-2

Feinstein, N. (2011). Salvaging science literacy. Science Education, 95(1), 168-185. https://doi.org/10.1002/sce.20414  

Fernandez, P. (2022). Facebook, Meta, the metaverse and libraries. Library Hi Tech News, 39(4), 1-3. https://doi.org/10.1108/LHTN-03-2022-0037

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104

Gadekallu, T. R., Huynh-The, T., Wang, W., Yenduri, G., Ranaweera, P., Pham, Q.-V., da Costa, D. B., & Liyanage, M. (2022). Blockchain for the metaverse: A review. arXiv preprint.  https://arxiv.org/abs/2203.09738

Hartley, D. (2006). Excellence and enjoyment: The logic of a ‘contradiction’. British Journal of Educational Studies, 54(1), 3-14. https://doi.org/10.1111/j.1467-8527.2005.00331.x 

Hidi, S., & Renninger, K. A. (2006). The four-phase model of interest development. Educational Psychologist, 41(2), 111-127. https://doi.org/10.1207/s15326985ep4102_4

Ho, H.-Y., Chen, Y.-L., & Yen, C.-F. (2020). Different impacts of COVID-19-related information sources on public worry: An online survey through social media. Internet Interventions, 22, Article 100350. https://doi.org/10.1016/j.invent.2020.100350

Hsu, T.-C., Huang, H.-L., Hwang, G.-J., & Chen, M.-S. (2023). Effects of incorporating an expert decision-making mechanism into chatbots on students’ achievement, enjoyment, and anxiety. Educational Technology and Society, 26(1), 218-231. https://doi.org/10.30191/ETS.202301_26(1).0016

Hu, L.-T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55. https://doi.org/10.1080/10705519909540118

Hughes, H. E., Benson, K., Brody, D., Murphy, A., & Ranschaert, R. (2022). A case study: Enacting courage and collaboration in equity and justice-oriented educational leadership. Middle School Journal, 53(2), 5-11. https://doi.org/10.1080/00940771.2021.2022444

Jack, B. M., Chen, C.-C., & Smith, T. J. (2021). Validating Dewey’s notion of genuine interest. Journal of Psychoeducational Assessment, 39(3), 301-314. https://doi.org/10.1177/0734282920967133

Jack, B. M., Hong, Z.-R., Lin, H.-S., & Smith, T. J. (2024). Ecological stimuli predicting high school students’ genuine interest in socio-scientific issues. Science and Education, 33, 831-851.  https://doi.org/10.1007/s11191-022-00413-4

Jack, B. M., Lee, L., Yang, K.-K., & Lin, H.-S. (2017). A science for citizenship model: Assessing the effects of benefits, risks, and trust for predicting students’ interest in and understanding of science-related content. Research in Science Education, 47, 965-988. https://doi.org/10.1007/s11165-016-9535-9

Jack, B. M., & Lin, H.-S. (2014). Igniting and sustaining interest among students who have grown cold toward science. Science Education, 98(5), 792-814. https://doi.org/10.1002/sce.21119

Jack, B. M., & Lin, H.-S. (2018). Warning! Increases in interest without enjoyment may not be trend predictive of genuine interest in learning science. International Journal of Educational Development, 62, 136-147. https://doi.org/10.1016/j.ijedudev.2018.03.005

Kao, S.-F. (2014, July 13–19). Anti-nuclear movement in Taiwan: Fukushima disaster prompts the case for citizen participation in democratization of energy policy [Paper presentation]. XVIII ISA World Congress of Sociology, Yokohama, Japan.

Ke, L., Sadler, T. D., Zangori, L., & Friedrichsen, P. J. (2020). Students’ perceptions of socio-scientific issue-based learning and their appropriation of epistemic tools for systems thinking. International Journal of Science Education, 42(8), 1339-1361. https://doi.org/10.1080/09500693.2020.1759843

Koff, W. C., Schenkelberg, T., Williams, T., Baric, R. S., McDermott, A., Cameron, C. M., Cameron, M. J., Friemann, M. B., Neumann, G., Kawaoka, Y., Kelvin, A. A., Ross, T. M., Schultz-Cherry, S., Mastro, T. D., Priddy, F. H., Moore, K. A., Ostrowsky, J. T., Osterholm, M. T., & Goudsmit, J. (2021). Development and deployment of COVID-19 vaccines for those most vulnerable. Science Translational Medicine, 13(579), Article eabd1525. https://doi.org/10.1126/scitranslmed.abd1525

Krapp, A. (2002). Structural and dynamic aspects of interest development: Theoretical considerations from an ontogenetic perspective. Learning and Instruction, 12(4), 383-409. https://doi.org/10.1016/S0959-4752(01)00011-1

Li, Y., Tenchov, R., Smoot, J., Liu, C., Watkins, S., & Zhou, Q. (2021). A comprehensive review of the global efforts on COVID-19 vaccine development. ACS Central Science, 7(4), 512-533. https://doi.org/10.1021/acscentsci.1c00120

Liao, Y. (2023). Effects of immersive virtual reality technology on online learning outcomes. International Journal of Emerging Technologies in Learning, 18(13), 62-73. https://doi.org/10.3991/ijet.v18i13.41201

Lin, H.-S., Lawrenz, F., Lin, S.-F., & Hong, Z.-R. (2013). Relationships among affective factors and preferred engagement in science related activities. Public Understanding of Science, 22(8), 941-954. https://doi.org/10.1177/0963662511429412 

López-Fernández, M. d. M., González-García, F., & Franco-Mariscal, A. J. (2021). Should we ban single-use plastics? A role-playing game to argue and make decisions in a grade-8 school chemistry class. Journal of Chemical Education, 98(12), 3947-3956. https://doi.org/10.1021/acs.jchemed.1c00580

McDonald, R. P. (1999). Test theory: A unified treatment. Lawrence Erlbaum.

Mirahmadizadeh, A., Ranjbar, K., Shahriarirad, R., Erfani, A., Ghaem, H., Jafari, K., & Rahimi, T. (2020). Evaluation of students’ attitude and emotions towards the sudden closure of schools during the COVID-19 pandemic: A cross-sectional study. BMC Psychology, 8, Article 134. https://doi.org/10.1186/s40359-020-00500-7

National Academies of Sciences, Engineering, Medicine. (2018). Learning through citizen science, enhancing opportunities by design. The National Academies Press. https://doi.org/10.17226/25183

Nguyen, H. D., Pham, V. T., Tran, D. A., & Le, T. T. (2019, October). Intelligent tutoring chatbot for solving mathematical problems in high-school. In 2019 11th International Conference on Knowledge and Systems Engineering (KSE) (pp. 1-6). IEEE. https://doi.org/10.1109/KSE.2019.8919396

Organization for Economic Cooperation and Development. (2023). PISA 2025 science framework (Draft). https://bit.ly/3KWzWTh

Rao, M. E., & Rao, D. M. (2021). The mental health of high school students during the COVID-19 pandemic. Frontiers in Education, 6, Article 719539. https://doi.org/10.3389/feduc.2021.719539

Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1-36. https://doi.org/10.18637/jss.v048.i02

Sardar, Z. (2010). Welcome to postnormal times. Futures, 42(5), 435-444. https://doi.org/10.1016/j.futures.2009.11.028

Sardar, Z. (2021). Afterthoughts: Transnormal, the “new normal” and other varieties of “normal” in postnormal times. Word Futures Review, 13(2), 54-70. https://doi.org/10.1177/19467567211025755

Schiefele, U. (1992). Topic interest and levels of text comprehension. In K. A. Renninger, S. Hidi, & A. Kapp (Eds.), The role of interest in learning and development (pp. 151-182). Psychology Press.

Schraw, G., & Lehman, S. (2001). Situational interest: A review of the literature and directions for future research. Educational Psychology Review, 13, 23-52. https://doi.org/10.1023/A:1009004801455

Slaoui, M., & Hepburn, M. (2020). Developing safe and effective Covid vaccines - Operation Warp Speed’s strategy and approach. New England Journal of Medicine, 383(18), 1701-1703. https://doi.org/10.1056/NEJMp2027405

Stanovich, K. E., West, R. F., & Toplak, M. E. (2013). Myside bias, rational thinking, and intelligence. Current Directions in Psychological Science, 22(4), 259-264. https://doi.org/10.1177/0963721413480174

Steiger, J. H., & Lind, J. C. (1980, May 27-29). Statistically based tests for the numbers of factors [Paper presentation]. Psychometric Society Annual Meeting, Iowa, IA.

Stenseth, T., Bråten, I., & Strømsø, H. I. (2016). Investigating interest and knowledge as predictors of students' attitudes towards socio-scientific issues. Learning and Individual Differences, 47, 274-280. https://doi.org/10.1016/j.lindif.2016.02.005

Thakur, A. (2020). Mental health in high school students at the time of COVID-19: A student's perspective. Journal of the American Academy of Child and Adolescent Psychiatry, 59(12), 1309–1310. https://doi.org/10.1016/j.jaac.2020.08.005

Topcu, M. S. (2010). Development of Attitudes towards Socioscientific Issues Scale for undergraduate students. Evaluation and Research in Education, 23(1), 51-67. https://doi.org/10.1080/09500791003628187

Tran, L. T., Phan, H. L. T., & Bellgrove, A. (2021). ‘There's a much bigger world of science than just Australia': Australian students’ development of disciplinary knowledge, transferable skills and attributes through a New Colombo Plan short-term mobility program to Japan. International Journal of Science Education, 43(6), 888-905. https://doi.org/10.1080/09500693.2021.1891322 

Tucker, L. R., & Lewis, C. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38, 1-10. https://doi.org/10.1007/BF02291170

Ureta, J., & Rivera, J. P. (2018). Using chatbots to teach STEM related research concepts to high school students. In H. Ogata, Y. Song, J.-C. Yang, M. Chang, L.-H. Wong, & M. M. T. Rodrigo (Eds.), Workshop Proceedings of the 26th International Conference on Computers in Education (pp. 338-343). Asia-Pacific Society for Computers in Education.

Verdecia, M., Kokai-Kun, J. F., Kibbey, M., Acharya, S., Venema, J., & Atouf, F. (2021). COVID-19 vaccine platforms: Delivering on a promise? Human Vaccines and Immunotherapeutics, 17(9), 2873-2893. https://doi.org/10.1080/21645515.2021.1911204

Vuolanto, P., Almeida, A. N., Anderson, A., Auvinen, P., Beja, A., Bracke, P., Cardano, M., Ceuterick, M., Correia, T., De Vito, E., Delaruelle, K., Delicado, A., Esposito, M., Ferrara, M., Garilio, L., Guerreiro, C., Marhánková, J. H., Hilário, A. P., Hobson-West, P., … Wagner, A. (2024). Trust matters: The addressing vaccine hesitancy in Europe study. Scandinavian Journal of Public Health, 52(3), 379-390. https://doi.org/10.1177/14034948231223791

Wan, Y., & Bi, H. (2020). What major “socio-scientific topics” should the science curriculum focused on? A Delphi study of the expert community in China. International Journal of Science and Mathematics Education, 18, 61-77. https://doi.org/10.1007/s10763-018-09947-y

Weinberg, A. M. (1972). Science and trans-science. Minerva, 10, 209-222. https://doi.org/10.1007/BF01682418

Wu, L., & Kong, X. (2023). COVID-19 pandemic: Ethical issues and recommendations for emergency triage. Frontiers in Public Health, 11, Article 1160769. https://doi.org/10.3389/fpubh.2023.1160769

Yerdelen, S., Cansiz, M., Cansiz, N., & Akcay, H. (2018). Promoting preservice teachers’ attitudes toward socioscientific issues. Journal of Education in Science Environment and Health, 4(1), 1-11. https://bit.ly/4bdgZql

Zhu, J., & Mok, M. M. C. (2018). Predicting primary students’ self-regulated learning by their prior achievement, interest, personal best goal orientation and teacher feedback. Educational Psychology, 38(9), 1106-1128. https://doi.org/10.1080/01443410.2018.1497775

Zoumpourlis, V., Goulielmaki, M., Rizos, E., Baliou, S., & Spandidos, D. A. (2020). [Comment] The COVID-19 pandemic as a scientific and social challenge in the 21st century. Molecular Medicine Reports, 22(4), 3035-3048. https://doi.org/10.3892/mmr.2020.11393