Abidin, Z., Susilowati, S. M. E., Prasetyo, A. P. B., & Ridlo, S. (2020). The profile changes in pedagogical content knowledge of pre-service biology teachers based on the concept maps. Journal of Physics: Conference Series, 1567(4), 042083. https://doi.org/10.1088/1742-6596/1567/4/042083

Adams, T., Koster, B., & Brok, P. den. (2022). Patterns in student teachers’ learning processes and outcomes of classroom management during their internship. Teaching and Teacher Education, 120, 103891. https://doi.org/10.1016/j.tate.2022.103891

Adler, I., & Akad, I. (2024). New roles for science teachers: A cultural-historical activity theory intervention to support education for health, wellbeing, and citizenship. Teaching and Teacher Education, 145, 104635. https://doi.org/10.1016/j.tate.2024.104635

Agyare, B., Asare, J., Kraishan, A., Nkrumah, I., & Adjekum, D. K. (2025). A cross-national assessment of artificial intelligence (AI) Chatbot user perceptions in collegiate physics education. Computers and Education: Artificial Intelligence, 8, 100365. https://doi.org/10.1016/j.caeai.2025.100365

Akram, H., Aslam, S., Saleem, A., & Parveen, K. (2021). The Challenges of online teaching in COVID-19 pandemic: a case study of public universities in karachi, pakistan. Journal of Information Technology Education: Research, 20, 263–282. https://www.informingscience.org/Publications/4784

Alfi, B. R., Paidi, P., & Pratama, A. T. (2024). Validating instrument to assess science literacy and independent learning skills in high school. JPBI (Jurnal Pendidikan Biologi Indonesia), 10(3), Article 3. https://doi.org/10.22219/jpbi.v10i3.34770

Alias, N. F., & Razak, R. A. (2023). Exploring the pedagogical aspects of microlearning in educational settings: a systematic literature review. Malaysian Journal of Learning and Instruction, 20(2), 267–294. https://doi.org/10.32890/mjli2023.20.2.3

Alwan, A. A. (2011). Misconception of heat and temperature Among physics students. Procedia - Social and Behavioral Sciences, International Conference On Education and Educational Psychology 2010, 12, 600–614. https://doi.org/10.1016/j.sbspro.2011.02.074

Aljuhani, K., Sonbul, M., Althabiti, M., & Meccawy, M. (2018). Creating a virtual science lab (VSL): the adoption of virtual labs in Saudi schools. Smart Learning Environments, 5(1), 1–16.

Alneyadi, S. S. (2019). Virtual lab implementation in science literacy: Emirati science teachers’ perspectives. Eurasia Journal of Mathematics, Science and Technology Education, 15(12), em1786.

Andriani, W. (2021). Penggunaan metode sistematik literatur review dalam penelitian ilmu sosiologi [The use of a systematic literature review method in sociological research]. Jurnal PTK Dan Pendidikan, 7(2). 12–21.

Antonietti, C., Consoli, T., Schmitz, M.-L., Cattaneo, A., Gonon, P., & Petko, D. (2025). “Digital constructivists, activators or presenters? Different profiles of technology integration among Swiss upper secondary school teachers.” Computers & Education, 227, 105225. https://doi.org/10.1016/j.compedu.2024.105225

Arista, F. S., & Kuswanto, H. (2018). Virtual physics laboratory application based on the Android smartphone to improve learning independence and conceptual Understanding. International Journal of Instruction, 11(1), 1–16.

Badryatusyahryah, B., Winarsih, M., Kustandi, C., & Putro, P. A. (2022). Penerapan gamifikasi dalam pendidikan fisika: suatu studi literatur sistematis [The implementation of gamification in physics education: A systematic literature review]. Kwangsan: Jurnal Teknologi Pendidikan, 10(2), 283–301.

Booth, A., Papaioannou, D., & Sutton, A. (2012). Systematic approaches to a successful literature review. Sage Publications.

Bilotta, E., Demarco, F., Soranzo, A., Pantano, P., & Bertacchini, F. (2026). A Pilot Educational Framework for AI-Enhanced Digital Manufacturing and Reflective Skill Development. Computers and Education Open, 100342. https://doi.org/10.1016/j.caeo.2026.100342

Chan, C. K. Y., & Lee, K. K. W. (2023). The AI generation gap: Are Gen Z students more interested in adopting generative AI such as ChatGPT in teaching and learning than their Gen X and millennial generation teachers? Smart Learning Environments, 10(1), 60. https://doi.org/10.1186/s40561-023-00269-3

Chen, C., Rabu, S. N. A., & Jamiat, N. (2025). Enhancing physics learning achievement, motivation and inquiry skills in a flipped classroom: A structured inquiry-based virtual lab approach. Journal of Baltic Science Education, 24(1), 37-52

Chen, S., Yin, H., & Cheung, A. C. K. (2025). How professional capital empowers ICT Integration: The roles of teachers’ constructivist belief, differentiated instruction and AI literacy. International Journal of Educational Research, 133, 102715. https://doi.org/10.1016/j.ijer.2025.102715

Chen, X., Liu, J., Liu, Y., Xiang, H., Guo, X., Cai, X., & Wang, X. (2026). Can ChatGPT outperform college students in critical thinking skills during argumentation activities? A case study. Thinking Skills and Creativity, 61, 102166. https://doi.org/10.1016/j.tsc.2026.102166

Chen, Z. (2026). Metaverse Enabled virtual reality and simulation training for medical education review. iScience, 115656. https://doi.org/10.1016/j.isci.2026.115656

Chi, M. T. H., Slotta, J. D., & De Leeuw, N. (1994). From things to processes: A theory of conceptual change for learning science concepts. Learning and Instruction, 4(1), 27–43. https://doi.org/10.1016/0959-4752(94)90017-5

Clancy, M., Wade, I. S., & Young, J. J. (2023). Facile methods for reusing laboratory plastic in developmental biology experiments. Differentiation, 130, 1–6. https://doi.org/10.1016/j.diff.2022.11.001

Conica, M., Nixon, E., & Quigley, J. (2023). Talk outside the box: Parents’ decontextualized language during preschool years relates to child numeracy and literacy skills in middle childhood. Journal of Experimental Child Psychology, 236, 105746. https://doi.org/10.1016/j.jecp.2023.105746

Darby-White, T., Wicker, S., & Diack, M. (2019). Evaluating the effectiveness of virtual chemistry laboratory (VCL) in enhancing conceptual understanding: Using VCL as pre-laboratory assignment. Journal of Computers in Mathematics and Science Teaching, 38(1), 31-48

Demir, M., Leahy, S. M., Mishra, P., Chen, C. K., & Singharoy, A. (2023). Adaptive artificial intelligence to teach interactive molecular dynamics in the context of human-computer interaction. bioRxiv, 8(2). 12–25.

Dehghanzadeh, S., & Moaddab, F. (2026). The effects of nursing care planning through concept mapping on nursing students’ critical thinking skills. International Journal of Africa Nursing Sciences, 24, 100945. https://doi.org/10.1016/j.ijans.2025.100945

Dewi, S. M., Gunawan, G., Harjono, A., Susilawati, S., & Herayanti, L. (2020). Generative learning models assisted by virtual laboratory to improve mastery of student physics concept. In Journal of Physics: Conference Series, 1521(2), 022013.

Fadillah, M. A., Iyamuremye, A., Kaliampos, G., Ravanis, K., Usmeldi, U., & Asrizal, A. (2026). Social predictors of inquiry learning climate in physics education: Insights from explainable machine learning. Social Sciences & Humanities Open, 13, 102439. https://doi.org/10.1016/j.ssaho.2026.102439

Fılız, T., & Öztel, N. Ç. (2026). Strategy instruction integrated with realistic mathematics education: A design-based research on teaching word problem solving to students with learning disabilities. Thinking Skills and Creativity, 61, 102203. https://doi.org/10.1016/j.tsc.2026.102203

Garabet, M., & Miron, C. (2010). Conceptual map – didactic method of constructivist type during the physics lessons. Procedia - Social and Behavioral Sciences, Innovation and Creativity in Education, 2(2), 3622–3631. https://doi.org/10.1016/j.sbspro.2010.03.564

García-Vela, M., Zambrano, J. L., Falquez, D. A., Pincay-Musso, W., Duque, K. B., Zumba, N. V., & Jordá-Bordehore, L. (2020). Management of virtual laboratory experiments in the geosciences field in the time of COVID-19 pandemic. In Iceri2020 Proceedings, 2(1), 8702–8711.

Gezer, S. U. (2015). A Case Study on Preservice Science Teachers’ Laboratory Usage Self Efficacy and Scientific Process Skills. Procedia - Social and Behavioral Sciences, International Conference on New Horizons in Education, INTE 2014, 25-27 June 2014, Paris, France, 174, 1158–1165. https://doi.org/10.1016/j.sbspro.2015.01.732

Gilliam, C. A., Lurie, B., Winn, A. S., Barber, A., Jackson, D., Weisgerber, M., & Unaka, N. (2024). The role of competency based medical education in addressing health inequities and cultivating inclusive learning environments. Current Problems in Pediatric and Adolescent Health Care, Preparing Future Pediatricians and Pediatric Subspecialists: Competency-Based Medical Education - Part 1, 54(9), 101641. https://doi.org/10.1016/j.cppeds.2024.101641

Gu, C., Jin, F., & Li, Y. (2024). The mediating role of psychological capital in the relationship between foreign language anxiety and learning burnout among college students with different language environments. System, 126, 103499. https://doi.org/10.1016/j.system.2024.103499

Gunawan, G., Dewi, S. M., Herayanti, L., Lestari, P. A. S., & Fathoroni, F. (2020). Gender influence on student’s creativity in physics learning with virtual laboratory. In Journal of Physics: Conference Series, 1471(1), 012036.

Gunawan, G., Nisrina, N., Suranti, N. M. Y., Herayanti, L., & Rahmatiah, R. (2018). Virtual laboratory to improve students’ conceptual understanding in physics learning. In Journal of Physics: Conference Series, 1108(1), 012049.

Gutiérrez-García, L., Sánchez-Martín, J., Blanco-Salas, J., Ruiz-Téllez, T., & Corbacho-Cuello, I. (2024). Use of aromatic plants and essential oils in the teaching of physics and chemistry to enhance motivation and sustainability awareness among primary education trainee teachers. Heliyon, 10(15), e35301. https://doi.org/10.1016/j.heliyon.2024.e35301

Hamdani (2014). Penerapan model ecirr menggunakan kombinasi real laboratory dan virtual laboratory untuk mereduksi miskonsepsi mahasiswa [The implementation of the ecirr model using a combination of real and virtual laboratories to reduce students’ misconceptions]. Jurnal Visi Ilmu Pendidikan, 6(3). 34-42.

Hamdani, H. (2022). Penerapan virtual laboratory untuk mereduksi jumlah mahasiswa calon guru fisika yang mengalami miskonsepsi tentang efek foto Listrik [The implementation of virtual laboratories to reduce misconceptions on the photoelectric effect among pre-service physics teacher]. Jurnal Ilmiah Pendidikan Fisika, 6(2), 275–282.

Hamed, G., & Aljanazrah, A. (2020). The effectiveness if using virtual experiments on students’ learning in the general physics lab. Journal of Information Technology Education: Research, 19(1),977-996

Han, T.-Y., Wei, Z.-H., Bi, J.-W., & Wei, F.-Y. (2026). The impact of user-generated images on subsequent ratings: Evidence from a quasi-experimental design. Annals of Tourism Research, 117, 104134. https://doi.org/10.1016/j.annals.2026.104134

Herga, N. R., Čagran, B., & Dinevski, D. (2016). Virtual laboratory in the role of dynamic visualization for better understanding of chemistry in primary school. Eurasia Journal of Mathematics, Science and Technology Education, 12(3), 593-608.

Hidayat, A., & Redjeki, S. (2020). Pengaruh penggunaan laboratorium virtual terhadap keterampilan proses sains siswa dalam pembelajaran fisika (The effect of virtual laboratory use on students’ science process skills in physics learning). Jurnal Pendidikan Sains Indonesia, 8(1), 34–41.

Husnaini, S. J., & Chen, S. (2019). Effects of guided inquiry virtual and physical laboratories on conceptual understanding, inquiry performance, scientific inquiry self-efficacy, and enjoyment. Physical Review Physics Education Research, 15(1), 010119.

Hsu, T.-C., Wen, W.-N., Liao, C.-S., Tu, Y.-F., & Lee, M.-J. (2025). Virtual reality in P-12 education for improving presence, immersion, and 4C skills: A systematic review of empirical research. Thinking Skills and Creativity, 58, 101918. https://doi.org/10.1016/j.tsc.2025.101918

Iofciu, F., Miron, C., & Antohe, S. (2011). A constructivist approach of advanced physics concepts: Using a cognitive map for the study of magnetoresistive materials. Procedia - Social and Behavioral Sciences, 3rd World Conference on Educational Sciences - 2011, 15, 461–465. https://doi.org/10.1016/j.sbspro.2011.03.122

Jarutkamolpong, S., & Kwangmuang, P. (2025). Enhancing undergraduate creative thinking through a constructivist mobile learning application: Design, development, and evaluation. Thinking Skills and Creativity, 57, 101866. https://doi.org/10.1016/j.tsc.2025.101866

Kavargyris, D. C., Mittas, N., & Angelis, L. (2026). Growing skills from code via SciESCO: A tri-phasic bibliometric-driven framework of scientific software development. Journal of Systems and Software, 237, 112864. https://doi.org/10.1016/j.jss.2026.112864

Kitchenham, B., & Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering. EBSE Technical Report, Keele University and Durham University.

Kikas, E., Puusepp, I., & Aus, K. (2024). Expectancy-value-cost motivational profiles in biology and physics: Their relations with gender, self-reported satisfaction of needs, and learning behavior. Learning and Individual Differences, 115, 102520. https://doi.org/10.1016/j.lindif.2024.102520

Kirchhoff, T., Wilde, M., Randler, C., & Großmann, N. (2024). Are you learning or performing? A comparison of students’ goal orientation during experimentation at an outreach science laboratory and at school using the CEAS model. Learning and Instruction, 93, 101972. https://doi.org/10.1016/j.learninstruc.2024.101972

Kittel, A. (2026). Effective decision-making or affective? Affective learning design in sport officials’ training. Performance Enhancement & Health, 14(3), 100430. https://doi.org/10.1016/j.peh.2026.100430

Kong, S. C., & Zhu, J. (2026). Exploring the relationship between empowerment in using artificial intelligence for problem-solving and artificial intelligence ethical awareness: Multi-group structural equation modelling. Computers and Education: Artificial Intelligence, 10, 100555. https://doi.org/10.1016/j.caeai.2026.100555

Korthals Altes, T., Willemse, M., Goei, S. L., & Ehren, M. (2024). Higher education teachers’ understandings of and challenges for inclusion and inclusive learning environments: A systematic literature review. Educational Research Review, 43, 100605. https://doi.org/10.1016/j.edurev.2024.100605

Lee, K.-H. (2026). Validating experiential learning competencies in hospitality education: A three-study examination of leadership self-efficacy and community contribution. Journal of Hospitality, Leisure, Sport & Tourism Education, 38, 100606. https://doi.org/10.1016/j.jhlste.2026.100606

Lehesvuori, S., Lehtinen, A., Hämäläinen, R., Maunuksela, J., & Koskinen, P. (2023). Student-centredness in physics laboratory teaching sessions. Learning, Culture and Social Interaction, 43, 100773. https://doi.org/10.1016/j.lcsi.2023.100773

Lin, C., Wang, J., Chen, Y., & Man, S. S. (2026). A systematic review and meta-analysis on the effectiveness of virtual reality technology in laboratory safety training and education. International Journal of Industrial Ergonomics, 113, 103933. https://doi.org/10.1016/j.ergon.2026.103933

Marlina, R., Suwono, H., Ibrohim, I., Yuenyong, C., Hamdani, H., & Pamungkas, R. (2025). CRTP: Learning model for integrating STEM competencies in pre-service biology teachers. Journal of Education and Learning (EduLearn), 19(3), 1466–1473. http://edulearn.intelektual.org/index.php/EduLearn/article/view/21818

Marlina, R., Suwono, H., Yuenyong, C., Ibrohim, I., Mahanal, S., Saefi̇, M., & Hamdani̇, H. (2023). Technological Pedagogical Content Knowledge (TPACK) for Preservice Biology Teachers: Two Insights More Promising. Participatory Educational Research, 10(6), 245–265. https://doi.org/10.17275/per.23.99.10.6

McRorie, J. W., & McKeown, N. M. (2017). Understanding the Physics of Functional Fibers in the Gastrointestinal Tract: An Evidence-Based Approach to Resolving Enduring Misconceptions about Insoluble and Soluble Fiber. Journal of the Academy of Nutrition and Dietetics, 117(2), 251–264. https://doi.org/10.1016/j.jand.2016.09.021

Mielke, P. W., & Berry, K. J. (2009). A note on Cohen’s weighted kappa coefficient of agreement with linear weights. Statistical Methodology, 6(5), 439–446. https://doi.org/10.1016/j.stamet.2009.03.002

Mishra, H., Kumar, A., Sharma, M., Singh, M., Sharma, R., & Ambikapathy, A. (2021). Application of augmented reality in the field of virtual labs. In 2021 International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), 12(2), 403–405.

Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & The PRISMA Group. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Medicine, 6(7), e1000097.

Muhali & Asy’ari, M. (2026). Conceptual problem-based learning model: Promising intervention to enhance prospective science teachers’ critical thinking skills. Social Sciences & Humanities Open, 13, 102509. https://doi.org/10.1016/j.ssaho.2026.102509

Mukagihana, J., Nsanganwimana, F., & Aurah, C. M. (2022). Dataset related to the effect of resource-based instruction on Rwandan pre-service biology teachers’ academic achievement, attitude, and motivation. Data in Brief, 41, 107939. https://doi.org/10.1016/j.dib.2022.107939

Napirah, M., & Safiuddin, A. (2024). Studi literatur penggunaan laboratorium virtual dalam pembelajaran fisika [A literature review on the use of virtual laboratories in physics education]. Jurnal Penelitian Pendidikan Fisika, 9(3), 108–116.

O'Dea, R. E., Lagisz, M., Jennions, M. D., Koricheva, J., Noble, D. W., Parker, T. H., & Nakagawa, S. (2021). Preferred reporting items for systematic reviews and meta‐analyses in ecology and evolutionary biology: a PRISMA extension. Biological Reviews, 96(5), 1695-1722.

Price, C. B., & Price-Mohr, R. (2019). PhysLab: a 3D virtual physics laboratory of simulated experiments for advanced physics learning. Physics Education, 54(3), 035006.

Rizki, I. A., Mirsa, F. R., Islamiyah, A. N., Saputri, A. D., Ramadani, R., & Habibbulloh, M. (2025). Ethnoscience-enhanced physics virtual simulation and augmented reality with inquiry learning: Impact on students’ creativity and motivation. Thinking Skills and Creativity, 57, 101846. https://doi.org/10.1016/j.tsc.2025.101846

Rodríguez-Molina, A., Cruz-Martínez, M. A., Aldape-Pérez, M., Rueda-Gutiérrez, A. B., Villarreal-Cervantes, M. G., & Flores-Caballero, G. (2026). Framework for the development of virtual laboratories for dynamic systems in WebVR: A robotics laboratory case study. Alexandria Engineering Journal, 142, 17–40. https://doi.org/10.1016/j.aej.2026.03.042

Rosen, D. J., & Kelly, A. M. (2020). Epistemology, socialization, help seeking, and gender-based views in in-person and online, hands-on undergraduate physics laboratories. Physical Review Physics Education Research, 16(2), 020116. https://doi.org/10.1103/PhysRevPhysEducRes.16.020116

Rosi, T., Onorato, P., & Oss, S. (2022). Augmented reality active learning (AnReAL) activities for teaching/learning motion concepts. In Journal of Physics: Conference Series, 2297(1), 012005.

Saefan, J., Hardyanto, W., & Wiyanto. (2026). Dynamical modeling as a pathway to scientific creativity: Evidence from physics education students. Social Sciences & Humanities Open, 13, 102402. https://doi.org/10.1016/j.ssaho.2025.102402

Samsudin, A., Suhendi, E., & Wulan, A. R. (2017). Effectiveness of virtual physics laboratory in enhancing students’ understanding on heat and temperature. Jurnal Pendidikan Fisika Indonesia, 13(2), 78–85.

Saparini, S., Andriani, N., & Misbah, M. (2021). Publications related to virtual laboratories during the covid 19 pandemic: A bibliometric review and analysis. In Journal of Physics: Conference Series, 2104(1), p. 012012.

Saputra, O. (2022). Development of virtual simulation to reduce the number of high school students' misconceptions about fluid topics. JPPS (Jurnal Penelitian Pendidikan Sains), 12(1), 100–107.

Savytska, І., Bulgakova, O., Zbaravska, L., Ruciņš, A., Aboltins, A., Torchuk, M., & Vasileva, V. (2025). Application of the educational information systems in professional training of agricultural engineers studying physics. Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference, 3(2), 277–282.

Shapiyeva, A., Baigissova, K., Altybayev, G., Daineko, Y., Nurakhmetova, S., & Abdramanova, G. (2025). Using blended learning and ai in teaching physics in higher education institutions. Procedia Computer Science, 16th International Conference on Emerging Ubiquitous Systems and Pervasive Networks / 15th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare, 272, 439–444. https://doi.org/10.1016/j.procs.2025.10.228

Sharma, B., Gargrish, S., Kaur, A., & Mantri, A. (2022). Effect of virtual reality-based pre-lab training simulator on students’ learning and skills in laboratory work: A comparative exploration. In AIP Conference Proceedings 2357(1), 53–67.

Sulistina, O., Andhini, A. R., Mahmudah, H. A., Al Maudrey, L. I., & Wahyuni, R. (2024). Systematic literature review: penggunaan media pembelajaran virtual lab pada pembelajaran kimia (Systematic literature review: the use of virtual laboratory learning media in chemistry education). UNESA Journal of Chemical Education, 13(2), 100–107.

Silitonga, H. T. M., Sutiana, W., Panjaitan, M., & Supriyati, Y. (2020). Metacognitive learning strategy with reflective-lesson log toward students’ physics achievement. Journal of Physics: Conference Series, 1491(1), 012014. https://iopscience.iop.org/article/10.1088/1742-6596/1491/1/012014/meta

Smallwood, E., Burke, R., Barnes, A. P., & Ivarson, M. (2026). The DaTUM framework: A multi-sector thematic analysis of data quality dimensions and their impacting factors. International Journal of Information Management Data Insights, 6(1), 100407. https://doi.org/10.1016/j.jjimei.2026.100407

Soeharto, S., & Csapó, B. (2021). Evaluating item difficulty patterns for assessing student misconceptions in science across physics, chemistry, and biology concepts. Heliyon, 7(11), e08352. https://doi.org/10.1016/j.heliyon.2021.e08352

Suno, H., & Ohno, N. (2023). Virtual Hydrogen, a virtual reality education tool in physics and chemistry. Procedia Computer Science, 27th International Conference on Knowledge Based and Intelligent Information and Engineering Sytems (KES 2023), 225, 2283–2291. https://doi.org/10.1016/j.procs.2023.10.219

Sweller, J. (2010). Cognitive load theory: Recent theoretical advances. In Cognitive Load Theory (pp. 29–47). Cambridge University Press. https://doi.org/10.1017/CBO9780511844744.004

Sypsas, A., Zafeiropoulos, V., & Kalles, D. (2026). Reinforcement Learning in Virtual Environments for Education: Trends and Future Applications. Procedia Computer Science, 7th International Conference on Industry of the Future and Smart Manufacturing (Former International Conference on Industry 4.0 and Smart Manufacturing), 277, 3185–3194. https://doi.org/10.1016/j.procs.2026.02.354

Thees, M., Kapp, S., Strzys, M. P., Beil, F., Lukowicz, P., & Kuhn, J. (2020). Effects of augmented reality on learning and cognitive load in university physics laboratory courses. Computers in Human Behavior, 108(2), 106316.

Udin, W. N., & Ramli, M. (2020). Virtual laboratory for enhancing students’ understanding on abstract biology concepts and laboratory skills: a systematic review. In Journal of Physics: Conference Series 1521(4), 042025.

Vasiliadou, R. (2020). Virtual laboratories during coronavirus (COVID‐19) pandemic. Biochemistry and Molecular Biology Education, 48(5), 482–483.

Wang, J., Stebbins, A., & Ferdig, R. E. (2022). Examining the effects of students’ self-efficacy and prior knowledge on learning and visual behavior in a physics game. Computers & Education, 178, 104405. https://doi.org/10.1016/j.compedu.2021.104405

Widiyatmoko, A., & Shimizu, K. (2018). The effectiveness of virtual lab compared to real lab for student conceptual understanding and science process skills. Jurnal Pendidikan IPA Indonesia, 7(3), 265–272.

Zhang, E., & Choate, J. (2026). Bridging the virtual and the physical laboratory for physiology education. Current Opinion in Physiology, 47, 100916. https://doi.org/10.1016/j.cophys.2026.100916