Effects of a Flipped Classroom Learning System Integrated With ChatGPT on Students: a Survey From China.

Jing Chen; Nur Azlina Mohamed Mokmin; Qi Shen

doi:10.9781/ijimai.2025.02.007

Authors

Jing Chen Universiti Sains Malaysia.
Nur Azlina Mohamed Mokmin Universiti Sains Malaysia.
Qi Shen Jiangsu Maritime Institute.

DOI:

https://doi.org/10.9781/ijimai.2025.02.007

Keywords:

Chinese Traditional Culture, Cognitive Load, Designed Education, Engagement, Generative AI

Abstract

In design education, patterns and symbols representing traditional national cultures are often utilized as teaching materials. However, conventional teaching methods frequently fall short in aiding students' comprehension of these intricate symbolisms and abstract concepts, leading to reduced engagement and ineffective learning outcomes. Therefore, we aim to explore whether ChatGPT, as a powerful tool, can assist in solving this problem. Specifically, we integrate ChatGPT into a flipped classroom learning system to assess its effectiveness in enhancing students' understanding of traditional Chinese culture. This research contributes to the feasibility of integrating ChatGPT in design education, particularly in the context of Chinese culture. Additionally, it serves as an exploratory attempt to apply ChatGPT in teaching practices within the field of design.

Downloads

Download data is not yet available.

References

W. Yang, “Artificial Intelligence education for young children: Why, what, and how in curriculum design and implementation,” Computers and Education: Artificial Intelligence, vol. 3, pp. 100061, 2022, doi: 10.1016/J.CAEAI.2022.100061.

A. Y. Q. Huang, O. H. T. Lu, and S. J. H. Yang, “Effects of artificial Intelligence–Enabled personalized recommendations on learners’ learning engagement, motivation, and outcomes in a flipped classroom,” Computers and Education, vol. 194, 2023, doi: 10.1016/J.COMPEDU.2022.104684.

C. Vallis, S. Wilson, D. Gozman, and J. Buchanan, “Student Perceptions of AI-Generated Avatars in Teaching Business Ethics: We Might not be Impressed,” Postdigital Science and Education, pp. 1–19, 2023, doi: 10.1007/S42438-023-00407-7.

D. Leiker, A. R. Gyllen, I. Eldesouky, and M. Cukurova, “Generative AI for learning: Investigating the potential of synthetic learning videos,” 2023. Available: https://arxiv.org/abs/2304.03784v2.

D. Baidoo-Anu and L. Owusu Ansah, “Education in the Era of Generative Artificial Intelligence (AI): Understanding the Potential Benefits of ChatGPT in Promoting Teaching and Learning,” SSRN Electronic Journal, 2023, doi: 10.2139/SSRN.4337484.

Z. Epstein, A. Hertzmann, M. Akten, H. Farid, J. Fjeld, M. R. Frank, M. Groh, L. Herman, N. Leach, R. Mahari, A. Pentland, O. Russakovsky, H. Schroeder, and A. Smith, “Art and the science of generative AI,” Science (New York, N.Y.), vol. 380, no. 6650, pp. 1110–1111, 2023, doi: 10.1126/SCIENCE.ADH4451.

OpenAI, “OpenAI,” 2023. Available: https://openai.com/.

OpenAI, “Introducing ChatGPT,” 2023. Available: https://openai.com/blog/chatgpt.

D. Zhou, S. Liu, and S. Grassini, “Shaping the Future of Education: Exploring the Potential and Consequences of AI and ChatGPT in Educational Settings,” Education Sciences, vol. 13, no. 7, pp. 692, 2023, doi: 10.3390/EDUCSCI13070692.

M. M. Rahman and Y. Watanobe, “ChatGPT for Education and Research: Opportunities, Threats, and Strategies,” Applied Sciences, vol. 13, no. 9, pp. 5783, 2023, doi: 10.3390/APP13095783.

H. Krystal, “ChatGPT sets record for fastest-growing user base - analyst note | Reuters,” 2023, February 2. Available: https://www.reuters.com/technology/chatgpt-sets-record-fastest-growing-user-base-analyst-note-2023-02-01/.

M. Montenegro-Rueda, J. Fernández-Cerero, J. M. Fernández-Batanero, & E. López-Meneses, “Impact of the Implementation of ChatGPT in Education: A Systematic Review,” Computers, vol. 12, no. 8, p. 153, 2023, doi: 10.3390/COMPUTERS12080153.

R. Hadi Mogavi, C. Deng, J. Juho Kim, P. Zhou, Y. D. Kwon, A. Hosny Saleh Metwally, A. Tlili, S. Bassanelli, A. Bucchiarone, S. Gujar, L. E. Nacke, & P. Hui, “ChatGPT in education: A blessing or a curse? A qualitative study exploring early adopters’ utilization and perceptions,” Computers in Human Behavior: Artificial Humans, vol. 2, no. 1, p. 100027, 2024, doi: 10.1016/J.CHBAH.2023.100027.

M. Farrokhnia, S. K. Banihashem, O. Noroozi, & A. Wals, “A SWOT analysis of ChatGPT: Implications for educational practice and research,” Innovations in Education and Teaching International, pp. 1–15, 2023, doi: 10.1080/14703297.2023.2195846.

I. Adeshola & A. P. Adepoju, “The opportunities and challenges of ChatGPT in education,” Interactive Learning Environments, pp. 1–14, 2023, doi: 10.1080/10494820.2023.2253858.

M. Pradana, H. P. Elisa, & S. Syarifuddin, “Discussing ChatGPT in education: A literature review and bibliometric analysis,” Cogent Education, vol. 10, no. 2, 2023, doi: 10.1080/2331186X.2023.2243134.

Y. Cao, L. Zhou, S. Lee, L. Cabello, M. Chen, & D. Hershcovich, “Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical Study,” in EACL 2023 - Cross-Cultural Considerations in NLP @ EACL, Proceedings of the Workshop, pp. 53–67, 2023, doi: 10.18653/v1/2023.c3nlp-1.7.

M. Virvou, G. A. Tsihrintzis, D. N. Sotiropouloss, K. Chrysafiadi, E. Sakkopoulos, & E.-A. Tsichrintzi, “ChatGPT in Artificial Intelligence-Empowered E-Learning for Cultural Heritage: The case of Lyrics and Poems,” pp. 1–9, 2023, doi: 10.1109/IISA59645.2023.10345878.

J. Żammit, “Harnessing the Power of ChatGPT for Mastering the Maltese Language: A Journey of Breaking Barriers and Charting New Paths,” Studies in Computational Intelligence, vol. 1105, pp. 161–178, 2023, doi: 10.1007/978-3-031-37454-8_8/COVER.

C. K. Lo, “What Is the Impact of ChatGPT on Education? A Rapid Review of the Literature,” Education Sciences, vol. 13, no. 4, p. 410, 2023, doi: 10.3390/educsci13040410

F. Kieser, P. Wulff, J. Kuhn, & S. Küchemann, “Educational data augmentation in physics education research using ChatGPT,” Physical Review Physics Education Research, vol. 19, no. 2, p. 020150, 2023, doi: 10.1103/PhysRevPhysEducRes.19.020150.

H. Lee, “The rise of ChatGPT: Exploring its potential in medical education,” Anatomical Sciences Education, 2023, doi: 10.1002/ASE.2270.

G. van den Berg & E. du Plessis, “ChatGPT and Generative AI: Possibilities for Its Contribution to Lesson Planning, Critical Thinking and Openness in Teacher Education,” Education Sciences, vol. 13, no. 10, p. 998, 2023, doi: 10.3390/EDUCSCI13100998.

H. Li, “Effects of a ChatGPT-based flipped learning guiding approach on learners’ courseware project performances and perceptions,” Australasian Journal of Educational Technology, vol. 39, no. 5, pp. 40–58, 2023, doi: 10.14742/ajet.8923.

A. Tlili, B. Shehata, M. A. Adarkwah, A. Bozkurt, D. T. Hickey, R. Huang, & B. Agyemang, “What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education,” Smart Learning Environments, vol. 10, no. 1, pp. 1–24, 2023, doi: 10.1186/S40561-023-00237-X.

F. H. Nah, R. Zheng, J. Cai, K. Siau, & L. Chen, “Generative AI and ChatGPT: Applications, challenges, and AI-human collaboration,” Journal of Information Technology Case and Application Research, vol. 25, no. 3, pp. 277–304, 2023, doi: 10.1080/15228053.2023.2233814.

A. Bozkurt & R. C. Sharma, “Challenging the Status Quo and Exploring the New Boundaries in the Age of Algorithms: Reimagining the Role of Generative AI in Distance Education and Online Learning,” Asian Journal of Distance Education, vol. 18, no. 1, 2023. Available: https://asianjde.com/ojs/index.php/AsianJDE/article/view/714.

L. Carter, D. Liu, & C. Cantrell, “Exploring the Intersection of the Digital Divide and Artificial Intelligence: A Hermeneutic Literature Review,” AIS Transactions on Human-Computer Interaction, vol. 12, no. 4, pp. 253–275, 2020, doi: 10.17705/1thci.00138.

P. Strelan, A. Osborn, & E. Palmer, “The flipped classroom: A meta-analysis of effects on student performance across disciplines and education levels,” Educational Research Review, vol. 30, p. 100314, 2020, doi: 10.1016/J.EDUREV.2020.100314.

G. Akçayır & M. Akçayır, “The flipped classroom: A review of its advantages and challenges,” Computers & Education, vol. 126, pp. 334–345, 2018, doi: 10.1016/J.COMPEDU.2018.07.021.

Meyliana, B. Sablan, S. Surjandy, & A. N. Hidayanto, “Flipped learning effect on classroom engagement and outcomes in university information systems class,” Education and Information Technologies, vol. 27, no. 3, pp. 3341–3359, 2022, doi: 10.1007/s10639-021-10723-9.

H. Al-Samarraie, A. Shamsuddin, & A. I. Alzahrani, “A flipped classroom model in higher education: a review of the evidence across disciplines,” Educational Technology Research and Development, vol. 68, no. 3, pp. 1017–1051, 2020, doi: 10.1007/s11423-019-09718-8.

R. Brewer & S. Movahedazarhouligh, “Successful stories and conflicts: A literature review on the effectiveness of flipped learning in higher education,” Journal of Computer Assisted Learning, vol. 34, no. 4, pp. 409–416, 2018, doi: 10.1111/JCAL.12250.

C. Jia, K. F. Hew, J. Diahui, & L. Liuyufeng, “Towards a fully online flipped classroom model to support student learning outcomes and engagement: A 2-year design-based study,” The Internet and Higher Education, vol. 56, p. 100878, 2023, doi: 10.1016/J.IHEDUC.2022.100878.

M. K. Kim, S. M. Kim, O. Khera, & J. Getman, “The experience of three flipped classrooms in an urban university: an exploration of design principles,” The Internet and Higher Education, vol. 22, pp. 37–50, 2014, doi: 10.1016/J.IHEDUC.2014.04.003.

L. Cheng, A. D. Ritzhaupt, & P. Antonenko, “Effects of the flipped classroom instructional strategy on students’ learning outcomes: a meta-analysis,” Educational Technology Research and Development, vol. 67, no. 4, pp. 793–824, 2019, doi: 10.1007/s11423-018-9633-7.

J. Lee, C. Lim, & H. Kim, “Development of an instructional design model for flipped learning in higher education,” Educational Technology Research and Development, vol. 65, no. 2, pp. 427–453, 2017, doi: 10.1007/S11423-016-9502-1.

K. Missildine, R. Fountain, L. Summers, & K. Gosselin, “Flipping the classroom to improve student performance and satisfaction,” Journal of Nursing Education, vol. 52, no. 10, pp. 597–599, 2013, doi: 10.3928/01484834-20130919-03.

T. Wang, “Overcoming barriers to ‘flip’: building teacher’s capacity for the adoption of flipped classroom in Hong Kong secondary schools,” Research and Practice in Technology Enhanced Learning, vol. 12, no. 1, p. 6, 2017, doi: 10.1186/s41039-017-0047-7.

M. Förster, A. Maur, C. Weiser, & K. Winkel, “Pre-class video watching fosters achievement and knowledge retention in a flipped classroom,” Computers & Education, vol. 179, p. 104399, 2022, doi: 10.1016/J.COMPEDU.2021.104399.

S. C. Chang & G. J. Hwang, “Impacts of an augmented reality-based flipped learning guiding approach on students’ scientific project performance and perceptions,” Computers & Education, vol. 125, pp. 226–239, 2018, doi: 10.1016/J.COMPEDU.2018.06.007.

M. Bond, “Facilitating student engagement through the flipped learning approach in K-12: A systematic review,” Computers & Education, vol. 151, p. 103819, 2020, doi: 10.1016/J.COMPEDU.2020.103819.

M. Bond, K. Buntins, S. Bedenlier, O. Zawacki-Richter, & M. Kerres, “Mapping research in student engagement and educational technology in higher education: a systematic evidence map,” International Journal of Educational Technology in Higher Education, vol. 17, no. 1, p. 1, 2020, doi: 10.1186/S41239-019-0176-8.

J. Reeve, “How students create motivationally supportive learning environments for themselves: The concept of agentic engagement,” Journal of Educational Psychology, vol. 105, no. 3, pp. 579–595, 2013, doi: 10.1037/A0032690.

J. Reeve, H. Jang, D. Carrell, S. Jeon, & J. Barch, “Enhancing students’ engagement by increasing teachers’ autonomy support,” Motivation and Emotion, vol. 28, no. 2, pp. 147–169, 2004, doi: 10.1023/B:MOEM.0000032312.95499.6F.

J. Reeve, S. H. Cheon, & H. Jang, “How and why students make academic progress: Reconceptualizing the student engagement construct to increase its explanatory power,” Contemporary Educational Psychology, vol. 62, p. 101899, 2020, doi: 10.1016/J.CEDPSYCH.2020.101899.

A. Y. Q. Huang, O. H. T. Lu, & S. J. H. Yang, “Effects of artificial Intelligence–Enabled personalized recommendations on learners’ learning engagement, motivation, and outcomes in a flipped classroom,” Computers & Education, vol. 194, p. 104684, 2023, doi: 10.1016/j.compedu.2022.104684.

E. A. Skinner & J. R. Pitzer, “Developmental dynamics of student engagement, coping, and everyday resilience,” in Handbook of Research on Student Engagement, pp. 21–44, 2012, doi: 10.1007/978-1-4614-2018-7_2/COVER.

W. Schnotz & C. Kürschner, “A reconsideration of cognitive load theory,” Educational Psychology Review, vol. 19, no. 4, pp. 469–508, 2007, doi: 10.1007/S10648-007-9053-4.

M. Klepsch & T. Seufert, “Understanding instructional design effects by differentiated measurement of intrinsic, extraneous, and germane cognitive load,” Instructional Science, vol. 48, no. 1, pp. 45–77, 2020, doi: 10.1007/S11251-020-09502-9/TABLES/11.

J. L. Plass & S. Kalyuga, “Four Ways of Considering Emotion in Cognitive Load Theory,” Educational Psychology Review, vol. 31, no. 2, pp. 339–359, 2019, doi: 10.1007/S10648-019-09473-5/METRICS.

T. de Jong, “Cognitive load theory, educational research, and instructional design: Some food for thought,” Instructional Science, vol. 38, no. 2, pp. 105–134, 2010, doi: 10.1007/S11251-009-9110-0/METRICS.

J. Sweller, “The Role of Independent Measures of Load in Cognitive Load Theory,” in Cognitive Load Measurement and Application, pp. 3–7, 2017, doi: 10.4324/9781315296258-1.

N. A. M. Mokmin, Hanjun, S., Jing, C., & Qi, S., “Impact of an AR-based learning approach on the learning achievement, motivation, and cognitive load of students on a design course,” Journal of Computers in Education, 2023, doi: 10.1007/s40692-023-00270-2.

A. P. Underhill & L. C. Salazar, Eds., Finding Solutions for Protecting and Sharing Archaeological Heritage Resources, 2016, doi: 10.1007/978-3-319-20255-6.

UNESCO, “Craftsmanship of Nanjing Yunjin brocade,” 2009. Available: https://ich.unesco.org/en/RL/craftsmanship-of-nanjing-yunjin-brocade-00200.

N. Singh, “‘A Little Flip Goes a Long Way’—The Impact of a Flipped Classroom Design on Student Performance and Engagement in a First-Year Undergraduate Economics Classroom,” Education Sciences, vol. 10, no. 11, p. 319, 2020, doi: 10.3390/EDUCSCI10110319.

G. J. Hwang, L. H. Yang, & S. Y. Wang, “A concept map-embedded educational computer game for improving students’ learning performance in natural science courses,” Computers & Education, vol. 69, pp. 121–130, 2013, doi: 10.1016/J.COMPEDU.2013.07.008.

G. J. Hwang, T. C. Yang, C. C. Tsai, & S. J. H. Yang, “A context-aware ubiquitous learning environment for conducting complex science experiments,” Computers & Education, vol. 53, no. 2, pp. 402–413, 2009, doi: 10.1016/J.COMPEDU.2009.02.016.

C.-J. Lin & H. Mubarok, “Learning Analytics for Investigating the Mind Map-Guided AI Chatbot Approach in an EFL Flipped Speaking Classroom,” Educational Technology & Society, vol. 24, no. 4, pp. 16–35, 2021, Available: https://www.jstor.org/stable/48629242.

A. Martinez-Lincoln, M. A. Barnes, & N. H. Clemens, “The influence of student engagement on the effects of an inferential reading comprehension intervention for struggling middle school readers,” Annals of Dyslexia, vol. 71, no. 2, pp. 322–345, 2021, doi: 10.1007/s11881-020-00209-7.

Y. B. Rajabalee & M. I. Santally, “Learner satisfaction, engagement and performances in an online module: Implications for institutional e-learning policy,” Education and Information Technologies, vol. 26, no. 3, pp. 2623–2656, 2021, doi: 10.1007/S10639-020-10375-1/FIGURES/5.

I. Buil, S. Catalán, & E. Martínez, “Engagement in business simulation games: A self-system model of motivational development,” British Journal of Educational Technology, vol. 51, no. 1, pp. 297–311, 2020, doi: 10.1111/BJET.12762.

L. Ding, C. M. Kim, & M. Orey, “Studies of student engagement in gamified online discussions,” Computers & Education, vol. 115, pp. 126–142, 2017, doi: 10.1016/J.COMPEDU.2017.06.016.

J. A. Fredricks, P. C. Blumenfeld, & A. H. Paris, “School Engagement: Potential of the Concept, State of the Evidence,” Review of Educational Research, vol. 74, no. 1, pp. 59–109, 2004, doi: 10.3102/00346543074001059.

J. Reeve & C. M. Tseng, “Agency as a fourth aspect of students’ engagement during learning activities,” Contemporary Educational Psychology, vol. 36, no. 4, pp. 257–267, 2011, doi: 10.1016/J.CEDPSYCH.2011.05.002.

S. G. Fussell, J. L. Derby, J. K. Smith, W. J. Shelstad, J. D. Benedict, B. S. Chaparro, R. Thomas, & A. R. Dattel, “Usability Testing of a Virtual Reality Tutorial,” Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 63, no. 1, pp. 2303–2307, 2019, doi: 10.1177/1071181319631494.

I. Miguel-Alonso, B. Rodriguez-Garcia, D. Checa, & A. Bustillo, “Countering the Novelty Effect: A Tutorial for Immersive Virtual Reality Learning Environments,” Applied Sciences, vol. 13, no. 1, p. 593, 2023, doi: 10.3390/app13010593.

M. Koch, K. von Luck, J. Schwarzer, & S. Draheim, “The Novelty Effect in Large Display Deployments – Experiences and Lessons-Learned for Evaluating Prototypes,” 2018. Available: https://doi.org/10.18420/ECSCW2018_3.

L. Rodrigues, F. D. Pereira, A. M. Toda, P. T. Palomino, M. Pessoa, L. S. G. Carvalho, D. Fernandes, E. H. T. Oliveira, A. I. Cristea, & S. Isotani, “Gamification suffers from the novelty effect but benefits from the familiarization effect: Findings from a longitudinal study,” International Journal of Educational Technology in Higher Education, vol. 19, no. 1, p. 13, 2022, doi: 10.1186/s41239-021-00314-6.

C. H. Tsay, A. K. Kofinas, S. K. Trivedi, & Y. Yang, “Overcoming the novelty effect in online gamified learning systems: An empirical evaluation of student engagement and performance,” Journal of Computer Assisted Learning, vol. 36, no. 2, pp. 128–146, 2020, doi: 10.1111/jcal.12385.

W. Atiomo, “Cognitive load theory and differential attainment,” BMJ, vol. 368, 2020, doi: 10.1136/BMJ.M965.

W. Leahy & J. Sweller, “Cognitive load theory and the effects of transient information on the modality effect,” Instructional Science, vol. 44, no. 1, pp. 107–123, 2016, doi: 10.1007/S11251-015-9362-9/METRICS.

T. Li, Y. Ji, & Z. Zhan, “Expert or machine? Comparing the effect of pairing student teacher with in-service teacher and ChatGPT on their critical thinking, learning performance, and cognitive load in an integrated-STEM course,” Asia Pacific Journal of Education, 2024, doi: 10.1080/02188791.2024.2305163.

J. Schmidhuber, S. Schlogl, & C. Ploder, “Cognitive Load and Productivity Implications in Human-Chatbot Interaction,” Proceedings of the 2021 IEEE International Conference on Human-Machine Systems, ICHMS 2021, 2021, doi: 10.1109/ICHMS53169.2021.9582445.

T. T. Wu, H. Y. Lee, P. H. Li, C. N. Huang, & Y. M. Huang, “Promoting Self-Regulation Progress and Knowledge Construction in Blended Learning via ChatGPT-Based Learning Aid,” Journal of Educational Computing Research, vol. 61, no. 8, pp. 3–31, 2023, doi: 10.1177/07356331231191125.

T. H. Kung, M. Cheatham, A. Medenilla, C. Sillos, L. De Leon, C. Elepaño, M. Madriaga, R. Aggabao, G. Diaz-Candido, J. Maningo, & V. Tsengid, “Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models,” PLOS Digital Health, vol. 2, no. 2, e0000198, 2023, doi: 10.1371/JOURNAL.PDIG.0000198.

L. Li, H. Zhang, C. Li, H. You, & W. Cui, “Evaluation on ChatGPT for Chinese Language Understanding,” Data Intelligence, vol. 5, no. 4, pp. 885–903, 2023, doi: 10.1162/dint_a_00232.

M. Liu, Y. Ren, L. M. Nyagoga, F. Stonier, Z. Wu, & L. Yu, “Future of education in the era of generative artificial intelligence: Consensus among Chinese scholars on applications of ChatGPT in schools,” Future in Educational Research, vol. 1, no. 1, pp. 72–101, 2023, doi: 10.1002/fer3.10.

G. Cooper, “Examining Science Education in ChatGPT: An Exploratory Study of Generative Artificial Intelligence,” Journal of Science Education and Technology, vol. 32, no. 3, pp. 444–452, 2023, doi: 10.1007/S10956-023-10039-Y/TABLES/1.

J.-N. García-Sánchez, H.-C. K. Lin, J. S. Jauhiainen, & A. G. Guerra, “Generative AI and ChatGPT in School Children’s Education: Evidence from a School Lesson,” Sustainability, vol. 15, no. 18, p. 14025, 2023, doi: 10.3390/SU151814025.

A. Gilson, C. W. Safranek, T. Huang, V. Socrates, L. Chi, R. A. Taylor, & D. Chartash, “How Does ChatGPT Perform on the United States Medical Licensing Examination? The Implications of Large Language Models for Medical Education and Knowledge Assessment,” JMIR Medical Education, vol. 9, no. 1, e45312, 2023, doi: 10.2196/45312.

N. A. M. Mokmin & M. Masood, “Case-based reasoning and profiling system for learning mathematics (CBR-PROMATH),” in Lecture Notes in Electrical Engineering (Vol. 315, pp. 939–948), 2015, doi: 10.1007/978-3-319-07674-4_88.

N. A. M. Mokmin & M. Masood, “The design and development of an intelligent tutoring system as a part of the architecture of the Internet of Things (IoT),” in ACM International Conference Proceeding Series (Vol. 2017-Octob), 2017, doi: 10.1145/3145777.3145793.

S. Shahriar & K. Hayawi, “Let’s Have a Chat! A Conversation with ChatGPT: Technology, Applications, and Limitations,” Artificial Intelligence Applications, pp. 1–16, 2023, doi: 10.47852/bonviewaia3202939.