Sage Journals: Discover world-class research

Abstract

Recent advancements in robot project-based training have attracted considerable interest in professional education, particularly in fields such as nursing and healthcare. Fostering students’ higher-order thinking skills, such as critical thinking and decision-making, through educational robotics is essential for achieving the goals of vocational training. However, learners often face challenges in designing and programming effective, interactive robots tailored to healthcare-specific tasks. To address this gap, this study proposed a Generative AI-empowered collaborative robot project-based training (GenAI-CRPT) approach to support healthcare education. A quasi-experimental study was conducted at a university to examine the impact of the GenAI-CRPT approach on students’ learning achievement and higher-order thinking tendencies, including critical thinking, problem solving, collaboration, and design thinking. The experimental group (n = 25) participated in the GenAI-CRPT intervention, while the control group (n = 25) engaged in a conventional collaborative robot project-based training method. Results revealed that students in the experimental group significantly outperformed those in the control group in all assessed areas, including learning achievement, critical thinking, problem solving, collaboration, and design thinking. Epistemic Network Analysis (ENA) indicated that the experimental group engaged in more integrated learning processes, where collaboration and reflective practices played pivotal roles in enhancing cognitive engagement and problem-solving performance.

Keywords

generative artificial intelligence design thinking robot project-based training collaborative learning

Get full access to this article

View all access options for this article.

References

Akbar

Ahmad

Muhammad

(2023). College students' struggles with career decisions and their personality: Struggles of college students in career making decisions. Pakistan Journal of Health Sciences, 62–66. https://doi.org/10.54393/pjhs.v4i08.885

Aleksandrova

N. S.

Sokolova

E. G.

Kosarenko

N. N.

Ibragimova

E. M.

Budkevich

R. L.

Yagudina

R. I.

(2024). Exploring the frontiers: A comprehensive bibliometric analysis of robotics in science education. Eurasia Journal of Mathematics, Science and Technology Education, 20(10), em2520. https://doi.org/10.29333/ejmste/15432

Allison

(2026). RAISE the standard: A framework for transparent reporting of artificial intelligence studies in education. Journal of Educational Computing Research, 64(1), 3–15. https://doi.org/10.1177/07356331251377430

Antunes

Aguiar

M. L.

Gaspar

P. D.

(2023). A dynamic STEM-driven approach through mobile robotics to enhance critical thinking and interdisciplinary skills for empowering industry 4.0 competencies. Technologies, 11(6), 170. https://doi.org/10.3390/technologies11060170

Aslanoglou

Zygouris

N. C.

Tsermentseli

Beazidou

Xenakis

(2025). Utilizing educational robotics in elementary school to foster problem-solving skills and enhance the teaching of history. Pedagogical Research, 10(1), em0231. https://doi.org/10.29333/pr/15680

Atman Uslu

Yavuz

G. Ö.

Koçak Usluel

(2023). A systematic review study on educational robotics and robots. Interactive Learning Environments, 31(9), 5874–5898. https://doi.org/10.1080/10494820.2021.2023890

Bano

Atif

Mehdi

S. A.

(2024). Systematic review: Potential effectiveness of educational robotics for 21st century skills development in young learners. Education and Information Technologies, 29(9), 11135–11153. https://doi.org/10.1007/s10639-023-12233-2

Bender-Salazar

(2023). Design thinking as an effective method for problem-setting and needfinding for entrepreneurial teams addressing wicked problems. Journal of innovation and entrepreneurship, 12(1), 24. https://doi.org/10.1186/s13731-023-00291-2

Çakır

Korkmaz

Ö.

İdil

Ö.

Erdoğmuş

F. U.

(2021). The effect of robotic coding education on preschoolers’ problem solving and creative thinking skills. Thinking Skills and Creativity, 40, Article 100812. https://doi.org/10.1016/j.tsc.2021.100812

10.

Chai

C. S.

Deng

Tsai

P. S.

Koh

J. H. L.

Tsai

C. C.

(2015). Assessing multidimensional students’ perceptions of twenty-first-century learning practices. Asia Pacific Education Review, 16(3), 389–398. https://doi.org/10.1007/s12564-015-9379-4

11.

Chang

C. Y.

Setiani

Yang

J. C.

(2025). An escape room-based computer-supported collaborative learning approach to enhancing students’ learning achievement, collaboration awareness, learning motivation and problem-solving skills. Journal of Educational Computing Research, 63(2), 496–524. https://doi.org/10.1177/07356331241302513

12.

Chang

C. Y.

Yang

C. L.

Jen

H. J.

Ogata

Hwang

G. H.

(2024). Facilitating nursing and health education by incorporating ChatGPT into learning designs. Educational Technology & Society, 27(1), 215–230. https://www.jstor.org/stable/48754852

13.

Chen

Lyu

Zheng

(2024). Using peer feedback to improve critical thinking in computer‐supported collaborative argumentation: An exploratory study. Journal of Computer Assisted Learning, 40(6), 3390–3405. https://doi.org/10.1111/jcal.13078

14.

Chiu

M. C.

Hwang

G. J.

(2024). Enhancing students’ critical thinking and creative thinking: An integrated mind mapping and robot-based learning approach. Education and Information Technologies, 29(17), 22779–22812. https://doi.org/10.1007/s10639-024-12752-6

15.

Chu

H. C.

Hwang

G. J.

Chang

C. Y.

(2025). An integrative review with word cloud analysis of computer-supported collaborative learning. Journal of Science Education and Technology, 34(5), 1213–1226. https://doi.org/10.1007/s10956-024-10156-2

16.

Crilly

(2024). Design thinking and other approaches: How different disciplines see, think and act. Elements in Creativity and Imagination. https://doi.org/10.1017/9781009498685

17.

Da Silva

R. H.

Kaminski

P. C.

Armellini

(2020). Improving new product development innovation effectiveness by using problem solving tools during the conceptual development phase: Integrating design thinking and TRIZ. Creativity and Innovation Management, 29(4), 685–700. https://doi.org/10.1111/caim.12399

18.

Demetroulis

E. A.

Theodoropoulos

Wallace

Poulopoulos

Antoniou

(2023). Collaboration skills in educational robotics: A methodological Approach—Results from two case studies in primary schools. Education Sciences, 13(5), 468. https://doi.org/10.3390/educsci13050468

19.

El-Hamamsy

Bruno

Chessel-Lazzarotto

Chevalier

Roy

Zufferey

J. D.

Mondada

(2021). The symbiotic relationship between educational robotics and computer science in formal education. Education and Information Technologies, 26(5), 5077–5107. https://doi.org/10.1007/s10639-021-10494-3

20.

Foglia

Wilson

R. A.

(2013). Embodied cognition. Wiley Interdisciplinary Reviews. Cognitive Science, 4(3), 319–325. https://doi.org/10.1002/wcs.1226

21.

Zheng

Zhu

Ding

Wang

(2024). Teaching plan generation and evaluation with GPT-4: Unleashing the potential of LLM in instructional design. IEEE Transactions on Learning Technologies, 17, 1445–1459. https://doi.org/10.1109/TLT.2024.3384765

22.

(2024). Programming and 21st century skill development in K‐12 schools: A multidimensional meta‐analysis. Journal of Computer Assisted Learning, 40(2), 610–636. https://doi.org/10.1111/jcal.12904

23.

Hwang

G. J.

Chen

C. H.

(2017). Influences of an inquiry‐based ubiquitous gaming design on students’ learning achievements, motivation, behavioral patterns, and tendency towards critical thinking and problem solving. British Journal of Educational Technology, 48(4), 950–971. https://doi.org/10.1111/bjet.12464

24.

Lai

C. L.

Hwang

G. J.

(2014). Effects of mobile learning time on students’ conception of collaboration, communication, complex problem-solving, meta-cognitive awareness and creativity. International Journal of Mobile Learning and Organisation, 8(3/4), 276–291. https://doi.org/10.1504/IJMLO.2014.067029

25.

Lai

Y. H.

(2024). Learning efficacy of understanding by design-Internet of Things (UbD-IoT) education integrated with design thinking and computational thinking. Library Hi Tech, 42(2), 730–747. https://doi.org/10.1108/LHT-01-2023-0002

26.

Lampropoulos

(2025). Social robots in education: Current trends and future perspectives. Information, 16(1), 29. https://doi.org/10.3390/info16010029

27.

Lämsä

Hämäläinen

Koskinen

Viiri

Lampi

(2021). What do we do when we analyse the temporal aspects of computer-supported collaborative learning? A systematic literature review. Educational Research Review, 33, Article 100387. https://doi.org/10.1016/j.edurev.2021.100387

28.

Liu

C. C.

Hsieh

I. C.

Wen

C. T.

Chang

M. H.

Fan Chiang

S. H.

Tsai

M. J.

Chang

C. J.

Hwang

F. K.

(2021). The affordances and limitations of collaborative science simulations: The analysis from multiple evidences. Computers & Education, 160, Article 104029. https://doi.org/10.1016/j.compedu.2020.104029

29.

Liu

Zhao

(2023). Promoting primary school students’ creativity via reverse engineering pedagogy in robotics education. Thinking Skills and Creativity, 49, Article 101339. https://doi.org/10.1016/j.tsc.2023.101339

30.

Luka

(2014). Design thinking in pedagogy. Journal of Education, Culture and Society, 5(2), 63-74. https://doi.org/10.15503/jecs20142.63.74

31.

Marquart

C. L.

Hinojosa

Swiecki

Eagan

Shaffer

D. W.

(2018). Epistemic network analysis (1.7. 0). https://app.epistemicnetwork.org

32.

Orcan

(2020). Parametric or non-parametric: Skewness to test normality for mean comparison. International Journal of Assessment Tools in Education, 7(2), 255–265. https://doi.org/10.21449/ijate.656077

33.

Ramírez-Montoya

M. S.

Castillo-Martínez

I. M.

Sanabria-Z

Miranda

(2022). Complex thinking in the framework of education 4.0 and open innovation—A systematic literature review. Journal of Open Innovation: Technology, Market, and Complexity, 8(1), 4. https://doi.org/10.3390/joitmc8010004

34.

Rösch

Tiberius

Kraus

(2023). Design thinking for innovation: Context factors, process, and outcomes. European Journal of Innovation Management, 26(7), 160–176. https://doi.org/10.1108/EJIM-03-2022-0164

35.

Rusmann

Ejsing-Duun

(2022). When design thinking goes to school: A literature review of design competences for the K-12 level. International Journal of Technology and Design Education, 32(4), 2063–2091. https://doi.org/10.1007/s10798-021-09692-4

36.

Sáez-López

J. M.

Buceta Otero

De Lara García-Cervigón

(2021). Introducing robotics and block programming in elementary education. RIED. Revista Iberoamericana de Educación a Distancia, 24(1), 95-113. https://doi.org/10.5944/ried.24.1.27649

37.

Shaffer

Ruis

(2017). Epistemic network analysis: A worked example of theory-based learning analytics. Handbook of learning analytics. https://doi.org/10.18608/hla17.015

38.

Shaffer

D. W.

Collier

Ruis

A. R.

(2016). A tutorial on epistemic network analysis: Analyzing the structure of connections in cognitive, social, and interaction data. Journal of Learning Analytics, 3(3), 9–45. https://doi.org/10.18608/jla.2016.33.3

39.

Shashidhara

V. V.

Prabhu

Chippar

(2024). Transforming ideas into products: Project based learning in prototyping, fabrication, and testing course for first year engineering students. International Journal of Mechanical Engineering Education, Article 03064190241307026. https://doi.org/10.1177/03064190241307026

40.

Toker

Baturay

M. H.

(2022). Developing disposition to critical thinking and problem-solving perception in instructional design projects for producing digital materials. International Journal of Technology and Design Education, 32(2), 1267–1292. https://doi.org/10.1007/s10798-020-09646-2

41.

Tsai

C. A.

Song

M. Y. W.

Y. F.

C. C.

(2023). Design thinking with constructivist learning increases the learning motivation and wicked problem-solving capability—An empirical research in Taiwan. Thinking Skills and Creativity, 50, Article 101385. https://doi.org/10.1016/j.tsc.2023.101385

42.

Valls Pou

Canaleta

Fonseca

(2022). Computational thinking and educational robotics integrated into project-based learning. Sensors, 22(10), 3746. https://doi.org/10.3390/s22103746

43.

Wei

Wang

Lee

L. K.

Liu

(2025). Multiple generative AI pedagogical agents in augmented reality environments: A study on implementing the 5E model in science education. Journal of Educational Computing Research, 63(2), 336–371. https://doi.org/10.1177/07356331241305519

44.

Yang

C. L.

Chang

C. Y.

Jen

H. J.

(2023). Facilitating undergraduate students’ problem-solving and critical thinking competence via online escape room learning. Nurse Education in Practice, 73, Article 103828. https://doi.org/10.1016/j.nepr.2023.103828

45.

Yilmaz Ince

Koc

(2021). The consequences of robotics programming education on computational thinking skills: An intervention of the Young Engineer's Workshop (YEW). Computer Applications in Engineering Education, 29(1), 191–208. https://doi.org/10.1002/cae.22321

46.

Pasinelli

Brem

(2018). Prototyping in theory and in practice: A study of the similarities and differences between engineers and designers. Creativity and Innovation Management, 27(2), 121–132. https://doi.org/10.1111/caim.12242

47.

Zhang

Gao

Sun

Cai

Tang

Liu

(2022). Understanding student teachers’ collaborative problem solving: Insights from an epistemic network analysis (ENA). Computers & Education, 183, Article 104485. https://doi.org/10.1016/j.compedu.2022.104485

48.

Zhou

Tsai

C. W.

(2023). The effects of socially shared regulation of learning on the computational thinking, motivation, and engagement in collaborative learning by teaching. Education and Information Technologies, 28(7), 8135–8152. https://doi.org/10.1007/s10639-022-11527-1

Effects of Generative AI-Empowered Collaborative Robot Project-Based Learning on Students’ Learning Achievements and Higher Order Thinking Tendencies in Professional Training

Abstract

Keywords

Get full access to this article

References