Exploring the Relationship between Brain-based Learning and Thinking Skills through Smart Education: A Scoping Review on the Development of Study Material and its Effectiveness

Hao Xuan Tan, Arkendu Sen
pp. 58 – 96, download
(https://doi.org/10.55612/s-5002-067-003)

Abstract

This scoping review examines the relationship between Brain-based Learning (BBL) and thinking skills in the context of smart education. The success of technological advancements in smart education depends on well-structured pedagogical approaches. The research investigates how BBL based on cognitive and neuroscience knowledge helps develop thinking skills in smart education. This review combines 36 studies from 2013 to 2023 through the Technology-Enhanced Learning of Thinking Skills (TELoTS) and smart pedagogy frameworks. The research shows that BBL enables students to develop higher-order thinking skills (HOTS) through learner-centred approaches that include problem-solving, critical thinking, and metacognition. The implementation of BBL faces ongoing difficulties related to curriculum development, assessment consistency, and expert participation. The study demonstrates how BBL strengthens smart pedagogy through its combination of cognitive principles with technology-based instruction which produces a learner-centered and educationally sound teaching model. The study emphasizes the need for standardized assessment instruments, along with interdisciplinary teamwork, to maximize the benefits of BBL in smart education.

Keywords: BBL, Thinking Skills, smart pedagogy, smart learning environments, smart education

References

1. Abidin, S.R.Z. et al.: Guidelines of brain-based learning through serious game for slow reader students. Presented at the Proceedings of the 2017 6th International Conference on Electrical Engineering and Informatics: Sustainable Society Through Digital Innovation, ICEEI 2017 (2017). https://doi.org/10.1109/ICEEI.2017.8312461.
2. Adams, N.: Bloom’s taxonomy of cognitive learning objectives. J. Med. Libr. Assoc. JMLA. 103, 152–3 (2015). https://doi.org/10.3163/1536-5050.103.3.010.
3. Al.ljrish H.H., Naser M.S.: Effects of brain-based learning method on academic achievement of undergraduate students at the college of basic education. Indian J. Public Health Res. Dev. 9, 8, 1371–1376 (2018). https://doi.org/10.5958/0976-5506.2018.00922.1.
4. Ariës, R.J. et al.: Improving reasoning skills in secondary history education by working memory training. Br. Educ. Res. J. 41, 2, 210–228 (2015). https://doi.org/10.1002/berj.3142.
5. Azzahra, W., Dwiputra, D.F.K.: Unraveling the Evolution of Brain-Based Learning in Indonesia: An In-Depth Exploration through Systematic Literature Review. Int. J. Educ. Reform. 33, 4, 483–502 (2024). https://doi.org/10.1177/10567879241258134.
6. Bada, A.A., Jita, L.C.: Integrating brain-based learning in The science classroom: A systematic review. Int. J. Pedagogy Teach. Educ. 6, 1, 24–36 (2022).
7. Ball, A., Garton, B.: Modeling Higher Order Thinking: The Alignment Between Objectives, Classroom Discourse, And Assessment. J. Agric. Educ. 46, (2005). https://doi.org/10.5032/jae.2005.02058.
8. Bouck, Z. et al.: Systematic Versus Rapid Versus Scoping ReviewsScoping reviews. In: Evangelou, E. and Veroniki, A.A. (eds.) Meta-Research: Methods and Protocols. pp. 103–119 Springer US, New York, NY (2022). https://doi.org/10.1007/978-1-0716-1566-9_6.
9. Braun, V. et al.: Thematic Analysis. In: Liamputtong, P. (ed.) Handbook of Research Methods in Health Social Sciences. pp. 843–860 Springer, Singapore (2019). https://doi.org/10.1007/978-981-10-5251-4_103.
10. Bressler, S.L., Menon, V.: Large-scale brain networks in cognition: emerging methods and principles. Trends Cogn. Sci. 14, 6, 277–290 (2010). https://doi.org/10.1016/j.tics.2010.04.004.
11. Burke, L.A., Williams, J.M.: Two thinking skills assessment approaches: “Assessment of Pupils’ Thinking Skills” and “Individual Thinking Skills Assessments.” Think. Ski. Creat. 7, 1, 62–68 (2012). https://doi.org/10.1016/j.tsc.2011.11.002.
12. Butterworth, J., Thwaites, G.: Thinking Skills: Critical Thinking and Problem Solving. Cambridge University Press (2013).
13. Caine, R.N. et al.: 12 Brain/Mind Learning Principles in Action. , Thousand Oaks, California (2016). https://doi.org/10.4135/9781483394275.
14. Caine, R.N., Caine, G.: Making Connections: Teaching and the Human Brain. Association for Supervision and Curriculum Development, 11141 Georgia Avenue, Suite 200, Wheaton, MD 20902 (ASCD Stock No (1991).
15. Caine, R.N., Caine, G.: Making Connections: Teaching and the Human Brain. Addison-Wesley Publishing Company (1994).
16. Caine, R.N., Caine, G.: Understanding a Brain-Based Approach to Learning and Teaching. Educ. Leadersh. 48, 2, 66–70 (1990).
17. Clapper, T.C. et al.: A Brain-Based Instruction Simulation Approach to Improve Code Team Response in an Internal Medicine Unit. Simul. Gaming. 49, 5, 479–496 (2018). https://doi.org/10.1177/1046878118794992.
18. Clapper, T.C. et al.: A TeamSTEPPS® implementation plan for recently assigned interns and nurses. Taylor & Francis Ltd, Philadelphia, Pennsylvania (2019).
19. Cooke, A. et al.: Beyond PICO: the SPIDER tool for qualitative evidence synthesis. Qual. Health Res. 22, 10, 1435–1443 (2012). https://doi.org/10.1177/1049732312452938.
20. Cui, Y., Zhang, H.: Educational Neuroscience Training for Teachers’ Technological Pedagogical Content Knowledge Construction. Front. Psychol. 12, (2021). https://doi.org/10.3389/fpsyg.2021.792723.
21. Dai C. et al.: Creative teaching model of civil engineering classroom based on brain cognitive science. NeuroQuantology. 16, 5, 334–340 (2018). https://doi.org/10.14704/nq.2018.16.5.1289.
22. Sen A., Liew S.H.: Augmented reality and its use in education. In: Tatnall A. (ed.) Encyclopedia of Education and Information Technologies, pp. 202-211, Springer, Cham (2020). https://doi.org/10.1007/978-3-030-10576-1_211
23. Darmawan, W. et al.: Students’ response to the implementation of brain-based learning (the BBL) approach in history teaching. Cypriot J. Educ. Sci. 17, 9, 3409–3422 (2022). https://doi.org/10.18844/cjes.v17i9.8080.
24. Darwis, R. et al.: Higher Order Thinking and Critical Thinking Skills in Problem-Based Learning Environments: A Systematic Review. J. Learn. Dev. Stud. 4, 21–33 (2024). https://doi.org/10.32996/jlds.2024.2.2.3.
25. Demir, K.A.: Smart education framework. Smart Learn. Environ. 8, 1, 29 (2021). https://doi.org/10.1186/s40561-021-00170-x.
26. Demirhan, E. et al.: Brain based biology teaching: Effects on cognitive and affective features and opinions of science teacher trainees. J. Turk. Sci. Educ. 11, 3, 65–78 (2014). https://doi.org/10.12973/tused.10119a.
27. Sen A.: Revisiting brain-based learning: Strategies and implications in the higher education scenario. In: INTED2022 Proceedings, pp. 10084-10090, IATED, Valencia (2022). https://doi.org/10.21125/inted.2022.2654
28. DiTullio, G.: An Examination of Planning and Implementing Brain-Based Strategies in the Elementary Classroom. Presented at the (2018).
29. Dwiputra, D.F.K. et al.: A Systematic Literature Review on Enhancing the Success of Independent Curriculum through Brain-Based Learning Innovation Implementation. Indones. J. Learn. Adv. Educ. IJOLAE. 5, 3, 262–276 (2023).
30. El-Wakeel, H.A.: Design studio: Creativity, neuroscience, and brain-based learning. Int. J. Des. Educ. 15, 1, 43–55 (2020). https://doi.org/10.18848/2325-128X/CGP/V15I01/43-55.
31. Erkan, I.: Early Design Stage Analysis with Brain Imaging Method. Interact. Des. Archit. 44, 53–70 (2020). https://doi.org/10.55612/s-5002-044-003
32. Erol M., Batdal Karaduman G.: The effect of activities congruent with brain based learning model on students’ mathematical achievement. NeuroQuantology. 16, 5, 13–22 (2018). https://doi.org/10.14704/nq.2018.16.5.1342.
33. Fengchun, M. et al.: AI and education: A guidance for policymakers. UNESCO Publishing (2021).
34. Fragkaki, M. et al.: Higher Education Faculty Perceptions and Needs on Neuroeducation in Teaching and Learning. Educ. Sci. 12, 10, (2022). https://doi.org/10.3390/educsci12100707
35. Funa, A.A. et al.: Effectiveness of Brain-Based Learning Toward Improving Students’ Conceptual Understanding: A Meta-Analysis. Int. J. Instr. 17, 1, 361–380 (2024).
36. Goulden, N. et al.: The salience network is responsible for switching between the default mode network and the central executive network: replication from DCM. NeuroImage. 99, 180–190 (2014). https://doi.org/10.1016/j.neuroimage.2014.05.052
37. Gozuyesil, E., Dikici, A.: The Effect of Brain Based Learning on Academic Achievement: A Meta-Analytical Study. Educ. Sci. Theory Pract. 14, 2, 642–648 (2014).
38. Hambley, C.: Connect©: A brain-friendly model for leaders and organizations. Consult. Psychol. J. 72, 3, 168–197 (2020). https://doi.org/10.1037/cpb0000187
39. Hamel, C. et al.: Defining Rapid Reviews: a systematic scoping review and thematic analysis of definitions and defining characteristics of rapid reviews. J. Clin. Epidemiol. 129, 74–85 (2021). https://doi.org/10.1016/j.jclinepi.2020.09.041
40. Hassan, A. et al.: Developing an ESP-Based Language Learning Environment to Help Students Improve Critical Thinking Skills in Written Output. Inf. Sci. Lett. 12, 4, 1131–1140 (2023). https://doi.org/10.18576/isl/120431.
41. Immordino-Yang, M.H. et al.: The Brain Basis for Integrated Social, Emotional, and Academic Development: How Emotions and Social Relationships Drive Learning. Aspen Institute (2018).
42. Intasena, A. et al.: Brain-based learning management in primary students: Language literacy studies. Int. J. Adv. Appl. Sci. 10, 6, 107–112 (2023). https://doi.org/10.21833/ijaas.2023.06.013
43. Iranmanesh, F. et al.: A brain-based model of language instruction: from theory to practice. Res. Dev. Med. Educ. 10, 1, 1–10 (2021). https://doi.org/10.34172/rdme.2021.017
44. Iranmanesh, F. et al.: From medical research to educational practices: brain-based learning in developing English-speaking skills among medical students. Res. Dev. Med. Educ. 11, 1, 1–8 (2022). https://doi.org/10.34172/rdme.2022.027
45. Jang, C.S. et al.: Brain-based learning research for adult education and human resource development. Eur. J. Train. Dev. 46, 5/6, 627–651 (2022).
46. Jangjarat, K. et al.: The Impact of Smart Education on Learning Outcomes in the Digital Era: A Systematic Review, https://papers.ssrn.com/abstract=4424676, (2023).
47. Jensen, E.: A Fresh Look at Brain-Based Education. Phi Delta Kappan. 89, (2008). https://doi.org/10.1177/003172170808900605.
48. Jensen, E.: Brain-based learning: The new paradigm of teaching. Corwin Press (2008).
49. Jensen, E., McConchie, L.: Brain-based learning: Teaching the way students really learn. Corwin (2020).
50. Ji Y.-A., Woo H.: Brain-based medical education model for expert’s clinical decision making. Korean J. Med. Educ. 35, 3, 275–283 (2023). https://doi.org/10.3946/kjme.2023.265.
51. Nagarajan A., Sen A.: Can Bloom’s higher order thinking skills be achieved by gamified learning through social networking sites (SNS) like Facebook? Interaction Design and Architecture(s) Journal (IxD&A), 53, pp. 144-160 (2022). https://doi.org/10.55612/s-5002-053-007
52. Jian, M.J.K.O.: Personalized learning through AI. Adv. Eng. Innov. 5, 16–19 (2023). https://doi.org/10.54254/2977-3903/5/2023039.
53. Kania, N., Kusumah, Y.S.: The Measurement Of Higher-Order Thinking Skills: A Systematic Literature Review. Malays. J. Learn. Instr. 22, 1, 97–116 (2025). https://doi.org/10.32890/mjli2025.22.1.6.
54. Kosar, G., Bedir, H.: Improving Knowledge Retention via Establishing Brain-Based Learning Environment. (2018).
55. Krippendorff, K.: Content Analysis: An Introduction to Its Methodology. SAGE Publications, Inc. (2019). https://doi.org/10.4135/9781071878781.
56. Lagoudakis, N. et al.: The effectiveness of a teaching approach using brain-based learning elements on students’ performance in a Biology course. Cogent Educ. 9, (2022). https://doi.org/10.1080/2331186X.2022.2158672.
57. Lane, H.C.: Cognitive Models of Learning. In: Seel, N.M. (ed.) Encyclopedia of the Sciences of Learning. pp. 608–610 Springer US, Boston, MA (2012). https://doi.org/10.1007/978-1-4419-1428-6_241.
58. Levac, D. et al.: Scoping studies: advancing the methodology. Implement. Sci. 5, 1, 69 (2010). https://doi.org/10.1186/1748-5908-5-69.
59. Li, W. et al.: Animated pedagogical agents enhance learning outcomes and brain activity during learning. J. Comput. Assist. Learn. 38, 3, 621–637 (2022). https://doi.org/10.1111/jcal.12634.
60. Lidiastuti, A.L. et al.: The development of EXAIR (example auditory thinking repetition) learning model based on BBL (Brain-Based Learning) and its effect on problem solving capability on secondary school in coastal area. Presented at the IOP Conference Series: Earth and Environmental Science (2019). https://doi.org/10.1088/1755-1315/243/1/012094.6261.
61. Liu, J. et al.: A Systematic Review of Higher-Order Thinking by Visualizing its Structure Through HistCite and CiteSpace Software. Asia-Pac. Educ. Res. 31, 6, 635–645 (2022). https://doi.org/10.1007/s40299-021-00614-5.
62. Lusiana, R., Andari, T.: Brain based learning to improve students’ higher order thinking skills. Presented at the Journal of Physics: Conference Series (2020). https://doi.org/10.1088/1742-6596/1613/1/012004.
63. Malik, M.: Effectiveness of Brain-Based Learning Theory on Secondary Level Students of Urban Areas.
64. Martín, H.R. et al.: Can adolescents make better decisions? The answer of Physics Physics as critical thinking training. Eur. J. Educ. Psychol. 14, 1, (2021). https://doi.org/10.32457/ejep.v14i1.1550.
65. McGilchrist, I.: The Matter With Things: Our Brains, Our Delusions, and the Unmaking of the World. Perspectiva, London (2021).
66. Mak, S., Thomas, A.: Steps for Conducting a Scoping Review. J. Grad. Med. Educ. 14, 5, 565–567 (2022). https://doi.org/10.4300/JGME-D-22-00621.1.
67. Meng, Q. et al.: A framework of smart pedagogy based on the facilitating of high order thinking skills. Interact. Technol. Smart Educ. 17, 3, 251–266 (2020). https://doi.org/10.1108/ITSE-11-2019-0076.
68. Mensan, T., Osman, K.: Development of bic-science module: An interdisciplinary approach of computer science and primary science education. Presented at the Proceedings of International Conference on Computational Thinking Education (2018).
69. Muhammad, A.A.S., Saleh, S.: Linking Neuroscience And Education: A Systematic Review Of Brain-Based Approach In Stem. J. Contemp. Soc. Sci. Educ. Stud. JOCSSES E-ISSN-2785-8774. 4, 3 (Special Issue), 133–144 (2024).
70. Murthy, S. et al.: Pedagogical Framework for Developing Thinking Skills Using Smart Learning Environments. In: Spector, M.J. et al. (eds.) Learning, Design, and Technology: An International Compendium of Theory, Research, Practice, and Policy. pp. 1–49 Springer International Publishing, Cham (2016). https://doi.org/10.1007/978-3-319-17727-4_14-1.
71. Nicholson, D.: Organisms ≠ Machines. Stud. Hist. Philos. Sci. Part C Stud. Hist. Philos. Biol. Biomed. Sci. 44, 669–678 (2013). https://doi.org/10.1016/j.shpsc.2013.05.014.
72. Onello, R.: Brain Science Learning Guides: An Innovative Strategy for Cultivating Effective Study Skills. Nurse Educ. 48, 6, 332–335 (2023). https://doi.org/10.1097/NNE.0000000000001415.
73. Prakash, R., Litoriya, R.: Pedagogical Transformation of Bloom Taxonomy’s LOTs into HOTs: An Investigation in Context with IT Education. Wirel. Pers. Commun. 122, 1, 725–736 (2022). https://doi.org/10.1007/s11277-021-08921-2.
74. Privitera, A.J.: A scoping review of research on neuroscience training for teachers. Trends Neurosci. Educ. 24, 100157 (2021). https://doi.org/10.1016/j.tine.2021.100157.
75. Raghavendran, M., Begum, A.J.: Brain-based teaching: A tangible burgeoning technique in our present educational scenario. In: Neuro-Systemic Applications in Learning. pp. 309–331 (2021). https://doi.org/10.1007/978-3-030-72400-9_16.
76. Rahman, A. et al.: Developing e-module of English for tourism based on brain-based learning approach at state polytechnic of Lampung. Int. J. Innov. Creat. Change. 6, 2, 29–47 (2019).
77. Rizky Amelia, E.K.E.S.: Neuroscience Study in Science Development Elementary School. J. Hunan Univ. Nat. Sci. 48, 1, (2021).
78. Sen A., Selvaratnam L.: Future-proofing healthcare skills education: Technology-enhanced collaborative learning and peer teaching strategies for large student cohorts in anatomy practicals. In: Collaborative active learning: Practical activity-based approaches to learning, assessment and feedback, pp. 179-212, Springer Nature, Singapore (2022) DOI: 10.1007/978-981-19-4383-6_8
79. Rizky Amelia, E.K.E.S.: Neuroscience Study in Science Development Elementary School. J. Hunan Univ. Nat. Sci. 48, 1, (2021).
80. Saiin, S. et al.: Teacher Pedagogical Competence In A Neuroscience Perspective: A Systematic Review And Meta-Analysis. J. Neosantara Hybrid Learn. 1, 2, 79–93 (2023). https://doi.org/10.55849/jnhl.v1i2.99.
81. Saleh Al Rasheed L., Hanafy A.A.M.: Effects of brain-based instruction on executive function and habits of mind among young children at-risk for learning disabilities. Appl. Neuropsychol. Child. (Saleh Al Rasheed) College of Education, Department of Psychology, Qassim University, Buraidah, Saudi Arabia, 1–8 (2023). https://doi.org/10.1080/21622965.2022.2161904.
82. Saleh, S., Mazlan, A.: The effects of brain-based teaching with i-think maps and brain gym approach towards physics understanding. J. Pendidik. IPA Indones. 8, 1, 12–21 (2019). https://doi.org/10.15294/jpii.v8i1.16022.
83. Sari, D.P. et al.: Development of mathematics learning devices using the brain-based learning methodology to help students enhance their mathematical creative thinking skills class X SMA students. Presented at the AIP Conference Proceedings (2023). https://doi.org/10.1063/5.0122566.
84. Schell, G., Janicki, T.: Online Course Pedagogy and the Constructivist Learning Model. J. South. Assoc. Inf. Syst. 1, 1, 26–36 (2013). https://doi.org/10.3998/jsais.11880084.0001.104.
85. Schwartz, M.S. et al.: Neuroscience knowledge enriches pedagogical choices. Teach. Teach. Educ. 83, 87–98 (2019). https://doi.org/10.1016/j.tate.2019.04.002.
86. Seaba, V.: Revolutionizing Education – Exploring the Potential of AI-Enabled Brain-Based Learning for Enhanced Cognitive Development, https://www.techrxiv.org/doi/full/10.36227/techrxiv.23733885.v2, (2023). https://doi.org/10.36227/techrxiv.23733885.v2.
87. Sestito, M. et al.: Grasping the world from a cockpit: perspectives on embodied neural mechanisms underlying human performance and ergonomics in aviation context. Theor. Issues Ergon. Sci. 19, 6, 692–711 (2018). https://doi.org/10.1080/1463922X.2018.1474504.
88. Siming, L., Abraha, A.: Natural science and engineering instructors’ knowledge and practice of brain-based instruction in Ethiopian higher education institutions. Heliyon. 9, 11, (2023). https://doi.org/10.1016/j.heliyon.2023.e22325.
89. Solomon, J. et al.: Course material delivery in engineering using brain-based learning techniques. Presented at the Proceedings – Frontiers in Education Conference, FIE (2016). https://doi.org/10.1109/FIE.2016.7757696.
90. Solomon, J.T. et al.: Improving student engagement in engineering using brain-based learning principles as instructional delivery protocols. Presented at the ASEE Annual Conference and Exposition, Conference Proceedings (2017).
91. Staboulis, M., Lazaridou, I.: Application of alpha and beta brainwaves on e-learning projects in terms of expanding critical and cognitive skills: An experimental approach. Presented at the Multi Conference on Computer Science and Information Systems, MCCSIS 2019 – Proceedings of the International Conference on e-Learning 2019 (2019). https://doi.org/10.33965/el2019_201909c043.
92. Stang, K.: Brain-Based Learning Methods and Student Achievement. Electron. Theses Diss. (2022).
93. Susanti, V.D. et al.: Development of learning devices: Brain-based learning and mathematics critical thinking. Presented at the Journal of Physics: Conference Series (2019). https://doi.org/10.1088/1742-6596/1254/1/012082.
94. Tabuenca, B. et al.: Affordances and Core Functions of Smart Learning Environments: A Systematic Literature Review. IEEE Trans. Learn. Technol. 14, 2, 129–145 (2021). https://doi.org/10.1109/TLT.2021.3067946.
95. Tang, Y.-Y.: Chapter 1 – Challenges and Issues in Education. In: Tang, Y.-Y. (ed.) Brain-Based Learning and Education. pp. 1–5 Academic Press, San Diego (2017). https://doi.org/10.1016/B978-0-12-810508-5.00001-8.
96. Tang, Y.-Y.: Chapter 9 – Insight for Optimal Learning and Education. In: Tang, Y.-Y. (ed.) Brain-Based Learning and Education. pp. 49–54 Academic Press, San Diego (2017). https://doi.org/10.1016/B978-0-12-810508-5.00012-2.
97. Ti-Shen, E.T., Sen, A.: Effective use of interactive videos as an educational tool in higher education–An Asian context. In: EDULEARN19 Proceedings. pp. 10379–10385 IATED (2019).
98. Tricco, A.C. et al.: PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation. Ann. Intern. Med. 169, 7, 467–473 (2018). https://doi.org/10.7326/M18-0850.
99. Utomo, D.H.: Brain Based Learning: Effects Model A-Car in Critical Thinking Skills. In: Handoyo, B. (ed.) Proceedings of The Lst International Conference On Geography And Education (ICGE 2016). pp. 339–343 Atlantis Press, Paris (2016).
100. Wollscheid, S., Tripney, J.: Rapid Reviews as an Emerging Approach to Evidence Synthesis in Education. Lond. Rev. Educ. 19, 1, (2021).
101. Wu J., Xie Y.: Creative english classroom teaching model considering brain cognition enhancement. NeuroQuantology. 16, 5, 266–272 (2018). https://doi.org/10.14704/nq.2018.16.5.1246.
102. Miterianifa, M. et al.: Higher Order Thinking Skills in the 21st Century: Critical Thinking. Presented at the Proceedings of the 1st International Conference on Social Science, Humanities, Education and Society Development, ICONS 2020, 30 November, Tegal, Indonesia January 26 (2021).
103. Xuan, T.H., Sen, A.: Exploring the relationship between Brain-Based Learning and Thinking Skills: A Scoping Review on the Development of Study Material and Its Effectiveness. (2024).
104. Yager, R.E.: The Constructivist Learning Model. Sci. Teach. 58, 6, 52 (1991).
105. Yanti, F.A., Thohir, M.A.: Higher order thinking skills in science learning: a systematic review from 2014-2023. Int. J. Eval. Res. Educ. IJERE. 13, 4, 2419–2427 (2024). https://doi.org/10.11591/ijere.v13i4.28082.
106. Yudha, C.B. et al.: Use brain based learning during the Covid-19 pandemic: Descriptive qualitative. Presented at the ACM International Conference Proceeding Series (2020). https://doi.org/10.1145/3452144.3453741.
107. Zainuddin, Z. et al.: The impact of gamification on learning and instruction: A systematic review of empirical evidence. Educ. Res. Rev. 30, 100326 (2020). https://doi.org/10.1016/j.edurev.2020.100326.
108. Zhu, Z.-T. et al.: A research framework of smart education. Smart Learn. Environ. 3, 1, 4 (2016). https://doi.org/10.1186/s40561-016-0026-2.

back to Table of Contents