The notion of “multiple intelligences” (MI) was established by Howard Gardner, a psychologist from the United States, during the latter part of the 1970s and the early part of the 1980s. Gardner introduced the concept of MI in his 1983 publication titled Frames of Mind: The Theory of Multiple Intelligences, positing that individuals possess unique cognitive abilities across eight discrete domains. As per the theory, there exist nine discrete categories of intelligence, such as logical-mathematical, visual-spatial, musical-rhythmic, verbal-linguistic, bodily-kinesthetic, intrapersonal, interpersonal, existential, and naturalistic. Individuals construct their distinct cognitive frameworks by engaging in activities that are highly valued within their respective cultural contexts. The present article furnishes a comprehensive outline of the rationales and plausible scenarios for deliberating MI theory with pre-service educators during their teacher training. This study examines the significance of Universal Design for Learning (UDL) and comparable models in the context of teacher training, taking into account the distinctions between the semantic theoretical foundations of intelligence in Multiple Intelligences (MI) theory and learning styles theory.
D. J. Pless, C. Chakrabarti, R. Rammohan, and G. F. Luger, “The design and testing of a first-order logic-based stochastic modeling language,” Int. J. Artif. Intell. Tools, vol. 15, no. 06, pp. 979–1005, 2006.
J. Han et al., “Hybrid high dynamic range imaging fusing neuromorphic and conventional images,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 45, no. 7, pp. 8553–8565, 2023.
K. R. Fogelman, “Modern Maths And Intelligence Tests,” Educ. Res. (Windsor), vol. 11, no. 1, pp. 71–73, 1968.
A. Stevens and R. Bernier, “Stanford-Binet intelligence scales and revised versions,” in Encyclopedia of Autism Spectrum Disorders, Cham: Springer International Publishing, 2021, pp. 4604–4607.
P. M. Salmon et al., “Managing the risks of artificial general intelligence: A human factors and ergonomics perspective,” Hum. Factors Ergon. Manuf., 2023.
S. S. Mahmoud and M. M. Alaraj, “Integrating multiple intelligences in the EFL syllabus: Content analysis,” Theory Pr. Lang. Stud., vol. 9, no. 11, p. 1410, 2019.
A. M. Alawieh et al., “Abstract 150: Multicenter validation of SPOT, an artificial intelligence based tool, to optimize selection of elderly stroke patients for mechanical thrombectomy - insights from the STAR collaboration,” Stroke, vol. 51, no. Suppl_1, 2020.
L. Barberis Canonico, N. J. McNeese, and C. Duncan, “Machine learning as grounded theory: Human-centered interfaces for social network research through artificial intelligence,” Proc. Hum. Factors Ergon. Soc. Annu. Meet., vol. 62, no. 1, pp. 1252–1256, 2018.
P. Maftoon and S. N. Sarem, “The realization of Gardner’s multiple intelligences (MI) theory in second language acquisition (SLA),” J. Lang. Teach. Res., vol. 3, no. 6, 2012.
L. Rousseau, “‘neuromyths’ and multiple intelligences (MI) theory: A comment on Gardner, 2020,” Front. Psychol., vol. 12, p. 720706, 2021.
F. Nie, Y. Cao, J. Wang, C.-Y. Lin, and R. Pan, “Mention and entity description co-attention for entity disambiguation,” Proc. Conf. AAAI Artif. Intell., vol. 32, no. 1, 2018.
S. Mithen, The prehistory of the mind. Oxford, England: Weidenfeld & Nicolson, 1998.
H. Gardner, Frames of mind, 2nd ed. London, England: Fontana Press, 1993.
H. Gardner, “Changing minds: How the application of the multiple intelligences (MI) framework could positively contribute to the theory and practice of international negotiation,” in Psychological and Political Strategies for Peace Negotiation, New York, NY: Springer New York, 2011, pp. 1–14.
R. Pacheco Rios, “Las Teorías de Enseñanza y los Estilos de Aprendizaje y los Modelos Teóricos para ajustarlos / Teaching Theories, Learning Styles and Theoretical Models for their Adjustment,” GKA revEDUSUP, vol. 6, no. 1, pp. 21–34, 2019.
S. Rizqiningsih and M. S. Hadi, “Multiple Intelligences (MI) on Developing Speaking Skills,” English Language in Focus (ELIF), vol. 1, no. 2, p. 127, 2019.
N. Cowan, E. M. Elliott, J. S. Saults, L. D. Nugent, P. Bomb, and A. Hismjatullina, “Rethinking speed theories of cognitive development. Increasing the rate of recall without affecting accuracy: Increasing the rate of recall without affecting accuracy,” Psychol. Sci., vol. 17, no. 1, pp. 67–73, 2006.
P. McNamee et al., “E-learning, Multiple Intelligences theory (MI) and learner-centred instruction: Adapting MI learning theoretical principles to the instruction of health and safety to construction managers,” J. Coll. Teach. Learn., vol. 6, no. 2, 2009.
J. E. Ormrod, Educational psychology: Developing learners: International edition, 7th ed. Upper Saddle River, NJ: Pearson, 2010.
“A Conceptual Analysis of the Semantic Use of Multiple Intelligences Theory and Implications for Teacher Education Adam I,” Attwood*.
A. W. Yusuf, R. B. Bako, A. Guga, and S. U. El-Yakub, “Effect of heuristic teaching approach on students performance in economics in senior secondary schools in Kano state, Nigeria,” J. Teach. Teach. Educ., vol. 08, no. 01, pp. 54–60, 2020.
S. Sariani and M. E. Khairat, “Factors affecting the language learning of EFL students through ABC model: A cross cultural analysis,” polingua, vol. 5, no. 2, pp. 80–89, 2018.
D. Cavilla, “The effects of student reflection on academic performance and motivation,” SAGE Open, vol. 7, no. 3, p. 215824401773379, 2017.
H. Sharma, “Statistical significance or clinical significance? A researcher’s dilemma for appropriate interpretation of research results,” Saudi J. Anaesth., vol. 15, no. 4, pp. 431–434, 2021.
J. M. Pocaan, “Multiple intelligences and perceptual learning style preferences of education and engineering students,” International Journal of Professional Development, Learners and Learning, vol. 4, no. 2, p. ep2209, 2022.
A. Bovt, “The influence of artistic and aesthetic education of schoolchildren on development of multiple intelligences,” The Pedagogical Process: Theory and Practice, no. 1–2, 2018.
P. Pluye, R. M. Grad, A. Levine, and B. Nicolau, “Understanding divergence of quantitative and qualitative data (or results) in mixed methods studies,” Int. J. Mult. Res. Approaches, vol. 3, no. 1, pp. 58–72, 2009.
T. I. Tawalbeh, “Investigating EFL learners’ multiple intelligences in the preparatory year at Taif University,” Theory Pr. Lang. Stud., vol. 6, no. 7, p. 1347, 2016.
L. Shi, “Multi dimensional dynamic evaluation method of English MOOCS autonomous learning based on Multiple Intelligences Theory,” Int. J. Contin. Eng. Educ. Life Long Learn., vol. 1, no. 1, p. 1, 2024.
M. Mujib, S. Sukestiyarno, H. Suyitno, and I. Junaedi, “Mathematical critical thinking profile-based Ennis and Gardner’s theory of multiple intelligences,” AlphaMath, vol. 8, no. 1, p. 60, 2022.
C. Ma and M. Schapira, The bell curve: Intelligence and class structure in American life. London, England: Routledge, 2017
H. Nanda, S. Marwaha, and G. Nanda, “Impact of multiple intelligence based intervention on cognitive abilities of students,” European journal of behavioral sciences, 2018. doi:10.33422/ejbs.2018.07.66
A. Wahab, K. Mahbub, and A.-R. Tawil, “Neurosymbolic spike concept learner towards Neuromorphic General Intelligence,” Proceedings of the 13th International Conference on Agents and Artificial Intelligence, 2021. doi:10.5220/0010339911681176.
“The general education context of special education,” Handbook of Special Education, pp. 187–261, 2017. doi:10.4324/9781315517698-16
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FORE School of Management, Qutab Institutional Area, New Delhi, Delhi 110016.
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Parvesh Sharma, “A Review of Semantic Application of MI Theory and Effects for Teacher Training”, Journal of Enterprise and Business Intelligence, vol.3, no.4, pp. 201-212, October 2023. doi: 10.53759/5181/JEBI202303020.