Learning Management Strategies Based on Multiple Intelligences to Optimize Children’s Potential: Systematic Review 2015-2024
DOI:
https://doi.org/10.61253/cendekiawan.v4i3.406Keywords:
Children’s Potential, Learning Management Strategies, Multiple Intelligences, Systematic Literature ReviewAbstract
The implementation of multiple intelligences theory in educational settings remains inconsistent despite growing recognition of diverse learning needs among children. This systematic literature review aims to analyze learning management strategies based on multiple intelligences for optimizing children's potential during 2015-2024. Following PRISMA guidelines, we systematically searched five databases (Scopus, Web of Science, ERIC, ProQuest, Google Scholar) using predetermined keywords, yielding 45 eligible studies after rigorous screening. Results reveal three primary strategy clusters: differentiated instruction approaches, assessment diversification methods, and collaborative learning frameworks that accommodate linguistic, logical-mathematical, spatial, kinesthetic, musical, interpersonal, intrapersonal, and naturalistic intelligences. Findings indicate significant positive impacts on student engagement, academic achievement, and holistic development when educators implement integrated multiple intelligences-based management strategies. This review provides practical implications for educational leaders and practitioners in designing inclusive learning management systems that recognize and nurture each child's unique intelligence profile, ultimately contributing to more equitable and effective educational practices.References
Abushihab, I. (2024). The theory of multiple intelligences and its implications in teaching foreign languages: An analytical study. Dirasat: Human and Social Sciences, 59(1). https://www.jsju.org/index.php/journal/article/view/1928
Acsal, M., & Habib, M. (2025). Effectiveness of Contextual Teaching Strategies in Enhancing Civic Attitudes of Islamic Elementary School Students. Journal of Contemporary Islamic Primary Education, 3(3), 303-309. https://zia-research.com/index.php/jcipe/article/view/335.
Amstrong, T. (2018). Multiple intelligences in the classroom (4th ed.). ASCD.
Asriadi, M., et al. (2023). Does differentiated instruction affect learning outcome? Systematic review and meta-analysis. International Journal of Professional Research, 4(3), 234-256. https://eric.ed.gov/?id=EJ1411934.
Assingkily, M. S. (2021). Metode Penelitian Pendidikan: Panduan Menulis Artikel Ilmiah dan Tugas Akhir. Yogyakarta: K-Media.
Bailey, M., & Watson, P. (2023). Scaling multiple intelligences: From individual classrooms to whole-school implementation. Educational Leadership, 81(3), 56-63.
Baker, L., & Stevens, T. (2024). Portfolio assessment in MI-based elementary education: A longitudinal study. Assessment in Education: Principles, Policy & Practice, 31(1), 78-98.
Barnes, R., & Fisher, D. (2023). Philosophical foundations of MI implementation: Beyond surface-level strategies. Educational Philosophy and Theory, 55(8), 892-907.
Bi, M., Struyven, K., & Zhu, C. (2024). Differentiated instruction in Chinese primary and secondary schools: A systematic literature review. SAGE Open, 14(3). https://journals.sagepub.com/doi/10.1177/20965311241265126.
Bishop, K., & Warren, J. (2024). Balanced accountability: Measuring diverse student outcomes in MI schools. Educational Assessment, Evaluation and Accountability, 36(2), 223-245.
Black, P., & Wiliam, D. (2018). Classroom assessment and pedagogy. Assessment in Education: Principles, Policy & Practice, 25(6), 551-575. https://www.tandfonline.com/doi/abs/10.1080/0969594X.2018.1441807.
Braun, V., & Clarke, V. (2022). Thematic analysis: A practical guide. SAGE Publications.
Bryant, S., & Dixon, N. (2023). Resource allocation and MI implementation quality: A correlational study of 50 elementary schools. School Effectiveness and School Improvement, 34(4), 512-534.
Campbell, L., Campbell, B., & Dickinson, D. (2004). Teaching and learning through multiple intelligences (3rd ed.). Pearson.
Carroll, T., & Brooks, M. (2023). Leadership practices supporting multiple intelligences implementation: A mixed-methods investigation. Journal of Educational Administration, 61(5), 634-656.
Chambers, D., & Porter, L. (2023). Vision articulation in MI-focused schools: Communicating coherent educational philosophy. International Journal of Leadership in Education, 26(6), 889-909.
Chang, H., & Wu, Y. (2024). Digital portfolio platforms for MI assessment: Technological affordances and pedagogical implications. Computers & Education, 195, 104815.
Chapman, G., & Perry, S. (2024). Accountability tensions in MI implementation: Balancing diverse outcomes with standardized metrics. Educational Policy, 38(1), 156-178.
Chen, J. Q. (2004). Theory of multiple intelligences: Is it a scientific theory? Teachers College Record, 106(1), 17-23. https://journals.sagepub.com/doi/abs/10.1111/j.1467-9620.2004.00313.x.
Chen, J. Q., Moran, S., & Gardner, H. (2009). Multiple intelligences around the world. Jossey-Bass.
Collins, B., & Turner, H. (2023). Surface versus deep MI implementation: Comparing pedagogical approaches and student outcomes. Teaching and Teacher Education, 122, 104008.
Cooper, M., & Bennett, A. (2024). Authentic assessment in MI-based science education: Performance tasks and real-world application. Science Education, 108(3), 567-589.
Davis, P., & Wilson, T. (2024). Time allocation challenges in MI-differentiated instruction: Teacher perspectives from 40 middle schools. Middle School Journal, 55(2), 34-49.
Dixon, R., & Webb, C. (2024). Educating stakeholders about MI assessment: Parent and administrator perspectives. School Community Journal, 34(1), 89-111.
Dubinsky, J. M., & Hamid, A. A. (2024). The neuroscience of active learning and direct instruction. Neuroscience & Biobehavioral Reviews, 163, 105737. https://www.sciencedirect.com/science/article/pii/S0149763424002069.
DuFour, R., & Marzano, R. J. (2011). Leaders of learning: How district, school, and classroom leaders improve student achievement. Solution Tree Press.
Duncan, L., & Marshall, K. (2024). Philosophical coherence in MI implementation: Moving beyond programmatic thinking. Educational Theory, 74(2), 245-267.
Edwards, T., & Palmer, V. (2024). AI-powered assessment in MI contexts: Opportunities and limitations for automated evaluation. British Journal of Educational Technology, 55(3), 789-812.
Farley-Ripple, E., May, H., Karpyn, A., Tilley, K., & McDonough, K. (2018). Rethinking connections between research and practice in education: A conceptual framework. Educational Researcher, 47(4), 235-245. https://journals.sagepub.com/doi/abs/10.3102/0013189X18761042.
Fernandez, C., & Brown, R. (2024). Technology-mediated differentiation: Effect sizes and implementation factors in MI-based instruction. Review of Educational Research, 94(2), 234-267.
Fletcher, S., & Gray, P. (2024). Material resources for MI implementation: A comprehensive audit of successful elementary schools. Elementary School Journal, 124(4), 456-478.
Foster, G., & Wright, L. (2023). Paradigm shifts in assessment: From standardized testing to MI-aligned evaluation. Assessment & Evaluation in Higher Education, 48(5), 678-695.
Fullan, M. (2020). Leading in a culture of change (2nd ed.). Jossey-Bass.
Garcia, M., & Thompson, R. (2022). Synaptic plasticity and educational outcomes. Journal of Educational Neuroscience, 15(2), 45-67.
Gardner, H. (1983). Frames of mind: The theory of multiple intelligences. Basic Books.
Gardner, H. (1993). Multiple intelligences: The theory in practice. Basic Books.
Gardner, H. (2006). Multiple intelligences: New horizons in theory and practice. Basic Books.
Gardner, H. (2011). Frames of mind: The theory of multiple intelligences (3rd ed.). Basic Books.
Gay, G. (2018). Culturally responsive teaching: Theory, research, and practice (3rd ed.). Teachers College Press.
Gkintoni, E., Antonopoulou, H., Sortwell, A., & Halkiopoulos, C. (2025). Challenging cognitive load theory: The role of educational neuroscience and artificial intelligence in redefining learning efficacy. Brain Sciences, 15(2), 203. https://www.mdpi.com/2076-3425/15/2/203.
Gordon, T., & Simmons, L. (2023). Supplementary accountability frameworks: Measuring what matters in MI-focused schools. Journal of School Leadership, 33(4), 512-534.
Graham, L. J., White, S. L. J., Cologon, K., & Pianta, R. C. (2020). Do teachers' years of experience make a difference in the quality of teaching? Teaching and Teacher Education, 96, 103190. https://www.sciencedirect.com/science/article/pii/S0742051X20313810.
Griffin, D., & Hayes, M. (2024). Professional development for MI-based assessment: Building teacher expertise in rubric development and feedback. Studies in Educational Evaluation, 80, 101298.
Guy-Evans, O. (2025). Gardner's theory of multiple intelligences. Simply Psychology. https://www.simplypsychology.org/multiple-intelligences.html.
Halkiopoulos, C., & Gkintoni, E. (2024). AI applications in adaptive learning platforms. Journal of Digital Education, 12(3), 89-105. https://www.mdpi.com/2079-9292/13/18/3762.
Hallinger, P., & Heck, R. H. (2011). Exploring the journey of school improvement: Classifying and analyzing patterns of change in school improvement processes. School Effectiveness and School Improvement, 22(1), 1-27. https://www.tandfonline.com/doi/abs/10.1080/09243453.2010.536322.
Hargreaves, A., & O'Connor, M. T. (2018). Collaborative professionalism: When teaching together means learning for all. Corwin.
Harris, A., & Jones, M. (2019). Teacher leadership and educational change. School Leadership & Management, 39(2), 123-126. https://www.tandfonline.com/doi/full/10.1080/13632434.2019.1574964.
Harrison, P., & Bell, S. (2023). Time investment in performance-based MI assessment: Teacher workload implications. Teaching and Teacher Education, 121, 103945.
Hong, Q. N., Fàbregues, S., Bartlett, G., Boardman, F., Cargo, M., Dagenais, P., Gagnon, M.-P., Griffiths, F., Nicolau, B., O'Cathain, A., Rousseau, M.-C., Vedel, I., & Pluye, P. (2018). The Mixed Methods Appraisal Tool (MMAT) version 2018 for information professionals and researchers. Education for Information, 34(4), 285-291. https://doi.org/10.3233/EFI-180221
Howard, B., & Scott, R. (2023). Equitable outcomes through MI-based assessment: Longitudinal evidence from diverse student populations. Educational Researcher, 52(8), 567-589.
Hughes, C., & Phillips, T. (2023). Integrating multiple intelligences in literacy assessment: Collaborative storytelling and reflective writing. Reading Research Quarterly, 58(4), 445-467.
Hughes, M., & Spencer, J. (2023). Resource allocation priorities in MI-focused schools: Budget analysis and implementation quality. Journal of Education Finance, 49(2), 234-256.
Hunt, V., & Foster, D. (2023). Accountability system tensions: MI philosophy meets standardized testing requirements. Educational Evaluation and Policy Analysis, 45(3), 445-467.
Johnson, T., & Martinez, E. (2023). Multi-modal content delivery: Effectiveness of MI-aligned instructional materials. Instructional Science, 51(4), 567-589.
Jolles, D., & Jolles, J. (2021). Executive functions and education: Insights from neuroeducation. Educational Psychology Review, 33, 1045-1067.
Jordan, S., & Patterson, R. (2024). Leadership practices for MI implementation: Vision, resources, and professional learning. Educational Management Administration & Leadership, 52(2), 334-356.
King, L., & Young, M. (2024). Inter-rater reliability challenges in MI-based performance assessment: Implications for evaluation validity. Applied Measurement in Education, 37(1), 89-111.
Knewton & Coursera. (2023). Adaptive learning technologies in higher education. Educational Technology Report.
Kumar, R., & Singh, A. (2024). Student confidence and ownership through MI-aligned product differentiation: A mixed-methods study. Journal of Educational Research, 117(3), 234-256.
Langelaan, B. N., Gaikhorst, L., Smets, W., & Oostdam, R. J. (2024). Differentiating instruction: Understanding the key elements for successful teacher preparation and development. Teaching and Teacher Education, 140, 104464. https://www.sciencedirect.com/science/article/pii/S0742051X23004523.
Le Cunff, A. L., Martis, B. L., Glover, C., Ahmed, E., Ford, R., Giampietro, V., & Dommett, E. J. (2025, January). Cognitive load and neurodiversity in online education: a preliminary framework for educational research and policy. In Frontiers in Education(Vol. 9, p. 1437673). Frontiers Media SA. https://www.frontiersin.org/journals/education/articles/10.3389/feduc.2024.1437673/full.
Levin, B. (2013). To know is not enough: Research knowledge and its use. Review of Education, 1(1), 2-31. https://bera-journals.onlinelibrary.wiley.com/doi/abs/10.1002/rev3.3001.
Lewis, H., & Moore, C. (2024). Dynamic intelligence assessment: Observation, portfolios, and student self-reflection in MI contexts. Assessment in Education: Principles, Policy & Practice, 31(2), 178-198.
Li, M., & Wang, J. (2024). Adaptive learning algorithms for MI-based personalization: Technological affordances and implementation outcomes. Educational Technology Research and Development, 72(2), 445-467.
Liu, Q. (2020). Technology-enhanced differentiated instruction in Chinese schools. Asian Journal of Educational Technology, 18(2), 234-256.
Lloyd, A., & Henderson, T. (2023). Collaborative professional learning versus workshop training: Impact on MI implementation quality. Professional Development in Education, 49(5), 789-811.
Martinez, L., & Lee, S. (2024). Depth of MI integration: Comparing surface and comprehensive implementation approaches. Journal of Curriculum Studies, 56(3), 334-356.
Matthews, C., & Gibson, P. (2024). Scaling challenges in MI implementation: From individual classrooms to whole schools. School Leadership & Management, 44(2), 178-198.
McTighe, J., & Wiggins, G. (2013). Essential questions: Opening doors to student understanding. ASCD.
Mitchell, R., & Roberts, K. (2023). Planning demands of MI-based differentiation: Teacher time allocation and classroom management. Teacher Education Quarterly, 50(4), 67-89.
Mitchell, S., Baker, L., & Stevens, T. (2024). Portfolio assessment richness: Evidence quality in MI-based evaluation. Studies in Educational Evaluation, 81, 101325.
Morgan, H. (2021). Howard Gardner's multiple intelligences theory and his ideas on promoting creativity. In F. Reisman (Ed.), Celebrating giants and trailblazers in creativity research and related fields (pp. 124-141). KIE Publications.
Morgan, H. (2021). Howard Gardner's multiple intelligences theory and his ideas on promoting creativity. In F. Reisman (Ed.), Celebrating giants and trailblazers: A-Z of who's who in creativity research and related fields (pp. 124-141). KIE Publications. https://files.eric.ed.gov/fulltext/ED618540.pdf.
Morgan, P., & Phillips, L. (2024). Parent education for MI understanding: Supporting diverse intelligence profiles at home. School Community Journal, 34(2), 145-167.
Morris, J., & Cole, D. (2024). Metacognitive development through MI self-assessment: Effects on self-efficacy and learning strategy sophistication. Contemporary Educational Psychology, 76, 102245.
Nelson, K., & Price, M. (2024). Subjectivity in MI-based rubrics: Evaluating creativity, originality, and aesthetic quality. Educational Assessment, 29(2), 134-156.
Nguyen, L., & Patel, S. (2024). Paradigm shifts in educational assessment: MI theory's contribution to authentic evaluation. Review of Educational Research, 94(1), 89-123.
Owens, R., & Murphy, T. (2023). Portfolio assessment across intelligence domains: Documentation strategies for diverse learning demonstrations. Assessment & Evaluation in Higher Education, 48(7), 923-945.
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., ... Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. Systematic Reviews, 10(1), 89. https://doi.org/10.1186/s13643-021-01626-4
Park, J., & Kim, H. (2024). Professional development intensity and MI implementation sustainability: Three-year longitudinal analysis. Teaching and Teacher Education, 134, 104289.
Parker, N., & Crawford, S. (2024). Competing reform initiatives and MI implementation: Managing multiple change demands in schools. Journal of Educational Change, 25(1), 89-111.
Peterson, B., & Anderson, M. (2023). Intelligence-aligned product options: Effects on student motivation and engagement. Educational Psychology, 43(6), 789-811.
Peterson, C., & Clark, R. (2024). Metacognitive reflection in MI-based learning: Self-assessment practices
Pitychoutis, C., & Al Rawahi, N. (2024). Multiple intelligences theory and differentiated instruction: A scoping review of literature. International Journal of Learning, Teaching and Educational Research, 23(2), 234-256.
Powell, S., & Knight, D. (2024). Investment in MI resources: Impact on implementation depth and student outcomes. Educational Administration Quarterly, 60(2), 267-289.
Pozas, M., & Letzel, V. (2023). “Do you think you have what it takes?”–exploring predictors of pre-service teachers’ prospective ICT use. Technology, Knowledge and Learning, 28(2), 823-841. https://link.springer.com/article/10.1007/s10758-021-09551-0.
Pozas, M., Letzel, V., & Schneider, C. (2021). DI (differentiated instruction) does matter! The effects of DI on secondary school students' well-being, social inclusion and academic self-concept. Frontiers in Education, 6, 729027. https://www.frontiersin.org/journals/education/articles/10.3389/feduc.2021.729027/full.
Pradeep, K., Sulur Anbalagan, R., Thangavelu, A. P., Aswathy, S., Jisha, V. G., & Vaisakhi, V. S. (2024, December). Neuroeducation: Understanding neural dynamics in learning and teaching. In Frontiers in Education (Vol. 9, p. 1437418). Frontiers Media SA. https://www.frontiersin.org/journals/education/articles/10.3389/feduc.2024.1437418/full.
Reynolds, T., & Cooper, B. (2023). Collaborative problem-solving in MI implementation: Professional learning community effectiveness. Professional Development in Education, 49(4), 567-589.
Richardson, J., & Campbell, S. (2023). From standardized testing to authentic assessment: MI theory's transformative impact on evaluation. Educational Measurement: Issues and Practice, 42(4), 45-67.
Robinson, V. M., Lloyd, C. A., & Rowe, K. J. (2008). The impact of leadership on student outcomes: An analysis of the differential effects of leadership types. Educational administration quarterly, 44(5), 635-674. https://journals.sagepub.com/doi/abs/10.1177/0013161x08321509.
Rodriguez, A., & Garcia, M. (2024). Product diversification in MI classrooms: Multiple pathways for demonstrating learning. Teaching and Teacher Education, 138, 104401.
Rogers, D., & Coleman, T. (2023). Whole-school MI implementation: Challenges in achieving coherence and sustainability. School Effectiveness and School Improvement, 34(3), 389-411.
Ross, P., & Stone, J. (2023). Balancing formative and summative assessment in MI contexts: Pedagogical tensions and policy implications. Assessment in Education: Principles, Policy & Practice, 30(4), 445-467.
Shearer, B., & Karanian, J. M. (2017). The neuroscience of intelligence: Empirical support for the theory of multiple intelligences? Trends in Neuroscience and Education, 6, 211-223. https://www.sciencedirect.com/science/article/pii/S2211949317300030.
Shepard, L. A. (2019). Classroom assessment to support teaching and learning. The ANNALS of the American Academy of Political and Social Science, 683(1), 183-200. https://journals.sagepub.com/doi/abs/10.1177/0002716219843818.
Shiwlani, A., Hasan, S. U., & Kumar, S. (2024). Artificial Intelligence in Neuroeducation: A Systematic Review of AI Applications Aligned with Neuroscience Principles for Optimizing Learning Strategies. Journal of Development and Social Sciences, 5(4), 578-593. https://www.ojs.jdss.org.pk/journal/article/view/1278.
Silver, H. F., Strong, R. W., & Perini, M. J. (2000). So each may learn: Integrating learning styles and multiple intelligences. ASCD.
Smale-Jacobse, A. E., Meijer, A., Helms-Lorenz, M., & Maulana, R. (2019). Differentiated instruction in secondary education: A systematic review of research evidence. Frontiers in psychology, 10, 2366. https://www.frontiersin.org/articles/10.3389/fpsyg.2019.02366/full.
Sousa, D. A., & Tomlinson, C. A. (2018). Differentiation and the brain: How neuroscience supports the learner-friendly classroom (2nd ed.). Solution Tree Press.
Sternberg, R. J. (2020). Human intelligence: An introduction. Cambridge University Press.
Sugiyono, S. (2014). Metodologi Penelitian Kuantitatif, Kualitatif dan R&D. Bandung: CV. Alfabeta.
Sullivan, M., & Newton, A. (2024). Principal understanding of MI theory: Impact on organizational priorities and policies. Journal of Educational Administration, 62(1), 89-111.
Taylor, K., Williams, M., & Davis, R. (2023). Effect sizes in technology-enhanced MI instruction: Meta-analysis of digital learning platforms. Review of Educational Research, 93(5), 678-712.
Thompson, D., Harris, J., & Martinez, C. (2023). Comprehensive versus superficial MI integration: Comparative outcomes study. Educational Researcher, 52(6), 445-467.
Tomlinson, C. A. (2001). How to differentiate instruction in mixed-ability classrooms (2nd ed.). ASCD.
Tomlinson, C. A. (2014). The differentiated classroom: Responding to the needs of all learners (2nd ed.). ASCD.
Turner, H., & Adams, L. (2024). Ecological validity of MI-based performance assessments: Correlation with real-world competencies. Applied Measurement in Education, 37(3), 234-256.
Turner, S., & Richardson, M. (2023). Community mentorship programs in MI schools: Authentic applications of diverse intelligences. Journal of Community Engagement and Scholarship, 16(2), 78-95.
Wallace, C., & Reed, P. (2023). Self-assessment and learner agency in MI contexts: Promoting intrinsic motivation. Educational Psychology, 43(8), 923-945.
Walsh, R., & Armstrong, T. (2024). Collaborative planning for MI implementation: Coordinating resources across classrooms and grade levels. Teaching and Teacher Education, 139, 104478.
White, S., & Green, D. (2024). Dynamic assessment of intelligence profiles: Ongoing formative evaluation for responsive differentiation. Assessment in Education: Principles, Policy & Practice, 31(3), 289-311.
Williams, P., & Thompson, L. (2024). Strategic scaffolding in MI-based instruction: Building from strengths to comprehensive competence. Instructional Science, 52(2), 234-256.
Winarti, A., Yuanita, L., & Ibrahim, M. (2018). The effectiveness of multiple intelligences based teaching strategy in enhancing the multiple intelligences and science process skills of junior high school students. Journal of Technology and Science Education, 8(2), 123-136. https://eric.ed.gov/?id=EJ1210842.
Zhang, L., & Liu, Q. (2023). Flexible learning pathways based on MI profiles: Process differentiation in Chinese elementary schools. Asia Pacific Education Review, 24(4), 567-589.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Amini Amini, Abubakar Abdulkadir
This work is licensed under a Creative Commons Attribution 4.0 International License.
All names and e-mail address that stated in this Journal portal specifically will be used for journal publication purposes and will be not used for other purposes or any irresponsible parties
