Evaluating the Robustness of a Conceptual Framework for Blended Learning
DOI:
https://doi.org/10.22456/2175-2745.151734Keywords:
blended learning, educational conceptual structure, conceptual framework, student engagement, hybrid education in brazilAbstract
The increasing adoption of Blended Learning (BL) models in Brazilian education, particularly after the COVID-19 pandemic, has led to diverse approaches and inconsistent implementations. Motivated by this scenario, this study aimed to analyze how BL has been conceptualized and applied across different contexts. A Systematic Literature Review (SLR) of studies published between 2013 and 2022 was conducted, followed by a hierarchical clustering process to identify conceptual similarities. As a result, five distinct BL models were identified: Integrated, Connected, Intra-school, Team-Based, and Highly Tutored. These models were synthesized into a Conceptual Structure, which was subsequently organized into conceptual frameworks to support educators’ decision-making. To explore the applicability of the proposed structure, three of the identified models were implemented in 8th-grade classrooms in a Brazilian public school in Minas Gerais. Each group experienced a different BL model over a five-week period, and students were evaluated using performance measures, Likert-scale self-assessments, and statistical analyses. The results indicate higher levels of student engagement and academic performance in the Team-Based model when compared to the other two models, while the Intra-school model, although supported by existing school infrastructure, showed limitations in fostering student autonomy and participation. The findings indicate that there is no single hybrid learning model applicable to all contexts. Its effectiveness depends on pedagogical alignment, technological infrastructure, and students’ profiles. The study provides a practical conceptual framework and empirically grounded references to guide teachers and educational managers in implementing hybrid learning in Brazil.
Downloads
References
[1] MORAN, J. Educação híbrida: um conceito-chave para a educação, hoje. Ensino híbrido: personalização e tecnologia na educação. Porto Alegre: Penso, p. 27–45, 2015.
[2] BACICH, L.; NETO, A. T.; TREVISANI, F. de M. Ensino híbrido: personalização e tecnologia na educação. [S.l.]: Penso Editora, 2015.
[3] MOREIRA, F. P.; MAISSIAT, J. Ensino híbrido: Investigação de uma proposta pedagógica em tempos de pandemia. In: VI Workshop de Tecnologias, Linguagens e Mídias na Educação. [S.l.: s.n.], 2021. p. 341–355.
[4] CORREA, T.; SILVA, D. Educação em tempos de pandemia: o uso de diferentes termos para denominar o atual modelo de ensino. In: Anais do XXIX Seminário de Educação. Porto Alegre, RS, Brasil: SBC, 2021. p. 402–412. ISSN 2447-8776. Disponível em: ⟨https://sol.sbc.org.br/index.php/semiedu/article/view/20182⟩.
[5] GOMES, S.; BRANDÃO, M.; SANTOS, Z. A transição do ensino remoto para o ensino híbrido na rede municipal de educação de Cuiabá. In: Anais Estendidos do XXIX Seminário de Educação. Porto Alegre, RS, Brasil: SBC, 2021. p. 736–739. ISSN 0000-0000. Disponível em: ⟨https://sol.sbc.org.br/index.php/semiedu_estendido/article/view/21122⟩.
[6] NASCIMENTO, I. M. do et al. Os efeitos da gamificação personalizada na experiência de ensino e aprendizagem durante o ensino remoto emergencial. Revista Brasileira de Informática na Educação, v. 30, p. 210–236, 2022.
[7] MOREIRA, F. P.; LIMA, D. A. Systematic literature review on the impact of blended learning in promoting student engagement and autonomy: findings and recommendations. Revista Brasileira de Informática na Educação, v. 32, p. 242–269, 2024.
[8] CARVALHO, E. A.; SILVA, A.; CARVALHO, H. Ensino híbrido no ensino superior: desafios do trabalho docente. In: Anais do III Seminário de Educação a Distância da Região Centro-Oeste. Porto Alegre, RS, Brasil: SBC, 2020. ISSN 2763-8995. Disponível em: ⟨https://sol.sbc.org.br/index.php/seadco/article/view/14680⟩.
[9] AHMED, A. et al. Is blended learning the future of education? students perspective using discrete choice experiment analysis. Journal of University Teaching & Learning Practice, v. 19, n. 3, p. 06, 2022.
[10] OLIVEIRA, M.; LIMA, J.; PAIM, G. Avaliações formativas coordenadas por estratégias de participação inspiradas na abordagem de ensino híbrido. In: Anais do XXV Workshop de Informática na Escola. Porto Alegre, RS, Brasil: SBC, 2019. p. 451–460. ISSN 0000-0000. Disponível em: ⟨https://sol.sbc.org.br/index.php/wie/article/view/13193⟩.
[11] SILVA, P. C. da; COUTINHO, D. J. G. Tecnologias na gestão escolar: Inovações e desafios no contexto educacional contemporâneo. Revista Ibero-Americana de Humanidades, Ciências e Educação, v. 11, n. 3, p. 2134–2151, 2025.
[12] JABAREEN, Y. Building a conceptual framework: philosophy, definitions, and procedure. International journal of qualitative methods, SAGE Publications Sage CA: Los Angeles, CA, v. 8, n. 4, p. 49–62, 2009.
[13] AUSUBEL, D. P.; NOVAK, J. D.; HANESIAN, H. Psicologia educacional. [S.l.]: Interamericana, 1980.
[14] MOREIRA, F. P.; LIMA, D. A. Conceptual framework proposal based on a new taxonomy for blended learning: an approach to enhance and modernize education. Revista Novas Tecnologias Na Educação, v. 21, n. 2, p. 44–56, 2023.
[15] MAXWELL, J. A. Qualitative research design: An interactive approach: An interactive approach. [S.l.]: sage, 2013.
[16] NOVAK, J. D.; CAÑAS, A. J. The theory underlying concept maps and how to construct and use them. Institute for Human and Machine Cognition, 2008.
[17] RAVITCH, S. M.; RIGGAN, M. Reason & rigor: How conceptual frameworks guide research. [S.l.]: Sage Publications, 2016.
[18] DAHLBERG, I. A referent-oriented, analytical concept theory for interconcept. KO KNOWLEDGE ORGANIZATION, Nomos Verlagsgesellschaft mbH & Co. KG, v. 5, n. 3, p. 142–151, 1978.
[19] SHULMAN, L. Knowledge and teaching: Foundations of the new reform. Harvard educational review, Harvard Education Publishing Group, v. 57, n. 1, p. 1–23, 1987.
[20] KUHN, T. S. A estrutura das revoluções científicas. [S.l.]: Editora Perspectiva SA, 2020.
[21] LINDEN, R. Técnicas de agrupamento. Revista de Sistemas de Informação da FSMA, v. 4, n. 4, p. 18–36, 2009.
[22] JAIN, A. K.; MURTY, M. N.; FLYNN, P. J. Data clustering: a review. ACM computing surveys (CSUR), Acm New York, NY, USA, v. 31, n. 3, p. 264–323, 1999.
[23] SANDER, J. et al. Automatic extraction of clusters from hierarchical clustering representations. In: SPRINGER. Advances in Knowledge Discovery and Data Mining: 7th Pacific-Asia Conference, PAKDD 2003, Seoul, Korea, April 30–May 2, 2003 Proceedings 7. [S.l.], 2003. p. 75–87.
[24] METZ, J.; MONARD, M. C. Clustering hierárquico: uma metodologia para auxiliar na interpretação dos clusters. In: XXIII Congresso da Sociedade Brasileira de Computação. [S.l.: s.n.], 2005. v. 3, p. 347–395.
[25] LIMA, D. A.; FERREIRA, M. E. A.; SILVA, A. F. F. Machine learning and data visualization to evaluate a robotics and programming project targeted for women. Journal of Intelligent & Robotic Systems, Springer, v. 103, n. 1, p. 4, 2021.
[26] HULT, G. T. M. et al. Stakeholder marketing: a definition and conceptual framework. AMS review, Springer, v. 1, p. 44–65, 2011.
[27] FAYAD, M. E.; SCHMIDT, D. C.; JOHNSON, R. E. Building application frameworks: object-oriented foundations of framework design. [S.l.]: John Wiley & Sons, Inc., 1999.
[28] MATTSSON, M. Object-oriented frameworks. Licentiate thesis, Citeseer, 1996.
[29] JOHNSON, R. E. Components, frameworks, patterns. In: Proceedings of the 1997 symposium on Software reusability. [S.l.: s.n.], 1997. p. 10–17.
[30] MACEDO, M.; SOUZA, M. R. de. Teoria, modelos e frameworks: Conceitos e diferenças. 2022.
[31] YANG, C. C.; OGATA, H. Personalized learning analytics intervention approach for enhancing student learning achievement and behavioral engagement in blended learning. Education and Information Technologies, Springer, p. 1–20, 2022. GS Search. Disponível em: ⟨https://doi.org/10.1007/s10639-022-11291-2⟩.
[32] PHELPS, C.; MORO, C. Using live interactive polling to enable hands-on learning for both face-to-face and online students within hybrid-delivered courses. Journal of University Teaching & Learning Practice, v. 19, n. 3, p. 08, 2022. GS Search.
[33] CHEN, J. Effectiveness of blended learning to develop learner autonomy in a chinese university translation course. Education and Information Technologies, Springer, v. 27, n. 9, p. 12337–12361, 2022. GS Search. Disponível em: ⟨https://doi.org/10.1007/s10639-022-11125-1⟩.
[34] WONG, R. Basis psychological needs of students in blended learning. Interactive Learning Environments, Taylor & Francis, v. 30, n. 6, p. 984–998, 2022. GS Search. Disponível em: ⟨https://doi.org/10.1080/10494820.2019.1703010⟩.
[35] CHUA, K.; ISLAM, M. The hybrid project-based learning–flipped classroom: A design project module redesigned to foster learning and engagement. International Journal of Mechanical Engineering Education, SAGE Publications Sage UK: London, England, v. 49, n. 4, p. 289–315, 2021. GS Search. Disponível em: ⟨https://doi.org/10.1177/0306419019838335⟩.
[36] AHLIN, E. M. A mixed-methods evaluation of a hybrid course modality to increase student engagement and mastery of course content in undergraduate research methods classes. Journal of Criminal Justice Education, Taylor & Francis, v. 32, n. 1, p. 22–41, 2020. GS Search. Disponível em: ⟨https://doi.org/10.1080/10511253.2020.1831034⟩.
[37] SARITEPECI, M.; ÇAKIR, H. The effect of blended learning environments on student motivation and student engagement: A study on social studies course. Education & Science/Egitim ve Bilim, v. 40, n. 177, 2015. GS Search.
[38] ETOM, R. et al. The use of elearning tools in blended learning approach on students’ engagement and performance. In: Journal of Physics: Conference Series. [S.l.: s.n.], 2021. v. 1835, n. 1, p. 012075. GS Search.
[39] DARMAWAN, I. et al. The effectiveness of the blended learning approach in algorithm and programming courses. In: IOP PUBLISHING. Journal of Physics: Conference Series. [S.l.], 2021. v. 1722, n. 1, p. 012104. GS Search.
[40] ARGYRIOU, P.; BENAMAR, K.; NIKOLAJEVA, M. What to blend? exploring the relationship between student engagement and academic achievement via a blended learning approach. Psychology Learning & Teaching, SAGE Publications Sage UK: London, England, v. 21, n. 2, p. 126–137, 2022. GS Search.
[41] AVRAMENKO, B. V. et al. Organization of individual
work of students in blended learning of foreign languages at higher educational institutions. REVISTA GEINTEC-GESTAO INOVACAO E TECNOLOGIAS, v. 11, n. 3, p. 930–944, 2021. GS Search.
[42] SUDIRTHA, I. G. et al. The impact of blended learning assisted with self-assessment toward learner autonomy and creative thinking skills. International Journal of Emerging Technologies in Learning, v. 17, n. 6, 2022. GS Search.
[43] RAHIM, R. A.; KALAICHELVEN, J.; IBRAHIM, R. Measuring user experience of blended learning application: A case study of higher education. In: 2022 13th International Conference on E-Education, E-Business, E-Management, and E-Learning (IC4E). [s.n.], 2022. p. 274–279. GS Search. Disponível em: ⟨https://doi.org/10.1145/3514262.3514284⟩.
[44] LIMA, F. de B.; LAUTERT, S. L.; GOMES, A. S. Learner behaviors associated with uses of resources and learning pathways in blended learning scenarios. Computers & Education, Elsevier, v. 191, p. 104625, 2022. GS Search. Disponível em: ⟨https://doi.org/10.1186/s12909-022-03676-1⟩.
[45] KUNDU, A.; BEJ, T.; RICE, M. Time to engage: Implementing math and literacy blended learning routines in an indian elementary classroom. Education and Information Technologies, Springer, v. 26, n. 1, p. 1201–1220, 2021. GS Search.
[46] INDRIYANTI, N.; YAMTINAH, S.; MUAWIYAH, D. An inquiry into students’ metacognition and learning achievement in a blended learning design. International Journal of Emerging Technologies in Learning (iJET), International Journal of Emerging Technology in Learning, v. 15, n. 21, p. 77–88, 2020. GS Search.
[47] SHEN, J. et al. Incorporating modified team-based learning into a flipped basic medical laboratory course: impact on student performance and perceptions. BMC Medical Education, BioMed Central, v. 22, n. 1, p. 1–9, 2022. GS Search. Disponível em: ⟨https://doi.org/10.1186/s12909-022-03676-1⟩.
[48] CUI, Y.; ZHAO, G.; ZHANG, D. Improving students’ inquiry learning in web-based environments by providing structure: Does the teacher matter or platform matter? British Journal of Educational Technology, Wiley Online Library, v. 53, n. 4, p. 1049–1068, 2022. GS Search. Disponível em: ⟨https://doi.org/10.1111/bjet.13184⟩.
[49] OLEJNIK, S.; ALGINA, J. Generalized eta and omega squared statistics: measures of effect size for some common research designs. Psychological methods, American Psychological Association, v. 8, n. 4, p. 434, 2003.
[50] ROJEWSKI, J.; LEE, I. H.; GEMICI, S. Use of t-test and anova in career-technical education research. Career and Technical Education Research, Association for Career and Technical Education Research, v. 37, n. 3, p. 263–275, 2012.
[51] PEREIRA, D. G.; AFONSO, A.; MEDEIROS, F. M. Overview of friedman’s test and post-hoc analysis. Communications in Statistics-Simulation and Computation, Taylor & Francis, v. 44, n. 10, p. 2636–2653, 2015.
[52] SLAVIERO, C.; HAEUSLER, E. H. Computational thinking tools: Analyzing concurrency and its representations. Journal on Interactive Systems, v. 9, n. 1, 2018.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Franciely Pereira Moreira, Danielli Araújo Lima

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Autorizo aos editores a publicação de meu artigo, caso seja aceito, em meio eletrônico de acordo com as regras do Public Knowledge Project.Accepted 2026-05-11
Published 2026-06-21













