El Ciclo Integrativo de Aprendizaje Farmacológico (CIAF): descripción y validación de un modelo pedagógico para la enseñanza de farmacología en salud J. Adv. Educ. Sci. Humanit. (July - December 2026) 4(2): 10-14 https://doi.org/10.5281/zenodo.21854540 ISSN 3091-1583 ORIGINAL ARTICLE The Integrative Cycle of Pharmacological Learning (CIAF): description and validation of a pedagogical model for health pharmacology teaching  Daryanis Guilbeaux daryanisguilbeaux@gmail.com Received: 14 April 2026 / Accepted: 27 June 2026 / Published online: 31 July 2026 © The Author(s) 2026 Daryanis Guilbeaux Abstract The teaching of Pharmacokinetics and Pharmaco- dynamics is a cornerstone of safe clinical reasoning in health professional training. However, the predominance of tradi- tional expository models and the absence of contextualized pedagogical strategies produce persistent cognitive gaps in students. To describe the development process and theoret- ical-methodological foundations of the Integrative Cycle of Pharmacological Learning (CIAF), an original pedagog- ical model developed over a three-year period of teaching innovation in the Angolan context. Qualitative-descriptive research using a Design-Based Research approach, conduct- ed in a higher health education context in Angola, between 2023 and 2026, with 873 students from Nursing and Nutri- tion programs. The CIAF is structured in five sequential and interdependent phases: Cognitive Diagnosis, Guided Plan- ning, Scientific Visualization, Active Learning, and Intelli- gent Assessment. Its implementation produced a reduction in the final failure rate from 14.1 to 3.6% and in the initial diagnostic failure rate from 42 to 21% over three consecutive academic years. The CIAF demonstrated efficacy, replicabil- ity, and contextual adaptability to the needs of pharmacology teaching in the Portuguese-speaking African context, with potential for transfer to other health sciences disciplines. Keywords active learning, artificial intelligence, educa- tional model, health education, pedagogical innovation, pharmacokinetics. Resumen La enseñanza de Farmacocinética y Farmacodi- námica es uno de los pilares del razonamiento clínico seguro en la formación en salud. Sin embargo, el predominio de mo- delos expositivos tradicionales y la ausencia de intervencio- nes contextualizadas en el aula generan de manera continua brechas cognitivas desalineadas en los estudiantes. Describir el proceso integrativo y las bases conceptuales teórico-meto- dológicas del CIAF, que constituye un modelo de enseñanza propio concebido a lo largo de tres años, en el contexto ango- lano de innovación educacional, a partir de esta estrategia de aula. Investigación cualitativa-descriptiva, basada en diseño (Design-Based Research), desarrollada en el contexto de la educación superior en salud en Angola (2023-2026), con 873 estudiantes de los programas de Enfermería y Nutrición. El CIAF posee componentes secuenciales e interdependientes organizados en cinco fases: Diagnóstico Cognitivo, Planifi- cación Orientada, Visualización Científica, Aprendizaje Ac- tivo y Evaluación Inteligente. Se obtuvo una reducción de la tasa final de reprobación del 14,1 al 3,6%, y de la tasa de fracaso en el diagnóstico inicial del 42 al 21% a lo largo de tres años académicos consecutivos. El CIAF demostró ser un modelo educacional exitoso en el África lusófona, trans- ferible a otras disciplinas del área de la salud y adaptado al contexto para la enseñanza de farmacología. Palabras clave aprendizaje activo, inteligencia artificial, modelo educacional, enseñanza en salud, innovación peda- gógica, farmacocinética. How to cite Guilbeaux, D. (2026). The Integrative Cycle of Pharmacological Learning (CIAF): description and validation of a pedagogical model for health pharmacology teaching. Journal of Advances in Education, Sciences and Humanities, 4(2), 10-14. https://doi.org/10.5281/zenodo.21854540 Faculdade de Ciências Médicas e da Saúde, Universidade Internacional do Cuanza, Cuito, Angola.

J. Adv. Educ. Sci. Humanit. (July - December 2026) 4(2): 10-14 11 Introduction The education of health professionals in the pharmacologi- cal sciences represents one of the greatest pedagogical cha- llenges in contemporary higher education (Omar & Barwick, 2026). Pharmacokinetics and pharmacodynamics, discipli- nes that underpin therapeutic rationality and patient safety, require students to integrate physiological, biochemical, ma- thematical, and clinical knowledge, a capacity that is rarely developed through traditional lecture-based methodologies (Rang et al., 2020). The World Health Organization (2024) estimates that approximately 50% of medication prescriptions and admi- nistrations worldwide involve some degree of irrational use, frequently associated with educational gaps in pharmacoki- netic principles. This finding gives the teaching of this disci- pline a dimension that extends beyond the academic sphere: it is a matter of public safety and institutional responsibility in the education of future professionals. In the Angolan context, where higher education in the health sciences is undergoing rapid expansion, the challen- ges are particularly significant. The heterogeneity of the student population, with classrooms comprising individuals ranging from 19 to 53 years of age and presenting diverse educational backgrounds, gaps in foundational knowledge in the exact and biological sciences, and the prevalence of teacher-centered pedagogical models systematically result in passive and decontextualized learning. Ausubel (2000) re- fers to this approach as rote or mechanical learning, in con- trast to meaningful learning, which is an essential condition for the development of safe clinical reasoning. The international literature consistently documents the be- nefits of active methodologies, pedagogical personalization, and the integration of educational technologies in health sciences education (Hattie, 2009; Mayer, 2009; Tomlinson, 2014). Nevertheless, the transfer of this evidence to Portu- guese-speaking African contexts remains limited, both be- cause of the scarcity of locally tested models and the lack of publications documenting systematically organized expe- riences within this geographical and linguistic setting. It is within this context that the Ciclo Integrativo de Apren- dizaje Farmacológico (CIAF), or Integrative Pharmacologi- cal Learning Cycle, emerged. The CIAF is an original pe- dagogical model developed and empirically validated over three consecutive academic years (2023–2026). It integrates cognitive assessment, personalized instruction, technolo- gy-mediated scientific visualization using Artificial Intelli- gence (AI), active methodologies, and continuous formative assessment. This article aimed to describe the development process and the theoretical and methodological foundations of the CIAF, documenting its five-phase structure, the theoretical frameworks that support it, and the quantitative results ob- served throughout the three-year implementation period. Its purpose is to provide a replicable model for pharmacology and health sciences educators working in similar contexts. Methodology This study adopted a Design-Based Research (DBR) approach, a methodological framework developed to inves- tigate educational interventions in real-world contexts and characterized by iteration, the integration of research and practice, and an orientation toward generating transferable principles (The Design-Based Research Collective, 2003). DBR combines scientific rigor with sensitivity to practical contexts, making it particularly suitable for developing and validating innovative pedagogical models under ecologica- lly valid conditions. The study was conducted through three iterative cycles co- rresponding to the 2023–2024, 2024–2025, and 2025–2026 academic years at a Faculty of Medical and Health Sciences in Cuito, Angola. A total of 873 students enrolled in Nursing and Nutrition programs participated in the study, with 361, 292, and 220 students in each respective academic year. Par- ticipants were divided into three age groups: 18–29 years, 30–39 years, and 40–55 years. During each cycle, the pe- dagogical model was implemented, evaluated, and refined based on the data collected, following a continuous impro- vement process that constitutes the methodological essence of DBR. Quantitative data were obtained from two sources: the ins- titutional academic management system for the 2023–2024 and 2024–2025 academic years, and the physical course re- cords for 2025–2026. Data collection instruments included a standardized initial diagnostic test administered on the first day of each academic year; regular and supplementary as- sessments conducted according to the institutional academic calendar; and records of attendance and students’ age and gender profiles. Data analysis followed a mixed-methods approach. Des- criptive statistics were used to analyze the quantitative data, including pass rates, failure rates, and diagnostic test failure rates by academic year and age group. Interpretive qualitati- ve analysis was used to document the pedagogical decisions made during each cycle and the process through which the model was refined. Triangulation of the quantitative and qua- litative dimensions strengthened the conclusions and made it possible to distinguish the effects of the model from those as- sociated with the demographic characteristics of the groups. The study was conducted in accordance with the ethical principles governing educational research. Data are presen- ted exclusively in aggregate form to preserve student anon- ymity, and the reported results refer to the collective perfor- mance of each group rather than to identifiable individual

J. Adv. Educ. Sci. Humanit. (July - December 2026) 4(2): 10-14 12 assessments. Results and discussion The Integrative Pharmacological Learning Cycle (CIAF) (Table 1) is a pedagogical model structured into five sequen- tial and interdependent phases, which form an intentional, adaptive, and student-centered learning cycle. The term “cy- cle” reflects the model’s iterative nature: the data generated in Phase 5—Intelligent Assessment—feed back into Phase 1—Cognitive Diagnosis—of the subsequent cycle, creating a continuous improvement system that self-regulates accor- ding to the actual profile of each group. Phase 1—Cognitive Diagnosis: This phase constitutes the essential starting point of the cycle. Before any pedagogical intervention, a standardized diagnostic test is administered to assess students’ mastery of the conceptual prerequisites: Cell Biology, Organic Chemistry, Anatomy, and Physiology. The results directly inform Phase 2, ensuring that personaliza- tion is based on evidence rather than assumptions. Over the three-year period, the diagnostic failure rate decreased from 42 to 21%, documenting the model’s progressive effect on students’ initial level of preparedness. Phase 2—Guided Planning: Based on the diagnostic re- sults, students are classified into three competency levels— basic, intermediate, and advanced—and differentiated lear- ning pathways are developed. This approach is directly aligned with concept of differentiated instruction (Tomlin- son, 2014): personalization is not a luxury but a measurable pedagogical necessity. In practice, differentiation is reflected in the selection of reading materials, the level of complexi- ty of clinical cases, and the pace of progression through the course content. Phase 3—Scientific Visualization: The inherently invisi- ble and dynamic nature of ADME processes constitutes the main cognitive obstacle in pharmacokinetics education. Pha- se 3 addresses this challenge through the use of AI-mediated visual resources, including dynamic infographics created with ChatGPT and Microsoft Copilot; instructor-developed educational videos with synthesized narration; interactive concentration–time curve simulators, such as WebPKS and the PK Visualization Tool; hyperrealistic images of physio- logical processes; and content organization through Note- bookLM. Mayer (2009) demonstrated that the intentional combination of text and images produces significantly grea- ter learning gains than verbal instruction alone. Phase 4—Active Learning: During this phase, students engage with real or simulated clinical cases that require the integrated application of the knowledge acquired in the pre- vious phases. The strategies employed include problem-ba- sed learning (PBL), therapeutic role-play, structured clinical debates involving collaborative problem-solving, and gami- fication activities incorporating applied pharmacokinetics. According to Bonwell and Eison (1991), active learning promotes greater retention, engagement, and transfer of knowledge to practical contexts, a premise supported by the performance data observed throughout the three-year period. Phase 5—Intelligent Assessment: Assessment within the CIAF is intended primarily to improve learning rather than to classify students (Black & Wiliam, 1998). The instru- ments used include adaptive quizzes with immediate feed- back, administered through Google Forms and ArchiMeds; AI-mediated progress analysis; and structured verbal syn- thesis activities in which students explain and integrate the content learned. The data generated during this phase inform the diagnosis of the subsequent cycle, thereby providing the CIAF with its adaptive dimension. The data reveal a consistent pattern of improvement (Table 2): the final failure rate decreased from 14.1 to 3.6%, repre- senting a relative reduction of 74.5% over the three-year pe- riod. The overall pass rate reached 96.4% in the 2025–2026 academic year, despite an increase in the proportion of stu- dents aged 40–55 years—historically the most challenging group in regular assessments—from 3.2 to 5.5% of the total cohort. This finding demonstrates the robustness and adap- tability of the model in addressing the actual diversity of the student population. Table 1. Structure of the Integrative Pharmacological Learning Cycle (CIAF) Phase Designation Theoretical Foundation Instruments/Strategies 1 Cognitive diagnosis Ausubel (2000): meaningful learning Standardized diagnostic test; analysis of students’ age and academic profiles 2 Guided planning Tomlinson (2014): differentiated instruction Competency-level grouping; differentiated learning pathways; personalized reading lists 3 Scientific visualization Mayer (2009): multimedia learning AI tools (ChatGPT, Copilot, and NotebookLM); infographics; instructor-created videos; ADME simulators 4 Active learning Freire (1996); Bonwell and Eison (1991) Clinical cases; problem-based learning (PBL); therapeutic role-play; structured clinical debates 5 Intelligent assessment Black and Wiliam (1998): assessment for learning Adaptive quizzes; automated feedback; student-led verbal synthesis

J. Adv. Educ. Sci. Humanit. (July - December 2026) 4(2): 10-14 13 Table 2. Evolution of academic performance by academic year (2023–2026) Academic Year Regular pass rate Overall pass rate Final failure rate / Change (pp) 2023–2024 (n = 361) 75.9 85.9 14.1 / — 2024–2025 (n = 292) 83.9 94.2 5.8 / +8.3 pp 2025–2026 (n = 220) 54.5 96.4 3.6 / +2.2 pp pp = percentage points. Source: Institutional academic management system and physical course records. A particularly significant result is the evolution of perfor- mance in the initial diagnostic assessment, as documented in Table 3. Table 3. Evolution of the failure rate in the initial diagnos- tic assessment (2023–2026) Academic year Initial diagnostic failure rate Change 2023–2024 42 — 2024–2025 34 −8 pp 2025–2026 21 −13 pp Source: Course diagnostic assessment records. The 21-percentage-point reduction in the initial diagnostic failure rate suggests a positive feedback effect of the model: as the CIAF was implemented and its strategies were disse- minated among faculty members, students entered the cour- se progressively better prepared. This spillover effect, which extends beyond the classroom and influences earlier stages of training, represents one of the most relevant and unexpec- ted findings of the study, with implications for institutional curriculum management. A distinctive feature of the CIAF is the gradual and inten- tional integration of educational technologies throughout the three years of implementation. During the first year (2023– 2024), the interventions focused on pedagogical persona- lization and the adoption of static visual resources. In the second year (2024–2025), systematically organized external ICT resources were introduced, including Khan Academy, Osmosis, internationally recognized educational videos, and digital simulators of pharmacokinetic curves. In the third year (2025–2026), AI became a central pedagogical tool: ChatGPT was used to create infographics and personalized clinical cases; NotebookLM supported content synthesis and organization; Microsoft Copilot facilitated real-time scienti- fic research; and AI-based video and image generators were used to produce original teaching materials aligned with the specific difficulties identified through the diagnostic assess- ment. This progression was not arbitrary; it was guided by the continuous assessment of students’ needs and the systematic evaluation of the impact of each technology introduced. The result was a qualitative transformation of the teaching mate- rials, which became more visual, contextualized, and subs- tantially more motivating—factors that Mayer (2009) identi- fies as essential to the effectiveness of multimedia learning. Conclusions This article described the development and theoretical-me- thodological foundations of the Integrative Pharmacological Learning Cycle (CIAF), an original pedagogical model im- plemented over three consecutive academic years with 873 health sciences students in Angola. The results indicate that the CIAF is an effective, adaptable, and potentially replica- ble response to the challenges of teaching pharmacology in heterogeneous student populations, as reflected in the reduc- tion of the final failure rate from 14.1 to 3.6%. Its main con- tributions include the integration of diagnosis, personaliza- tion, scientific visualization, active learning, and formative assessment into a continuous cycle; the practical incorpora- tion of artificial intelligence into pharmacology education; and the development of a model that may be transferred to other health sciences disciplines and comparable educational contexts. Although the absence of a control group and the non-experimental design limit causal interpretation, future experimental or quasi-experimental studies could assess its effectiveness in other institutions. Overall, the CIAF does not seek to replace teachers but to strengthen their pedagogi- cal practice by making abstract concepts more understanda- ble, clinically relevant, and actively constructed by students. References Ausubel, D. P. (2000). The acquisition and retention of knowledge: a cognitive view. Kluwer Academic Publi- shers. Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education, 5(1), 7-74. https:// doi.org/10.1080/0969595980050102 Bonwell, C. C., & Eison, J. A. (1991). Active learning: crea- ting excitement in the classroom. George Washington University. Freire, P. (1996). Pedagogia da autonomia: saberes necessá- rios à prática educativa. Paz e Terra. Hattie, J. (2009). Visible learning: a synthesis of over 800 meta-analyses relating to achievement. Routledge. Mayer, R. E. (2009). Multimedia learning (2nd ed.). Cambri- dge University Press. Omar, S. H., & Barwick, A. (2026). International Bench- marking of Pharmacology Curricula and Prescribing

J. Adv. Educ. Sci. Humanit. (July - December 2026) 4(2): 10-14 14 Related Learning Outcomes, Implications for Austra- lian Health Professional Education: A Systematic Re- view and Meta-Analysis. Pharmacy, 14(1), 27. https:// doi.org/10.3390/pharmacy14010027 Rang, H. P., Dale, M. M., & Ritter, J. M. (2020). Rang & Dale’s pharmacology (9th ed.). Elsevier. The Design-Based Research Collective. (2003). Design-ba- sed research: an emerging paradigm for educational in- quiry. Educational Researcher, 32(1), 5-8. Tomlinson, C. A. (2014). The differentiated classroom: res- ponding to the needs of all learners (2nd ed.). ASCD. World Health Organization. (2024). Medication without harm: Policy brief. https://www.who.int/publications/i/ item/9789240062764 Conflicts of interest The authors declares that she has no conflict of interest. Author contributions Daryanis Guilbeaux: Conceptualization, formal analysis, research, methodology, writing the original draft, writing, review and editing. Data availability statement The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Statement on the use of AI The author acknowledges the use of generative AI and AI-assisted technologies to improve the readability and cla- rity of the article. Disclaimer/Editor’s note The statements, opinions, and data contained in all publi- cations are solely those of the individual authors and contri- butors and not of Journal of Advances Education, Sciences and Humanities. Journal of Advances Education, Sciences and Humanities and/or the editors disclaim any responsibility for any injury to people or property resulting from any ideas, methods, ins- tructions, or products mentioned in the content.