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transmission-based model persists, focused on the teacher and content (Flórez, 1999). Other
teachers, lacking training in the area, prioritize quantitative assessments, neglecting didactic as-
pects. Competency-based models seek to develop investigative skills through exploration and
practice (Inf. 2), while constructivism promotes direct experimentation to stimulate curiosity and
autonomy (Inf. 3).
On the other hand, teachers must assume a "mediator role" (Vygotsky, 2009; Tebar, 2009), fos-
tering autonomy and meaningful learning through practical activities (Inf. 3). While some adopt
a traditional approach based on memorization and behavioral assessment (Flórez, 1999; Novak
& Gowin, 1988), others promote constructivism by facilitating investigative experiences (labs,
projects) that develop scientific skills (Dewey, 1960). Discovery learning requires students to ac-
tively select and analyze information (Novak & Gowin, 1988), while teachers guide through for-
mative assessment and key questions for meaningful learning.
The use of innovative pedagogical strategies, such as artificial intelligence (AI), fosters scientific
and investigative skills through active and personalized learning (Inf. 4). AI enables simulations
and data analysis, promoting critical thinking and interdisciplinarity. Other techniques include:
(a) Brainstorming (Cirigliano & Villaverde, 1981; Pimienta, 2008), which stimulates creativity
through free and structured ideas. (b) Oral presentations (Castro, 2017), where students organize
and communicate scientific knowledge. (c) Group discussions (Cirigliano & Villaverde, 1981), fa-
cilitating idea exchange in a collaborative environment. (d) Question formulation (Inf. 6), key to
developing critical thinking and scientific inquiry. (e) Problem-solving (Inf. 4), applying theoretical
knowledge in real contexts. (f) Conversational forums (Centro de Investigaciones y Servicios
Educativos, n.d.), promoting reflective dialogue. (g) Debates (Cirigliano & Villaverde, 1981; Pi-
mienta, 2008), encouraging argumentation and participation (Inf. 4, 5, and 6).
Regarding the axial category of learning assessment in natural sciences, this adopts a formative
and process-oriented character, allowing teachers to identify deviations and adjust pedagogical
strategies (Flórez, 1999; Amengual, 1989).
Formative assessment, highlighted in teacher testimonies (Inf. 5 and 6), provides real-time feed-
back, facilitating continuous improvement. Stefflebeam (1987) emphasizes its role as a guide
for decision-making, while summative assessment (Camilloni, 1998) certifies learning achieve-
ments and scientific competencies, integrating hypothesis formulation, experimentation, and
analysis (Inf. 5).
Process-oriented assessment (Alves y Acevedo, 1999) evaluates performance, attitude, and
achievement (Estévez, 2000), transcending final results. Techniques such as observation (anec-
dotal records, rating scales) allow assessment of practical and collaborative skills (Inf. 2, 4 and
6), though they require careful implementation to avoid subjective biases. Instruments like des-
criptive journals (Inf. 5) and checklists optimize objectivity.
On the other hand, from an integrative framework and by way of synthesis, it is proposed that