Knowledge-centered environments provide numerous of ways to comprehend
knowledge, as well as acquire problem-solving skills. Educators need to promote
literacy in the classroom. Students
have to be literate (able to understand, utilize and comprehend the subject’s
language) to create, communicate and compute with others. Math and science have
jargon and symbols that differ from the English language. For example,
mathematical and scientific literacy consists of mathematical & scientific knowledge,
methods, and processes applied in various contexts in metacognitive ways. In
order for that to happen, students need to follow the math and science proficiencies. The math proficiencies have five
components: conceptual understanding (comprehension of concepts, operations,
and relations), procedural fluency (carrying out procedures efficiently and
appropriately), strategic competence (formulating, representing, and solving
problems), adaptive reasoning (capacity for logical thought and reflection),
and productive disposition (seeing math as meaningful). The science
proficiencies are similar except its problems are not always computational;
they do not include procedural fluency and emphasizes more on scientific
explanations of the world. Although reading
strategies seem only useful in English class, they can be used in any
subject, especially math and science to teach students text comprehension. They
can increase students’ conceptual understanding of math and science. Once
students obtain the necessary information, they need a method. Fortunately,
there are student-driven approaches to solve a problem. One example is modeling, which involves either a
teacher demonstration (scaffolding) or a visual representation of the problem.
A specific case is a model eliciting
activity (MEA). MEAs pose as open-ended problems and challenge students to
build models in order to solve complex, real-world problems. MEAs encourage
students to invent and test models, which makes their thinking visible.  Another problem solving method is anchored instruction (AI). Like MEA, it
is a form of context-based learning designed to encourage students and teachers
to pose and solve realistic problems. Inquiry
differs from the rest because it is an active learning process in which students answer research
questions through actual data analysis. Inquiry instruction involves students in a form of
active learning that emphasizes questioning, data analysis, and critical
thinking. Another form of inquiry is argument-driven
inquiry (ADI). It attempts to develop an argument that provides and
supports an explanation for the research question using claim, evidence, and reasoning (CER). CER helps students learn how to determine if available data are relevant,
sufficient, and convincing enough to support their claims. Overall, a
knowledge-centered environment builds a strong foundational structure for
students to further their learning.