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.