<![CDATA[The dominance of lecture-based instruction in biology learning limits students’ ability to relate concepts to real-life phenomena, interpret graphical or tabular data, and construct scientific arguments, resulting in low cognitive achievement and inadequate science literacy. This study aims to examine the effect of a Deep Learning-based Problem-Based Learning (PBL) model on students’ cognitive learning outcomes and science literacy. A quantitative, quasi-experimental design was employed, involving an experimental and a control class selected via simple random sampling. Data were collected using pretest-posttest instruments and analyzed using descriptive statistics and the Independent Samples T Test. The results showed that the experimental class achieved higher average posttest scores for cognitive learning outcomes (60.86 vs. 56.33) and science literacy (72.25 vs. 68.67) compared to the control class. Hypothesis testing confirmed that the Deep Learning-oriented PBL model significantly influenced cognitive learning outcomes (t = −7.577; p = 0.000 < 0.05) and science literacy (t = −8.391; p = 0.000 < 0.05). These findings indicate that the Deep Learning-oriented PBL model is more effective than the Deep Learning-oriented Direct Instruction model in developing students’ cognitive learning outcomes and science literacy in 21st-century biology education.]]>
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