Paired Multiple-Choice Questions Reveal Students' Incomplete Statistical Thinking about Variation during Data...

Area of Science:

• Biology Education Research
• Quantitative Biology

Background:

• Understanding biological variability is crucial for data analysis and drawing valid conclusions in biology.
• Students often face challenges in applying quantitative concepts of variation during statistical analysis.
• Accurate statistical interpretation is essential for scientific reasoning and evidence-based conclusions.

Purpose of the Study:

• To assess introductory biology students' understanding of quantitative concepts related to biological variation.
• To identify specific areas where students struggle in statistically analyzing variation.
• To inform pedagogical approaches for improving students' quantitative reasoning skills in biology.

Main Methods:

• Quantitative and qualitative analyses were performed on student responses to multiple-choice questions.
• The questions targeted two key concepts in the quantitative analysis of variation.
• Student performance was analyzed based on identifying mathematical expressions and interpreting statistical values.

Main Results:

• More students correctly identified mathematical expressions of variation than correctly interpreted them.
• Students were more successful in interpreting nonsignificant p-values with small sample sizes than large ones.
• A significant portion of students demonstrated an incomplete grasp of quantitative variation concepts.

Conclusions:

• Introductory biology students exhibit deficits in quantitatively understanding and interpreting biological variation.
• Instruction should prioritize conceptual understanding of variation over procedural problem-solving to enhance learning.
• Targeted interventions focusing on statistical reasoning are needed to improve students' quantitative skills.