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A study assessing the potential of negative effects in interdisciplinary math-biology instruction.

Madlung A, Bremer M, Himelblau E, Tullis A - CBE Life Sci Educ (2011)

Bottom Line: We have developed and assessed an integrative learning module and found disciplinary learning gains to be equally strong in first-year students who actively engaged in embedded quantitative calculations as in those students who were merely presented with quantitative data in the context of interpreting biological and biostatistical results.When presented to advanced biology students, our quantitative learning tool increased test performance significantly.We conclude from our study that the addition of mathematical calculations to the first year and advanced biology curricula did not hinder overall student learning, and may increase disciplinary learning and data interpretation skills in advanced students.

View Article: PubMed Central - PubMed

Affiliation: Biological Science, California Polytechnic State University, San Luis Obispo, CA 93407, USA. amadlung@pugetsound.edu

ABSTRACT
There is increasing enthusiasm for teaching approaches that combine mathematics and biology. The call for integrating more quantitative work in biology education has led to new teaching tools that improve quantitative skills. Little is known, however, about whether increasing interdisciplinary work can lead to adverse effects, such as the development of broader but shallower skills or the possibility that math anxiety causes some students to disengage in the classroom, or, paradoxically, to focus so much on the mathematics that they lose sight of its application for the biological concepts in the center of the unit at hand. We have developed and assessed an integrative learning module and found disciplinary learning gains to be equally strong in first-year students who actively engaged in embedded quantitative calculations as in those students who were merely presented with quantitative data in the context of interpreting biological and biostatistical results. When presented to advanced biology students, our quantitative learning tool increased test performance significantly. We conclude from our study that the addition of mathematical calculations to the first year and advanced biology curricula did not hinder overall student learning, and may increase disciplinary learning and data interpretation skills in advanced students.

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An interdisciplinary computer module requiring students to calculate statistical problems by hand was an effective learning tool for advanced students. Students in an upper-level Plant Molecular Biology course were asked to perform statistical computations in a lab exercise after a lecture introduction to microarray analysis. They were tested on their overall understanding of the biological implications of microarray work before and after the exercise. Data represent the pooled data shown in Table 3. Results suggest that the assignment helped students effectively apply statistical data to interpret biological results and concepts. N = 27, p < 0.05 for a two-sided, paired t test. Values on the Y axis represent percentages out of 35 points. Error bars indicate SD.
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Figure 4: An interdisciplinary computer module requiring students to calculate statistical problems by hand was an effective learning tool for advanced students. Students in an upper-level Plant Molecular Biology course were asked to perform statistical computations in a lab exercise after a lecture introduction to microarray analysis. They were tested on their overall understanding of the biological implications of microarray work before and after the exercise. Data represent the pooled data shown in Table 3. Results suggest that the assignment helped students effectively apply statistical data to interpret biological results and concepts. N = 27, p < 0.05 for a two-sided, paired t test. Values on the Y axis represent percentages out of 35 points. Error bars indicate SD.

Mentions: We used a pre- and postassignment testing strategy as our experimental design to test if adding substantial mathematical and statistical computations negatively impacted the ability of advanced students to interpret biostatistical test results and understand the underlying biological concepts. This design was chosen because the small class sizes precluded us from splitting the sections into treatment and control groups. Thus, unlike our experiment with first-year students, knowledge of the advanced students was assessed before and after the assignment. As with the first-year students, assessment questions focused on biological concepts underlying microarray technology and the biological meaning of the statistical results (Figure 2). When classes were analyzed separately, two of the three classes showed significantly higher scores following the assignment (Table 3; paired t tests, df = 11, 7, and 6, respectively; 2 of 3 yr with p < 0.05). When the results of the 3 yr were pooled to generate a larger sample size, the results of our analysis suggested that the assignment significantly improved performance on the assessment questions (Figure 4; paired t test; df = 26, p < 0.05). Specifically, the combined scores of all three classes increased by 7.9% (Figure 4). These results suggest that experience and practice with computations increased the ability of advanced students to use statistics as a way to better understand biological results and concepts.


A study assessing the potential of negative effects in interdisciplinary math-biology instruction.

Madlung A, Bremer M, Himelblau E, Tullis A - CBE Life Sci Educ (2011)

An interdisciplinary computer module requiring students to calculate statistical problems by hand was an effective learning tool for advanced students. Students in an upper-level Plant Molecular Biology course were asked to perform statistical computations in a lab exercise after a lecture introduction to microarray analysis. They were tested on their overall understanding of the biological implications of microarray work before and after the exercise. Data represent the pooled data shown in Table 3. Results suggest that the assignment helped students effectively apply statistical data to interpret biological results and concepts. N = 27, p < 0.05 for a two-sided, paired t test. Values on the Y axis represent percentages out of 35 points. Error bars indicate SD.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3046887&req=5

Figure 4: An interdisciplinary computer module requiring students to calculate statistical problems by hand was an effective learning tool for advanced students. Students in an upper-level Plant Molecular Biology course were asked to perform statistical computations in a lab exercise after a lecture introduction to microarray analysis. They were tested on their overall understanding of the biological implications of microarray work before and after the exercise. Data represent the pooled data shown in Table 3. Results suggest that the assignment helped students effectively apply statistical data to interpret biological results and concepts. N = 27, p < 0.05 for a two-sided, paired t test. Values on the Y axis represent percentages out of 35 points. Error bars indicate SD.
Mentions: We used a pre- and postassignment testing strategy as our experimental design to test if adding substantial mathematical and statistical computations negatively impacted the ability of advanced students to interpret biostatistical test results and understand the underlying biological concepts. This design was chosen because the small class sizes precluded us from splitting the sections into treatment and control groups. Thus, unlike our experiment with first-year students, knowledge of the advanced students was assessed before and after the assignment. As with the first-year students, assessment questions focused on biological concepts underlying microarray technology and the biological meaning of the statistical results (Figure 2). When classes were analyzed separately, two of the three classes showed significantly higher scores following the assignment (Table 3; paired t tests, df = 11, 7, and 6, respectively; 2 of 3 yr with p < 0.05). When the results of the 3 yr were pooled to generate a larger sample size, the results of our analysis suggested that the assignment significantly improved performance on the assessment questions (Figure 4; paired t test; df = 26, p < 0.05). Specifically, the combined scores of all three classes increased by 7.9% (Figure 4). These results suggest that experience and practice with computations increased the ability of advanced students to use statistics as a way to better understand biological results and concepts.

Bottom Line: We have developed and assessed an integrative learning module and found disciplinary learning gains to be equally strong in first-year students who actively engaged in embedded quantitative calculations as in those students who were merely presented with quantitative data in the context of interpreting biological and biostatistical results.When presented to advanced biology students, our quantitative learning tool increased test performance significantly.We conclude from our study that the addition of mathematical calculations to the first year and advanced biology curricula did not hinder overall student learning, and may increase disciplinary learning and data interpretation skills in advanced students.

View Article: PubMed Central - PubMed

Affiliation: Biological Science, California Polytechnic State University, San Luis Obispo, CA 93407, USA. amadlung@pugetsound.edu

ABSTRACT
There is increasing enthusiasm for teaching approaches that combine mathematics and biology. The call for integrating more quantitative work in biology education has led to new teaching tools that improve quantitative skills. Little is known, however, about whether increasing interdisciplinary work can lead to adverse effects, such as the development of broader but shallower skills or the possibility that math anxiety causes some students to disengage in the classroom, or, paradoxically, to focus so much on the mathematics that they lose sight of its application for the biological concepts in the center of the unit at hand. We have developed and assessed an integrative learning module and found disciplinary learning gains to be equally strong in first-year students who actively engaged in embedded quantitative calculations as in those students who were merely presented with quantitative data in the context of interpreting biological and biostatistical results. When presented to advanced biology students, our quantitative learning tool increased test performance significantly. We conclude from our study that the addition of mathematical calculations to the first year and advanced biology curricula did not hinder overall student learning, and may increase disciplinary learning and data interpretation skills in advanced students.

Show MeSH