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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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Adding an interdisciplinary quantitative component to the biology curriculum did not adversely affect performance of first-year students on assessment questions. During a unit on the use of microarrays in biological research, biology students were given practice problems in which they focused on the broader concept of microarrays and their interpretation (passive math) or analyzed microarray data themselves by performing statistical computations (active math). Student performance on biological concepts and data interpretation was assessed twice within 2 wk. The first set of assessment questions was a stand-alone quiz, whereas the second set was integrated into a comprehensive final examination. Data presented in this figure represent the pooled data shown in Table 2. Using a two-sided t test there was no significant difference between how well the two groups performed on the quiz questions (t = 0.828, p = 0.409) or on the final examination questions (t = −0.213, p = 0.832). The results suggest that adding an intensive quantitative component did not negatively impact the students’ ability to interpret data in a biological context. Decreased retention of the material between the quiz and the final as measured by paired t tests was significant for both groups (p < 0.001). N: passive math = 78, active math = 81. Values on the Y axis represent percentages out of 25 points. Error bars indicate SD.
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Figure 3: Adding an interdisciplinary quantitative component to the biology curriculum did not adversely affect performance of first-year students on assessment questions. During a unit on the use of microarrays in biological research, biology students were given practice problems in which they focused on the broader concept of microarrays and their interpretation (passive math) or analyzed microarray data themselves by performing statistical computations (active math). Student performance on biological concepts and data interpretation was assessed twice within 2 wk. The first set of assessment questions was a stand-alone quiz, whereas the second set was integrated into a comprehensive final examination. Data presented in this figure represent the pooled data shown in Table 2. Using a two-sided t test there was no significant difference between how well the two groups performed on the quiz questions (t = 0.828, p = 0.409) or on the final examination questions (t = −0.213, p = 0.832). The results suggest that adding an intensive quantitative component did not negatively impact the students’ ability to interpret data in a biological context. Decreased retention of the material between the quiz and the final as measured by paired t tests was significant for both groups (p < 0.001). N: passive math = 78, active math = 81. Values on the Y axis represent percentages out of 25 points. Error bars indicate SD.

Mentions: Results for first-year students enrolled in an introductory biology course showed no significant difference between how well the passive math group and the active math group performed on the first set of assessment questions that was presented as a stand-alone quiz. This result held when each of the four sections was examined individually (Table 2) and when the data were pooled (Figure 3; unpaired t tests, p > 0.05 for all). We also compared the scores of the two groups on the second set of questions that were embedded in their comprehensive final examination. Again, the passive math group and the active math group performed equally well on these questions (Table 2, Figure 3; unpaired t tests, p > 0.05). Taken together, these results indicate that both groups understood equally well the meaning of the statistical results in the context of the biological concepts presented in the unit, even though the take-home assignment of the active math group emphasized quantitative tasks as opposed to passive interpretation of the results.


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)

Adding an interdisciplinary quantitative component to the biology curriculum did not adversely affect performance of first-year students on assessment questions. During a unit on the use of microarrays in biological research, biology students were given practice problems in which they focused on the broader concept of microarrays and their interpretation (passive math) or analyzed microarray data themselves by performing statistical computations (active math). Student performance on biological concepts and data interpretation was assessed twice within 2 wk. The first set of assessment questions was a stand-alone quiz, whereas the second set was integrated into a comprehensive final examination. Data presented in this figure represent the pooled data shown in Table 2. Using a two-sided t test there was no significant difference between how well the two groups performed on the quiz questions (t = 0.828, p = 0.409) or on the final examination questions (t = −0.213, p = 0.832). The results suggest that adding an intensive quantitative component did not negatively impact the students’ ability to interpret data in a biological context. Decreased retention of the material between the quiz and the final as measured by paired t tests was significant for both groups (p < 0.001). N: passive math = 78, active math = 81. Values on the Y axis represent percentages out of 25 points. Error bars indicate SD.
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Related In: Results  -  Collection

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Figure 3: Adding an interdisciplinary quantitative component to the biology curriculum did not adversely affect performance of first-year students on assessment questions. During a unit on the use of microarrays in biological research, biology students were given practice problems in which they focused on the broader concept of microarrays and their interpretation (passive math) or analyzed microarray data themselves by performing statistical computations (active math). Student performance on biological concepts and data interpretation was assessed twice within 2 wk. The first set of assessment questions was a stand-alone quiz, whereas the second set was integrated into a comprehensive final examination. Data presented in this figure represent the pooled data shown in Table 2. Using a two-sided t test there was no significant difference between how well the two groups performed on the quiz questions (t = 0.828, p = 0.409) or on the final examination questions (t = −0.213, p = 0.832). The results suggest that adding an intensive quantitative component did not negatively impact the students’ ability to interpret data in a biological context. Decreased retention of the material between the quiz and the final as measured by paired t tests was significant for both groups (p < 0.001). N: passive math = 78, active math = 81. Values on the Y axis represent percentages out of 25 points. Error bars indicate SD.
Mentions: Results for first-year students enrolled in an introductory biology course showed no significant difference between how well the passive math group and the active math group performed on the first set of assessment questions that was presented as a stand-alone quiz. This result held when each of the four sections was examined individually (Table 2) and when the data were pooled (Figure 3; unpaired t tests, p > 0.05 for all). We also compared the scores of the two groups on the second set of questions that were embedded in their comprehensive final examination. Again, the passive math group and the active math group performed equally well on these questions (Table 2, Figure 3; unpaired t tests, p > 0.05). Taken together, these results indicate that both groups understood equally well the meaning of the statistical results in the context of the biological concepts presented in the unit, even though the take-home assignment of the active math group emphasized quantitative tasks as opposed to passive interpretation of the results.

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