An official website of the United States government
Student experiences learning chemistry have been well studied in chemistry courses but less so in biology courses. Chemistry concepts are foundational to introductory biology courses, and student experiences learning chemistry concepts may impact their overall course experiences and subsequent student outcomes. In this study, we asked undergraduate students enrolled in introductory biology courses at a public R1 institution an open-response question asking how their experiences learning chemistry topics affected their identities as biologists. We used thematic analysis to identify common ideas in their responses. We found that while almost half of student respondents cited learning chemistry as having positive impacts on their experiences learning biology, students who struggled with chemistry topics were significantly more likely to have negative experiences learning biology. We also found significant relationships between prior chemistry preparation, student background, and the likelihood of students struggling with chemistry and negative experiences learning biology. These findings emphasize the impact of learning specific content on student psychosocial metrics and suggest areas for biology educators to focus on to support learning and alleviate student stress in introductory biology.
more »
« less
“Big Ideas” of Introductory Chemistry and Biology Courses and the Connections between Them
Introductory courses are often designed to cover a range of topics with the intent to offer students exposure to the given discipline as preparation to further their study in the same or related disciplines. Unfortunately, students in these courses are often presented with an overwhelming amount of information that may not support their formation of a usable coherent network of knowledge. In this study we conducted a mixed-method sequential exploratory study with students co-enrolled in General Chemistry II and Introductory Biology I to better understand what students perceived to be the “take-home” messages of these courses (i.e., core ideas) and the connections between these courses. We found that students identified a range of ideas from both courses; further analysis of students’ explanations and reasoning revealed that, when students talked about their chemistry ideas, they were more likely to talk about them as having predictive and explanatory power in comparison with reasons provided for their biology big ideas. Furthermore, students identified a number of overlapping ideas between their chemistry and biology courses, such as interactions, reactions, and structures, which have the potential to be used as a starting place to support students building a more coherent network of knowledge.
more »
« less
- PAR ID:
- 10349999
- Editor(s):
- Loertscher, Jennifer
- Date Published:
- Journal Name:
- CBE—Life Sciences Education
- Volume:
- 21
- Issue:
- 2
- ISSN:
- 1931-7913
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Thinking about knowledge and knowing (i.e., epistemic cognition) is an important part of student learning and has implications for how they apply their knowledge in future courses, careers, and other aspects of their lives. Three classes of models have emerged from research on epistemic cognition: developmental models, dimensional models, and resources models. These models can be distinguished by how value is assigned to particular epistemic ideas (hierarchy), how consistent epistemic ideas are across time and/or context (stability), and the degree to which people are consciously aware of their own epistemic ideas (explicitness). To determine the extent to which these models inform research on epistemic cognition in chemistry education specifically, we reviewed 54 articles on undergraduate chemistry students’ epistemologies. First, we sought to describe the articles in terms of the courses and unit of study sampled, the methods and study designs implemented, and the means of data collection utilized. We found that most studies focused on the epistemic cognition of individual students enrolled in introductory chemistry courses. The majority were qualitative and employed exploratory or quasi-experimental designs, but a variety of data collection methods were represented. We then coded each article for how it treated epistemic cognition in terms of hierarchy, stability, and explicitness. The overwhelming majority of articles performed a hierarchical analysis of students’ epistemic ideas. An equal number of articles treated epistemic cognition as stableversusunstable across time and/or context. Likewise, about half of the studies asked students directly about their epistemic cognition while approximately half of the studies inferred it from students’ responses, course observations, or written artifacts. These codes were then used to infer the models of epistemic cognition underlying these studies. Eighteen studies were mostly consistent with a developmental or dimensional model, ten were mostly aligned with a resources model, and twenty-six did not provide enough information to reasonably infer a model. We advocate for considering how models of epistemic cognition—and their assumptions about hierarchy, stability, and explicitness—influence the design of studies on students’ epistemic cognition and the conclusions that can be reasonably drawn from them.more » « less
-
Learning standards for biology courses have called for increasing statistics content. Little is known, however, about biology students’ attitudes towards statistics content and what students actually learn about statistics in these courses. This study aims to uncover changes in attitudes and content knowledge in statistics for students in biology courses. One hundred thirty-four introductory biology students across five different instructors participated in a pre-post study of statistical thinking and attitudes toward statistics. Students performed better on the statistics conceptual inventory at the end of a biology course compared to the beginning. Student attitudes showed no change. These preliminary results suggest the potential importance for laying a conceptual foundation in statistics prior to taking biology courses with little formal statistical instruction.more » « less
-
Wright, L Kate (Ed.)ABSTRACT Quantitative reasoning is a critical skill in biology and has been highlighted as a core competency byVision and Change. Despite its importance, students often struggle to apply mathematical skills in new contexts in biology, a process called transfer of knowledge. However, the supports and barriers that students perceive for this process remain unclear. To explore this further, we interviewed undergraduate students in an introductory biology lab course about how they understand and report the transfer of quantitative skills in these courses. We then applied these themes to the Step Back, Translate, and Extend (SBTE) framework to examine student perceptions of the supports and barriers to their knowledge transfer. Students reported different supports and barriers at each level of the transfer process. At the first step of the framework, the recognition level, students reported reflecting on previous chemistry, statistics, and physics learning as helpful cues to indicate a transfer opportunity. Others, however, reported perceiving math and science as separate subjects without overlap, causing a disconnect in their recognition of transferable knowledge. In the second level of the framework, students recall previous learning. Students reported repetition and positive dispositions toward science and math as supportive factors. In contrast, gaps of time between initial learning and new contexts and negative dispositions hindered recall ability. The final level of the SBTE framework focuses on application. Students reported being better able to apply previous learning to new contexts in the biology lab when they could relate their applied skills to “real-world” applications, external motivating factors, and future career goals. These students also reported proactively seeking outside resources to fill gaps in their understanding. Generating data in a lab setting was also mentioned by students as both a supportive factor of application when they felt confident in their answers and a hindrance to application when they felt unsure about its accuracy.more » « less
-
Computational thinking is identified as one of the “essential skills for 21st-Century students.” [1] Studies of CT in school programs are being funded by many organizations, including the United States National Science Foundation. In this paper, we describe “lessons learned” over the first two years of a research program (PREDICTS: Principles and Resources for Educators to Infuse Computational Thinking in the Sciences) with the goal of developing knowledge of how to integrate CT into introductory high school biology and chemistry classes for all students. Using curricular modules developed by program staff, two in biology and two in chemistry, teachers piloting the program engaged students in CT with computational evidence from authentic tools in order to develop understanding of science concepts. Each module, representing about a week of instruction, addresses science ideas in the prescribed course of study for high school programs. Project researchers have collected survey data on teachers’: (1) beliefs about effective science teaching; (2) beliefs about their effectiveness as a science teacher and their students’ ability to learn science, and; (3) content preparedness. In addition, we observed module implementation, collected and analyzed student artifacts, and interviewed teachers at the conclusion of module implementation. Preliminary results indicated some challenges (access to technology, varying levels of experience among students) and cause for optimism (student and teacher engagement in CT and the computational tools used in the modules). Continuing research efforts are described in this paper, along with descriptions of the curricular modules and the use of observations and “CT check-ins” to assess student engagement in, application of, and learning of CT.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1187/cbe.21-10-0301
