Designs in Action 

 Taylor, M. F. (2010). Making Biology Teaching More “Graphic”. The American Biology Teacher, 72(9), 568-571. In this short “how-to” essay, the author describes the step-wise general classroom approach taken to introduce the concept of variables and correlations as they pertain to relational line graphs. A hypothetical experiment with data on investigating the effect of light intensity on plant growth rate is presented and can be used as an example when teaching students how to create a graph and interpret the take-home message. The essay also provides advice on how to teach college students about positive and negative correlations and upon mastery, how to transfer this knowledge to positive and negative feedback loops. An example is provided on how to graphically teach negative feedback control as students are asked to predict how the duration of exercise affects a person’s blood glucose. In a sample discussion, the author explains how to help students think in terms of variables through multiple graph displays representing data relationships (e.g., insulin levels in response to glucose absorption) relevant to the situating problem. Although the context of this manuscript is largely focused on physiology, the author recommends teaching relational graphing in ecology (e.g. understand the effect of nutrient runoff up the food chain in a lake) or any sub-discipline where students have to make sense of large number of variables and how each variable impacts other variables.

Bray Speth E., Momsen, J.L., Moyerbrailean, G.A., Ebert-May, D., Long, T.M., Wyse, S.A. & Linton, D. (2010). 1, 2, 3, 4: Infusing quantitative literacy into introductory biology. CBE-Life Sciences Education 9: 323-332. This article explores how a team of instructors infused quantitative concepts within the existing framework (course content and learning objectives) of a large-scale introductory biology course to develop students’ quantitative literacy (QL) skills. Using a learner-centered instructional approach, students participated in quantitative thinking with biological scenarios throughout the term including: iterative assessments to test QL skills were regularly designed and administered as part of normal course activities (e.g., in-class work, homework, quizzes) allowing instruction to be tailored to the students’ needs and abilities. Pre- and post-semester performance tasks grounded in problems drawn from real-world biological research were used to evaluate students’ ability to represent data graphically and articulate data-driven arguments. Baseline data indicated introductory students had difficulties upon entering the class with representing data on a graph, properly labeling the graph axes, and formulating complete and correct data-based claims with appropriate reasoning – which the authors argue lends further evidence to the need for practice of quantitative skills in college science. Comparative analysis of the pre/post assessments found that students made significant gains in their ability to graphically represent numerical data during the course. The authors conclude that it is feasible to incorporate QL concepts in the context of an existing course to help students develop quantitative skills, and offer recommendations to other instructors on how to infuse the learning of quantitative skills into their courses. The article’s method section includes the performance tasks and associated rubrics as well as employed teaching modules that can be adopted or used as examples to construct quantitatively based teaching activities or assessments.

 Picone, C., Rhode, J., Hyatt, L., & Parshall, T. (2007). Assessing gains in undergraduate students’ abilities to analyze graphical data. Teaching Issues and Experiments in Ecology, 5(July), 1-54. This study examined the impact of activities designed and integrated into introductory ecology and environmental science courses on students’ data analysis and graphing abilities at four institutions. Teaching activities to train students how to interpret ecological data were developed to engage students in collaborative, active learning practices and incorporated several evidence-based strategies for teaching data skills, including: the “Step-One, Step-Two” approach of graph interpretation, requiring graphs to be sketched by hand prior to plotting data using visualization software, and introducing course content through data-driven exercises focused on real-world scientific problems. Students (n=240) completed assessments at the onset, during, and end of the term developed by the authors to measure whether the activities in the courses improved participants’ abilities to create and interpret graphs. Differences in pre-post test data indicated student gains in the interpretation of simple bar graphs and scatterplots as well as their ability to construct graphs from raw data. Persisting graphing difficulties were also documented via the performance measures as students showed smaller gains in their skills in identifying independent and dependent variables, detecting trends in data with variation, and interpreting interactions among variables in complex graphs which the authors then identify as challenges for instructors to focus on in the development of analytical skills. The article includes an unvalidated scenario-based assessment tool designed for the study that could be adopted by instructors interested in measuring their students’ graphing and data reasoning skills as well as an example handout to guide students in graph reading and interpretation.

Weigel, E., and Angra, A. (accepted) Teaching in Tandem: Using graphs in an active-learning classroom to shape students’ understanding of biology concepts. Journal of College Science Teaching. The goal in this study was to understand how explicit instruction on graphing and usage of published graphing materials affected students’ knowledge of various graph types and interpretation skills over the course of the semester in an upper-level animal behavior lecture course for biology majors. Each lecture began with an animal behavior scenario and students (n=41) were asked to: identify a research question and hypothesis, sketch their prediction in a graph, compare their sketch with the graph from literature, reflect on the findings and how they contribute to animal behavior. Individual and think-pair-share activities were discussed at each step to give students real-time feedback on their skills. Students’ graphing abilities were formally evaluated across three exams on open-ended questions. Improvement over the semester was observed, particularly in interpreting the purpose of the graph, the nature of the data, the relationships between independent and dependent variables and the take-home message. Responses to a  12-question pre-post survey containing open-ended and multiple choice questions revealed student improvement in recalling the different parts of a graph resulting from the use of a graphing rubric and peer assessment. However, in using a graph rubric, students gave more directed feedback on graph mechanics and graph communication, straying away from the graph choice elements in the graph rubric.  The use of published graphing materials together with explicit instruction and repeated practice was helpful in supporting students to improve their graphing knowledge and  identified potential targets for guidance and instruction.

Crowther, G. J. (2017). Which way do the ions go? A graph-drawing exercise for understanding electrochemical gradients. Advances in Physiology Education, 41: 556–559. In this short illuminations essay, the author presents a five-step graph-drawing method as a way to help his introductory biology students solve problems with electrochemical driving forces. Specifically, the five-step process allows students to determine the membrane potential, the specificity of the ion’s potential to flow inwards or outwards, and whether the cell will depolarize or hyperpolarize.  Although this process is less mathematical and graphically simple (no axes scale), it helps the student quickly visualize the process. This is an example of how instructors can encourage higher-order thinking with the biology content while allowing them a new way to graphically visualize biological phenomena in a lecture classroom.

Harsh J.A. and Schmitt-Harsh M.L. (2016)  Instructional Strategies to Develop Graphing Skills in the College Science Classroom.  The American Biology Teacher 78(1):  49-56. This article explores the design and implementation of a short-term intervention to hone college science students’ graphing skills. The authors developed an inquiry-based ecology unit for introductory, non-science students that emphasized graphing theory and practice as part of studying a real-world problem (i.e. the water quality of a campus stream). Five key instructional design features for teaching graphing drawn from the literature were incorporated into the unit for the deliberate practice of graph construction and interpretation:  (1) engaging students in authentic scientific inquiry through the investigation of realistic and contextualized problems, (2) exposing students to “messy” or complex data sets, (3) a two-step data analysis approach that first engages students’ cognitive processes and then uses technology for visualization purposes, (4) explicit graphing instruction that includes instructor modeling, and (5) collaborative practices to make sense of and communicate data. Students improved significantly from a pre- to a post assessment consisting of graphing construction and interpretation questions which  were informed from pre existing validated instruments. Likewise, in a supplemental questionnaire, students self-reported lower levels of anxiety and frustration when presented graph data upon completion of the unit. Student feedback highlighted the perceived positive impact of the unit on their graphing skills as well as identified the instructional design features that they felt most contributed to their learning, with a high rating for: personal data collection, working in a group, understanding each group’s role in the overall class data, and using graphing software. The authors conclude the article with suggestions for implementation adaptations to meet the needs of course- and lab-based activities across disciplines to help advance secondary and college students’ graphing skills.

Kirby, C. K., Fleming-Davies, A., & White, P. J. (2019). The Figure of the Day: A Classroom Activity to Improve Students’ Figure Creation Skills in Biology. The American Biology Teacher, 81(5), 317-325. This article examines the effects of a scaffolded graph interpretation learning activity on college students’ graph generation skills. The authors share an inquiry-style, puzzle-like figure analysis activity called “Figure of the Day” (FotD) which was implemented once a week for six weeks in an introductory organismal biology laboratory using data displays not related to the field or course content. In the treatment condition, students were asked to interpret a figure with one or several elements of contextual information missing (e.g., titles, captions, axes labels, axes units, legend text, and labels within figures), while the control condition of FotD did not contain any missing contextual information. In the treatment activity, students were asked to, individually and then collaboratively, observe the figure and brainstorm ideas about the variables displayed and possible explanations to the colors or symbols present. This was followed by a class debriefing, in which the instructor displayed the original published figure with all of the contextual information and led a discussion on the ideas that the figure authors were trying to communicate. A similar approach was taken with the control FoTD activities, however, students in the control group did not brainstorm ideas about missing information. To measure the impact of the FotD on students’ figure creation skills, students were asked to construct a graph pre- and post- FotD in a series of prompts. Student graphs were scored using a seven- category rubric, which revealed significant gains in both the treatment and control FoTD groups in the post-assessment.  When asked to provide feedback on the positive and negative aspects of the FotD, students in the treatment group enjoyed the activity more. However, students in the control treatment reported a higher perceived impact of the FotD on their figure interpretation and creation skills.  This suggests that regular interaction with figures in the style of the FotD activity can improve all students’ figure creation skills in a meaningful and enjoyable way.

 Violin, C. R., & Forster, B. M. (2019). An Introductory Module and Experiments To Improve the Graphing Skills of Non-Science Majors. Journal of Microbiology & Biology Education, 20(3). In this article, the authors share a three-part graphing module created for non-science undergraduate students enrolled in a laboratory course. The three-part scaffolded activity consists of the lecture, the class activity, and a group activity which is followed by a discussion on experimental design, variables, data types and data collection methods. For graph construction, graph choice is discussed as well as the appropriate mechanics needed to construct an informative graph. For graph interpretation, students are instructed on correlations, linear and non-linear trends, interpolating and extrapolating data. Students are also provided a two-sentence framework on how to convey the graph interpretation. Students practice graphing data in Microsoft Excel with guided instruction on computing regression models. Students work in small groups, collect their own data, and practice graphing four times over the semester. The authors state anecdotally that frequent graphing assignments have improved graphing skills in non-majors.

Hammett, A., & Dorsey, C. (2020). Messy Data, Real Science. The Science Teacher, 87(8). In this article, the authors present a real-world  data experience for students in the context of harmful algal blooms (HABs), which poses danger to humans and other animal life.  Given the relevance to students’ everyday lives (water quality) and that there is still not a clear answer as to why HABs occur, the topic is well-fit  for supporting an authentic and meaningful investigation for learners of various backgrounds. The authors outline design considerations drawn from the literature for effectively engaging students in data-rich investigations (i.e. making it interesting, embracing a systems view, being mindful of data complexity, and scaffolding data learning activities) and their respective instructional enactment. In their paper, the authors explain how they engaged students in authentic data experience in two ways. First, students are asked to collect and process data from their local water reservoirs using various instruments, students can measure a variety of variables (e.g. turbidity, pH, dissolved oxygen, phytoplankton). By processing and analyzing their own data first, students have more contextual familiarity with the larger, messier data sets that are collected from scientists doing HAB research. Second, students are exposed to “big data” sets to ensure authentic data exploration with enough data points and parameters for data analysis, visualization, and understanding the relationship between variables. Finding the right sized data set, with appropriate scope and messiness are important considerations to make when engaging students in data that they have not collected themselves.

Gray, C. E., & Contreras-Shannon, V. E. (2017). Using Models From the Literature and Iterative Feedback to Teach Students to Construct Effective Data Figures for Poster Presentations. Journal of College Science Teaching, 46(3), 74. The purpose of this study was to test a pedagogical method to teach students how to generate effective data representations in a sophomore-level Cell and Molecular Methods course-based research experience (CURE). There were two course instructors who each taught a control and a treatment section. Comparisons were drawn between figures prepared for posters by students who were (treatment group) and were not (control group) part of the intervention designed to develop and practice skills in representing authentic, messy data. To prepare effective figures, students in the treatment group were asked to: (a) find a few examples of published figures that included the same experimental data as their project, (b) assess the published figure on its components and effectiveness, and (c) create their own checklist from the figure which they used when preparing their own figure. The instructor then provided detailed feedback on the figure generated by the students, who then revised their figure. Towards the end of the semester, students collaborated with one or two classmates to pool their knowledge in designing their final figures for the poster.  A general rubric was created to score 34 figures (17 figures form the control group and 17 from the experimental group) from the final poster presentations. Across all rubric categories, students who were engaged in the pedagogy sections received the highest scores. The authors conclude with excerpts from students on the usefulness of iterative feedback. Although it may take more time to provide iterative feedback to students, the authors state that it is an excellent opportunity for the student and instructor to engage in real-world tasks of understanding and visualizing data.

Angra, A., Dalgleish, H. J., Chambers, S. M., Pita, D., & Emery, N. C. (2020). Data, distributions, and hypotheses: Exploring diversity and disturbance in the tallgrass prairie. CourseSource. In the context of ecological disturbance and how it shapes a tallgrass prairie ecosystem, the authors present a four-week lab module designed for an ecology laboratory course. Over the course of the module, students engage in authentic science practices consisting of: reading primary literature, working in teams to write hypotheses, designing experiments, collecting species composition data from a local tallgrass prairie ecosystem and comparing portions that were burned in different seasons, and presenting findings in graphs. At each step, students complete writing assignments and receive feedback. The module concludes by giving students real-world scenarios and asking them to form management decisions that integrate content from their prairie study with the constraints in their scenario. Students then present and defend their proposed solution to the class. All course materials (readings, pre-lab quizzes, writing and graphing assignments, etc.) for instructors and students can be accessed through the CourseSource website.

 A project of BioQUEST, the Quantitative Undergraduate Biology Education and Synthesis (QUBES) platform provides an open community space for life science educators to advance transformative STEM education efforts. The website hosts open-access classroom activities and CourseSource, a peer-reviewed journal of teaching resources, as well as faculty mentoring networks and educator communities on varying topics. Of relevance here, a range of resources pertaining to graph instruction are available from this platform.