Appropriating a Climate Science Discourse About Uncertainty in Online Lessons

In an online lesson on climate change, pairs of students make claims in the context of uncertainties, using graphs from authentic scientific publications designed originally for public use. As students grapple with describing and delimiting sources of uncertainty discerned from these rather sophisticated graphs, they migrate from attributing uncertainty to themselves to climate-related phenomena. The dialogue between students appears to be instrumental in the strengthening of uncertainty-based claims and explanations. Discourse about uncertainty Some of the earliest studies on human experience with uncertainty noted the distinction between internal attributions of uncertainty and external ones (Kahneman & Tversky, 1982). To attribute uncertainty internally to the competence of the self forecloses personal agency to resolve or delimit uncertainties arising from natural phenomena. To attribute uncertainty externally suggests a disposition to make sense of the indeterminacy of events in the world. Science curricula have traditionally downplayed or ignored the essential uncertainty of scientific practice, discouraging those students otherwise disposed to look externally to not bother trying. This inaccurate depiction of science deprives students of agency to formulate and explain claims based on limited and fallible evidence and thereby diminishes incentives to learn science (Lemke, 1990). Content understanding is enhanced with attention to the scientific practices of constructing and critiquing claims (Ford, 2008). For this reason, scientific practices have become a central feature of the Next Generation Science Standards (NGSS Lead States, 2013). The online lessons described here on the topic of climate science are part of a suite of lessons where public concerns intersect with controversies within specific fields of science. Climate change is a collective problem complicated by, and perhaps even limited by, citizens’ abilities to participate in productive conversation about it (Corner, 2012). These lessons provide scaffolded instruction around scientific graphical representations as well as user-friendly simulations so as to facilitate explanations and conversation. Students make claims based on evidence while also reflecting specifically on how certain they are and to which factors they attribute any uncertainty. Analyzing screen captures The students described here participated in a series of online tasks on climate science in a public high school in the northeast of the United States. We recorded their work via computer screen capture, a process that also captured their talk. This paper limits itself to two episodes, as the analysis is ongoing and results are preliminary. The first episode involves a lesson on solar irradiance and the second involves future trends in temperature. In our analysis we transcribe student talk and then search for themes, using methods of interaction analysis (Jordan & Henderson, 1995). Our guiding concern is to determine interactional factors that contribute to the written responses that students provide in these online tasks. Each task sits on a single webpage along which students can scroll and into which they submit a series of responses to prompts. Due to constraints in our study at the time, our data do not include video of the students themselves, only their shared screen. Though this is not ideal, it is still feasible to inspect their interaction via their speech and, at times, their cursor movements. Appropriating an uncertainty-infused discourse These lessons discursively position students as competent agents capable of making claims. They orient students to features of authentic graphical representations by providing some contextual information. This is necessary because interpretation goes beyond merely taking up presented evidence. Interpretation is predicated on ways of seeing and making things see-able distinctive to a given discipline (e.g., “highlighting”, Goodwin, 1994). That is, people have to be taught to see. So, the extent to which students can draw evidence from data depends crucially on how the data are framed for them. Explicitly addressing uncertainty as part of scientific activity raises questions for students as to how to construe uncertainty in relation to themselves. Typical curricular materials rarely elevate or highlight uncertainty as a salient and productive aspect of scientific practice. It is perhaps counterintuitive to dwell on uncertainty when cultivating the making of claims. But concerted reflection CSCL 2017 Proceedings 577 © ISLS on the tentative and provisional nature of scientific claims should foster greater confidence in them, not less (Latour, 2004). This is because the means of creating an argument conveys essential information about its strength and durability. The students working on these tasks tend to engage in considerable uncertainty-related talk as they prepare written responses to uncertainty-enriched argumentation prompts. In doing so they “appropriate” (Levrini, Fantini, Tasquier, Pecori, & Levin, 2015) climate science discourse in order to deal with what for them are novel forms of uncertainty. To appropriate a discourse is a matter in part of identifying oneself as a legitimate practitioner and of having the resources available to begin to participate successfully. Uncertainties in the solar irradiance task: General imitation versus waviness In the Solar Activity Task (see Figure 1), students are told they will make arguments based on evidence. They are first prompted to make claims about whether, “Based on the graph, is Earth’s temperature dependent on the level of solar activity?” Since this is an original graph from a scientific publication, let us first note the rich senses of uncertainty embedded in it that the general public would encounter. Both the following year’s temperature and solar activity are highly uncertain based on what we know about the present one, as indicated by the light-colored, erratically-varying lines. This uncertainty in yearly fluctuations is managed somewhat by means of a darker, relatively smooth lines described as the “11 yr average” for each quantity. Based on our knowledge of the 11-year average for a given year, the 11-year average for the next year is comparatively less uncertain. By taming somewhat the fluctuations in quantities in this way, it becomes more feasible to see beyond year-to-year variations so as to inspect trends over decades. The original authors’ intent was to show to the general public that solar activity and temperature run parallel (until about 1960) and then diverge. Figure 1. Cropped Portion of Screenshot of the Solar Activity Webpage for Annie and Betty. The audience for this lesson consists of students rather than the general public. In providing a limited synopsis, the webpage for the lesson explains that, “The graph shows Earth's air temperature and solar activity (irradiance) from 1880 to 2009. Solar activity includes sunspots, solar flares, and other solar weather events. The light-colored lines show the yearly measurements, and the darker lines show the average of 11 years of temperature or solar irradiance data. Earth's temperature is affected by many different factors” (cropped out of Figure 1). By giving students the task of making claims with only limited additional information, the task frames the interpretation of this authentic scientific graph as an activity students are capable of doing as well as any other public person. And they can presumably do so without having to attend to the layered meanings of some terms (e.g., the unit, W/m2) or deeper reflections on the data processing of measurements (e.g., How the earth comes to have a singular temperature for a given year). Table 1 illustrates the kind of conversation that can transpire with a task of this kind. The left column includes the time elapsed in seconds since the beginning of the episode, to provide information on the duration of turns of speech. In the right column, brackets indicate overlapping speech. The two speakers are Annie and Betty (all names are pseudonyms). In Line 1, Annie reads the question out loud and the two students take some time to think about a response. In Lines 2 and 3, they do not initially agree as to which bullet to select, “yes” or “no.” In Line 3 Annie asks rhetorically whether temperature imitates solar activity, answering her own question negatively. In Line 4, Betty signals disagreement, while nevertheless expressing some new doubt in that it may only imitate it partially. In Lines 5 and 7 Annie contrasts an imitation that is (merely) general in some way with a waviness that shows lack of (authentic) imitation. In Lines 6 and 8 Betty agrees but it is unclear whether this agreement is in regard to the general imitation or to the lack of imitation in waviness. In Lines 7-9 Annie elaborates further, characterizing the waviness in terms of some curve being especially “spikey.” She appears to CSCL 2017 Proceedings 578 © ISLS indicate the Total Solar Irradiance Yearly, since it is the most erratic-looking. In Line 10, Betty at first goes back to her initial pick of, “yes,” despite having just agreed to what Annie had just been saying about the waviness. But after a pause, she assents to Annie’s preferred answer. In Line 11 Annie follows up by elaborating on the lack of dependence in terms of not fitting. Later, after Line 11, Annie and Betty wrote, “The temperature and solar activity do not match in terms of “fitting together” because their graphs are not aligned, the temperature is not dependent on the solar activity.” Betty appears to initially construe imitation in terms of a correspondence between the darker lines up to 1960 (“for a little bit”). What is uncertain, then, is the permanence of this relation between 11-year running means. But Annie construes imitation in terms of how erratic the light lines are. What is uncertain is how well measures remain stable f