View in EDS HTML Full Text PDF Full Text

A Framework for Evidentiary Reasoning in Biology: Insights from Laboratory Courses Focused on Evolutionary Tree-Thinking

Saved in:
Bibliographic Details
Title: A Framework for Evidentiary Reasoning in Biology: Insights from Laboratory Courses Focused on Evolutionary Tree-Thinking
Language: English
Authors: Shiyao Liu (ORCID 0000-0002-5092-782X), Chaonan Liu, Ala Samarapungavan, Stephanie M. Gardner, Kari L. Clase, Nancy J. Pelaez
Source: Science & Education. 2024 33(6):1435-1466.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 32
Publication Date: 2024
Sponsoring Agency: National Science Foundation (NSF)
Contract Number: 1661124
Document Type: Journal Articles
Reports - Research
Descriptors: Biology, Science Instruction, Laboratory Experiments, Evolution, Scientific Concepts, Scaffolding (Teaching Technique), Evidence Based Practice, Thinking Skills, Discussion (Teaching Technique), Research Design
DOI: 10.1007/s11191-023-00435-6
ISSN: 0926-7220
1573-1901
Abstract: Science educators report that students struggle with understanding, using, and evaluating the evidence underpinning scientific knowledge. However, there are not many studies focused on helping instructors address those difficulties. Here, we report on a laboratory instructor's scaffolding of students' evidentiary reasoning with and about evidence for evolutionary trees with guidance from the Conceptual Analysis of Disciplinary Evidence (CADE) framework, which links biological knowledge with epistemic considerations. To consider both domain-general and discipline-specific aspects of evidence, CADE was implemented to inform scaffolds in two ways: (1) generic evidence scaffolds (GES) reminded students of general epistemic considerations; (2) disciplinary evidence scaffolds (DES) explicitly reminded students of the disciplinary knowledge of relevance for considering biological evidence. An instructor's lab discussions were compared before and after they had a workshop with CADE. CADE helped the lab instructor facilitate students' evidentiary reasoning about evolutionary trees. In comparison to baseline, both GES and DES discussions covered more aspects and relationships among types of evidence for evolutionary tree-thinking and the instructor prompted more kinds of general epistemic considerations and biological knowledge. DES discussions emphasized the importance of disciplinary knowledge for research design. The CADE framework guided planning and implementation of intentional scaffolding aimed at guiding evidentiary reasoning.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1450685
Database: ERIC
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
    Url: https://content.ebscohost.com/cds/retrieve?content=AQICAHj0k_4E0hTGH8RJwT4gCJyBsGNe_WN95AvKlDbXJGqwxwEd3nNgfbrELFNit-V42SvHAAAA4zCB4AYJKoZIhvcNAQcGoIHSMIHPAgEAMIHJBgkqhkiG9w0BBwEwHgYJYIZIAWUDBAEuMBEEDPKdjAftSvIoQeK_1gIBEICBm_EgUAY9IMdqQC7aHvr_thNsjrwepn7JgGwlnrgYrgcbgjz7g7k8q89EXeRXvxAlQLnlKWPK2nqt0Z2Sju-6SZNnkAfzumKWHMm7jpULgkKmhif4Nz2sNie9PQ3yUE95aXRXAoDK0tXQRLm3qC5hzYKTGkgi7fW6cM0cJtM7rXGkp-Ho8sofwvJezmYrH2QH6kQa4atmB4rt7wco
Text:
  Availability: 1
  Value: <anid>AN0181133845;nmo01dec.24;2024Nov29.02:25;v2.2.500</anid> <title id="AN0181133845-1">A Framework for Evidentiary Reasoning in Biology: Insights from Laboratory Courses Focused on Evolutionary Tree-thinking </title> <p>Science educators report that students struggle with understanding, using, and evaluating the evidence underpinning scientific knowledge. However, there are not many studies focused on helping instructors address those difficulties. Here, we report on a laboratory instructor's scaffolding of students' evidentiary reasoning with and about evidence for evolutionary trees with guidance from the Conceptual Analysis of Disciplinary Evidence (CADE) framework, which links biological knowledge with epistemic considerations. To consider both domain-general and discipline-specific aspects of evidence, CADE was implemented to inform scaffolds in two ways: (<reflink idref="bib1" id="ref1">1</reflink>) generic evidence scaffolds (GES) reminded students of general epistemic considerations; (<reflink idref="bib2" id="ref2">2</reflink>) disciplinary evidence scaffolds (DES) explicitly reminded students of the disciplinary knowledge of relevance for considering biological evidence. An instructor's lab discussions were compared before and after they had a workshop with CADE. CADE helped the lab instructor facilitate students' evidentiary reasoning about evolutionary trees. In comparison to baseline, both GES and DES discussions covered more aspects and relationships among types of evidence for evolutionary tree-thinking and the instructor prompted more kinds of general epistemic considerations and biological knowledge. DES discussions emphasized the importance of disciplinary knowledge for research design. The CADE framework guided planning and implementation of intentional scaffolding aimed at guiding evidentiary reasoning.</p> <p>Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/s11191-023-00435-6.</p> <hd id="AN0181133845-2">Introduction</hd> <p>Thinking with and about evidence in biology labs is emphasized in recent reform documents (Brewer & Smith, [<reflink idref="bib10" id="ref3">10</reflink>]; National Academies of Sciences, Engineering, and Medicine., [<reflink idref="bib69" id="ref4">69</reflink>]; NGSS Lead States, [<reflink idref="bib73" id="ref5">73</reflink>]). In modern science, it is essential for students to understand scientific evidence and how to use scientific evidence in scientific knowledge construction (Chinn et al., [<reflink idref="bib17" id="ref6">17</reflink>]; Carey & Smith, [<reflink idref="bib16" id="ref7">16</reflink>]; Duschl et al., [<reflink idref="bib30" id="ref8">30</reflink>]; Erduran, [<reflink idref="bib33" id="ref9">33</reflink>]; Osborne et al., [<reflink idref="bib76" id="ref10">76</reflink>], [<reflink idref="bib77" id="ref11">77</reflink>]; Ratcliffe and Millar, [<reflink idref="bib80" id="ref12">80</reflink>]). A report from the American Association for the Advancement of Science, <emph>Vison and Change in Undergraduate Biology Education</emph> (Brewer & Smith, [<reflink idref="bib10" id="ref13">10</reflink>]), emphasizes having students design, analyze, and describe the process of science in disciplinary practice in the context of core concepts, and to practice science communication. Furthermore, since 2013, <emph>Next Generation Science Standards</emph> (NGSS) has been highlighting the importance of multiple lines of evidence in making stronger explanations (NGSS Lead States, [<reflink idref="bib73" id="ref14">73</reflink>]).</p> <p>A significant body of literature in sciences education focuses on students' development of scientific knowledge, including their use of evidence and epistemic understandings about science. Nevertheless, educators consistently find that both K-12 and undergraduate students struggle to understand evidence to support their advanced science knowledge (Abd-El-Khalick et al., [<reflink idref="bib1" id="ref15">1</reflink>]; Bybee, [<reflink idref="bib14" id="ref16">14</reflink>]; Duncan & Reiser, [<reflink idref="bib27" id="ref17">27</reflink>]; Duncan et al., [<reflink idref="bib28" id="ref18">28</reflink>]; Duschl, [<reflink idref="bib29" id="ref19">29</reflink>]; Liu et al., [<reflink idref="bib53" id="ref20">53</reflink>], [<reflink idref="bib55" id="ref21">55</reflink>], [<reflink idref="bib54" id="ref22">54</reflink>]; Tsui & Treagust, [<reflink idref="bib100" id="ref23">100</reflink>]), and they have difficulty applying and evaluating evidence when using scientific practices (Crujeiras Pérez & Jiménez Aleixandre, [<reflink idref="bib22" id="ref24">22</reflink>]; Labov et al., [<reflink idref="bib51" id="ref25">51</reflink>]; Manz et al., [<reflink idref="bib59" id="ref26">59</reflink>]; McNeill & Berland, [<reflink idref="bib64" id="ref27">64</reflink>]; Walker et al., [<reflink idref="bib102" id="ref28">102</reflink>]). Areas of student difficulty include controlling variables and generating hypotheses (Dasgupta et al, [<reflink idref="bib23" id="ref29">23</reflink>]), contextualizing research practices in terms of relevant disciplinary knowledge (Crujeiras Pérez & Jiménez Aleixandre, [<reflink idref="bib22" id="ref30">22</reflink>]), managing uncertainty (Dolan & Grady, [<reflink idref="bib26" id="ref31">26</reflink>]), managing discrepancies (Novak & Treagust, [<reflink idref="bib74" id="ref32">74</reflink>]), and logical argumentation (Manz et al., [<reflink idref="bib59" id="ref33">59</reflink>]). Although de Lima Tavares et al. ([<reflink idref="bib24" id="ref34">24</reflink>]) found that students do illustrate theoretical claims with data, Duncan et al. ([<reflink idref="bib28" id="ref35">28</reflink>]) and others are finding that students have difficulty evaluating the quality and strength of evidence and deciding how different sources and kinds of evidence should be weighted and integrated to support claims.</p> <p>Without appropriate understanding of scientific evidence, students may have difficulty in mastering advanced scientific knowledge, which may discourage them from careers in science and science research (Hathaway et al., [<reflink idref="bib42" id="ref36">42</reflink>]; Lopatto, [<reflink idref="bib57" id="ref37">57</reflink>]; Osborne et al., [<reflink idref="bib76" id="ref38">76</reflink>], [<reflink idref="bib77" id="ref39">77</reflink>]). Moreover, failing to use multiple interdisciplinary sources of evidence to reason with and about advanced science concepts may lead to misunderstandings of important scientific issues relevant to daily life, such as climate change, vaccine safety, and gene technology (Brulle, et al., [<reflink idref="bib12" id="ref40">12</reflink>]; Gellin, et al., [<reflink idref="bib37" id="ref41">37</reflink>]; Sadler & Zeidler, [<reflink idref="bib85" id="ref42">85</reflink>]). In summary, even though current science standards and supporting policy documents emphasize the importance of evidence in understanding biological knowledge, multiple studies reveal difficulties students still have with understanding and using scientific evidence.</p> <p>Most prior research on students' use of evidence in science is based on under-analyzed concepts of evidence, focusing only on limited aspects of evidence. A conventional starting point for science educators is Toulmin's ([<reflink idref="bib99" id="ref43">99</reflink>]) definition of evidence as data/phenomena that are connected to a knowledge claim through argument (Erduran et al., [<reflink idref="bib34" id="ref44">34</reflink>]; McNeill & Krajcik, [<reflink idref="bib65" id="ref45">65</reflink>]; Sandoval & Millwood, [<reflink idref="bib89" id="ref46">89</reflink>]). However, Toulmin's definition leaves much to be unpacked with regard to the plausibility of mechanism, the relevance and quality of the evidence, and its congruence with other available evidence. For example, Duncan et al. ([<reflink idref="bib28" id="ref47">28</reflink>]) point out that the framework within the NGSS supporting documents does not define the features of evidence to be evaluated, nor does it provide guidance on how to integrate and weight multiple kinds of evidence in decision making. Therefore, instructors need a more comprehensive understanding of and guidance on how to help students to develop and coordinate complex evidentiary reasoning.</p> <p>This study focuses on evidentiary reasoning, by which we mean application of shared disciplinary norms for the generation and evaluation of evidence, as a basis for scientific consensus (Giere, [<reflink idref="bib38" id="ref48">38</reflink>]; Manz et al., [<reflink idref="bib59" id="ref49">59</reflink>]; Samarapungavan, [<reflink idref="bib86" id="ref50">86</reflink>]). More specifically, evidentiary reasoning is the application of evidence generated from a set of theoretical and methodological frameworks to assess the consistency or fit between potential theories and the reality (Giere, [<reflink idref="bib38" id="ref51">38</reflink>]). For example, evidentiary reasoning about evolutionary relationships requires the application of evidence derived from observation, calculation, or experiment guided by biological methodological frameworks, in conjunction with the evaluation of evidence pertaining to theoretical frameworks such as reproductive isolation as a cause for speciation, in order to ascertain the actual evolutionary relationships. To have the opportunity to develop scientific competence with evidentiary reasoning, students must be granted the opportunity to engage in complex and abstract tasks where they can understand, identify, apply, and evaluate scientific evidence in the context of advanced science concepts (National Research Council, [<reflink idref="bib70" id="ref52">70</reflink>]). Data from the learning sciences suggest that having students frame a research problem in the context of a disciplinary perspective will promote stronger reasoning about the evidence which results from their investigations (Brewer & Smith, [<reflink idref="bib10" id="ref53">10</reflink>]; Chinn et al., [<reflink idref="bib17" id="ref54">17</reflink>]; Duschl, [<reflink idref="bib29" id="ref55">29</reflink>]; Osborne et al., [<reflink idref="bib76" id="ref56">76</reflink>], [<reflink idref="bib77" id="ref57">77</reflink>]; Sandoval & Reiser, [<reflink idref="bib88" id="ref58">88</reflink>]; Singer et al., [<reflink idref="bib90" id="ref59">90</reflink>]). However, studies indicate that teachers often have difficulty when engaging students with complex reasoning tasks, such as generating, analyzing, and evaluating data (Anderson et al., [<reflink idref="bib4" id="ref60">4</reflink>]; Blumenfeld et al., [<reflink idref="bib9" id="ref61">9</reflink>]; Soysal, [<reflink idref="bib93" id="ref62">93</reflink>]; Tekkumru-Kisa et al., [<reflink idref="bib98" id="ref63">98</reflink>]). In fact, Manz et al. ([<reflink idref="bib59" id="ref64">59</reflink>]) point out that instead of having students do research, instructors have simplified investigations to focus students only on the materials and processes in the investigation. Here, we report on a study that uses a framework unpacking the notion of evidence to help undergrade biology lab instructors to facilitate students' discussions of evidentiary reasoning about evolutionary tree-thinking, a complex and abstract research task.</p> <hd id="AN0181133845-3">The Conceptual Analysis of Disciplinary Evidence (CADE) Framework</hd> <p>As mentioned above, evidence is the data used to answer a question or support/refute a claim (NGSS Lead States, [<reflink idref="bib73" id="ref65">73</reflink>]; Sandoval & Reiser, [<reflink idref="bib88" id="ref66">88</reflink>]). However, this definition begs the question of what counts as "data," or more importantly, what counts as sound and robust data. In this study, the CADE framework (Samarapungavan, [<reflink idref="bib86" id="ref67">86</reflink>]) was adapted as a tool to define the notion of evidence and guide laboratory instructors in facilitating students' reasoning with and about evidence in their investigations. The CADE is a theoretical synthesis of diverse literatures to extend and expand considerations of what counts as adequate or good evidence for the teaching of scientific practice. It aims to enable advanced evidentiary reasoning by deconstructing the idea of evidence to include disciplinary knowledge and epistemic considerations of evidence relevant to scientific research practice. The CADE framework has been used to guide the design of biology lab instruction in the context of Hardy–Weinberg equilibrium (Liu, Dreger, et al., [<reflink idref="bib56" id="ref68">56</reflink>]), to evaluate assessments of student learning about biological evolution (Liu et al., [<reflink idref="bib53" id="ref69">53</reflink>], [<reflink idref="bib55" id="ref70">55</reflink>], [<reflink idref="bib54" id="ref71">54</reflink>]), and as a framework for biology faculty development (Liu et al., [<reflink idref="bib53" id="ref72">53</reflink>], [<reflink idref="bib55" id="ref73">55</reflink>], [<reflink idref="bib54" id="ref74">54</reflink>]). In this study, we are simultaneously extending the framework and testing its practical utility in contexts of teaching and learning. Epistemic considerations in CADE highlight the need for a fine-grained disciplinary perspective. Specifically, epistemic considerations refer to logical approaches, grounded in the discipline, to analyzing and evaluating the nature, scope, and quality of the data, knowledge, theories, technologies, and assumptions that underpin the evidence.</p> <p>CADE provides a practical framework for developing scaffolding questions in a contextual manner. CADE not only relates the disciplinary knowledge with epistemic considerations, but it further deconstructs evidence into four reciprocally interrelated relationships of relevance to the use of evidence: (<reflink idref="bib1" id="ref75">1</reflink>) <emph>Theory</emph> = > <emph>Evidence (T</emph> = > <emph>E)</emph> relationships frame and articulate a set of potentially testable models; (<reflink idref="bib2" id="ref76">2</reflink>) <emph>Evidence⟺Data (E⟺D)</emph> relationships are interactions of relevance to the design and process of investigation; (<reflink idref="bib3" id="ref77">3</reflink>) <emph>Evidence</emph> = > <emph>Theory (E</emph> = > <emph>T)</emph> relationships relate to the evaluation of evidence to draw conclusions; (<reflink idref="bib4" id="ref78">4</reflink>) <emph>Social Dimensions</emph> relationships are of relevance to communicating evidence in a public sphere. Within each of the four relationships, both disciplinary knowledge and epistemic considerations are deconstructed and emphasized, as detailed in Tables 1, 2, and 3. Here, we focus on evolutionary tree-thinking as the disciplinary knowledge context for a lab research activity in which there is much evidence to consider and evaluate. The disciplinary knowledge questions in Tables 1, 2, and 3 would be modified according to each specific lab research topic.</p> <p>Table 1 Theory to Evidence relationships (code <emph>T</emph> = > <emph>E</emph><uline>)</uline></p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>Constructs and practices</p></th><th align="left"><p>Disciplinary knowledge in biology</p></th><th align="left"><p>Reflective evaluation of the reasoning (epistemic considerations)</p></th></tr></thead><tbody><tr><td align="left" rowspan="3"><p>Model articulation: formulate testable hypotheses or explanations</p></td><td align="left"><p>What are the key domain phenomena?</p><p>What are the important unsolved problems?</p></td><td align="left"><p>Is relevant evidence used to render the question, hypotheses, plausible?</p></td></tr><tr><td align="left"><p>What are the possible mechanisms, causal relationships, and processes?</p></td><td align="left"><p>Is articulated model complete, specific, and internally consistent?</p><p>Are alternative models or theories considered?</p></td></tr><tr><td align="left"><p>What variables are relevant? Why did you decide to look at those variables?</p></td><td align="left"><p>Have relationships between variables been clearly specified?</p></td></tr></tbody></table> </ephtml> </p> <p>Table 2 Evidence ⟺ Data relationships (code <emph>E </emph>⟺<emph> D</emph>)</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>Constructs and practices</p></th><th align="left"><p>Disciplinary knowledge in biology</p></th><th align="left"><p>Reflective evaluation of the reasoning (epistemic considerations)</p></th></tr></thead><tbody><tr><td align="left" rowspan="5"><p>Designing, executing, analyzing investigations</p></td><td align="left"><p>Deciding what to observe or measure:</p><p> • How are variables defined?</p><p> • Continuous or categorical,</p><p> • Independent, dependent, control etc</p><p> • Intervals, range of values sampled</p></td><td align="left"><p>Are variables clearly defined?</p><p>Are variables defined in a way that is consistent with what is known (similarity versus differences)?</p></td></tr><tr><td align="left"><p>What instruments, techniques, apparatus will be used to collect/record data and why are these appropriate?</p><p>What sampling procedures are used?</p></td><td align="left"><p>Is technical precision, power, sensitivity, reliability, of data collection procedures adequate?</p></td></tr><tr><td align="left"><p>What data models are used to organize/analyze data (e.g., graphs, statistical models)?</p></td><td align="left"><p>Are the models used appropriate?</p></td></tr><tr><td align="left"><p>What are known sources of error and how will they be accounted for?</p></td><td align="left"><p>Have potential sources of error and confounding factors been evaluated?</p></td></tr><tr><td align="left"><p>Have relevant investigations been conducted?</p><p>Are diverse relevant data types collected?</p></td><td align="left"><p>Are different types of data collected from diverse measures and trials to provide support?</p></td></tr></tbody></table> </ephtml> </p> <p>Table 3 Evidence to Theory relationships (code <emph>E</emph> = > <emph>T</emph>)</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>Constructs and practices</p></th><th align="left"><p>Disciplinary knowledge in biology</p></th><th align="left"><p>Reflective evaluation of the reasoning (epistemic considerations)</p></th></tr></thead><tbody><tr><td align="left" rowspan="5"><p>Models of inference and argument: Sufficiency of conclusions</p></td><td align="left"><p>What data reporting standards apply? (e.g., attrition, error rates, outliers)?</p></td><td align="left"><p>Are data reports fair/complete?</p></td></tr><tr><td align="left"><p>What has been learned from the evidence?</p></td><td align="left"><p>Are the conclusions internally consistent?</p></td></tr><tr><td align="left"><p>Are findings/conclusions explained in terms of what is already known in biology?</p></td><td align="left"><p>Are the conclusions aligned with what is known?</p></td></tr><tr><td align="left"><p>What other conclusions are compatible with the evidence?</p></td><td align="left"><p>How does the evidence distinguish between multiple interpretations or hypotheses? Have alternative conclusions been explored and rebutted?</p></td></tr><tr><td align="left" /><td align="left"><p>Are limitations and uncertainties explicitly acknowledged/ addressed?</p></td></tr></tbody></table> </ephtml> </p> <hd id="AN0181133845-4">Evolutionary Tree-Thinking</hd> <p>Evolution is among the five core concepts identified by <emph>Vison and Change in Undergraduate Biology Education</emph> (Brewer & Smith, [<reflink idref="bib10" id="ref79">10</reflink>]), as it builds the foundation for interpreting all biological phenomena. An evolutionary tree, also known as a phylogenetic tree or cladogram, is a diagram created to represent proposed evolutionary relationships among populations or species (Halverson et al., [<reflink idref="bib40" id="ref80">40</reflink>]; Raven et al., [<reflink idref="bib81" id="ref81">81</reflink>]). Evolutionary trees provide a framework for evaluating evolutionary evidence and they are generated from data to facilitate understanding of evolutionary relationships (Kong et al, [<reflink idref="bib48" id="ref82">48</reflink>]). Interpretation of evolutionary trees as illustrated in Fig. 1 makes it possible to answer research questions related to information contained in a phylogeny, such as the origin of an emerging disease like COVID-19 or the chronological sequence of evolutionary events (Brooks et al., [<reflink idref="bib11" id="ref83">11</reflink>]; Halverson et al., [<reflink idref="bib40" id="ref84">40</reflink>]; Kong et al., [<reflink idref="bib48" id="ref85">48</reflink>]; O'Hara, [<reflink idref="bib75" id="ref86">75</reflink>]; Sober & Steel, [<reflink idref="bib92" id="ref87">92</reflink>]).</p> <p>Graph: Fig. 1 Evolutionary tree examples used in lab. A The structures of an evolutionary tree (Kong, et al., [<reflink idref="bib48" id="ref88">48</reflink>], used with permission). The arrow shows the chronology of life, since the direction of time for evolutionary events goes from the root (ancestor) toward the taxa at the branch tips. B An example of an evolutionary tree constructed to show the relationships between fish, whale, and human. Fish is the outgroup; human and whale are sister taxa. In order to reason about evidence for the evolutionary relationships between fish, whale, and human, disciplinary knowledge, such as understanding homology and homoplasy, is needed. Namely, similar traits between fish and whale may have been inherited from a common ancestor (homology) or be caused by selection pressures or genetic drift (homoplasy). Epistemic consideration is needed to determine a chronological sequence, such as the order of occurrence of fins</p> <p>Evolutionary tree-thinking requires the coordination of varied biological evidence at multiple levels (Ayala, [<reflink idref="bib5" id="ref89">5</reflink>]). To be more specific, the evidence that underpins evolutionary tree-thinking requires coordinated reasoning about data sources (Kong et al., [<reflink idref="bib49" id="ref90">49</reflink>]), as well as the disciplinary knowledge and conventions of the tree features identified in Fig. 1A (Kong et al., [<reflink idref="bib48" id="ref91">48</reflink>]). Thus, both disciplinary knowledge and epistemic considerations are relevant when deciding what counts as sound and robust data.</p> <p>The epistemic considerations include evaluating the nature of different traits in order to reason about data sources like morphological features, molecular or developmental patterns, or behaviors that would provide useful convergent evidence in deciding if shared traits are evidence of homology (traits inherited from a shared ancestor). Moreover, the epistemic considerations include evaluating the scope and quality of the evidence that is used in deciding on evolutionary relationships and the chronology of ancestral features of organisms. The disciplinary knowledge specifically called on for reasoning about evidence for evolutionary relationships includes understanding the concept of clade (a branch that includes a single common ancestor and all of its descendants) and how a clade in an evolutionary tree is depicted with a node (showing the common ancestor) and connected branches.</p> <p>Difficulty with evolutionary tree-thinking has been reported among undergraduate biology students (Abraham et al., [<reflink idref="bib2" id="ref92">2</reflink>], [<reflink idref="bib3" id="ref93">3</reflink>]; Baum et al., [<reflink idref="bib7" id="ref94">7</reflink>]; Ferrari & Chi, [<reflink idref="bib36" id="ref95">36</reflink>]; Meir et al., [<reflink idref="bib66" id="ref96">66</reflink>]; Nehm & Ha, [<reflink idref="bib71" id="ref97">71</reflink>]; Nehm & Reilly, [<reflink idref="bib72" id="ref98">72</reflink>]; Smith et al., [<reflink idref="bib91" id="ref99">91</reflink>];). However, only a few studies (e.g., de Lima Tavares et al., [<reflink idref="bib24" id="ref100">24</reflink>]; Smith et al., [<reflink idref="bib91" id="ref101">91</reflink>]) focused on students' use of data as evidence for investigating and understanding evolution. More specifically considering phylogenetic trees, in addition to the general public (Evans et al., [<reflink idref="bib35" id="ref102">35</reflink>]), even graduate students of biology and some professional biologists (Baum et al., [<reflink idref="bib7" id="ref103">7</reflink>]; Crisp & Cook, [<reflink idref="bib21" id="ref104">21</reflink>]; Gregory & Ellis, [<reflink idref="bib39" id="ref105">39</reflink>]; Krell & Cranston, [<reflink idref="bib50" id="ref106">50</reflink>]) have difficulty with evolutionary tree-thinking. However, few studies investigate ways to guide instructors on how better to engage students with scientific evidence to address identified difficulties.</p> <hd id="AN0181133845-5">Scaffolding Student Scientific Reasoning</hd> <p>Scaffolding refers to the process whereby teachers or competent peers use temporary supports to assist learners in completing activities that are beyond the learners' independent capacity (Wood et al., [<reflink idref="bib104" id="ref107">104</reflink>]). Scaffolding for this study means to provide prompts and cues to support students as they reason with and about evidence by recognizing key epistemic considerations and relevant biological disciplinary knowledge to facilitate their competence.</p> <p>Studies show that instructional scaffolding can help students to be more successful in integrating, interpreting, evaluating, and using evidence in a science classroom (Koslowski et al.,[<reflink idref="bib47" id="ref108">47</reflink>]; Masnick and Klahr., [<reflink idref="bib61" id="ref109">61</reflink>]; Russ et al., [<reflink idref="bib83" id="ref110">83</reflink>]; Ryu & Sandoval, [<reflink idref="bib84" id="ref111">84</reflink>]; Sandoval & Cam, [<reflink idref="bib87" id="ref112">87</reflink>]). However, instead of scaffolding students' evidentiary reasoning, recent studies indicate that teachers in K-12 as well as instructors at the undergraduate level tend to transform complex tasks into cookbook-style steps and emphasize completion and correct answers rather than focusing on reasoning abilities (Baldwin & Wawrzynski, [<reflink idref="bib6" id="ref113">6</reflink>]; Kang et al., [<reflink idref="bib44" id="ref114">44</reflink>]; Manz et al., [<reflink idref="bib59" id="ref115">59</reflink>]; Tabak & Radinsky, [<reflink idref="bib97" id="ref116">97</reflink>]). To further exacerbate this problem, according to one survey, teaching assistants serve as lab instructors and teach 91% of undergraduate level biological science laboratories at a typical set of research institutions (Sundberg et al., [<reflink idref="bib96" id="ref117">96</reflink>]). Compared to science teachers and professors, lab instructors such as undergraduate and graduate teaching assistants (TAs) may be less prepared with the relevant pedagogical and content knowledge (Kendall, & Schussler, [<reflink idref="bib45" id="ref118">45</reflink>]; Luft et al., [<reflink idref="bib58" id="ref119">58</reflink>]; Muzaka, [<reflink idref="bib68" id="ref120">68</reflink>]). Thus, teachers, professors, and lab instructors may benefit from professional support to master facilitation of evidentiary reasoning (Kendall & Schussler, [<reflink idref="bib45" id="ref121">45</reflink>]; Kloser et al., [<reflink idref="bib46" id="ref122">46</reflink>]; Maskiewicz, [<reflink idref="bib60" id="ref123">60</reflink>]). Here, we employed the CADE framework as a potential tool to guide TAs in a biology lab to engage students in high level reasoning about evidence for evolutionary trees.</p> <hd id="AN0181133845-6">Theoretical Rationale</hd> <p>As mentioned above, evidentiary reasoning about evolutionary trees requires reasoning with evolutionary theory to frame and articulate a set of potential testable models (CADE <emph>T</emph> = > <emph>E</emph>) and to evaluate and draw conclusions (CADE <emph>E</emph> = > <emph>T</emph>), based on reasoning about data sources (CADE <emph>E ⟺ D</emph>). The research process involves deciding what data to include in the design and process of an investigation in order to evaluate and draw conclusions (CADE <emph>E</emph> = > <emph>T</emph>). This also requires reasoning about evolutionary tree features such as the root, node, and branches to construct or interpret evolutionary trees in communicating with others (Social Dimensions) (Kong et al., [<reflink idref="bib49" id="ref124">49</reflink>]; Samarapungavan, [<reflink idref="bib86" id="ref125">86</reflink>]). These practices involve the four relationships that are deconstructed in the CADE framework. Thus, evolutionary tree-thinking is a relevant context for testing instructors' use of CADE to develop and implement scaffolding focused on evidentiary reasoning. Furthermore, it is relevant to instructors of introductory biology courses given the known challenges undergraduate students have in understanding and using evolutionary trees.</p> <p>There is some debate in the cognitive research literature about whether reasoning and epistemic cognition are domain general (see examples:Buehl & Alexander, [<reflink idref="bib13" id="ref126">13</reflink>]; Mason & Scirica, [<reflink idref="bib62" id="ref127">62</reflink>]; Muis et al., [<reflink idref="bib67" id="ref128">67</reflink>]; Qian & Alvermann, [<reflink idref="bib79" id="ref129">79</reflink>]; Weinstock & Cronin, [<reflink idref="bib103" id="ref130">103</reflink>]) or contextualized, meaning tightly linked to specific disciplinary knowledge (see examples: Hammer & Elby, [<reflink idref="bib41" id="ref131">41</reflink>]; Chinn et al., [<reflink idref="bib17" id="ref132">17</reflink>]; Elby & Hammer, [<reflink idref="bib32" id="ref133">32</reflink>], [<reflink idref="bib31" id="ref134">31</reflink>]). Of relevance to these debates is how thinking and reasoning should be taught (see examples:Chinn et al., [<reflink idref="bib17" id="ref135">17</reflink>]; Duschl, [<reflink idref="bib29" id="ref136">29</reflink>]; Jiménez-Aleixandre, [<reflink idref="bib43" id="ref137">43</reflink>]; Sandoval & Reiser, [<reflink idref="bib88" id="ref138">88</reflink>]), whether with a domain-general approach or with a domain-specific approach. Despite these debates, current studies focused on scaffolding students' evidentiary reasoning still rely heavily on general scaffolds (Berland et al., [<reflink idref="bib8" id="ref139">8</reflink>]). While the general scaffold approach has been shown to enhance epistemic cognition, it is not entirely successful in helping students with evidentiary reasoning. Disciplinary knowledge plays an important role in scaffolding questions, yet little is known about how to integrate epistemic considerations with disciplinary knowledge (e.g., Sandoval & Reiser, [<reflink idref="bib88" id="ref140">88</reflink>]). Thus, here, we examine how an instructor guides students to integrate epistemic considerations with disciplinary knowledge in scaffolding an undergraduate lab investigation where students have already established some disciplinary knowledge foundations.</p> <p>Taking account of the argument that epistemic considerations are both domain general and specific (e.g., Muis et al., [<reflink idref="bib67" id="ref141">67</reflink>]), CADE was used to guide development of evidence scaffolding for two different instructional methods for facilitating students' evidentiary reasoning: generic evidence scaffolds (GES) and disciplinary evidence scaffolds (DES). Generic evidence scaffolds reminded students of general epistemic considerations for evidence without explicitly connecting to the relevant disciplinary knowledge. Disciplinary evidence scaffolds explicitly reminded students of the domain-specific disciplinary knowledge relevant to the biological evidence. Both GES and DES scaffolding questions were based on the first three relationships of CADE, <emph>Theory</emph> = > <emph>Evidence</emph>, <emph>Evidence ⟺ Data</emph>, and <emph>Evidence</emph> = > <emph>Theory</emph>. GES provided students with a more open-ended inquiry, linking students to the context of evolution or to their prior disciplinary knowledge. As an example, a GES question "How might additional data provide evidence to change the 'big picture' conclusion?" was posed to help students recall epistemic considerations of relevance to the use of evidence for drawing an evolutionary tree (<emph>E</emph> = > <emph>T, Epistemic Consideration</emph>). A corresponding DES question "What other qualities might a biologist consider to gain confidence in the chronology of evolutionary events?" was posed to help students link their biological knowledge to explicitly consider how evidence is used to identify the chronological sequence of life history (<emph>E</emph> = > <emph>T, Disciplinary Knowledge & Epistemic Consideration</emph>). The GES question invites students to think about the conclusion in a general way. The students may consider qualities like fossil evidence and molecular evidence to increase confidence in a chronology. But they can also address this question with statistical knowledge, like additional tests for internal consistency, or literature to add external consistency. In contrast, the DES question invites students to consider specifically fossil evidence and molecular evidence from biology as a research discipline.</p> <p>Ideally, instructors might learn how to scaffold students' evidentiary reasoning with guidance from the CADE framework, <emph>T</emph> = > <emph>E</emph>,<emph> E ⟺ D</emph>, and <emph>E</emph> = > <emph>T</emph> using a general evidence approach applied to an evolutionary tree-thinking context. General evidence scaffolds could then transfer to other situations. As a first step, however, this study aims to contribute to our knowledge about general or discipline-specific ways to develop scaffolding questions that prompt reasoning with and about evidence within a specific disciplinary context, evolutionary tree-thinking. The insight from this study might help us prepare lab instructors to better target instruction. In summary, here, we examine how an instructor could aim to guide students' evidentiary reasoning by developing and implementing scaffolds according to the various relationships relevant to understanding and using evidence in the CADE framework.</p> <hd id="AN0181133845-7">The Research Questions</hd> <p>(<reflink idref="bib1" id="ref142">1</reflink>) How did CADE influence the development and implementation of scaffolding for GES and DES treatments during an evolutionary tree-thinking task? (<reflink idref="bib2" id="ref143">2</reflink>) What challenges remain in the implementation of discussions about evidence for evolutionary tree-thinking informed by CADE?</p> <hd id="AN0181133845-8">Methodology</hd> <p>This study is part of a larger project involving multiple high school and undergraduate college level biology courses with design-based research (DBR) (Cobb et al., [<reflink idref="bib19" id="ref144">19</reflink>]). Here, we report findings collected in an introductory biology lab course at a large midwestern university with high research activity in the USA. This comparative case study analysis of one instructor is based on data from the first and fourth semesters when the same instructor taught the lab course repeatedly over a 2-year period.</p> <p>We examined changes in classroom discussion with the instructor before and after training with the CADE framework. Instead of a detached investigator, the authors posit ourselves as supporters and facilitators who actively participated in a pre-lab workshop with the course professor and multiple lab instructors who were undergraduate and graduate TAs. Changes in their ideas about how to moderate a discussion about evidence in the lab were documented as the teaching staff collaborated with us to design scaffolding questions. Overall, our primary motivation was to see if the practices of scaffolding discussion and theory of evidentiary reasoning improved with implementation of the CADE framework. Findings from our qualitative analyses focus not only on the outputs but also on the processes of learning promoted by the study.</p> <hd id="AN0181133845-9">Participants</hd> <p>The participant instructor and students were in a semester-long biology lab course for first-year undergraduate students. Students in the course attended a weekly lab prep lecture (40 min) given by the course professor in addition to attending a lab (165 min) taught by three undergraduate student peer leaders and led by one undergraduate or graduate TA lab instructor. The participant lab instructor contributed to course improvements and was paid for participation in this study according to a protocol that was reviewed and approved by the institutional review board (IRB#1,702,018,760,251). The participant lab instructor taught one lab section in the 2017 fall semester (baseline) and two lab sections in the 2019 spring semester (DES versus GES treatments). Students enrolled in these three sections were invited to participate in the study. A total of 48 students (16 per lab section) volunteered. Of the student participants, 79% had not completed any previous lab course at the undergraduate level, but 82% had completed an advanced placement (AP) or honors biology course in high school. The lab instructor was familiar with the course before volunteering to participate in this study. In addition to having previously taken the course, she had also previously served as a peer instructor for the course. Indeed, according to end-of-course student evaluations, this instructor "genuinely seemed to care about every question we had and would take extra time to look things up or even hold extra office hour times if we needed help" and was "very knowledgeable about all of the topics" (typical comments written by students for the 2017 fall end-of-course evaluation).</p> <hd id="AN0181133845-10">Data Collection</hd> <p>The lab discussion data reported in this study is from the 2017 fall semester (baseline) before the training with CADE and the 2019 spring semester following three semesters of CADE training (DES versus GES treatments). The data were examined to compare how plans and implementation to facilitate students' evidentiary reasoning with scaffolded discussions might have changed after the CADE training. Data from the participant lab instructor's 2018 spring and fall semesters was excluded since DBR aspects of the larger study are not the focus of this report.</p> <p>Lesson plans and video recordings of the discussion process for baseline, GES, and DES treatments were transcribed and used to address the research questions. As the lab discussions were recorded, the lab instructor agreed to repeat the students' ideas to clearly capture their words and ideas according to the approved protocol. Although student data is not included in this report, it was important to recruit student volunteers to the study so that we could include the instructor's responses to the students' activities.</p> <hd id="AN0181133845-11">Study Context</hd> <p>The focus of this study was an evolutionary tree-thinking task that was used to introduce a 5-week blood dilution research module. In the pre-lab lecture, a professor presented the necessary background knowledge for the task including the methods of cladistics, the concepts of clades, homology, homoplasy and convergent evolution, and ideas about the chronology of evolution represented in evolutionary trees and how to examine clades with the "snip" rule (Kong et al., [<reflink idref="bib49" id="ref145">49</reflink>]). During the lecture, students were asked to consider features of six animal skeletons as data sources to construct an evolutionary tree where dog and cat are sister taxa; dog, cat, and rats are in a mammal clade; and fish is the outgroup clade (Fig. 2). Since different students may have drawn their evolutionary trees in different ways, to determine whether two diagrams actually represent the same evolutionary relationships, the "snip" rule was practiced. Figure 2A and B illustrate the "snip" rule by showing that the same relationships among taxa in a clade can be depicted in different ways. At the end of the lecture, a question was posed about additional data sources for evaluating the evolutionary relationships. To prepare for lab, students were asked to relate different animals by exploring the National Center for Biotechnology Information (NCBI) Taxonomy Browser. They added animals to a common tree (https://<ulink href="http://www.ncbi.nlm.nih.gov/Taxonomy/CommonTree/wwwcmt.cgi">www.ncbi.nlm.nih.gov/Taxonomy/CommonTree/wwwcmt.cgi</ulink>) as illustrated in Fig. 2C to address questions about vertebrate animal evolutionary history.</p> <p>Graph: Fig. 2 An example evolutionary tree for six animals based on pictures of their skeleton structures. The figure shows how disciplinary knowledge such as the meaning of nodes and a root is necessary to understand what a tree indicates about evolutionary relationships. The blue circle within the figure shows the bird together with the mammalian clade. Because the fish as an outgroup positions the root at the bottom of panel A, there is no way to "snip" off a clade with birds that contains frogs but not the rat, cat, and dog branch. In panel B, the branch with birds also contains the same relationship with the rat, cat, and dog branch so the relationship to common ancestors can be drawn and arranged in different ways (A or B) but still showing the same evolutionary relationships. In contrast, panel C is ambiguous because fish is not clearly indicated as the outgroup in a tree created with the NCBI data and Taxonomy Browser tool. If the root were at the node below "Chordata" in panel C, then a "snip" below the node with Mammalia would position birds on a branch with frog and fish. After drawing an evolutionary tree based on evidence from skeleton structures, the Taxonomy Browser tool does give more certainty to position cat and dog as sister taxa within a larger clade that includes the rat. But the tree in panel C is not the same as A or B according to disciplinary knowledge of the position of an ancestral root according to the identified outgroup. In terms of epistemological considerations, the NCBI tool raises questions about the relative positions of bird, frog, and fish and the need for more information about the data underpinning the NCBI data and Taxonomy Browser as evidence for confirmation</p> <p>In lab following the lecture, the lab instructor reviewed the necessary disciplinary knowledge for evolutionary tree-thinking. Table 4 shows the time allocation to each part of the lab. Task introduction took 20 min of lab time. As guided practice, teams of students reviewed the nature of phylogenetic trees under the guidance of their undergraduate peer leader by constructing an evolutionary tree for five animals based on anatomical structures from a table of data in the Phylogeny Assessment Tool (PhAT), according to Smith et al. ([<reflink idref="bib91" id="ref146">91</reflink>]). During this activity, students and a peer leader discussed evidentiary reasoning while making their own drawing of a phylogenetic tree, and then, as they compared their drawing to the two PhAT diagrams, they evaluated the nature, scope, and quality of data provided by Smith et al. ([<reflink idref="bib91" id="ref147">91</reflink>]) that underpin the evidence (epistemic consideration) as well as calling on their own disciplinary knowledge from readings, the lecture, and personal experience.</p> <p>Table 4 Lab activity timeline</p> <p> <ephtml> <table frame="hsides" rules="groups"><tbody><tr><td align="left"><p>Activity</p></td><td align="left"><p>Task introduction</p></td><td align="left"><p>Pre-task discussion</p></td><td align="left" colspan="2"><p>Task performance</p></td><td align="left"><p>Post-task discussion</p></td></tr><tr><td align="left"><p>Time</p></td><td align="left"><p>20 min</p></td><td align="left"><p>30 min</p></td><td align="left"><p>30 min</p></td><td align="left"><p>15 min</p></td><td align="left"><p>30 min</p></td></tr><tr><td align="left"><p>Format</p></td><td align="left"><p>Disciplinary knowledge introduced with a review of cladistics, homology, and convergent evolution (Fig. 1)</p></td><td align="left"><p>Scaffolded think-pair-share and class discussion of evolutionary tree examples in Fig. 2</p></td><td align="left"><p>Individual students use data (Table 5) to build an evolutionary tree</p></td><td align="left"><p>Groups of three students discuss their drawings to reach consensus on one evolutionary tree (Fig. 3)</p></td><td align="left"><p>Scaffolded class discussion of Table 5 data and critique of team consensus evolutionary trees</p></td></tr></tbody></table> </ephtml> </p> <p>After the task introduction, the lab instructor scaffolded evolutionary tree-thinking discussions about the lab task, as students planned to investigate blood parameters for ten different animal species. Lab instruction was recorded during pre-task, task performance, and post-task discussions. The investigation prompted students to use data from blood parameters for ten animal species (Table 5) and to consider relationships among the different species by constructing an evolutionary tree. Students were given a list of references to the original data sources (available as Supplementary Material, S1). The task is aligned with the idea that to promote epistemic growth, educators should provide students with an epistemically authentic learning environment but with bounded knowledge (Campbell, [<reflink idref="bib15" id="ref148">15</reflink>]; Chinn, et al., [<reflink idref="bib18" id="ref149">18</reflink>]). It is also in line with a recent focus on the need to consider the nature of the measurement which includes both a measure and the uncertainty (Plant et al., [<reflink idref="bib78" id="ref150">78</reflink>]). The task required evidentiary reasoning as students were expected to relate different theories in determining the structure of their evolutionary tree, they weighed different kinds of data and considered the quality of data coming from different sources in selecting evidence, and they paid close attention to the limitations of each kind of evidence in drawing their representation of an evolutionary tree.</p> <p>Table 5 Blood parameters as a data source for evolutionary tree-thinking^</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>Blood serum measures</p></th><th align="left"><p>Dog</p></th><th align="left"><p>Cow</p></th><th align="left"><p>Horse</p></th><th align="left"><p>Pig</p></th><th align="left"><p>Sheep</p></th><th align="left"><p>Rat</p></th><th align="left"><p>Guinea pig</p></th><th align="left"><p>Rabbit</p></th><th align="left"><p>Goose</p></th><th align="left"><p>Chicken</p></th></tr></thead><tbody><tr><td align="left"><p>Protein (g/L)</p></td><td char="–" align="char"><p>60–75</p></td><td char="–" align="char"><p>60–75</p></td><td char="–" align="char"><p>60–80</p></td><td char="–" align="char"><p>60–85</p></td><td char="–" align="char"><p>60–80</p></td><td char="–" align="char"><p>45–102</p></td><td char="–" align="char"><p>33–61</p></td><td char="–" align="char"><p>60–75</p></td><td char="." align="char"><p>45</p></td><td char="–" align="char"><p>29–43</p></td></tr><tr><td align="left"><p>pH (healthy arterial-venous range)</p></td><td char="–" align="char"><p>7.31–7.46</p></td><td char="–" align="char"><p>7.36–7.46</p></td><td char="–" align="char"><p>7.36–7.43</p></td><td char="–" align="char"><p>7.3–7.6</p></td><td char="–" align="char"><p>7.3–7.48</p></td><td char="–" align="char"><p>7.35–7.51</p></td><td char="–" align="char"><p>7.27–7.52</p></td><td char="–" align="char"><p>7.2–7.6</p></td><td char="–" align="char"><p>7.35–7.45</p></td><td char="–" align="char"><p>7.37–7.46</p></td></tr><tr><td align="left"><p>Sodium (mM)</p></td><td char="–" align="char"><p>142–152</p></td><td char="–" align="char"><p>136–144</p></td><td char="–" align="char"><p>128–142</p></td><td char="–" align="char"><p>135–150</p></td><td char="–" align="char"><p>139–152</p></td><td char="–" align="char"><p>89–144</p></td><td char="–" align="char"><p>82–140</p></td><td char="–" align="char"><p>138–150</p></td><td char="–" align="char"><p>136–156</p></td><td char="." align="char"><p>158</p></td></tr><tr><td align="left"><p>Chloride (mM)</p></td><td char="–" align="char"><p>110–124</p></td><td char="–" align="char"><p>93–107</p></td><td char="–" align="char"><p>98–104</p></td><td char="–" align="char"><p>94–106</p></td><td char="–" align="char"><p>95–103</p></td><td char="–" align="char"><p>79–111</p></td><td char="–" align="char"><p>83–105</p></td><td char="–" align="char"><p>85–105</p></td><td char="–" align="char"><p>97–115</p></td><td char="." align="char"><p>117.8</p></td></tr><tr><td align="left"><p>Bicarbonate (mM)</p></td><td char="–" align="char"><p>17–24</p></td><td char="–" align="char"><p>20–30</p></td><td char="–" align="char"><p>24–30</p></td><td char="–" align="char"><p>18–27</p></td><td char="–" align="char"><p>20–25</p></td><td char="–" align="char"><p>24–27</p></td><td char="." align="char" /><td char="." align="char" /><td char="–" align="char"><p>22–32</p></td><td char="–" align="char"><p>19–23</p></td></tr><tr><td align="left"><p>Urea nitrogen (mg/100 mL)</p></td><td char="–" align="char"><p>8–28</p></td><td char="–" align="char"><p>10–25</p></td><td char="–" align="char"><p>11–27</p></td><td char="–" align="char"><p>10–30</p></td><td char="–" align="char"><p>8–20</p></td><td char="–" align="char"><p>8–27</p></td><td char="–" align="char"><p>12–41</p></td><td char="–" align="char"><p>9–31</p></td><td char="–" align="char"><p>1–8</p></td><td char="–" align="char"><p>0.4–1.2</p></td></tr><tr><td align="left"><p>Glucose (mg/100 mL)</p></td><td char="–" align="char"><p>76–119</p></td><td char="–" align="char"><p>40–100</p></td><td char="–" align="char"><p>62–134</p></td><td char="–" align="char"><p>85–150</p></td><td char="–" align="char"><p>50–80</p></td><td char="–" align="char"><p>48–137</p></td><td char="–" align="char"><p>43–161</p></td><td char="–" align="char"><p>75–155</p></td><td char="–" align="char"><p>213–226</p></td><td char="–" align="char"><p>215–241</p></td></tr><tr><td align="left"><p>RBCs (× 10<sup>12</sup>/L)</p></td><td char="–" align="char"><p>4.95–7.87</p></td><td char="–" align="char"><p>5.0–10.0</p></td><td char="–" align="char"><p>5.0–10.0</p></td><td char="–" align="char"><p>6.0–10.4</p></td><td char="–" align="char"><p>5.0–8.0</p></td><td char="–" align="char"><p>5.0–11.4</p></td><td char="–" align="char"><p>3.4–6.9</p></td><td char="–" align="char"><p>5.0–8.0</p></td><td char="–" align="char"><p>2.0–3.6</p></td><td char="–" align="char"><p>2.5–4.5</p></td></tr><tr><td align="left"><p>packed-cell volume (PCV) hematocrit (% of total volume of blood plasma)</p></td><td char="–" align="char"><p>35–57</p></td><td char="–" align="char"><p>30–45</p></td><td char="–" align="char"><p>24–46</p></td><td char="–" align="char"><p>27–43</p></td><td char="–" align="char"><p>36–43</p></td><td char="–" align="char"><p>42–51</p></td><td char="–" align="char"><p>37–50</p></td><td char="–" align="char"><p>38–50</p></td><td char="–" align="char"><p>30–50</p></td><td char="–" align="char"><p>28–52</p></td></tr></tbody></table> </ephtml> </p> <p>^Students were given a reference list of original sources for these data. Supplementary Materials S1 provides the sources</p> <p>Scaffolding questions were implemented by the instructor during the pre-task discussion, task performance, and post-task discussions. Each discussion involved think-pair-share to give students the time to think about the evidence before a whole-class discussion about their evidentiary reasoning with evolutionary tree-thinking. After reasoning about evidence by participating in the pre-task scaffolded discussion, the instructor had individual students use data to build an evolutionary tree (task performance in Table 4). Then, the instructor had groups of three students compare their trees and discuss their use of evidence to reach consensus on one evolutionary tree. Finally, the instructor had one student draw their team's consensus tree on the white board. Afterwards, the instructor leads a discussion for everyone to participate in the scaffolded post-task discussion to compare and justify all the teams' trees. Both pre-task and post-task discussions were video recorded. Figure 3 provides three typical examples of different types of evolutionary trees that the teams depicted on the white board for discussion.</p> <p>Graph: Fig. 3 The instructor had a student draw their team's evolutionary tree on a white board for whole-class discussion. Different evolutionary trees were depicted by different groups even though they all used Table 5 as their data source. The instructor had students analyze different kinds of evidence as illustrated by the trees from Orange, Yellow, and White teams who chose what to focus on as they interpreted the clades differently. The tree from the Orange team illustrated how to consider and combine multiple sorts of evidence from the data table provided. The guinea pig and rat as sister taxa were put on the same branch with chicken and goose based on protein levels. The Yellow team used at least three different kinds of evidence. Their evolutionary tree shows a typical answer where goose and chicken as sister taxa make up an outgroup clade, and the mammals are assigned into several clusters or clades. The White team used their previous knowledge (birds with wings versus "No W") and only glucose levels from the data provided as evidence. They put the goose and chicken as sister taxa without putting any of the mammals into different clusters. The instructors' scaffolded post-task discussion was meant to engage everyone to participate in considering how the different teams used evidence to draw different conclusions about the chronology of life by comparing and justifying the different trees such as these (Photos of the white board drawings were traced for clarity.)</p> <hd id="AN0181133845-12">Instructor Professional Development with the CADE Framework</hd> <p>Lab discussions were recorded and examined at baseline in Fall 2017. For each of the three semesters (Spring 2018-Spring 2019), a 40-min professional development workshop was held 2 weeks before the target lab. At workshops, the lab instructors were given relevant excerpts from recorded lab discussions, but they did not participate in the process of video data analysis. Then, CADE (Tables 1, 2, and 3) was introduced to the lab instructors by the researchers (the first and last authors). Scaffolding questions from baseline instruction transcripts were modified or new prompts (GES versus DES) were developed according to the CADE framework by participant lab instructors in collaboration with the researchers. The workshop focused on how to use the three relationships (<emph>E</emph> = > <emph>T</emph>, <emph>E ⟺ D</emph>, <emph>T</emph> = > <emph>E</emph>) identified by CADE to inform the development or improvement of scaffolding questions relevant to constructing evolutionary trees. Each scaffolding question aimed to prompt evidentiary reasoning by revealing one or more of the subcategories within each relationship of the CADE framework. A project timeline for the data reported here is available as Supplementary Material, S2. In addition, each semester, the researchers collaborated with the instructors to adapt the scaffolding questions based on implementation data from a previous DBR cycle and the finalized questions were included as part of the lesson plan.</p> <p>For the baseline lesson, discussion questions were suggested in a lesson plan for instructors by the course professor and actual discussion questions during teaching were examined without any influence from the CADE framework. After professional development for all of the teaching staff with the CADE framework, both GES and DES lesson plans were implemented in various lab sections for the following three semesters. Participant instructors also asked students for elaboration with follow-up questions that were not in the lesson plan. Except for the difference in suggested scaffolding questions designed for different parts of the lab task, the baseline, GES, and DES lesson plans were identical.</p> <hd id="AN0181133845-13">Data Analysis</hd> <p>CADE was used as a coding scheme for data analysis. Lesson plans were segmented by scaffolding questions. Video recordings from baseline, DES, and GES treatments were collected in English, transcribed and segmented by scaffolding questions. Each scaffolding question and discussion segment were coded according to three types of relationships of relevance to evidence shown in Tables 1, 2, and 3. In each table, the first column shows the science practice related to that relationship, the second column shows the biology disciplinary knowledge that was required for reasoning, and the third column shows the epistemic considerations of relevance to the corresponding evidentiary reasoning. For example, a <emph>T</emph> = > <emph>E</emph> relationship includes disciplinary knowledge of what variables are relevant, etc., according to theoretical knowledge of biology. The corresponding epistemic consideration is whether relationships between variables have been clearly specified. An <emph>E⟺D</emph> relationship includes disciplinary knowledge of how the variables are defined. The corresponding epistemic consideration is whether variables are clearly defined in terms of accurate measurement.</p> <p>A first order or primary coding aimed to break down data into semantically distinct chunks or categories while staying as close to the participants' original meaning as possible. The first author inductively coded all the data for the first pass, and then, to enhance the accuracy of the findings, the strategy of "peer debriefing to enhance the accuracy of the account" was used as suggested by Creswell and Creswell ([<reflink idref="bib20" id="ref151">20</reflink>]). The last author, who is an experienced researcher on evolutionary tree-thinking, played the role of peer debriefer by consistently raising questions about the coding. All disagreements raised during the second pass were discussed until consensus. For the second order coding, the first-order primary codes were grouped and categorized based on our theoretical judgments of how they inform or relate to categories in the CADE framework. All first-tier chunks with the features of each quote were carefully described and then grouped to align the initial codes with CADE categories by the two coders (see Table 6). In most cases, the two coders did not change the code but instead clarified the category within CADE more carefully until consensus among two co-authors was reached.</p> <p>Table 6 Examples of scaffolding questions that were raised to prompt evidentiary reasoning</p> <p> <ephtml> <table frame="hsides" rules="groups"><tbody><tr><td align="left"><p>Discussion</p></td><td align="left" /><td align="left"><p>CADE</p></td></tr><tr><td align="left" colspan="3"><p>Baseline scaffolding questions</p></td></tr><tr><td align="left"><p>Pre-task</p></td><td align="left"><p><italic>The instructor gave instructions but no questions about evidentiary reasoning to prepare students for the task</italic></p></td><td align="left" /></tr><tr><td align="left" rowspan="4"><p>Post-task</p></td><td align="left"><p>There were nine variables. Which ones did you guys find most useful and are there any that you did not find? So what about the protein levels? Raise your hand if you guys as groups found that to be a helpful way to help differentiate. (Q1)</p></td><td align="left"><p>E ⟺ D: Are different types of data collected from diverse measures and trials to provide support?</p><p>Are the models used appropriate?</p></td></tr><tr><td align="left"><p>So, do you guys think that you have enough evidence to have confidence in that tree? (Q2)</p></td><td align="left"><p>E = > T: Are limitations discussed?</p></td></tr><tr><td align="left"><p>Do all these trees, did you guys interpret the evidence all in the same way? Using the snip rule we discussed earlier? (Q3)</p></td><td align="left"><p>E= >T: How does the evidence distinguish between multiple interpretations or hypotheses?</p></td></tr><tr><td align="left"><p>... how similar are your evidence to previously established reports? So, on things we currently know about the species or if you guys after you come up your trees look up what the tree for the NCBI looks like. How many of you guys found that your tree was pretty consistent with already established knowledge? (Q4)</p></td><td align="left"><p>E= >T: Are the conclusions aligned with what is known?</p><p>Are limitations discussed?</p></td></tr><tr><td align="left" colspan="3"><p>GES scaffolding questions</p></td></tr><tr><td align="left"><p>Pre-task</p></td><td align="left"><p>What do you guys notice about the ranges of data present here? What do you think about this range of data? So, knowing that some specific data points are given a wide range. And some data for certain conditions are given pretty much no range or a very short range, what can you guys say? What would you say about the quality of the data? (Q1)</p><p>I'm asking you guys what data you think will look the most helpful for you for making your tree? (Q4)</p></td><td align="left"><p>E ⟺ D: Is technical precision, power, sensitivity, reliability, of data collection procedures adequate?</p><p>Have potential sources of error and confounding factors been evaluated?</p></td></tr><tr><td align="left" /><td align="left"><p>Think of anything in the world which ... we could get you but if ... you can request additional data would you guys want to request additional data? And if so, what? (Q7)</p></td><td align="left"><p>T= >E: Is relevant evidence used to render the question, hypothesis plausible? (DES)</p><p>Is articulated model complete, specific, and internally consistent?</p></td></tr><tr><td align="left"><p>Post-task</p></td><td align="left"><p>So, which one of you guys are right? How many of you think there is no right answer, raise your hand? (Q8)</p></td><td align="left"><p>E= >T: How does the evidence distinguish between multiple interpretations or hypotheses?</p></td></tr><tr><td align="left" /><td align="left"><p>So, with that does anybody think that if they were to compare this data to kind of previous data in the literature it would align like very closely? Is there anything odd about the data that surprised them, or was it all what you guys expected to see? (Q10)</p></td><td align="left"><p>E= >T: Are the conclusions aligned with what is known?</p><p>Are limitations discussed?</p></td></tr><tr><td align="left" colspan="3"><p>DES scaffolding questions</p></td></tr><tr><td align="left"><p>Pre-task</p></td><td align="left"><p>... looking at the data we have here we have various compounds to get overall osmolarity, red blood cell count. So, looking at these different data sources why do you think biologists would care about that? (Q1)</p></td><td align="left"><p>T= >E: Is relevant evidence used to render the question, hypotheses plausible?</p></td></tr><tr><td align="left" /><td align="left"><p>... What if I told you specifically to look in the protein data, what would you tell me looking at some of these ranges here? (Q2)</p><p>So, with that what do you think would count as the strongest evidence here? To place an animal count in its own separate out group. Is there any data that jumps out at you for ... finding an outgroup? (Q4)</p></td><td align="left"><p>E ⟺ D: Is technical precision, power, sensitivity, reliability, of data collection procedures adequate?</p><p>Have potential sources of error and confounding factors been evaluated?</p></td></tr><tr><td align="left"><p>Post-task</p></td><td align="left"><p>Does anybody have any ideas ... to find more certainty about the chronology of this? What other kind of experiment you can do other data you might collect to give you more certainty on chronology? (Q8)</p></td><td align="left"><p>E ⟺ D: Are different types of data collected from diverse measures and trials to provide support? </p></td></tr><tr><td align="left" /><td align="left"><p>So, first step using the snip rule ..., did you guys all come up with the same evolutionary relationship? ... No? So are you guys able to determine which one is right, and which one is wrong? (Q9)</p></td><td align="left"><p>E= >T: How does the evidence distinguish between multiple interpretations or hypotheses?</p></td></tr></tbody></table> </ephtml> </p> <p>CADE unpacks the notion of evidence and offers a rather complex framework for people other than learning scientists. To maintain rigor, we chose to use consensus coding method throughout our coding processes (Richards & Hemphill, [<reflink idref="bib82" id="ref152">82</reflink>]). Compared to just interrater reliability, consensus coding allowed us to discover complexities in the data (Denzin and Lincoln, [<reflink idref="bib25" id="ref153">25</reflink>]; Stanton et al., [<reflink idref="bib94" id="ref154">94</reflink>], [<reflink idref="bib95" id="ref155">95</reflink>]).</p> <hd id="AN0181133845-14">Findings</hd> <p>Our research questions were as follows:</p> <p></p> <ulist> <item> How did CADE influence scaffolding for GES and DES during an evolutionary tree-thinking task?</item> <p></p> <item> What challenges remain in scaffolding GES and DES for evolutionary tree-thinking?</item> </ulist> <p>To answer our first research question, we compared baseline instruction with GES and DES lesson plans and lab implementations in terms of scaffolding intended to elicit ideas about evidence. Even though the baseline discussion questions were not developed using the CADE, they were found to align with several aspects of CADE. To answer our second research question, we provide a qualitative description of the difficulties shown in GES and DES discussion processes.</p> <p>The findings address the research questions about changes in teaching practices associated with facilitating students' evidentiary reasoning. Overall, the findings suggest that compared with the baseline, with CADE, the lab instructor included more scaffolding questions, providing the students with opportunities to delve into more aspects of evidentiary reasoning. However, to answer the second research question, we found that the lab instructor still had difficulty with limitations and the specific roles of evidence in testing an explanatory model.</p> <hd id="AN0181133845-15">How Did CADE Influence the Scaffolding for GES and DES Treatments?</hd> <p>CADE improved the lab instructor's ability to design scaffolding questions aiming to target more relationships and subcategories identified within each relationship unpacked by CADE (2 vs. 3 relationships, and 4 vs. 10 subcategories) in the lesson plans. In baseline, only four out of fourteen subcategories were targeted from <emph>T</emph> = > <emph>E</emph> and <emph>E</emph> = > <emph>T</emph> relationships, guiding students' evidentiary reasoning from identifying the key phenomena and plausible theories (<emph>T</emph> = > <emph>E</emph>) and evaluating the completeness and external consistency of the conclusion (<emph>E</emph> = > <emph>T</emph>). The baseline scaffolded discussion failed to guide evidentiary reasoning in several ways: 1. The instructor failed to facilitate evidentiary reasoning regarding the <emph>E</emph>⟺<emph>D</emph> relationship: designing, executing, and analyzing investigations as a whole and in terms of the uncertainty in measured values; 2. The instructor did not facilitate evidentiary reasoning in terms of considering the specific relationships between variables when formulating testable hypotheses (<emph>T</emph> = > <emph>E</emph>); 3. The instructor did not guide the students to consider the internal consistency or limitations of evidence and did not provide opportunities to think about generating alternative conclusions when evaluating the sufficiency of conclusions (<emph>E</emph> = > <emph>T</emph>) (see Tables S3–S5).</p> <p>Compared to baseline, both GES and DES treatments were able to facilitate students' evidentiary reasoning more comprehensively by targeting all three relationships unpacked by CADE, from <emph>T</emph> = > <emph>E</emph>, <emph>E</emph>⟺<emph>D</emph>, to <emph>E</emph> = > <emph>T</emph>. However, there were still some subcategories within each relationship that were not covered: consideration about alternative models (<emph>T</emph> = > <emph>E</emph>), consideration about the nature of variables being measured (<emph>E</emph>⟺<emph>D</emph>), and evaluation of the completeness and internal consistency of conclusions (<emph>E</emph> = > <emph>T</emph>) (see Tables S1–3).</p> <p>Overall, there is still room for improvement. The CADE framework revealed some gaps in the instructional plans related to relationships key to evidentiary reasoning. However, CADE guided improvements in the design of more comprehensive and practical scaffolding questions by targeting more subcategories and relationships to prompt students' evidentiary reasoning.</p> <hd id="AN0181133845-16">How Did CADE Influence the Implementation of Scaffolding for GES and DES Treatments?</hd> <p>Table 6 presents examples of raw data for scaffolding questions that have been asked in baseline, GES, and DES labs (see Tables S6–S8 for comprehensive data) The examples demonstrate the features of GES and DES questions and how those questions target different aspects of evidence unpacked in the CADE. In Table 6, the second column shows the scaffolding questions that were implemented in the baseline, the DES, and the GES lab sections respectively. The third column shows the CADE relationships that were targeted by scaffolding questions from each iteration. Table 6 only shows how each question targets different subcategories of CADE in terms of epistemic considerations. However, the corresponding disciplinary knowledge aligned with the epistemic considerations was also targeted by the DES questions, as indicated by the disciplinary knowledge underlined in each DES question shown in the second column of the table.</p> <hd id="AN0181133845-17">Findings</hd> <p>Overall, compared to baseline, both GES and DES approaches provided students with more scaffolding to get students through the evidentiary reasoning process. Lesson plans were implemented basically as they were intended. In addition to the planned scaffolding questions, the instructor used many follow-up questions to help guide the discussion. In baseline lab, the instructor used everyday language, including figures of speech the students might use. After the CADE training, the instructor was able to use questions that are more formal, using concise scientific language. Specifically, in the baseline lab, even though the lesson plan expected the lab instructor to consider the relevant disciplinary knowledge including homology, homoplasy, and chronology, no scaffolding question was used to inform students' evidentiary reasoning during the pre-task discussion. In the post-task discussion, scaffolding questions facilitated students' evidentiary reasoning from the <emph>E</emph>⟺<emph>D</emph> and <emph>E</emph> = > <emph>T</emph> relationships. Students were provided with opportunities to think about if the models used are appropriate (<emph>E</emph>⟺<emph>D</emph>), if limitations about evidence had been discussed, how the evidence would help distinguish between multiple interpretations or hypothesis, and if the conclusions aligned with what is known (<emph>E</emph> = > <emph>T</emph>). The baseline implementation process was different from the lesson plan, which may be because the lab instructor was unfamiliar with the scaffolding questions designed by the course professor.</p> <p>In the DES treatment, ten scaffolding questions were implemented during the discussions: seven in pre-task discussion and three in post-task discussion when the different evolutionary tree findings were examined. During the implementation process, most of the questions from the lesson plan were broken down and divided into several smaller questions that were actually asked. Several pre-task scaffolding questions from the DES lesson plan (Q6 and 7 in Table S7) explicitly asked the students to relate their study with the idea biologists have about the chronology of evolutionary processes that produced diversification (<emph>T</emph> = > <emph>E</emph>: linking the disciplinary knowledge about the possible mechanisms, causal relationships, and processes to the epistemic consideration if articulated model is complete, specific, and internally consistent). It is interesting to note, however, that one question asked during pre-task discussion in the DES treatment had no link to any disciplinary knowledge, as indicated by the box with nothing underlined in the first column of Table S7 (see Q3).</p> <p>Overall, in the DES treatment, all three relationships of CADE were addressed in the discussions. The scaffolding questions emphasized <emph>T</emph> = > <emph>E</emph> and <emph>E</emph>⟺<emph>D</emph> relationships during task preparation and a focus that shifted toward the <emph>E</emph>⟺<emph>D</emph> and <emph>E</emph> = > <emph>T</emph> relationships in discussing the findings, which is as one might expect for the research process. All subcategories within CADE were covered except three, whether alternative models or theories are considered (<emph>T</emph> = > <emph>E</emph>), are variables defined in a way that is valid for the model (<emph>E</emph>⟺<emph>D</emph>), and are the conclusions aligned with what is known (<emph>T</emph> = > <emph>E</emph>). The three subcategories not covered could be due to the nature of our task and/or limitations of lab time. These subcategories could be targeted by using other tasks, such as use of the NCBI tool (https://<ulink href="http://www.ncbi.nlm.nih.gov/Taxonomy/CommonTree/wwwcmt.cgi">www.ncbi.nlm.nih.gov/Taxonomy/CommonTree/wwwcmt.cgi</ulink>) to construct an evolutionary tree with the animals in Table 5 and Fig. 2C (targeting <emph>T</emph> = > <emph>E</emph> subcategory: are the conclusions aligned with what is known). This was done without using any scaffolding due to the lab time limit and impending end of class.</p> <p>In the GES treatment, it is interesting to note that even though eleven scaffolding questions were implemented in total, including seven in pre-task discussion and four in post-task discussion, the <emph>T</emph> = > <emph>E</emph> relationship of whether relevant evidence was used to render the question or hypotheses plausible was missing. Just as was the case for the DES treatment, during the GES scaffold implementation process, most questions from the lesson plan had been divided into several smaller questions that were actually discussed, and all GES scaffolding questions from the lesson plan were addressed during the implementation. As was the case for the DES treatment, all three relationships of CADE were addressed in the discussions with emphasis shifting toward <emph>E</emph> = > <emph>T</emph> relationships in discussing the findings. Finally, the scaffolding questions that had been asked in DES and GES treatments were not exactly aligned with each other (see Tables S7 and S8). In addition to the lack of a GES scaffolding question about evidence decisions being informed by disciplinary knowledge (DES Q1 in Table S7), no DES scaffolding questions corresponded with the GES scaffolding questions about data sources and quality during pre-task discussion (GES Q3 in Table S7) or about patterns noticed or odd data in the findings (GES Q9 in Table S8) were discussed in the GES treatment lab section.</p> <p>In summary, lesson plans were implemented basically as they were intended, with only a few misalignments: (<reflink idref="bib1" id="ref156">1</reflink>) The scaffolding questions were divided into several smaller questions to make students more comfortable and their evidentiary reasoning easier to follow; (<reflink idref="bib2" id="ref157">2</reflink>) The DES questions revised to be GES questions failed to link epistemic considerations with the corresponding biology disciplinary knowledge; (<reflink idref="bib3" id="ref158">3</reflink>) There was no GES question about informing choices of evidence with disciplinary knowledge and there were no DES questions corresponding to GES questions for prompting students to reflect upon the advantage and disadvantages of the various sources of data, or to ask students to think about the model they used in terms of different pieces of evidence and the conclusion they drew from their model. Compared to baseline questions, GES and DES questions provided students with more opportunities for evidentiary reasoning. As there were no corresponding baseline questions in the pre-task discussion, those students did not receive any guidance for thorough observation and reasoning about the data before letting them think on their own about which pieces of data could serve as evidence for their study.</p> <hd id="AN0181133845-18">What Challenges Remain in the Implementation of Discussion Process Informed by CADE?</hd> <p>One of the challenges found was how often the instructors asked for majority consent, as illustrated by the following quote from the instructor:Just show of hands how many of you guys feel like it is overall a net positive that this data comes from a variety of sources? How many of you guys feel like it is a net negative? (Discussion for pre-task discussion following a GES question)</p> <p>This quote illustrates how the lab instructor asked for majority agreement instead of raising a discussion of uncertainty in the measured values. During the whole discussion process, the lab instructor tended to ask students' opinions by counting the number of hands. This tendency was consistent from baseline to DES and GES treatments. According to the instructor, the rationale was to encourage student participation. "I feel like you have them answer your question. It is like I am saying I think this is the right answer. So, this is scary for everybody to think they are wrong." Even though this strategy provided students an opportunity to participate in a more comfortable way than answering the question individually, it could potentially mislead the students who are outvoted into thinking that they are wrong (Turner, [<reflink idref="bib101" id="ref159">101</reflink>]). Such students might feel discouraged from sharing their opinions and reasoning process. Clearly, these were not questions designed to launch a productive evidentiary reasoning discussion.</p> <p>Another challenge was found when the instructor wrapped up a discussion as follows:Yep, urea nitrogen, so that is also helpful because you see when you look at them, it is the same two that are different between both the red blood cell count and urea nitrogen. So, the point for this is sometimes you might use different data amongst your groups because each [member] of your group is going to develop their tree for this data but come up with the same conclusion. So that one of the points here is you guys are given 10 values to find this helpful or unhelpful as you would like. So red blood cell counts, urea nitrogen, and various others you guys might find helpful for finding the main outgroup. (Discussion for Task Preparation following a DES question)</p> <p>Here, this example shows where the lab instructor missed an opportunity to delve more deeply into the nature of science. It is essential to point out that urea nitrogen and red blood cell count are two different kinds of data that could be used in determining and then confirming the evolutionary relationship with convergent evidence. When constructing an evolutionary tree, the similar patterns of these two pieces of evidence show the internal consistency of the data, which can help the students in triangulating their conclusion. However, by saying "you might use different data amongst your groups," the lab instructor was indicating that urea nitrogen and the red blood cell count data were redundant as they shared a similar distribution pattern. Instead, the lab instructor could have emphasized the importance of convergent evidence in confirming and strengthening claims.</p> <p>Moreover, in wrap-up discussions, the instructor sometimes dwelled on disciplinary knowledge without relinking to general evidence as follows:<emph>The lab instructor repeated a student's idea:</emph> Okay, possibly overall blood composition in some of the different cell types present in the blood.<emph>Lab instructor follow up</emph>: Anybody else have any other data they think might be cool to add?Student: Bone structure.<emph>Lab instructor: </emph>Okay, so the point is, is.... there are many different ways and many different evidence types that biologists will use to try to get the chronology of an evolutionary history together. (Discussion for Task Preparation following a DES question)</p> <p>Here, the lab instructor wrapped up by dwelling on disciplinary knowledge without relinking to general evidence discussion in terms of the importance of convergent evidence. The lab instructor was asking students to think about additional evidence that they would like to use while constructing their evolutionary tree. Following the scaffolding question, students provided their answers by focusing on disciplinary knowledge without further explanations and reasoning. They did not mention what property of blood or bones could vary among the species in a way that would reveal the patterns. The lab instructor did not use the follow-up questions as a scaffold to direct students' thinking into a more in-depth way and to guide their discussion back to epistemic considerations of variable properties. Instead, the lab instructor wrapped up the scaffolding question by saying biologists would collect different kinds of data to get the chronology of evolutionary history. Similar to the students, the lab instructor did not provide any deeper thinking or explanation about chronology, nor did she provide any general evidence discussion about the importance of obtaining evidence for chronology of evolutionary history. Compiling a list of parts without considering their properties does not launch a productive discussion about the evidence.</p> <p>Overall, further analysis by using CADE suggests that the lab instructor still had difficulty scaffolding the limitations and the specific roles of the evidence in setting up a testable model. This may indicate lack of proper scope of disciplinary knowledge and/or epistemic considerations.</p> <hd id="AN0181133845-19">Summary and Discussion</hd> <p>The aim of this study was to observe the impact on scaffolding designed to engage students with evidentiary reasoning when a laboratory instructor used CADE as a framework for planning how to support first-year undergraduate students to reason with and about biological evidence during an evolutionary tree-thinking investigation. We were interested in understanding whether the CADE framework can guide the development of evidence scaffolding and focus a lab instructor's attention on facilitating students' evidentiary reasoning. Findings based on detailed qualitative analysis of discussions led by one instructor before and after workshops to improve instruction with CADE suggest it to be a practical framework for instructors to plan and implement how to facilitate and scaffold students' evidentiary reasoning. CADE unpacks the construct of evidence, providing the instructor with a feasible guideline for designing and facilitating discussions. Compared to baseline, the instructor became better able to scaffold students' evidentiary reasoning more comprehensively, providing opportunities for students to observe and analyze data from different aspects and dimensions of evidence. CADE focused the lab instructor on both disciplinary and epistemological features of evidence, specifically for evolutionary tree-thinking. Findings also reveal areas where there is room for improvement for instructors who aim to lead better quality class discussion to develop students with evidentiary reasoning through guided practice.</p> <p>The research question on how CADE influenced the development and implementation of scaffolding was answered by examining instruction at baseline and after workshops to observe how the scaffolding for discussions was modified based on CADE. It was feasible for the instructor to encourage different kinds of epistemic considerations and to prompt the corresponding biological disciplinary knowledge with guidance from CADE, both as part of pre-task and post-task discussions. In lab discussions, the instructor was able to guide students to connect epistemological features of evidence and disciplinary knowledge, for why and in what sense a piece of data would count as part of the total evidence used in drawing a conclusion (Chinn et al., [<reflink idref="bib17" id="ref160">17</reflink>]; Giere, [<reflink idref="bib38" id="ref161">38</reflink>]; Samarapungavan, [<reflink idref="bib86" id="ref162">86</reflink>]).</p> <p>In this study, two kinds of scaffolding, GES and DES, were implemented by the same lab instructor in two different lab sections. A difference was found in the implementation of general evidence scaffolding (GES) compared with disciplinary evidence scaffolding (DES) treatment in this study. With GES, the discussion surrounding use of the data was not informed by disciplinary knowledge of relevance to the investigation such as homoplasy, homology, or using an outgroup to position the root in ways that relate to the chronology represented in an evolutionary tree. This was surprising for the current study since the instructor had previously been involved with teaching this material, which the students had studied in lecture. Moreover, one might think that certain practices are intrinsically grounded in the discipline and cannot be talked about generally in the absence of disciplinary understanding of what needs to be considered. Thus, the GES scaffold was too broad to cue the discussion toward the knowledge and reflection needed for reasoning about the evidence. Furthermore, even with GES during the pre-task discussion, the students were not encouraged to make decisions about the uncertainty in the measured values, which reinforces the need to discuss principles of measurement science in agreement with Plant et al. ([<reflink idref="bib78" id="ref163">78</reflink>]). In fact, the disciplinary part of CADE in both treatments highlights considerations that are clearly important in the planning stage for any research study, where connections are needed between the epistemological features of evidence and the relevant disciplinary knowledge. Thus, CADE may help an instructor more effectively discuss a research study task with disciplinary evidence scaffolds and not isolated general scaffolds.</p> <p>Findings from the current study also reveal several challenges with implementation of discussion processes informed by CADE. First, although the lab instructor was able to scaffold students' evidentiary reasoning process more comprehensively with CADE, she was dwelling on disciplinary knowledge without linking to general epistemic considerations during a discussion. This finding indicates that to facilitate evidentiary reasoning effectively, instructors should keep the CADE framework in mind throughout the whole discussion. Second, as instructors increasingly shift toward a disciplinary focus as recommended by Sandoval and Reiser ([<reflink idref="bib88" id="ref164">88</reflink>]), Samarapungavan ([<reflink idref="bib86" id="ref165">86</reflink>]), and others (National Academies of Sciences, Engineering, and Medicine., [<reflink idref="bib69" id="ref166">69</reflink>]), they need to recognize the importance of linking the disciplinary knowledge to the relevant epistemic considerations essential to construct comprehensive evidentiary reasoning. Third, CADE as a framework can alert instructors to habits that fail to promote evidentiary reasoning, such as asking for an opinion vote with a show of hands without a follow-up to ask for reasoning about evidence to explain the show of hands. Consensus in science is based on the strength of evidence and not a majority of votes. Instructors should explicitly relay that to students and encourage them to engage in evidentiary reasoning. Instructors who use the CADE to frame the direction of an entire lab conversation could become more sensitive about when to redirect the conversation and to connect disciplinary knowledge with the relevant epistemic considerations.</p> <p>There are several limitations to this study. First, only data from one instructor was examined in this paper. There is a need to examine how a broad sample of instructors understand CADE and how they integrate CADE with their prior experiential and pedagogical knowledge in making instructional decisions to support students' evidentiary reasoning in laboratory research discussions. Furthermore, more detailed measures of instructors' disciplinary knowledge are needed. The instructor in this study was a developing scientist and a senior undergrad student who is certainly not typical of most lab instructors, even though the reality is that large-enrollment lab courses are heavily taught by novice science instructors. The instructor in the present study did not understand the disciplinary knowledge about the role of an outgroup for reference as important to defining the root of a clade. Such observations suggest that gaps in an instructor's disciplinary knowledge related to the lab activity may impact the results. In spite of these limitations, our findings suggest that CADE can facilitate planning and implementation of instruction aiming to guide students' evidentiary reasoning in laboratory investigations. CADE helped the instructor plan and implement scaffolds for connecting evidence to its disciplinary context in discussing evidentiary reasoning.</p> <p>This study has implications for future studies aimed at examining students' evidentiary reasoning and for teachers who facilitate such reasoning in science learning. Specifically, our findings suggest the importance of deconstructing and unpacking the abstract and complex features of evidence. Researchers and recent curricular reform documents have advocated for an understanding of the construct of evidence as well as the relationships between evidence and the knowledge or belief it justifies (Brewer & Smith, [<reflink idref="bib10" id="ref167">10</reflink>]; Mayr, [<reflink idref="bib63" id="ref168">63</reflink>]; NGSS lead States, [<reflink idref="bib73" id="ref169">73</reflink>]). However, our use of CADE is among the first attempts to provide instructors with a feasible way to apply the ideas about evidence when students perform investigations. Further connections between epistemological features of evidence and the theories, technologies, instruments, and literature behind and beyond the evidence for different types of investigations are necessary to help students with evidentiary reasoning. Future studies could advance and develop and examine CADE within a broader range of investigations than the evolutionary tree-thinking task explored in the current study.</p> <p>Both GES and DES treatments brought about a productive, comprehensive conversation, by covering most of the relevant CADE subcategories of relevance to evidentiary reasoning about the evolutionary tree-thinking task in the current study. The present study provides a feasible theoretical and analytic framework for instructors to explain the concept of evidence in order to facilitate their students' evidentiary reasoning; the present study makes several additional contributions. The current study supports the effectiveness of scaffolding for facilitating discussions about evidence (Koslowski et al., [<reflink idref="bib47" id="ref170">47</reflink>]; Masnick and Klahr., [<reflink idref="bib61" id="ref171">61</reflink>]; Russ et al., [<reflink idref="bib83" id="ref172">83</reflink>]; Ryu & Sandoval, [<reflink idref="bib84" id="ref173">84</reflink>]; Sandoval & Cam, [<reflink idref="bib87" id="ref174">87</reflink>]). Future studies could make significant advances by developing and examining a pedagogical toolkit based on evidence for situations where GES or DES may be the preferred scaffold approach. Studies can examine how to combine both ways most effectively together, such as using GES question as an entry point to generate conversation, bringing in DES as follow-up questions to ensure the corresponding disciplinary knowledge is emphasized and related to the epistemic considerations, and linking back to the epistemic considerations by using GES questions to wrap up the discussion if necessary.</p> <p>Moreover, this study provides a starting point for combining CADE as an entry to introduce other types of pedagogical knowledge needed especially by undergraduate lab instructors, many of whom are teaching lab students without much training (Kendall & Schussler, [<reflink idref="bib45" id="ref175">45</reflink>]). Even though the participant in this study was an experienced lab instructor who had gained some general pedagogical knowledge by experience, she had not received educational training regarding pedagogical content knowledge or scaffolding beyond the limited professional development provided for the specific evolutionary tree-thinking context for this study. Her implementation of CADE into planning the discussion process helped to facilitate group discussions before, during, and after the activity. As a result, the instructor gained awareness of the aim to connect the epistemic considerations with the corresponding disciplinary knowledge to be emphasized. This effort may help to support instructors with limited training to be more responsive to students' ideas (Levin et al., [<reflink idref="bib52" id="ref176">52</reflink>]). Here, we advocate that professional development will provide the instructor with pedagogical knowledge for the best practices of facilitating discussion about evidence.</p> <p>Finally, this study provides a model of how to facilitate students' evidentiary reasoning in ways that could be further developed, such as by combining small group and interactive teaching approaches using scaffolding questions. This study also provides insight that could be applied to instructional approaches, such as direct instruction and individual seatwork, where scaffolding questions can be incorporated into a worksheet for students to reflect on and discuss. GES and DES scaffolding questions can also be integrated into formative assessments in order to understand students' evidentiary reasoning in order to help them with difficulties that have not yet been documented.</p> <hd id="AN0181133845-20">Acknowledgements</hd> <p>First, we gratefully acknowledge the editor and three anonymous reviewers whose feedback helped us more narrowly focus this report. We also thank members of our research collaborators focused on Exploring Biological Evidence for their contributions to the progress of our study. Thanks go to Soo Won Shim for thoughtful discussions during the course of our research. We especially thank our laboratory class teaching staff and students for willingly participating in this study.</p> <hd id="AN0181133845-21">Funding</hd> <p>This work was supported by the National Science Foundation under grant #1661124.</p> <hd id="AN0181133845-22">Declarations</hd> <p></p> <hd id="AN0181133845-23">Conflict of Interest</hd> <p>The authors declare no competing interests.</p> <hd id="AN0181133845-24">Disclaimer</hd> <p>Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.</p> <hd id="AN0181133845-25">Supplementary Information</hd> <p>Below is the link to the electronic supplementary material.</p> <p>Graph: Supplementary file1 (DOCX 33 KB)</p> <hd id="AN0181133845-26">Publisher's Note</hd> <p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p> <ref id="AN0181133845-27"> <title> References </title> <blist> <bibl id="bib1" idref="ref1" type="bt">1</bibl> <bibtext> Abd-El-Khalick F, Boujaoude S, Duschl R, Lederman NG, Mamlok-Naaman R, Hofstein A, Tuan HL. Inquiry in science education: International perspectives. Science Education. 2004; 88; 3: 397-419. 10.1002/sce.10118</bibtext> </blist> <blist> <bibl id="bib2" idref="ref2" type="bt">2</bibl> <bibtext> Abraham JK, Meir E, Perry J, Herron JC, Maruca S, Stal D. Addressing undergraduate student misconceptions about natural selection with an interactive simulated laboratory. Evolution: education and outreach. 2009; 2; 3: 393. 10.1007/s12052-009-0142-3</bibtext> </blist> <blist> <bibl id="bib3" idref="ref77" type="bt">3</bibl> <bibtext> Abraham JK, Perez KE, Downey N, Herron JC, Meir E. Short lesson plan associated with increased acceptance of evolutionary theory and potential change in three alternate conceptions of macroevolution in undergraduate students. CBE—Life Sciences Education. 2012; 11; 2: 152-164. 10.1187/cbe.11-08-0079</bibtext> </blist> <blist> <bibl id="bib4" idref="ref60" type="bt">4</bibl> <bibtext> Anderson LW, Krathwohl DR, Airasian PW, Cruikshank KA, Wittrock MC. A taxonomy for learning, teaching, and assessing: A revision of Bloom's taxonomy of educational objectives. Longman. 2001. 10.1002/tea.10053</bibtext> </blist> <blist> <bibl id="bib5" idref="ref89" type="bt">5</bibl> <bibtext> Ayala FJ. Science, evolution, and creationism. Proceedings of the National Academy of Sciences. 2008; 105; 1: 3-4. 10.1073/pnas.0711608105</bibtext> </blist> <blist> <bibl id="bib6" idref="ref113" type="bt">6</bibl> <bibtext> Baldwin RG, Wawrzynski MR. Contingent faculty as teachers: What we know; what we need to know. American Behavioral Scientist. 2011; 55; 11: 1485-1509. 10.1177/0002764211409194</bibtext> </blist> <blist> <bibl id="bib7" idref="ref94" type="bt">7</bibl> <bibtext> Baum DA, Smith SD, Donovan SS. The tree-thinking challenge. Science. 2005; 310; 5750: 979-980. 10.1126/science.1117727</bibtext> </blist> <blist> <bibl id="bib8" idref="ref139" type="bt">8</bibl> <bibtext> Berland LK, Schwarz CV, Krist C, Kenyon L, Lo AS, Reiser BJ. Epistemologies in practice: Making scientific practices meaningful for students. Journal of Research in Science Teaching. 2016; 53; 7: 1082-1112. 10.1002/tea.21257</bibtext> </blist> <blist> <bibl id="bib9" idref="ref61" type="bt">9</bibl> <bibtext> Blumenfeld PC, Soloway E, Marx RW, Krajcik JS, Guzdial M, Palincsar A. Motivating project-based learning: Sustaining the doing, supporting the learning. Educational Psychologist. 1991; 26; 3&4: 369-398. 10.1080/00461520.1991.9653139</bibtext> </blist> <blist> <bibtext> Brewer CA, Smith D. Vision and change in undergraduate biology education: A call to action. 2011; American Association for the Advancement of Science</bibtext> </blist> <blist> <bibtext> Brooks, D. R, McLennan, D. A, & McLennan, D. A. (1991). Phylogeny, ecology, and behavior: A research program in comparative biology. University of Chicago press.</bibtext> </blist> <blist> <bibtext> Brulle RJ, Carmichael J, Jenkins JC. Shifting public opinion on climate change: An empirical assessment of factors influencing concern over climate change in the US, 2002–2010. Climatic Change. 2012; 114; 2: 169-188. 10.1007/s10584-012-0403-y</bibtext> </blist> <blist> <bibtext> Buehl MM, Alexander PA. Motivation and performance differences in students' domain-specific epistemological belief profiles. American Educational Research Journal. 2005; 42; 4: 697-726. 10.3102/00028312042004697</bibtext> </blist> <blist> <bibtext> Bybee, R. (2015). Scientific literacy. Encyclopedia of Science Education, 944–947.</bibtext> </blist> <blist> <bibtext> Campbell AM. Open Access: A PLoS for Education. PLoS Biol. 2004; 2; 5: e145. 10.1371/journal.pbio.0020145</bibtext> </blist> <blist> <bibtext> Carey S, Smith C. On understanding the nature of scientific knowledge. Educational Psychologist. 1993; 28; 3: 235-251. 10.1093/acprof:oso/9780195115772.003.0003</bibtext> </blist> <blist> <bibtext> Chinn CA, Buckland LA, Samarapungavan A. Expanding the dimensions of epistemic cognition: Arguments from philosophy and psychology. Educational Psychologist. 2011; 46; 3: 141-167. 10.1080/00461520.2011.587722</bibtext> </blist> <blist> <bibtext> Chinn, C. A, Barzilai, S, & Duncan, R. G. (2020). Education for a "post-truth" world: New directions for research and practice. Educational Researcher, 0013189X20940683. https://doi.org/10.3102/0013189X20940683</bibtext> </blist> <blist> <bibtext> Cobb P, Confrey J, DiSessa A, Lehrer R, Schauble L. Design experiments in educational research. Educational Researcher. 2003; 32; 1: 9-13. 10.3102/0013189X032001009</bibtext> </blist> <blist> <bibtext> Creswell, J. W, & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications.</bibtext> </blist> <blist> <bibtext> Crisp MD, Cook LG. Do early branching lineages signify ancestral traits?. Trends in Ecology and Evolution. 2005; 20; 3: 122-128. 10.1016/j.tree.2004.11.010</bibtext> </blist> <blist> <bibtext> Crujeiras Pérez B, Jiménez Aleixandre MP. Challenges posed by open inquiry tasks in the laboratory: Articulation of theoretical and practical knowledge in scientific practices. Enseñanza De Las Ciencias. 2015; 33; 1: 63-84. 10.5565/rev/ensciencias.1469</bibtext> </blist> <blist> <bibtext> Dasgupta AP, Anderson TR, Pelaez N. Development and validation of a rubric for diagnosing students' experimental design knowledge and difficulties. CBE—Life Sciences Education. 2014; 13; 2: 265-284. 10.1187/cbe.13-09-0192</bibtext> </blist> <blist> <bibtext> de Lima Tavares M, Jiménez-Aleixandre MP, Mortimer EF. Articulation of conceptual knowledge and argumentation practices by high school students in evolution problems. Science and Education. 2010; 19: 573-598. 10.1007/s11191-009-9206-6</bibtext> </blist> <blist> <bibtext> Denzin, N. K, & Lincoln, Y. S. (2008). Introduction: The Discipline and Practice of Qualitative Research.https://doi.org/10.1177/1035719x1101100208</bibtext> </blist> <blist> <bibtext> Dolan E, Grady J. Recognizing students' scientific reasoning: A tool for categorizing complexity of reasoning during teaching by inquiry. Journal of Science Teacher Education. 2010; 21; 1: 31-55. 10.1007/s10972-009-9154-7</bibtext> </blist> <blist> <bibtext> Duncan RG, Reiser BJ. Reasoning across ontologically distinct levels: Students' understandings of molecular genetics. Journal of Research in Science Teaching. 2007; 44; 7: 938-959. 10.1002/tea.20186</bibtext> </blist> <blist> <bibtext> Duncan RG, Chinn CA, Barzilai S. Grasp of evidence: Problematizing and expanding the next generation science standards' conceptualization of evidence. Journal of Research in Science Teaching. 2018; 55; 7: 907-937. 10.1002/tea.21468</bibtext> </blist> <blist> <bibtext> Duschl R. Science education in three-part harmony: Balancing conceptual, epistemic, and social learning goals. Review of Research in Education. 2008; 32; 1: 268-291. 10.3102/0091732X07309371</bibtext> </blist> <blist> <bibtext> Duschl, R. A, Schweingruber, H. A, & Shouse, A. W. (Eds.). (2007). Taking science to school: Learning and teaching science in grades K-8 (Vol. 500). Washington, DC: National Academies Press. https://doi.org/10.12973/ejmste/75381</bibtext> </blist> <blist> <bibtext> Elby, A, & Hammer, D. (2010). Epistemological resources and framing: A cognitive framework for helping teachers interpret and respond to their students' epistemologies. In L. D. Bendixen & F. C. Feucht (Eds.), Personal epistemology in the classroom: Theory, research, and implications for practice (pp. 409–434). New York, NY: Cambridge University Press. https://doi.org/10.1002/sce.1023</bibtext> </blist> <blist> <bibtext> Elby A, Hammer D. On the substance of a sophisticated epistemology. Science Education. 2001; 85: 554-567. 10.1017/CBO9780511691904.013</bibtext> </blist> <blist> <bibtext> Erduran S. Respect for evidence: Can science education deliver it?. Science and Education. 2021; 30: 441-444. 10.1007/s11191-021-00245-8</bibtext> </blist> <blist> <bibtext> Erduran S, Ozdem Y, Park JY. Research trends on argumentation in science education: A journal content analysis from 1998–2014. International Journal of STEM Education. 2015; 2; 1: 1-12. 10.1186/s40594-015-0020-1</bibtext> </blist> <blist> <bibtext> Evans EM, Spiegel AN, Gram W, Frazier BN, Tare M, Thompson S, Diamond J. A conceptual guide to natural history museum visitors' understanding of evolution. Journal of Research in Science Teaching: The Official Journal of the National Association for Research in Science Teaching. 2010; 47; 3: 326-353. 10.1002/tea.20337</bibtext> </blist> <blist> <bibtext> Ferrari M, Chi MT. The nature of naive explanations of natural selection. International Journal of Science Education. 1998; 20; 10: 1231-1256. 10.1080/0950069980201005</bibtext> </blist> <blist> <bibtext> Gellin BG, Maibach EW, Marcuse EK. Do parents understand immunizations? A National Telephone Survey. Pediatrics. 2000; 106; 5: 1097-1102. 10.1542/peds.106.5.1097</bibtext> </blist> <blist> <bibtext> Giere RN. Scientific perspectivism. 2010; University of Chicago Press</bibtext> </blist> <blist> <bibtext> Gregory TR, Ellis CA. Conceptions of evolution among science graduate students. BioScience. 2009; 59; 9: 792-799. 10.1525/bio.2009.59.9.10</bibtext> </blist> <blist> <bibtext> Halverson KL, Pires CJ, Abell SK. Exploring the complexity of tree thinking expertise in an undergraduate systematics course. Science Education. 2011; 95; 5: 794-823. 10.1002/sce.20436</bibtext> </blist> <blist> <bibtext> Hammer, D, & Elby, A. (2002). On the form of personal epistemology. In B. K. Hofer & P. R. Pintrich (Eds.), Personal epistemology: The psychology of beliefs about knowledge and knowing (pp. 169–190). Mahwah, NJ: Erlbaum. https://doi.org/10.4324/9780203424964</bibtext> </blist> <blist> <bibtext> Hathaway RS, Nagda BA, Gregerman SR. The relationship of undergraduate research participation to graduate and professional education pursuit: An empirical study. Journal of College Student Development. 2002; 43; 5: 614-631</bibtext> </blist> <blist> <bibtext> Jiménez-Aleixandre MP. Determinism and Underdetermination in Genetics: Implications for Students' Engagement in Argumentation and Epistemic Practices. Science and Education. 2014; 23: 465-484. 10.1007/s11191-012-9561-6</bibtext> </blist> <blist> <bibtext> Kang H, Windschitl M, Stroupe D, Thompson J. Designing, launching, and implementing high quality learning opportunities for students that advance scientific thinking. Journal of Research in Science Teaching. 2016; 53; 9: 1316-1340. 10.1002/tea.21329</bibtext> </blist> <blist> <bibtext> Kendall KD, Schussler EE. Does instructor type matter? Undergraduate student perception of graduate teaching assistants and professors. CBE—Life Sciences Education. 2012; 11; 2: 187-199. 10.1187/cbe.11-10-0091</bibtext> </blist> <blist> <bibtext> Kloser MJ, Brownell SE, Chiariello NR, Fukami T. Integrating teaching and research in undergraduate biology laboratory education. PLoS Biology. 2011; 9; 11: e1001174. 10.1371/journal.pbio.1001174</bibtext> </blist> <blist> <bibtext> Koslowski B, Marasia J, Chelenza M, Dublin R. Information becomes evidence when an explanation can incorporate it into a causal framework. Cognitive Development. 2008; 23; 4: 472-487. 10.1016/j.cogdev.2008.09.007</bibtext> </blist> <blist> <bibtext> Kong Y, Anderson T, Pelaez N. How to identify and interpret evolutionary tree diagrams. Journal of Biological Education. 2016; 50; 4: 395-406. 10.1080/00219266.2015.1117514</bibtext> </blist> <blist> <bibtext> Kong Y, Thawani A, Anderson T, Pelaez N. A model of the use of evolutionary trees (MUET) to inform K-14 biology education. The American Biology Teacher. 2017; 79; 2: 81-90. 10.1525/abt.2017.79.2.81</bibtext> </blist> <blist> <bibtext> Krell FT, Cranston PS. Which side of the tree is more basal?. Systematic Entomology. 2004; 29; 3: 279-281. 10.1111/j.0307-6970.2004.00262.x</bibtext> </blist> <blist> <bibtext> Labov JB, Reid AH, Yamamoto KR. Integrated biology and undergraduate science education: A new biology education for the twenty-first century?. CBE-Life Sciences Education. 2010; 9; 1: 10-16. 10.1187/cbe.09-12-0092</bibtext> </blist> <blist> <bibtext> Levin DM, Grant T, Hammer D. Attending and responding to student thinking in science. The American Biology Teacher. 2012; 74; 3: 158-162. 10.1525/abt.2012.74.3.6</bibtext> </blist> <blist> <bibtext> Liu C, Pelaez N, Liu S, Samarapungavan A, Gardner SM, Clase K, Allen DAnderson TR, Gardner SM, Pelaez N. Biological reasoning according to members of the faculty developer network for undergraduate biology education. Trends in Teaching Experimentation in the Life Sciences: Putting Research into Practice to Drive Institutional Change. 2022; Springer: 459-484. 10.1007/978-3-030-98592-9_21</bibtext> </blist> <blist> <bibtext> Liu S, Cai C, Liu C, Samarapungavan A, Gardner S, Clase K, Pelaez NAnderson TR, Gardner SM, Pelaez N. Assessment of evidence of evidentiary reasoning in undergraduate biology: A lit review and application of the Conceptual Analysis of Disciplinary Evidence (CADE) framework. Trends in Teaching Experimentation in the Life Sciences: Putting Research into Practice to Drive Institutional Change. 2022; Springer: 351-391. 10.1007/978-3-030-98592-9_17</bibtext> </blist> <blist> <bibtext> Liu, C, Dreger, D. L, Liu, S, Samarapungavan, A, Gardner, S. M, Clase, K. L, Pelaez, N, (2022). The Conceptual Analysis of Disciplinary Evidence (CADE) framework as a guide for evidentiary reasoning: A practical implementation in a Hardy-Weinberg Equilibrium (HWE) laboratory investigation. Journal of Biological Education, 1–25. https://doi.org/10.1080/00219266.2022.2100450</bibtext> </blist> <blist> <bibtext> Liu, C, Dreger, D. L, Liu, S, Samarapungavan, A, Gardner, S. M, Clase, K. L, & Pelaez, N.(2022). The Conceptual Analysis of Disciplinary Evidence (CADE) framework as a guide for evidentiary reasoning: A practical implementation in a Hardy-Weinberg Equilibrium (HWE) laboratory investigation. Journal of Biological Education, 1–25.</bibtext> </blist> <blist> <bibtext> Lopatto D. Undergraduate research experiences support science career decisions and active learning. CBE-Life Sciences Education. 2007; 6; 4: 297-306. 10.1187/cbe.07</bibtext> </blist> <blist> <bibtext> Luft JA, Kurdziel JP, Roehrig GH, Turner J. Growing a garden without water: Graduate teaching assistants in introductory science laboratories at a doctoral/research university. Journal of Research in Science Teaching. 2004; 41; 3: 211-233. 10.1002/tea.20004</bibtext> </blist> <blist> <bibtext> Manz E, Lehrer R, Schauble L. Rethinking the classroom science investigation. Journal of Research in Science Teaching. 2020; 57; 7: 1148-1174. 10.1002/tea.21625</bibtext> </blist> <blist> <bibtext> Maskiewicz, A. C. (2015). Navigating the challenges of teaching responsively: An insider's perspective. In Responsive teaching in science and mathematics (pp. 123–143). Routledge.</bibtext> </blist> <blist> <bibtext> Masnick AM, Klahr D. Error matters: An initial exploration of elementary school children's understanding of experimental error. Journal of Cognition and Development. 2003; 4; 1: 67-98. 10.1080/15248372.2003.9669683</bibtext> </blist> <blist> <bibtext> Mason L, Scirica F. Prediction of students' argumentation skills about controversial topics by epistemological understanding. Learning and Instruction. 2006; 16: 492-509. 10.1016/j.learninstruc.2006.09.007</bibtext> </blist> <blist> <bibtext> Mayr E. What makes biology unique? considerations on the autonomy of a scientific discipline. 2004; Cambridge University Press. 10.1017/CBO9780511617188</bibtext> </blist> <blist> <bibtext> McNeill KL, Berland L. What is (or should be) scientific evidence use in k-12 classrooms?. Journal of Research in Science Teaching. 2017; 54; 5: 672-689. 10.1002/tea.21381</bibtext> </blist> <blist> <bibtext> McNeill KL, Krajcik J. Scientific explanations: Characterizing and evaluating the effects of teachers' instructional practices on student learning. Journal of Research in Science Teaching: The Official Journal of the National Association for Research in Science Teaching. 2008; 45; 1: 53-78. 10.1002/tea.20201</bibtext> </blist> <blist> <bibtext> Meir, E, Perry, J, Herron, J. C, & Kingsolver, J. (2007). College students' misconceptions about evolutionary trees. The American Biology Teacher, 69(7). https://doi.org/10.1662/0002-7685(2007)69[71:csmaet]2.0.co;2</bibtext> </blist> <blist> <bibtext> Muis KR, Bendixen LD, Haerle FC. Domain-generality and domain-specificity in personal epistemology research: Philosophical and empirical reflections in the development of a theoretical framework. Educational Psychology Review. 2006; 18; 1: 3-54. 10.1007/s10648-006-9003-6</bibtext> </blist> <blist> <bibtext> Muzaka V. The niche of graduate teaching assistants (GTAs): Perceptions and reflections. Teaching in Higher Education. 2009; 14; 1: 1-12. 10.1080/13562510802602400</bibtext> </blist> <blist> <bibtext> National Academies of Sciences, Engineering, and Medicine. (2019). Science and engineering for grades 6–12: Investigation and design at the center. National Academies Press.</bibtext> </blist> <blist> <bibtext> National Research Council. (2012). Discipline-based education research: Understanding and improving learning in undergraduate science and engineering. National Academies Press.</bibtext> </blist> <blist> <bibtext> Nehm RH, Ha M. Item feature effects in evolution assessment. Journal of Research in Science Teaching. 2011; 48; 3: 237-256. 10.1002/tea.20400</bibtext> </blist> <blist> <bibtext> Nehm RH, Reilly L. Biology majors' knowledge and misconceptions of natural selection. BioScience. 2007; 57; 3: 263-272. 10.1641/B570311</bibtext> </blist> <blist> <bibtext> NGSS Lead States. Next generation science standards: For states, by states. 2013; The National Academies Press</bibtext> </blist> <blist> <bibtext> Novak AM, Treagust DF. Adjusting claims as new evidence emerges: Do students incorporate new evidence into their scientific explanations?. Journal of Research in Science Teaching. 2018; 55; 4: 526-549. 10.1002/tea.21429</bibtext> </blist> <blist> <bibtext> O'Hara RJ. Homage to Clio, or, toward an historical philosophy for evolutionary biology. Systematic Zoology. 1988; 37; 2: 142-155. 10.2307/2992272</bibtext> </blist> <blist> <bibtext> Osborne J, Collins S, Ratcliffe M, Millar R, Duschl R. What "ideas-about-science" should be taught in school science? A Delphi study of the expert community. Journal of Research in Science Teaching. 2003; 40; 7: 692-720. 10.1002/tea.10105</bibtext> </blist> <blist> <bibtext> Osborne J, Simon S, Collins S. Attitudes towards science: A review of the literature and its implications. International Journal of Science Education. 2003; 25; 9: 1049-1079. 10.1080/0950069032000032199</bibtext> </blist> <blist> <bibtext> Plant AL, Becker CA, Hanisch RJ, Boisvert RF, Possolo AM, Elliott JT. How measurement science can improve confidence in research results. PLoS Biology. 2018; 16; 4: e2004299. 10.1371/journal.pbio.2004299</bibtext> </blist> <blist> <bibtext> Qian G, Alvermann DE. Relationship between epistemological beliefs and conceptual change learning. Reading and Writing Quarterly. 2009; 16: 59-74. 10.1080/105735600278060</bibtext> </blist> <blist> <bibtext> Ratcliffe M, Millar R. Teaching for understanding of science in context: Evidence from the pilot trials of the Twenty First Century Science courses. Journal of Research in Science Teaching. 2009; 46; 8: 945-959. 10.1002/tea.20340</bibtext> </blist> <blist> <bibtext> Raven P, Johnson G, Losos J, Mason K, Singer S. Biology. 201410; McGraw-Hill</bibtext> </blist> <blist> <bibtext> Richards KAR, Hemphill MA. A practical guide to collaborative qualitative data analysis. Journal of Teaching in Physical Education. 2018; 37; 2: 225-231. 10.1123/jtpe.2017-0084</bibtext> </blist> <blist> <bibtext> Russ RS, Scherr RE, Hammer D, Mikeska J. Recognizing mechanistic reasoning in student scientific inquiry: A framework for discourse analysis developed from philosophy of science. Science Education. 2008; 92; 3: 499-525. 10.1002/sce.20264</bibtext> </blist> <blist> <bibtext> Ryu S, Sandoval WA. Improvements to elementary children's epistemic understanding from sustained argumentation. Science Education. 2012; 96; 3: 488-526. 10.1002/sce.21006</bibtext> </blist> <blist> <bibtext> Sadler TD, Zeidler DL. The significance of content knowledge for informal reasoning regarding socioscientific issues: Applying genetics knowledge to genetic engineering issues. Science Education. 2005; 89; 1: 71-93. 10.1002/sce.20023</bibtext> </blist> <blist> <bibtext> Samarapungavan AFischer F, Chinn C, Engelmann K, Osborne J. Construing scientific evidence: The role of disciplinary knowledge in reasoning with and about evidence in scientific practice. Scientific Reasoning and Argumentation: The Roles of Domain-specific and Domain-general Knowledge. 2018; Routledge: 56-76</bibtext> </blist> <blist> <bibtext> Sandoval WA, Cam A. Elementary children's judgements of the epistemic status of sources of justification. Science Education. 2011; 95; 3: 383-408. 10.1002/sce.20426</bibtext> </blist> <blist> <bibtext> Sandoval WA, Reiser BJ. Explanation-driven inquiry: Integrating conceptual and epistemic scaffolds for scientific inquiry. Science Education. 2004; 88; 3: 345-372. 10.1002/sce.10130</bibtext> </blist> <blist> <bibtext> Sandoval WA, Millwood KA. The quality of students' use of evidence in written scientific explanations. Cognition and instruction. 2005; 23; 1: 23-55. 10.1207/s1532690xci2301_2</bibtext> </blist> <blist> <bibtext> Singer SR, Hilton ML, Schweingruber HA. America's Lab Report: Investigations in High School Science. 2006; National Academies Press</bibtext> </blist> <blist> <bibtext> Smith JJ, Cheruvelil KS, Auvenshine S. Assessment of student learning associated with tree thinking in an undergraduate introductory organismal biology course. CBE—Life Sciences Education. 2013; 12: 542-552. 10.1187/cbe.11-08-0066</bibtext> </blist> <blist> <bibtext> Sober E, Steel M. Testing the hypothesis of common ancestry. Journal of Theoretical Biology. 2002; 218; 4: 395-408. 10.1016/S0022-5193(02)93086-9</bibtext> </blist> <blist> <bibtext> Soysal Y. Talking Science. Science and Education. 2021; 30: 33-65. 10.1007/s11191-020-00163-1</bibtext> </blist> <blist> <bibtext> Stanton JD, Neider XN, Gallegos IJ, Clark NC. Differences in metacognitive regulation in introductory biology students: When prompts are not enough. CBE—Life Sciences Education. 2015; 14; 2: ar15. 10.1187/cbe.14-08-0135</bibtext> </blist> <blist> <bibtext> Stanton JD, Dye KM, Johnson MS. Knowledge of learning makes a difference: A comparison of metacognition in introductory and senior-level biology students. CBE—Life Sciences Education. 2019; 18; 2: ar24. 10.1187/cbe.18-12-0239</bibtext> </blist> <blist> <bibtext> Sundberg MD, Armstrong JE, Wischusen EW. A reappraisal of the status of introductory biology laboratory education in US colleges & universities. The American Biology Teacher. 2005; 67; 9: 525-529. 10.2307/4451904</bibtext> </blist> <blist> <bibtext> Tabak I, Radinsky J. Educators' coaches, peers, and practices: Revisiting how teachers learn. Journal of the Learning Sciences. 2015; 24; 3: 343-346. 10.1080/10508406.2015.1065664</bibtext> </blist> <blist> <bibtext> Tekkumru-Kisa M, Stein MK, Coker R. Teachers' learning to facilitate high-level student thinking: Impact of a video-based professional development. Journal of Research in Science Teaching. 2018; 55; 4: 479-502. 10.1002/tea.21427</bibtext> </blist> <blist> <bibtext> Toulmin, S. E. (2003). The uses of argument. Cambridge university press.</bibtext> </blist> <blist> <bibtext> Tsui CY, Treagust DF. Understanding genetics: Analysis of secondary students' conceptual status. Journal of Research in Science Teaching. 2007; 44; 2: 205-235. 10.1002/tea.20116</bibtext> </blist> <blist> <bibtext> Turner, J. C. (1991). The dual-process model, self-categorization and social influence. Social influence, 143–173.</bibtext> </blist> <blist> <bibtext> Walker JP, Sampson V, Grooms J, Anderson B, Zimmerman CO. Argument-driven inquiry in undergraduate chemistry labs: The impact on students' conceptual understanding, argument skills, and attitudes toward science. Journal of College Science Teaching. 2012; 41; 4: 74-81</bibtext> </blist> <blist> <bibtext> Weinstock M, Cronin MA. The everyday production of knowledge: Individual differences in epistemological understanding and juror-reasoning skill. Applied Cognitive Psychology: The Official Journal of the Society for Applied Research in Memory and Cognition. 2003; 17; 2: 161-181. 10.1002/acp.860</bibtext> </blist> <blist> <bibtext> Wood D, Bruner JS, Ross G. The role of tutoring in problem solving. Journal of Child Psychology and Psychiatry. 1976; 17; 1: 89-100. 10.1111/j.1469-7610.1976.tb00381.x</bibtext> </blist> </ref> <aug> <p>By Shiyao Liu; Chaonan Liu; Ala Samarapungavan; Stephanie M. Gardner; Kari L. Clase and Nancy J. Pelaez</p> <p>Reported by Author; Author; Author; Author; Author; Author</p> </aug> <nolink nlid="nl1" bibid="bib10" firstref="ref3"></nolink> <nolink nlid="nl2" bibid="bib69" firstref="ref4"></nolink> <nolink nlid="nl3" bibid="bib73" firstref="ref5"></nolink> <nolink nlid="nl4" bibid="bib17" firstref="ref6"></nolink> <nolink nlid="nl5" bibid="bib16" firstref="ref7"></nolink> <nolink nlid="nl6" bibid="bib30" firstref="ref8"></nolink> <nolink nlid="nl7" bibid="bib33" firstref="ref9"></nolink> <nolink nlid="nl8" bibid="bib76" firstref="ref10"></nolink> <nolink nlid="nl9" bibid="bib77" firstref="ref11"></nolink> <nolink nlid="nl10" bibid="bib80" firstref="ref12"></nolink> <nolink nlid="nl11" bibid="bib14" firstref="ref16"></nolink> <nolink nlid="nl12" bibid="bib27" firstref="ref17"></nolink> <nolink nlid="nl13" bibid="bib28" firstref="ref18"></nolink> <nolink nlid="nl14" bibid="bib29" firstref="ref19"></nolink> <nolink nlid="nl15" bibid="bib53" firstref="ref20"></nolink> <nolink nlid="nl16" bibid="bib55" firstref="ref21"></nolink> <nolink nlid="nl17" bibid="bib54" firstref="ref22"></nolink> <nolink nlid="nl18" bibid="bib100" firstref="ref23"></nolink> <nolink nlid="nl19" bibid="bib22" firstref="ref24"></nolink> <nolink nlid="nl20" bibid="bib51" firstref="ref25"></nolink> <nolink nlid="nl21" bibid="bib59" firstref="ref26"></nolink> <nolink nlid="nl22" bibid="bib64" firstref="ref27"></nolink> <nolink nlid="nl23" bibid="bib102" firstref="ref28"></nolink> <nolink nlid="nl24" bibid="bib23" firstref="ref29"></nolink> <nolink nlid="nl25" bibid="bib26" firstref="ref31"></nolink> <nolink nlid="nl26" bibid="bib74" firstref="ref32"></nolink> <nolink nlid="nl27" bibid="bib24" firstref="ref34"></nolink> <nolink nlid="nl28" bibid="bib42" firstref="ref36"></nolink> <nolink nlid="nl29" bibid="bib57" firstref="ref37"></nolink> <nolink nlid="nl30" bibid="bib12" firstref="ref40"></nolink> <nolink nlid="nl31" bibid="bib37" firstref="ref41"></nolink> <nolink nlid="nl32" bibid="bib85" firstref="ref42"></nolink> <nolink nlid="nl33" bibid="bib99" firstref="ref43"></nolink> <nolink nlid="nl34" bibid="bib34" firstref="ref44"></nolink> <nolink nlid="nl35" bibid="bib65" firstref="ref45"></nolink> <nolink nlid="nl36" bibid="bib89" firstref="ref46"></nolink> <nolink nlid="nl37" bibid="bib38" firstref="ref48"></nolink> <nolink nlid="nl38" bibid="bib86" firstref="ref50"></nolink> <nolink nlid="nl39" bibid="bib70" firstref="ref52"></nolink> <nolink nlid="nl40" bibid="bib88" firstref="ref58"></nolink> <nolink nlid="nl41" bibid="bib90" firstref="ref59"></nolink> <nolink nlid="nl42" bibid="bib93" firstref="ref62"></nolink> <nolink nlid="nl43" bibid="bib98" firstref="ref63"></nolink> <nolink nlid="nl44" bibid="bib56" firstref="ref68"></nolink> <nolink nlid="nl45" bibid="bib40" firstref="ref80"></nolink> <nolink nlid="nl46" bibid="bib81" firstref="ref81"></nolink> <nolink nlid="nl47" bibid="bib48" firstref="ref82"></nolink> <nolink nlid="nl48" bibid="bib11" firstref="ref83"></nolink> <nolink nlid="nl49" bibid="bib75" firstref="ref86"></nolink> <nolink nlid="nl50" bibid="bib92" firstref="ref87"></nolink> <nolink nlid="nl51" bibid="bib49" firstref="ref90"></nolink> <nolink nlid="nl52" bibid="bib36" firstref="ref95"></nolink> <nolink nlid="nl53" bibid="bib66" firstref="ref96"></nolink> <nolink nlid="nl54" bibid="bib71" firstref="ref97"></nolink> <nolink nlid="nl55" bibid="bib72" firstref="ref98"></nolink> <nolink nlid="nl56" bibid="bib91" firstref="ref99"></nolink> <nolink nlid="nl57" bibid="bib35" firstref="ref102"></nolink> <nolink nlid="nl58" bibid="bib21" firstref="ref104"></nolink> <nolink nlid="nl59" bibid="bib39" firstref="ref105"></nolink> <nolink nlid="nl60" bibid="bib50" firstref="ref106"></nolink> <nolink nlid="nl61" bibid="bib104" firstref="ref107"></nolink> <nolink nlid="nl62" bibid="bib47" firstref="ref108"></nolink> <nolink nlid="nl63" bibid="bib61" firstref="ref109"></nolink> <nolink nlid="nl64" bibid="bib83" firstref="ref110"></nolink> <nolink nlid="nl65" bibid="bib84" firstref="ref111"></nolink> <nolink nlid="nl66" bibid="bib87" firstref="ref112"></nolink> <nolink nlid="nl67" bibid="bib44" firstref="ref114"></nolink> <nolink nlid="nl68" bibid="bib97" firstref="ref116"></nolink> <nolink nlid="nl69" bibid="bib96" firstref="ref117"></nolink> <nolink nlid="nl70" bibid="bib45" firstref="ref118"></nolink> <nolink nlid="nl71" bibid="bib58" firstref="ref119"></nolink> <nolink nlid="nl72" bibid="bib68" firstref="ref120"></nolink> <nolink nlid="nl73" bibid="bib46" firstref="ref122"></nolink> <nolink nlid="nl74" bibid="bib60" firstref="ref123"></nolink> <nolink nlid="nl75" bibid="bib13" firstref="ref126"></nolink> <nolink nlid="nl76" bibid="bib62" firstref="ref127"></nolink> <nolink nlid="nl77" bibid="bib67" firstref="ref128"></nolink> <nolink nlid="nl78" bibid="bib79" firstref="ref129"></nolink> <nolink nlid="nl79" bibid="bib103" firstref="ref130"></nolink> <nolink nlid="nl80" bibid="bib41" firstref="ref131"></nolink> <nolink nlid="nl81" bibid="bib32" firstref="ref133"></nolink> <nolink nlid="nl82" bibid="bib31" firstref="ref134"></nolink> <nolink nlid="nl83" bibid="bib43" firstref="ref137"></nolink> <nolink nlid="nl84" bibid="bib19" firstref="ref144"></nolink> <nolink nlid="nl85" bibid="bib15" firstref="ref148"></nolink> <nolink nlid="nl86" bibid="bib18" firstref="ref149"></nolink> <nolink nlid="nl87" bibid="bib78" firstref="ref150"></nolink> <nolink nlid="nl88" bibid="bib20" firstref="ref151"></nolink> <nolink nlid="nl89" bibid="bib82" firstref="ref152"></nolink> <nolink nlid="nl90" bibid="bib25" firstref="ref153"></nolink> <nolink nlid="nl91" bibid="bib94" firstref="ref154"></nolink> <nolink nlid="nl92" bibid="bib95" firstref="ref155"></nolink> <nolink nlid="nl93" bibid="bib101" firstref="ref159"></nolink> <nolink nlid="nl94" bibid="bib63" firstref="ref168"></nolink> <nolink nlid="nl95" bibid="bib52" firstref="ref176"></nolink>
Header DbId: eric
DbLabel: ERIC
An: EJ1450685
AccessLevel: 3
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: A Framework for Evidentiary Reasoning in Biology: Insights from Laboratory Courses Focused on Evolutionary Tree-Thinking
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Shiyao+Liu%22">Shiyao Liu</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-5092-782X">0000-0002-5092-782X</externalLink>)<br /><searchLink fieldCode="AR" term="%22Chaonan+Liu%22">Chaonan Liu</searchLink><br /><searchLink fieldCode="AR" term="%22Ala+Samarapungavan%22">Ala Samarapungavan</searchLink><br /><searchLink fieldCode="AR" term="%22Stephanie+M%2E+Gardner%22">Stephanie M. Gardner</searchLink><br /><searchLink fieldCode="AR" term="%22Kari+L%2E+Clase%22">Kari L. Clase</searchLink><br /><searchLink fieldCode="AR" term="%22Nancy+J%2E+Pelaez%22">Nancy J. Pelaez</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Science+%26+Education%22"><i>Science & Education</i></searchLink>. 2024 33(6):1435-1466.
– Name: Avail
  Label: Availability
  Group: Avail
  Data: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 32
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2024
– Name: SourceSuprt
  Label: Sponsoring Agency
  Group: SrcSuprt
  Data: National Science Foundation (NSF)
– Name: NumberContract
  Label: Contract Number
  Group: NumCntrct
  Data: 1661124
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Biology%22">Biology</searchLink><br /><searchLink fieldCode="DE" term="%22Science+Instruction%22">Science Instruction</searchLink><br /><searchLink fieldCode="DE" term="%22Laboratory+Experiments%22">Laboratory Experiments</searchLink><br /><searchLink fieldCode="DE" term="%22Evolution%22">Evolution</searchLink><br /><searchLink fieldCode="DE" term="%22Scientific+Concepts%22">Scientific Concepts</searchLink><br /><searchLink fieldCode="DE" term="%22Scaffolding+%28Teaching+Technique%29%22">Scaffolding (Teaching Technique)</searchLink><br /><searchLink fieldCode="DE" term="%22Evidence+Based+Practice%22">Evidence Based Practice</searchLink><br /><searchLink fieldCode="DE" term="%22Thinking+Skills%22">Thinking Skills</searchLink><br /><searchLink fieldCode="DE" term="%22Discussion+%28Teaching+Technique%29%22">Discussion (Teaching Technique)</searchLink><br /><searchLink fieldCode="DE" term="%22Research+Design%22">Research Design</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1007/s11191-023-00435-6
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0926-7220<br />1573-1901
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Science educators report that students struggle with understanding, using, and evaluating the evidence underpinning scientific knowledge. However, there are not many studies focused on helping instructors address those difficulties. Here, we report on a laboratory instructor's scaffolding of students' evidentiary reasoning with and about evidence for evolutionary trees with guidance from the Conceptual Analysis of Disciplinary Evidence (CADE) framework, which links biological knowledge with epistemic considerations. To consider both domain-general and discipline-specific aspects of evidence, CADE was implemented to inform scaffolds in two ways: (1) generic evidence scaffolds (GES) reminded students of general epistemic considerations; (2) disciplinary evidence scaffolds (DES) explicitly reminded students of the disciplinary knowledge of relevance for considering biological evidence. An instructor's lab discussions were compared before and after they had a workshop with CADE. CADE helped the lab instructor facilitate students' evidentiary reasoning about evolutionary trees. In comparison to baseline, both GES and DES discussions covered more aspects and relationships among types of evidence for evolutionary tree-thinking and the instructor prompted more kinds of general epistemic considerations and biological knowledge. DES discussions emphasized the importance of disciplinary knowledge for research design. The CADE framework guided planning and implementation of intentional scaffolding aimed at guiding evidentiary reasoning.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2024
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1450685
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1450685
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s11191-023-00435-6
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 32
        StartPage: 1435
    Subjects:
      – SubjectFull: Biology
        Type: general
      – SubjectFull: Science Instruction
        Type: general
      – SubjectFull: Laboratory Experiments
        Type: general
      – SubjectFull: Evolution
        Type: general
      – SubjectFull: Scientific Concepts
        Type: general
      – SubjectFull: Scaffolding (Teaching Technique)
        Type: general
      – SubjectFull: Evidence Based Practice
        Type: general
      – SubjectFull: Thinking Skills
        Type: general
      – SubjectFull: Discussion (Teaching Technique)
        Type: general
      – SubjectFull: Research Design
        Type: general
    Titles:
      – TitleFull: A Framework for Evidentiary Reasoning in Biology: Insights from Laboratory Courses Focused on Evolutionary Tree-Thinking
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Shiyao Liu
      – PersonEntity:
          Name:
            NameFull: Chaonan Liu
      – PersonEntity:
          Name:
            NameFull: Ala Samarapungavan
      – PersonEntity:
          Name:
            NameFull: Stephanie M. Gardner
      – PersonEntity:
          Name:
            NameFull: Kari L. Clase
      – PersonEntity:
          Name:
            NameFull: Nancy J. Pelaez
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 12
              Type: published
              Y: 2024
          Identifiers:
            – Type: issn-print
              Value: 0926-7220
            – Type: issn-electronic
              Value: 1573-1901
          Numbering:
            – Type: volume
              Value: 33
            – Type: issue
              Value: 6
          Titles:
            – TitleFull: Science & Education
              Type: main
ResultId 1