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Troubleshooting as an Inquiry Activity: Recognizing and Supporting the Mangle in the Classroom

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Title: Troubleshooting as an Inquiry Activity: Recognizing and Supporting the Mangle in the Classroom
Language: English
Authors: A. Lynn Stephens (ORCID 0000-0002-4343-340X)
Source: Science Education. 2025 109(6):1509-1530.
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 22
Publication Date: 2025
Sponsoring Agency: National Science Foundation (NSF), Division of Information and Intelligent Systems (IIS)
National Science Foundation (NSF), Division of Research on Learning in Formal and Informal Settings (DRL)
Contract Number: 1147621
1621301
Document Type: Journal Articles
Reports - Research
Education Level: Secondary Education
High Schools
Descriptors: Troubleshooting, Inquiry, Science Education, Science Process Skills, Secondary School Science, High School Students, Science Activities, Physics, Science Projects, Epistemology, Theory Practice Relationship, Learner Engagement
DOI: 10.1002/sce.21979
ISSN: 0036-8326
1098-237X
Abstract: Although there is a push to provide more student agency in science classrooms, teachers and students may become frustrated when inquiry activities and equipment do not work as planned--teachers because of the time crunch to "cover" topics and students because of the perceived lack of value in activities that are "off task." In classroom implementations of a data-rich high school physics activity sequence as part of the InquirySpace 2 (IS2) project, numerous episodes of equipment troubleshooting were observed. Teachers questioned whether the time spent had disciplinary value. Students expressed concern regarding what, if anything, they were learning. This qualitative case study of one such episode considers students' activity in terms of their engagement with the "mangle of practice" and misalignments between their conceptual and material worlds, their exercise of epistemic agency in recognizing and repairing those misalignments, and their epistemic affect during and after the activity. Video analysis revealed all three aspects deeply intertwined with evidence of student engagement in multiple science practices. The students expressed their feelings about the episode immediately afterward and the teacher and IS2 observer when interviewed much later, at the end of the project. One reason for the negative perceptions of teacher and students may be that the alignments being explored were related to the instrumentation more than to the target phenomenon. This study argues that in such situations, students may not recognize or value science practices that emerge, and may need explicit support to reframe their activity as valid scientific practice.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1486526
Database: ERIC
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  Value: <anid>AN0188607205;sed01nov.25;2025Oct14.06:28;v2.2.500</anid> <title id="AN0188607205-1">Troubleshooting as an Inquiry Activity: Recognizing and Supporting the Mangle in the Classroom </title> <p>Although there is a push to provide more student agency in science classrooms, teachers and students may become frustrated when inquiry activities and equipment do not work as planned—teachers because of the time crunch to "cover" topics and students because of the perceived lack of value in activities that are "off task." In classroom implementations of a data‐rich high school physics activity sequence as part of the InquirySpace 2 (IS2) project, numerous episodes of equipment troubleshooting were observed. Teachers questioned whether the time spent had disciplinary value. Students expressed concern regarding what, if anything, they were learning. This qualitative case study of one such episode considers students' activity in terms of their engagement with the "mangle of practice" and misalignments between their conceptual and material worlds, their exercise of epistemic agency in recognizing and repairing those misalignments, and their epistemic affect during and after the activity. Video analysis revealed all three aspects deeply intertwined with evidence of student engagement in multiple science practices. The students expressed their feelings about the episode immediately afterward and the teacher and IS2 observer when interviewed much later, at the end of the project. One reason for the negative perceptions of teacher and students may be that the alignments being explored were related to the instrumentation more than to the target phenomenon. This study argues that in such situations, students may not recognize or value science practices that emerge, and may need explicit support to reframe their activity as valid scientific practice.</p> <p>Keywords: epistemic agency; high school physics; mangle of practice; troubleshooting; video analysis</p> <hd id="AN0188607205-2">Introduction</hd> <p>There are many advantages to allowing students agency in designing their own science investigations. According to Etkina et al. ([<reflink idref="bib10" id="ref1">10</reflink>]), when design activities are embedded in an inquiry cycle and appropriately scaffolded, they can "promote the development of the habits of mind (scientific abilities) that are an important part of scientific practice" (p. 54). <emph>A Framework for K‐12 Science Education</emph> (National Research Council [<reflink idref="bib23" id="ref2">23</reflink>]) and the <emph>Next Generation Science Standards</emph> (NGSS Lead States [<reflink idref="bib24" id="ref3">24</reflink>]) promote <emph>planning and carrying out investigations</emph> as one of eight science practices in which they expect all students in inquiry‐based science classrooms to engage. At the high school level, this practice includes producing data to support explanations of phenomena. A closely related practice is <emph>analyzing and interpreting data</emph>, which the NGSS suggests should be done wherever possible with the use of digital tools (NGSS Lead States [<reflink idref="bib24" id="ref4">24</reflink>]).</p> <p>Over the course of two decades observing in high school inquiry‐based science classrooms, I have seen student engagement in these practices frequently involve something not stressed in the standards—troubleshooting the instrumentation. A scenario might go like this: <emph>A teacher plans a 3‐day lesson sequence around NGSS performance expectations mandated by the district. For the data‐rich activity in kinematics, she pulls out her motion sensors, testing them ahead of time. However, during the class some connections appear faulty and the readings are unpredictable. Her students remain focused and work with the teacher to find solutions, but at the end of the class period, three groups have still not produced usable data. The teacher tells the students that sometimes science is just messy, but the students are concerned they will not finish the investigation. Afterwards, the exhausted teacher tells an observer this is why she has become more reluctant to use these digital tools</emph>. Although this is a composite scenario, I have heard numerous teachers express frustration at the amount of time technical troubleshooting can pull away from exploring the NGSS disciplinary core ideas they had planned to cover.</p> <p>Troubleshooting instrumentation is common in the professional laboratory. Pickering ([<reflink idref="bib27" id="ref5">27</reflink>]) described a "mangle of practice" that occurs as scientists seek to make their instruments do what they want. This process can involve considerable effort as scientists work to construct alignments between their concepts of phenomena and the feedback they get from their instruments. Many aspects of the mangle have been considered in the classroom context. Manz et al. ([<reflink idref="bib19" id="ref6">19</reflink>]) suggested that alignments between conceptual and material worlds have been underutilized in educational research and at the K‐12 level. Stroupe ([<reflink idref="bib37" id="ref7">37</reflink>]) argued that science teachers need to embrace the mangle of practice as an alternative to panicking when students veer off in unplanned directions. He described in‐the‐moment decisions made by teachers that included recasting an entire unit of instruction around students' ideas. If the alignments students are constructing involve concepts closely related to target phenomena, this is one thing. But when the focus is on troubleshooting unpredictable classroom instruments, teachers may be justifiably concerned there will be no time left to explore the target concepts of the lessons.</p> <p>When inquiry introduces uncertainty into the procedures, issues of conceptual‐material misalignments, epistemic agency, and student epistemic affect arise. This study suggests there is benefit in interweaving these areas of theory to take a deeper look at how to apply the concept of the mangle to technical troubleshooting in the school science laboratory and examining the nature of the conceptual‐material alignments being repaired. If science practices are emerging at times when focus has been taken away from target phenomena, students and teachers—even teachers experienced in facilitating inquiry‐based explorations—may not recognize or value their emergence. At such times, students may need something more than perseverance or even practical troubleshooting advice to see worth in their activity.</p> <p>This case study explores a single exemplar episode involving a focal group of three students during a high school physics investigation into linear motion that was developed by InquirySpace 2 (IS2), an NSF project. It asks what value this and similar episodes may have had beyond teaching that doing science requires managing frustration. Qualitative analysis addresses two questions:</p> <p></p> <ulist> <item> 1. When the students in the exemplar group were troubleshooting technical issues with their instruments, did this activity appear to have disciplinary value in terms of engagement in science practices, the repair of misalignments between conceptual and material worlds, and the exercise of epistemic agency?</item> <p></p> <item> 2. What value did the students, teacher, and project observer place on this troubleshooting experience, as evidenced by their retrospective comments? How did the students feel about their knowledge construction experience?</item> </ulist> <p>The answers will have theoretical implications for how to think about inquiry and conceptual‐material alignments in this context. They also will have practical implications for facilitating technology‐rich science labs at the high school level.</p> <p>In the remainder of the introduction, I look first at recent thinking about students as doers of science, particularly in the context of the practice of planning and carrying out investigations, and about troubleshooting during inquiry. I then describe connections that have been drawn in the literature between the emergence of the mangle of practice in the classroom and its association with student epistemic agency and epistemic affect.</p> <hd id="AN0188607205-3">Inquiry: Students as Doers of Science</hd> <p>According to Passmore et al. ([<reflink idref="bib26" id="ref8">26</reflink>]), while classroom inquiry has almost always been hands‐on, the reverse has not been true. If hands‐on activity is to be consistent with inquiry, there should be fidelity between the intellectual work being asked of students and what might occur in the work of science. These authors defined scientific literacy as an understanding of the content coupled with an understanding of how that knowledge was generated and justified. The NGSS (NGSS Lead States [<reflink idref="bib24" id="ref9">24</reflink>]) suggests providing opportunities for students to gain this understanding by actively engaging in knowledge construction, by being doers of science rather than receivers of facts. However, a concern has been that educators will interpret this to mean that students should mimic practices others have selected as important to learn, depriving the students of epistemic agency, and in the process, continue to place them as receivers of facts and practices (Miller et al. [<reflink idref="bib22" id="ref10">22</reflink>]).</p> <p>Manz et al. ([<reflink idref="bib19" id="ref11">19</reflink>]) argued that the practice of planning and carrying out investigations should be approached from the perspective of science‐as‐practice, where practice and content understanding are interrelated, students experience their work as meaningful, instruction exposes students to the uncertainty central to scientific activity, and the students are, consequently, provided opportunities to take up epistemic agency. Manz ([<reflink idref="bib18" id="ref12">18</reflink>]) suggested designing uncertainty into learning environments to establish a need for the development of science practices, but noted a need to balance disruption and focus so that practices may emerge. Chen ([<reflink idref="bib3" id="ref13">3</reflink>]) posited that teachers become anxious, resisting the uncertainty of open‐ended problems and responding to students' uncertainty by reducing ambiguity because they have been unprepared to meet the demands of using uncertainty as a pedagogical resource—or as an element of learning in general. Manz and Suárez ([<reflink idref="bib20" id="ref14">20</reflink>]) considered how increasing the scientific uncertainty for students can also increase the pedagogical uncertainty for teachers and suggested several strategies for dealing with this. An important strategy is for educators to plan strategically which ambiguities and decisions students will face.</p> <p>In the high school activity that is the subject of the current study, the focus was on the structure of the experimental designs and the interpretation of data, which Manz et al. ([<reflink idref="bib19" id="ref15">19</reflink>]) warned can obfuscate the conceptual work involved in sense‐making and in refining explanatory models. However, the high school teachers and IS2 researchers had sought to introduce uncertainty into the activity by, among other things, providing minimal guidance on how students were to design the data collection setups. The conceptual work about the target phenomenon would be done later, after the students had collected reliable data. During this process, student work with digital measuring instruments introduced additional forms of pedagogical uncertainty. Questions arose as to what extent students were engaging in productive intellectual work when extended amounts of time were taken up trying to figure out whether their instruments were actually working. Much of the classroom observation time on data collection days involved the IS2 team members and teachers helping students troubleshoot their instruments, and teachers repeatedly expressed concern about the time this took. Because a convenient way for students to produce fairly large real‐world noisy datasets is with digital instruments, which the teachers had on hand, whether this kind of activity was something they wanted to continue was an important question for these inquiry‐oriented teachers.</p> <hd id="AN0188607205-4">Troubleshooting in Inquiry</hd> <p>When students participate in designing their investigations, it is not surprising that their designs will require troubleshooting. Unexpected behavior of an experimental setup presented one form of the uncertainty described by Manz et al. ([<reflink idref="bib19" id="ref16">19</reflink>]) and potentially created room for students to take up epistemic agency in trying to resolve the issue. Dixon et al. ([<reflink idref="bib9" id="ref17">9</reflink>]) identified troubleshooting as one of the forms of activity in which students were developing agency and disrupting identities oriented toward "doing school" during a classroom investigation of photosynthesis using CO<subs>2</subs> sensors. Technical troubleshooting has also been mentioned in connection with chemistry classes where students were constructing their own sensors (Albert [<reflink idref="bib1" id="ref18">1</reflink>]; Seroy et al. [<reflink idref="bib30" id="ref19">30</reflink>]), in classes where the focus was on design tasks in engineering (Crismond and Peterie [<reflink idref="bib6" id="ref20">6</reflink>]), and where students were engaged in block‐based programming of sensors (Bondaryk et al. [<reflink idref="bib2" id="ref21">2</reflink>]; Gendreau Chakarov et al. [<reflink idref="bib11" id="ref22">11</reflink>]; Sullivan and Keith [<reflink idref="bib39" id="ref23">39</reflink>]). Sullivan ([<reflink idref="bib38" id="ref24">38</reflink>]) identified a troubleshooting cycle in the context of a robotics exploration.</p> <p>In most of these studies, the main emphasis of the lessons was not on science content knowledge, but on design strategies, so the focus of the troubleshooting was consistent with the focus of the lesson. Seroy et al. ([<reflink idref="bib30" id="ref25">30</reflink>]) however, included chemistry concepts in a focus on transdisciplinary learning and that study reported that some students felt frustrated and confused by the technical issues. Although several of the studies in this section mentioned that teachers needed to understand the technology and be ready to provide support, these particular studies did not recommend teaching strategies for dealing with attendant frustration. Their recommendations were oriented more toward technical support (e.g., Seroy et al. [<reflink idref="bib30" id="ref26">30</reflink>]), or structuring the troubleshooting process and helping students maintain focus on their design work (Crismond and Peterie [<reflink idref="bib6" id="ref27">6</reflink>]).</p> <p>Providing technical support may not be enough in science classes when there is a tight schedule to cover a set of disciplinary core ideas. Even if students are good at troubleshooting their instruments and at persevering, both students and teachers may view time spent on this as beside the point of instruction, as interfering with the conceptual work involved in sense‐making and in refining their explanatory models of science phenomena. Student affect comes into play.</p> <p>The present study explores whether the work students engaged in while distracted by technical difficulties away from the target phenomenon they wanted to focus on supported their functioning as doers of science, their ability to experience their work as meaningful, and their exercise of epistemic agency. To do this, it will be helpful to look further at epistemic agency and its connections to the mangle of practice and epistemic affect.</p> <hd id="AN0188607205-5">Relationships Between Epistemic Agency, the Mangle, and Epistemic Affect</hd> <p>Miller et al. ([<reflink idref="bib22" id="ref28">22</reflink>]) defined epistemic agency as the power to shape the knowledge production and practices of a community. When students are epistemic agents, they become collaborators in co‐constructing knowledge rather than being receivers of scientific facts and practices who then follow the practices of science as mandated by authority (Ko and Krist [<reflink idref="bib17" id="ref29">17</reflink>]; Miller et al. [<reflink idref="bib22" id="ref30">22</reflink>]). Epistemic agency for students refers to their ownership in making decisions about what they know, how certain they are about it, and how to go about figuring out what they still need to know (Kelly et al. [<reflink idref="bib16" id="ref31">16</reflink>]).</p> <p>Stroupe ([<reflink idref="bib37" id="ref32">37</reflink>]) argued that to address recently expanded expectations for students to learn science‐as‐practice, they must take on a role as epistemic agents. In a study that examined five classrooms, he found that in the three classrooms where students took up roles as epistemic agents, science activity emerged that resembled Pickering's ([<reflink idref="bib27" id="ref33">27</reflink>]) mangle of practice. According to Pickering, scientists engage in the mangle when they are trying to extract some kind of information from nature and nature appears to resist their efforts. When things (typically, according to Pickering) do not go as expected, it is often due to a discrepancy between the scientists' ideas and the readings they are getting from their instruments. They are then led to modify their conceptions, their instruments, or both to bring their material and conceptual worlds into alignment.</p> <p>Manz ([<reflink idref="bib18" id="ref34">18</reflink>]) and Manz et al. ([<reflink idref="bib19" id="ref35">19</reflink>]) have argued for designing the mangle into science instruction. They described scientific practice as involving the development of alignments among phenomena, data, and explanatory models, and pointed out that these alignments have been both under‐theorized and under‐utilized in instructional environments. If these alignments are uncertain for students and they are not supported to make sense of them in productive ways, "teachers are left doing the mop‐up" (Manz et al. [<reflink idref="bib19" id="ref36">19</reflink>], 10). These authors have suggested the classroom investigation as a key locus for constructing these alignments. Manz et al. warned about "knowledge‐lean" tasks, where the primary focus is on the structure of the experimental design or the interpretation of data. Though they discussed the role of instrumentation, such as asking whether an instrument would produce trustworthy results, their middle school students did not use digital instruments, but recorded data by hand and developed their own data models.</p> <p>The problem addressed in the present study is precisely the one Manz et al. ([<reflink idref="bib19" id="ref37">19</reflink>]) warned about, where the primary focus has been pulled away from the phenomenon of interest to the problem of interpreting data from possibly faulty instruments. Returning to Pickering ([<reflink idref="bib27" id="ref38">27</reflink>]) may help. He paid considerable attention to the construction of alignments between machinic performance and knowledge in the professional laboratory, saying these got reciprocally tuned to one another. He described the development of specific scientific instruments, such as the bubble chamber, in terms of their resistance to capturing the information the scientists wanted. Thus, the conceptual models involved in his accounts were not only of the phenomena of interest, but of how the instruments functioned and interacted with the phenomena they were designed to detect. A question that arises with respect to the present study is whether secondary students, troubleshooting technical aspects of their measuring equipment, might respond by engaging productively with the mangle, creating alignments that—in at least some sense—parallel those created by Pickering's scientists.</p> <p>Closely related to epistemic agency is <emph>epistemic affect</emph>, which "can be thought of as those emotions, feelings, and dispositions that are experienced in the epistemic work of constructing and critiquing knowledge within epistemic pursuits and in reflection around those pursuits" (Davidson et al. [<reflink idref="bib7" id="ref39">7</reflink>], 1011). More particularly, epistemic affect in science refers to feelings experienced during knowledge construction within science, as opposed to feelings about or toward science (Davidson et al. [<reflink idref="bib7" id="ref40">7</reflink>]). Rather than excitement about a phenomenon, it might be excitement about learning about the phenomenon or about figuring out a method to solve a problem. DeBellis and Goldin ([<reflink idref="bib8" id="ref41">8</reflink>]) discussed the importance of <emph>meta‐affect</emph>, or feelings about feelings, during student mathematical problem solving. They suggested the most important affective goals in instruction are not to eliminate frustration or to make an activity easy, but to develop a meta‐affect that is productive of learning and accomplishment. They described positive and negative affective pathways, a series of feelings about feelings that could lead from frustration to pleasure, elation, and satisfaction, or alternatively, to anxiety and despair. Jaber and Hammer ([<reflink idref="bib14" id="ref42">14</reflink>]) argued that affect and motivation are part of the material students need to learn. Although their focus was on a positive example of meta‐affect, they indicated that less positive episodes in the same classroom suggested areas that could have used instructional attention with respect to epistemic affect. They suggested that teachers be attuned to students' affective experiences and at times be willing to "(relax) their concern about canonical knowledge" (Jaber and Hammer [<reflink idref="bib14" id="ref43">14</reflink>], 191). Stroupe ([<reflink idref="bib37" id="ref44">37</reflink>]) reported that some teachers dealt with potential frustration when activities did not work by embracing the mangle and explaining to students that science is often done in "fits and starts" (p. 512). However, as mentioned above, Manz ([<reflink idref="bib18" id="ref45">18</reflink>]) pointed out the need to balance disruption and focus.</p> <p>Taken together, the literature has argued persuasively that an experience of epistemic agency, engagement with the mangle to construct new alignments, and a productive epistemic affect can work together in the inquiry classroom to support the development of science practices. On the other hand, when disruption has arisen due to technical aspects of laboratory equipment, as in the present study, the question of how to achieve a productive balance of disruption and focus may not be an easy one, even for teachers experienced in inquiry and skilled in managing students' immediate affective responses. In the analysis presented here, the concepts of epistemic agency, the mangle, and epistemic affect will function as a set of lenses through which a troubleshooting episode can be examined. This will lay the foundation for a discussion of how the value of the episode in terms of science practices and the disruption the episode created were perceived differently by the different actors involved.</p> <p>After describing the context and methods, I present a brief overview of results from an earlier, preliminary analysis that raised questions and motivated the present analysis. Those results—from videos from the classrooms of multiple teachers—help situate the episode analyzed here as one of several with similar patterns of video codes that turned out to correspond to technical troubleshooting. The transcript of the exemplar episode is then examined for evidence of the exercise of student epistemic agency and the appearance of student epistemic affect, along with evidence of the kinds of alignments the students were trying to make between their conceptual and material worlds. I also note which NGSS science practices (NGSS Lead States [<reflink idref="bib24" id="ref46">24</reflink>]) the students appear to have engaged with. Because the entire episode, and the activity sequence in which it was embedded, was centered on the practice of planning and carrying out investigations, several different components of that practice are noted as an indication of the depth of student engagement in the practice. Next, students' meta‐affect is explored by taking a look at what they said about the episode immediately afterward. The retrospective perspectives of the teacher and IS2 observer are presented. The discussion section focuses on themes that emerged during analysis and looks back at the literature to suggest possible reasons for the results. Finally, I draw theoretical and practical implications for the scaffolding students may need to deal productively with these kinds of troubleshooting experiences when they arise in the school science laboratory.</p> <hd id="AN0188607205-6">Methods</hd> <p></p> <hd id="AN0188607205-7">Research Design</hd> <p>This study is emergent in that it was inspired by unexpected patterns in video coding of several classrooms completed in earlier rounds of qualitative analysis (Stephens and St. Clair [<reflink idref="bib34" id="ref47">34</reflink>]; Stephens, St. Clair, Ediss, Farmer et al. [<reflink idref="bib35" id="ref48">35</reflink>]; Stephens, St. Clair, Ediss and Lee [<reflink idref="bib36" id="ref49">36</reflink>]). Turning to a case study approach (Creswell and Poth [<reflink idref="bib5" id="ref50">5</reflink>]; Merriam and Tisdell [<reflink idref="bib21" id="ref51">21</reflink>]), I use video data from a single small group both to illustrate questions raised by those earlier results and to address those questions through in‐depth exploration of one extended troubleshooting episode, from the onset of a technical problem to its resolution. This approach is appropriate because the research questions are descriptive and explanatory, and focusing on a single, unusually rich episode allows in‐depth exploration of, and suggests potential explanations for, phenomena that were observed across several cases. Criteria for selecting a group and an episode are described below. First, I describe the curricular and classroom context within which the chosen group functioned.</p> <hd id="AN0188607205-8">Context</hd> <p>The troubleshooting episode occurred during a lesson that was conducted in the fall of 2018 as part of classroom trials in the third year of a 6‐year National Science Foundation‐funded project, InquirySpace 2: Broadening Access to Integrated Science Practices (IS2). This late stage design and development project developed activities and resources for use with the InquirySpace software environment, which integrates probeware (classroom sensors plus data collection software), a data analysis platform (Common Online Data Analysis Platform, or CODAP, https://codap.concord.org), and instructional guidance for data exploration. Using these tools, students in schools in several states from a wide range of cultural and socioeconomic backgrounds learned to design and carry out their own investigations in high school physical science, physics, biology, and chemistry classes using real, often noisy, data (e.g., St. Clair et al. [<reflink idref="bib31" id="ref52">31</reflink>], [<reflink idref="bib32" id="ref53">32</reflink>]; Stephens [<reflink idref="bib33" id="ref54">33</reflink>]). In each of these, the students designed physical setups to produce data and the probeware generated real‐time graphs as those data were collected. The activities sought to engage students in three‐dimensional learning as described in the <emph>Framework</emph> (National Research Council [<reflink idref="bib23" id="ref55">23</reflink>]), investigating phenomena involving change over time in the context of the science practice of planning and carrying out investigations along with several crosscutting concepts. The lessons were organized around inquiry phases of design, collect, analyze, explain, where classroom time was devoted to each phase. It was expected that uncertainty arising from material resistance experienced during the collect phase would be resolved as students revised their mental models of phenomena during the explain phase, leading, if necessary, to design revisions. (See the Supporting Information for a diagram of the inquiry framework used in lesson development.)</p> <p>The physics sequence, designed for 9th–12th grade courses, was revised following a pilot the first year and several classroom trials the second year. The Year 3 version included eight activities related to forces and motion with scaffolds fading across the sequence. The sequence lasted between 4 and 5 weeks if all activities were completed. "Forces and Motion" is a disciplinary core idea in the NGSS, and one of the performance expectations is that by the time students leave high school, they can use graphs of position or velocity as a function of time to support claims related to Newton's second law of motion (NGSS Lead States [<reflink idref="bib24" id="ref56">24</reflink>], 94). Disciplinary goals for the physics sequence were to work toward this expectation by fostering a rich understanding of graphs of position and velocity through participation in all phases of planning and carrying out investigations, along with several crosscutting concepts such as those related to cause and effect. The episode analyzed here occurred in a class taught by Mr. D (see the Participants section below). Table 1 shows the number of class periods his classes spent on each activity. The classroom sensors were motion detectors that captured position/time data using ultrasound.</p> <p>1 Table A summary of the activity sequence with average time spent on each by Mr. D's classes.</p> <p> <ephtml> <table><thead valign="bottom"><tr valign="bottom"><th>Activity</th><th>Length<ext-link href="a" /></th><th>Description</th><th>Focus</th></tr></thead><tbody valign="top"><tr><td>1.1</td><td>3 periods</td><td>Explore spring‐mass system</td><td>Introduction to experimentation</td></tr><tr><td>1.2</td><td>2 periods</td><td>Walk in front of a motion detector to match provided graphs</td><td>Introduction to digital tools: Motion detectors and graphed data</td></tr><tr><td>2.1</td><td>2 periods</td><td>Measure velocity of rolling ball using analog methods</td><td>Identify noise, outliers, and limits of analog tools</td></tr><tr><td>2.2<ext-link href="b" /></td><td>4 periods</td><td>Measure velocity of rolling ball at a specified location with motion detectors</td><td>Design setups, identify dependent and independent variables and constants, and limits of digital tools</td></tr><tr><td>2.3</td><td>3.5 periods</td><td>Test results of student data analysis, use results to meet a challenge</td><td>Develop testable question, carry out investigation</td></tr><tr><td>3.1</td><td>3.5 periods</td><td>Measure negative acceleration of rolling ball using analog methods</td><td>Plan and carry out investigation of acceleration using position‐time measurements</td></tr><tr><td>3.2</td><td>1 period</td><td>Explore positive and negative acceleration in simulation</td><td>Plan and carry out investigation of acceleration, identify causal relationships</td></tr><tr><td>3.3</td><td>4 periods</td><td>Independent experiments with acceleration</td><td>Independently design, conduct, and iterate an investigation</td></tr></tbody></table> </ephtml> </p> <p>1 a Each classroom period lasted between 55 and 75 min, depending on the day.</p> <p>2 b The troubleshooting episode analyzed here occurred during the second period of Activity 2.2.</p> <p>In Activity 2.2, students rolled a ball down a ramp and across the floor and measured its velocity immediately after it left the ramp using the motion detectors (Figure 1). They were tasked with figuring how to get reliable data to determine how ramp height affected the velocity reached by the ball at that location. Aspects of the design and testing procedures were left to the students, including what ramp heights to try and where to place the motion detectors. Sources of variation in class data included ramp heights, noise inherent in the motion, and differences among the groups due to their procedural choices.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/SED/01nov25/sce21979-fig-0001.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="sce21979-fig-0001.jpg" title="1 Student‐designed ball‐ramp setup for Activity 2.2. To measure the velocity just after the ball left the ramp, most groups chose to place the detector either back along the line of travel as shown, at the bottom of the ramp and across the line of travel, or at the top and aimed down the ramp." /> </p> <p></p> <p>This was the first time students had used motion detectors to collect noisy data, although they had become acquainted with them during Activity 1.2. Mr. D's class spent four class periods on Activity 2.2. The lesson structure for this activity was:</p> <p></p> <ulist> <item> whole class introduction;</item> <p></p> <item> small group first data collection: design data collection setups and conduct test runs;</item> <p></p> <item> whole class discussion: compare values calculated for velocity, identify sources of variation, come to class consensus on how to minimize variation across the class;</item> <p></p> <item> small group second data collection: use the procedures agreed upon by consensus; and</item> <p></p> <item> whole class discussion: pool small group values for velocity and compare mean, median, and standard deviations using CODAP for calculations.</item> </ulist> <p>The troubleshooting episode analyzed here occurred during the first data collection, which for this class, occurred on Day 2. Figure 1 is a sketch of the data collection setup these students were using.</p> <hd id="AN0188607205-10">Participants</hd> <p>The school was in an upper middle class professional, suburban town in which more than 67% of the adult residents held bachelor's degrees or higher. The teacher, Mr. D, had been teaching physics for 35 years, 25 of them at his current school, and this year was teaching both honors physics and engineering physics. He had participated in the original InquirySpace project, and in IS2, had taught parts of the physics sequence the previous 2 years. He had attended in‐person professional development workshops with the IS2 team each of the two preceding summers, the most recent of which had lasted 3 days. He said that by the time of this study, his approach to inquiry had begun to shift to be less open‐ended than it had been in his early teaching years.</p> <p>The class, one of two in which Mr. D implemented the IS2 activities, was honors physics, with 14 juniors and seniors who worked in five small groups. The group focused on here (for reasons discussed below) was one of two chosen by Mr. D as representative of this class. The students had agreed through IRB‐approved consent/assent procedures to have their activity captured by screencasts, which recorded video of onscreen activity and audio of student voices. In addition, the students used a small external camera connected to their laptop computer to capture their physical experiments. The group comprised three young women, two seniors and a junior. Because this was not one of the schools I observed in, I relied on notes from another team observer for information about the students. A pretest was administered, and though those results will not be analyzed here, they did suggest variation in ability and preparedness within this group, with the junior scoring above class average and the seniors below.</p> <p>The IS2 project that year included lesson sequences in multiple science subjects in several schools on the East Coast, and a team of project members rotated to observe as many classes as possible, assisting with the implementations as needed. Ms. O, the team observer/participant (or simply, the "observer") who was present the day of the troubleshooting episode that is the focus of this study, filled in as needed to observe in Mr. D's school. She held a master's degree in biology, had previously worked as a laboratory technician, and was very comfortable with technology. She had also been an instructor at the college level. She helped with the technology, scaffolded students, and also took detailed observation notes. She said her understanding of her role when interacting with the students was "guide the students but don't give it away." She observed three of the 4 days of Activity 2.2.</p> <hd id="AN0188607205-11">Researcher Role and Perspective</hd> <p>As one of the researchers on the team, I helped coordinate observation procedures, monitoring and compiling the observation notes from the entire team. I was an observer/participant in some of the physics classes, though not at this school. I was slightly acquainted with Mr. D, having observed his class once in a prior project and participated in one of the professional development workshops he had attended. My perspective was also informed by observations of inquiry‐based classes in previous projects. Those experiences had already heightened my interest in looking for learning, agency, and "seeds of mature science" (Hammer [<reflink idref="bib13" id="ref57">13</reflink>]) in student activity, in whatever form these might take.</p> <hd id="AN0188607205-12">Selection of Cases</hd> <p>Criteria for selecting a group among the 24 focal groups observed that year included choosing one with screencasts of most or all days of the activity, a student makeup that was stable, members who communicated with each other enough to provide video evidence of their reasoning, and students who exhibited issues observed broadly across the classes in which the physics activity sequence was implemented. The group chosen tended to express their thinking aloud, appeared to be generally representative of their class, and had a stable makeup. They also provided the richest source of audio/video data of issues observed across the classes.</p> <hd id="AN0188607205-13">Identifying Troubleshooting Episodes</hd> <p>Preliminary video analysis had focused on the extent to which the classes had engaged with the stated learning goals for each lesson, grouped under the inquiry phases around which the activity sequences had been constructed. Cross‐teacher case study analyses of Activity 2.2 had compared several teacher approaches to those lessons (Stephens, St. Clair, Ediss, Farmer et al. [<reflink idref="bib35" id="ref58">35</reflink>]; Stephens, St. Clair, Ediss and Lee [<reflink idref="bib36" id="ref59">36</reflink>]). Seeking to gain increased understanding of how students engaged in the inquiry process, I began to look at how small groups transitioned through the inquiry phases during this activity. Figure 2 shows the results for the group of focal students in Mr. D's class. (See the Supporting Information for corresponding code maps for representative small groups from the other physics teachers).</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/SED/01nov25/sce21979-fig-0002.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="sce21979-fig-0002.jpg" title="2 Timeline and video codes (produced with Transana video analysis software; Woods [40]) for inquiry phases in Activity 2.2 in Mr. D's class. The video record switches between whole class (WC) activity and the activity of the focal small group. Time on task across four days was approximately 2 h and 15 min. Note the clustering of inquiry phase codes on Day 2 in the small group." /> </p> <p></p> <p>Although I anticipated seeing movement back and forth between collecting and analyzing data on Day 2 when students were working to refine their data collection procedures, when I shared these results with colleagues, questions arose about points at which codes for three or four inquiry phases appeared together. These seemed to indicate that these "phases" were occurring simultaneously, which appeared unlikely. Going back to the video, I realized these and similar code clusters in other groups occurred during student troubleshooting. What I designate as a troubleshooting "episode" is student activity bounded by an initial expression of frustration or confusion, followed by efforts to either modify the data collection procedure(s), explain the readings, or both, and ending when students expressed satisfaction with their data collection. The episode to be analyzed here is indicated by the first code cluster for this group, starting approximately a third of the way into the Day 2 small group activity.</p> <p>Figure 3 shows coding of this episode recoded at a finer grain size, revealing distinct inquiry phases but with only seconds for each phase. (See the Supporting Information for re‐coded sections from other small groups showing similar patterns.) In the video, the students appeared to be having strong reactions to their motion detector data, exclaiming and exhibiting frustration. This raised yet more questions about what learning might be occurring, to what extent the students might be experiencing agency, what their perception of the episode was, and the roles played by the teacher and IS2 observer.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/SED/01nov25/sce21979-fig-0003.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="sce21979-fig-0003.jpg" title="3 The approximately 8‐min troubleshooting episode (starting at the 40‐min mark in Figure 2) re‐coded at a finer grain size. The teacher and IS2 observer stopped by the small group for several minutes as indicated by codes for "T/O at small group." Although the codes were no longer simultaneous at this resolution, the rapid movement from one to the next reinforced the impression that something unexpected was going on during the episode. (Code map produced with Transana; Woods [40].)" /> </p> <p></p> <hd id="AN0188607205-16">Data Sources for the Study</hd> <p>Data sources include field notes, video recordings of small group and whole class activity, and video recordings of retrospective interviews.</p> <p> <emph>Field notes</emph> for Day 2 of the activity, taken by Ms. O, were clear and fairly extensive, providing a guide to the overall activity in the class.</p> <p> <emph>Video and audio recordings</emph> captured the activity. A camera on a tripod captured whole class activity. Screencast software captured focal student activity on the computer as well as voices of those near the computer. The group also used a small external camera to capture their design and use of their data collection setup with a ball, ramp, and motion detector.</p> <p> <emph>Retrospective interviews</emph> with Mr. D and Ms. O were conducted 3 years later at the end of the project, after the video analysis had raised questions not considered during the follow‐up teacher survey and initial debrief. I assumed the teacher and observer would not remember the specific troubleshooting episode from the earlier year, and so the interviews centered on Mr. D's and Ms. O's reactions to the small group video record. I began each interview by showing a video excerpt where Mr. D or Ms. O was interacting with the focal students (the portions coded "T/O at small group" in Figure 3). Playback was paused after each interaction and the interviewee was asked to speculate on what they had been thinking at the time and what might have motivated that interaction. After playback was complete, they were asked how they decided when to let students problem‐solve technical issues and when to encourage students to refocus on the goal of the investigation and move on. They were also asked whether they saw students getting any value from the troubleshooting. An additional question for Mr. D was at what point in the entire activity sequence he felt that most learning had occurred. Questions from the interviews are summarized in the Supporting Information.</p> <hd id="AN0188607205-17">Analysis: What Was Occurring and Did It Have Value?</hd> <p>The present case study analysis was prompted by a desire to understand what was occurring in those moments when students were troubleshooting, where coding in terms of inquiry phases had raised more questions than it answered. The focus moved to an additional area of theory that underlay the development of the activity sequences, the idea that as students moved through the inquiry phases, there would be interplay between <emph>student agency</emph> in the development of science practices and <emph>material resistance</emph> as they tried to collect data (see the Supporting Information for a diagram of the theory that underlay the development). Digging deeper into the literature on material resistance and the mangle of practice (Manz et al. [<reflink idref="bib19" id="ref60">19</reflink>]; Pickering [<reflink idref="bib27" id="ref61">27</reflink>]), I became interested in the nature of the conceptual‐material misalignments the students appeared to be grappling with and whether this activity appeared to have disciplinary value. This led to the first research question, where I asked whether the students were repairing conceptual‐material misalignments and, if so, whether their repair appeared to lead to exercise of student epistemic agency. I developed and refined observation codes, working both deductively from the literature and inductively from the data in multiple rounds of analysis (Creswell and Poth [<reflink idref="bib5" id="ref62">5</reflink>]). To investigate the disciplinary value in terms of engagement with science practices, I used definitions from the NGSS (NGSS Lead States [<reflink idref="bib24" id="ref63">24</reflink>]). To address the second research question, to understand the value the students placed on the episode, I developed codes for epistemic affect to identify student feelings about their knowledge construction. A different procedure is used to understand the value the teacher and IS2 observer placed on the episode; I discuss their responses to direct questions about this, posed during retrospective interviews. As a check on validity, final codes, definitions, coding results, and interpretations of student, teacher, and observer utterances were reviewed by a senior researcher on the team, and clarified as a result. The codes themselves are presented in the following sections.</p> <p>Although the entire transcript corresponding to Figure 2 was subjected to analysis, for reasons of space, only the results for the troubleshooting episode in Figure 3 are explored in depth here. As mentioned, this episode exemplifies several issues noted across video recordings and field notes from the IS2 physics class implementations. In addition, the interactions of the group with Mr. D and Ms. O illustrate more than one way this kind of activity may be responded to. The students' clear articulation of their thinking provides insights into how they were reasoning, what questions they were asking themselves as they worked to construct alignments between their material and conceptual worlds, and how they felt about their knowledge construction.</p> <hd id="AN0188607205-18">Codes for the Mangle of Practice</hd> <p>The aspect of the mangle I focused on was the students' efforts to create alignments between their material and conceptual worlds (Pickering [<reflink idref="bib27" id="ref64">27</reflink>]). These concepts were anticipated to be about velocity and how it would be represented in position/time graphs, but during inductive rounds of coding, I broadened this to include student conceptions about how the sensors worked and what data patterns their experimental setups should yield. In addition to evidence of a lack of alignment or an attempt to produce alignment (by changing their ideas or their setups), I also looked for evidence of students experiencing material resistance, as described in Pickering ([<reflink idref="bib27" id="ref65">27</reflink>]). The codes were inspired by the literature and the definitions were refined during iterative rounds of inductive and deductive coding (Table 2).</p> <p>2 Table Engaging in the mangle of practice.</p> <p> <ephtml> <table><thead valign="bottom"><tr valign="bottom"><th>Code</th><th>Definition</th><th>Example</th></tr></thead><tbody valign="top"><tr><td>Material resistance</td><td>Materials used in an experiment do not do what the students want or expect them to</td><td>"We moved the detector, but it's still messing up!"</td></tr><tr><td>Lack of alignment</td><td>The results of data collection do not align with the students' conceptions of what is happening to produce those results</td><td>"Shouldn't this data reading be going down?"</td></tr><tr><td>Attempt at alignment</td><td>Students suggest a change in their methods and/or conceptions to try to align their data collection results with their conceptions</td><td>"Maybe the ball bounced?"</td></tr></tbody></table> </ephtml> </p> <hd id="AN0188607205-19">Codes for Epistemic Agency</hd> <p>Stroupe ([<reflink idref="bib37" id="ref66">37</reflink>]) describes epistemic agents as those who take, or are granted, responsibility for shaping the knowledge and practice of a community and who take or are granted the power to verify knowledge claims, ask research questions, and direct experiments. I examined the video record for evidence of students taking such power, then identified categories and developed descriptors during iterative rounds of coding. The resulting descriptive codes, definitions, and examples are shown in Table 3.</p> <p>3 Table Exercising epistemic agency.</p> <p> <ephtml> <table><thead valign="bottom"><tr valign="bottom"><th>Code</th><th>Definition</th><th>Example</th></tr></thead><tbody valign="top"><tr><td>Design decision</td><td>Makes decision about the design of their data collection setup</td><td>"Let's put the motion detector behind (where ball is headed)."</td></tr><tr><td>Suggest how to troubleshoot</td><td>Suggests how to troubleshoot an issue related to data collection</td><td>"Maybe stand to the side" away from the sensor</td></tr><tr><td>Enact troubleshooting idea</td><td>Enacts a troubleshooting idea suggested by the group</td><td>Student repositions the setup and they make another data run</td></tr><tr><td>Evaluate enactment of idea</td><td>Evaluates the enactment of a design or troubleshooting idea</td><td>"It only did it (messed up) a little bit, so that was better."</td></tr><tr><td>Spontaneously ask question about meaning of data</td><td>Unprompted, asks a question about the meaning of their data or data patterns</td><td>"The only thing I don't get is, why is (the graphed data) straight before it goes off the ramp?"</td></tr><tr><td>Evaluate quality of data</td><td>Evaluates the quality of data they have collected</td><td>"I like this data more, cause it's," (points to clean graphical shape)</td></tr><tr><td>Evaluate what info counts</td><td>Evaluates which information counts as data</td><td>Selects and exports only the meaningful portion of motion detector reading for analysis</td></tr><tr><td>Decide which data to use</td><td>Decides which of their data to use to best address the question</td><td>"Mmhm, we should just go with that data."</td></tr><tr><td>Decide sufficient amount of info</td><td>Decides whether they have gathered a sufficient amount of good data to address the question</td><td>"I think we definitely have enough data to get the velocity."</td></tr><tr><td>Student as "more knowledgeable other"</td><td>Acts as a "more knowledgeable other" toward another student, a teacher, or an observer by explaining something the other person indicates they do not understand</td><td>"Well, it's flat at the first part because it doesn't register it while it's on the ramp. 'Cause it's like, too high. But it's not supposed to register while it's on the ramp."</td></tr></tbody></table> </ephtml> </p> <hd id="AN0188607205-20">Codes for Epistemic Affect</hd> <p>DeBellis and Goldin ([<reflink idref="bib8" id="ref67">8</reflink>]) suggested it is important for students to develop a meta‐affect that is productive of learning and accomplishment. Seeking to understand what led to these students' meta‐affect, I looked for evidence of the epistemic affective pathway or pathways that accompanied the group's troubleshooting and culminated in their expressions of meta‐affect immediately after the episode. Affect was considered to be epistemic if it concerned the students' knowledge construction (following the description of Davidson et al. [<reflink idref="bib7" id="ref68">7</reflink>]), as when students expressed confusion about whether the information they were gathering was meaningful. Evidence for four distinct feelings about their knowledge construction was identified (Table 4).</p> <p>4 Table Experiencing epistemic affect.</p> <p> <ephtml> <table><thead valign="bottom"><tr valign="bottom"><th>Affective code</th><th>Definition (when concerning efforts to construct knowledge)</th><th>Example (when referring to efforts to construct knowledge)</th></tr></thead><tbody valign="top"><tr><td>Confusion</td><td>Uncertainty, bewilderment</td><td>"What the heck?"</td></tr><tr><td>Frustration</td><td>Annoyed at inability to achieve something</td><td>"No, it still did it!"</td></tr><tr><td>Confidence</td><td>Self‐assurance, certainty</td><td>"We definitely have enough data."</td></tr><tr><td>Relief</td><td>Reassurance and relaxation following distress</td><td>"Oh good, now I understand."</td></tr></tbody></table> </ephtml> </p> <hd id="AN0188607205-21">Codes for the NGSS Practice of Planning and Carrying Out Investigations</hd> <p>The eight NGSS scientific and engineering practices are defined and discussed extensively in the standards (NGSS Lead States [<reflink idref="bib24" id="ref69">24</reflink>]). For the practice of planning and carrying out investigations, which constituted the entire activity sequence, I consulted the NGSS practices matrix (NGSS Lead States [<reflink idref="bib24" id="ref70">24</reflink>], Appendix F, 7–8) to identify components that could help in gauging the richness of student engagement with that practice when dealing with technical issues. Through iterative rounds of video coding, I developed and honed criteria for four observation categories based on these components. The honed criteria were applied in a final round of coding. Description of the codes and criteria follow.</p> <p> <emph>Provide Evidence for or Test a Conceptual Model</emph>:</p> <p>I looked for any evidence of a student describing a conceptual model, even if it was not an explanatory model of the phenomenon that was the focus of the lesson. Although evaluating mental models of how the measurement tools worked was not the expected focus of the investigation, Pickering ([<reflink idref="bib27" id="ref71">27</reflink>], [<reflink idref="bib28" id="ref72">28</reflink>]) makes the case that figuring out how their material setups will perform and aligning or realigning this with their concepts is an important part of the practice of professional scientists.</p> <p> <emph>Evaluate the Investigation's Design to Ensure Variables Are Controlled</emph>:</p> <p>Because these students already understood the need to control variables, I looked for any discussion about possible changes in the data collection setup related to reliability of data. This could include details of detector placement or a need to control aspects of the environment around the detector.</p> <p> <emph>Decide on Types, How Much, and Accuracy of Data Needed to Produce Reliable Measurements</emph>:</p> <p>This included discussion to figure out what was accurate enough for the task at hand and how much "good data" was needed to obtain a reliable value for the velocity.</p> <p> <emph>Manipulate Variables and Collect Data to Identify Failure Points or Improve Performance Relative to Criteria for Success</emph>:</p> <p>The original wording in the NGSS Practices Matrix (the last bullet in the grade band) refers to collecting data about a complex model of a system (NGSS Lead States [<reflink idref="bib24" id="ref73">24</reflink>]). Here, data were collected to identify failure points in the design of the data collection setups, and the criterion for success was to be able to obtain reliable information about the velocity.</p> <p>Concise definitions, along with examples, are included in Table 5.</p> <p>5 Table Four relevant components of the practice of planning and carrying out investigations.</p> <p> <ephtml> <table><thead valign="bottom"><tr valign="bottom"><th>Code</th><th>Definition</th><th>Example</th></tr></thead><tbody valign="top"><tr><td>Provide evidence for or test conceptual model</td><td>Report a conceptual model or suggest a test of a model</td><td>"I feel like that part (of the data) should just be straight."</td></tr><tr><td>Evaluate design</td><td>Evaluate the investigation's design in the context of ensuring that variables are controlled or data are reliable</td><td>"How much space?" (to produce reliable results). "A little more."</td></tr><tr><td>Decide accuracy of data needed</td><td>Decide on types, how much, and accuracy of data needed to produce reliable measurements</td><td>Do they have the information needed to determine velocity? "We have an idea." "Yeah."</td></tr><tr><td>Collect data to evaluate failure points</td><td>Manipulate variables and collect data to identify failure points or improve performance relative to criteria for success</td><td>The students adjust their setup, roll the ball, evaluate the results as unsatisfactory, readjust and roll again</td></tr></tbody></table> </ephtml> </p> <p>Engagement in other science practices was noted as well, using the definitions in NGSS Appendix F (NGSS Lead States [<reflink idref="bib24" id="ref74">24</reflink>]).</p> <hd id="AN0188607205-22">Analysis: What Value Did the Participants Place on These Episodes?</hd> <p>The second research question, about the participants' views of these episodes, is addressed primarily through quotations from two sources. The first is the portion of the small group video recording that immediately followed the troubleshooting episode; the associated transcript is short and provided in full. Although the other codes are not relevant to this part of the discourse (the students were no longer engaged in the mangle or exhibiting agency), the affective codes in Table 4 are relevant; the students were giving voice to their meta‐affect. The second source consists of the transcripts of the teacher and observer retrospective interviews, during which they were shown the video of the episode to stimulate recall. These wide‐ranging transcripts were not coded and are not presented in full (being quite long), but are summarized and quoted. They help enrich the picture of the classroom episode by providing information about what, at least in hindsight, these educators believed lay behind their scaffolding moves.</p> <hd id="AN0188607205-23">Results</hd> <p>Section 5.1 addresses Research Question 1 by exploring what was occurring during the episode in Figure 3. Extended transcript excerpts are presented along with the coding results. Sections 5.2 and 5.3 address Research Question 2 by looking at what the students said among themselves immediately after the episode and what Mr. D and Ms. O said in retrospective interviews. Section 5.4 looks briefly at what happened in the remainder of Activity 2.2 to make the case that the described results appear to have been associated primarily with troubleshooting rather than with the student data analysis and class discussion about the target concepts that followed.</p> <hd id="AN0188607205-24">An Extended Troubleshooting Episode</hd> <p>In the transcript (Tables 6a–c), S1 and S3 are the seniors, S2 the junior. Just before the transcript begins in Table 6a, they had moved to the hallway to set up a ball and ramp system with a motion detector. Their task was to measure the velocity of the ball immediately after it left the ramp. They agreed to place the detector on the floor aimed toward the ramp so the ball would roll toward the detector as it left the ramp (as in Figure 1). S2's job was to release the ball on the ramp, S1's to stop the ball before it hit the detector, and S3's to operate the software interface on the laptop. First, S3 zeroed the detector, placing the zero point close to the foot of the ramp. The result was that as the ball rolled down and past the zero point and continued along the floor toward the detector, it was plotted by the software as moving into increasingly negative positions. S3 was the only one who could observe the position‐time readings arriving in real time on screen, although the others could come over to look shortly after. The episode began with the first ball roll (Figure 4) and lasted a little under 8 min. The entire episode is coded as <emph>Planning and Carrying out Investigations</emph> ("Investigating"), and, where appropriate, labeled with the relevant components of this practice from Table 5.</p> <p>6a Table The mangle, agency, affect, and scientific practices during a troubleshooting episode: First ball roll.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th>Transcript (Ellipses indicate omissions to reduce repetition)</th><th align="center">Mangle</th><th align="center">Epistemic agency</th><th align="center">Epistemic affect</th><th>NGSS practices<ext-link href="a" /></th></tr></thead><tbody valign="top"><tr><td>S2: So, I'll make the ball go towards the motion detector, right? (...) How much space (...)? Is that good?S1: A little bit more space</td><td align="center" /><td align="center">Design decision</td><td /><td>3. Investigating: evaluate design</td></tr><tr><td>(S2 rolls ball, Figure 4)</td><td /><td align="center" /><td align="center" /><td>3. Investigating: collect data to evaluate failure points</td></tr><tr><td>S3: Mm, that's weird.</td><td align="center">Lack of alignment</td><td align="center" /><td /><td>3. Investigating</td></tr><tr><td align="left">S1, S2, and Ms. O, the IS2 observer, come over to look at the graph. S1 laughs.</td></tr><tr><td>S1: What the heck?S3: Yeah, it's just weird looking.S2: Interesting. This is not right.</td><td align="center">Lack of alignment, Material resistance</td><td align="center" /><td>Confusion</td><td>3. Investigating4. Interpreting</td></tr><tr><td>S3: Is that when it like, bounces?</td><td align="center">Material resistance</td><td align="center">Spontaneously asks question about meaning of data</td><td /><td>3. Investigating1. Asking4. Interpreting6. Explaining</td></tr><tr><td align="left">Ms. O: It could be.</td></tr><tr><td>S2: It didn't bounce though.S1: It went pretty straight though, right?S2/S3: Yeah.</td><td align="center">Lack of alignment</td><td align="center" /><td /><td>3. Investigating1. Asking7. Evidence</td></tr><tr><td>S3: Like, I feel like that part should just be like, straight.(Uses her finger to trace over the graph as though the downward sloping line were smooth and continuous with no spikes.</td><td align="center">Lack of alignment</td><td align="center" /><td>Confusion</td><td>3. Investigating: conceptual model4. Interpreting</td></tr><tr><td align="left">Ms. O: Yeah. (...) If you could make a prediction about what happened there, what were you thinking?</td></tr><tr><td>S3: Um‐ I don't‐ oh, maybe (S1) ‐from back there.S2: Oh, maybe it's getting you, (S1). But you're not moving, but it's still getting you.</td><td align="center">Attempt at alignment</td><td align="center">Evaluates enactment of idea</td><td /><td>3. Investigating6. Explaining</td></tr><tr><td align="left">Ms. O: So try it again (...) a few different (...) methods (...) and see what you notice.</td></tr><tr><td>S3: (overlapping) Maybe like, stand to–</td><td align="center" /><td align="center">Suggests how to troubleshoot</td><td /><td>3. Investigating</td></tr><tr><td align="left">Ms. O: (overlapping) Make sure there's nothing else in the way of the‐</td></tr><tr><td>S2: Wait, move the laptop back.</td><td align="center" /><td align="center">Suggests how to troubleshoot</td><td /><td>3. Investigating</td></tr><tr><td align="left">Ms. O: There's a bunch of different things it could be picking up.</td></tr></tbody></table> </ephtml> </p> <p>3 a (<reflink idref="bib1" id="ref75">1</reflink>) Asking questions (<reflink idref="bib2" id="ref76">2</reflink>) Developing and using models (<reflink idref="bib3" id="ref77">3</reflink>) Planning and carrying out investigations (<reflink idref="bib4" id="ref78">4</reflink>) Analyzing and interpreting data (<reflink idref="bib5" id="ref79">5</reflink>) Using mathematics and computational thinking (<reflink idref="bib6" id="ref80">6</reflink>) Constructing explanations (<reflink idref="bib7" id="ref81">7</reflink>) Engaging in argument from evidence (<reflink idref="bib8" id="ref82">8</reflink>) Obtaining, evaluating, and communicating information. From NGSS Lead States (2013).</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/SED/01nov25/sce21979-fig-0004.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="sce21979-fig-0004.jpg" title="4 First ball roll. S3 said, "Mm, that's weird."." /> </p> <p></p> <p>All of the discussion in Table 6a was over a single ball roll. At this point, Ms. O stepped away and the students tried rolling the ball twice more (Figure 5). The coded transcript continues in Table 6b.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/SED/01nov25/sce21979-fig-0005.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="sce21979-fig-0005.jpg" title="5 (a) Second ball roll, (b) third ball roll." /> </p> <p></p> <p>6b Table Second and third ball rolls.</p> <p> <ephtml> <table><thead valign="bottom"><tr valign="bottom"><th>Transcript (Ellipses indicate omissions to reduce repetition)</th><th>Mangle</th><th>Epistemic agency</th><th>Epistemic affect</th><th>NGSS practices<ext-link href="a" /></th></tr></thead><tbody valign="top"><tr><td>(2nd ball roll, Figure 5a)</td><td /><td>Enacts trouble‐shooting idea</td><td /><td>3. Investigating</td></tr><tr><td>S3: I think you have to not sit back there,'cause it still did it, but it didn't do it as much.Yeah, like, sit off to the side.</td><td>Material resistance</td><td>Suggests how to troubleshootEvaluates quality of data</td><td /><td>3. Investigating6. Explaining7. Evidence</td></tr><tr><td>It only did it a little bit though, so that was better.</td><td /><td>Evaluates enactment of idea</td><td /><td /></tr><tr><td>(3rd ball roll, Figure 5b, S1 rolls)</td><td /><td>Enacts trouble‐shooting idea</td><td /><td>3. Investigating</td></tr><tr><td>S3: No, it still did it!</td><td>Material resistance,Lack of alignment</td><td /><td>Frustration</td><td>3. Investigating</td></tr><tr><td>S2: Is it my hand?S3: I don't know. No, I mean it getsyour hand at the end, but it like messes it up, like, right, like–S2: In the middle.S3: Yeah.</td><td>Attempt at alignment</td><td>Evaluates enactment of idea</td><td>Confusion</td><td>3. Investigating1. Asking4. Interpreting6. Explaining</td></tr><tr><td align="left">Ms. O: Let me see that last graph. So, save that data. Do like, one or two more runs. But what you guys can do (...), you're seeing spikes, right? And you know that's like, unclear, but you have a section in there that actually is pretty decent and has a nice slope to it. So, (...) you can (...) see, like, when you start to get that kind of like, sloping data when you know that there's nothing else in between there, and then just kind of work off of that.</td></tr><tr><td>S2: Maybe we should try putting the motion detector behind it and set it up, would that still work? (...) We want the ball going towards it.</td><td>Attempt at alignment</td><td>Design decision</td><td>Confidence</td><td>3. Investigating: test conceptual model (of how setup works)</td></tr><tr><td align="left">Ms. O: You want it as soon as it leaves the ramp. (...) That's the velocity that you're trying to measure. (...) you could be seeing spikes like, right before you're getting that smooth line? It could be (unclear).</td></tr><tr><td>S3: But it's getting it after it leaves the ramp, I think.</td><td>Lack of alignment</td><td /><td /><td>3. Investigating7. Evidence</td></tr><tr><td align="left">The teacher, Mr. D, comes by.Mr. D: So (...), do you have the information to tell me what the velocity is as it rolls down?</td></tr><tr><td>S2: We have an idea.S3: Yeah.</td><td /><td>Decide sufficient amount of info</td><td>Confidence</td><td>3. Investigating: decide accuracy of data needed</td></tr><tr><td align="left">Mr. D: If you have enough from that trial, you can do that. If you want to try to get rid of the noise, you can maybe try one more trial. (...) Actually, you could probably save that and then move forward with some data. And there's ways to—if you see an outlier like that, you know, if you can predict why, it would make sense to keep it.</td></tr><tr><td align="left">Ms. O: I mean, one of the things you guys could think about is, are you consistently seeing something like that or is it variable every time?</td></tr><tr><td>S3: Consistent. (...) I think we definitely have enough data to get the velocity.</td><td>Alignment</td><td>Decide sufficient amount of info</td><td>Confidence</td><td>3. Investigating4. Interpreting</td></tr></tbody></table> </ephtml> </p> <p>4 a (<reflink idref="bib1" id="ref83">1</reflink>) Asking questions (<reflink idref="bib2" id="ref84">2</reflink>) Developing and using models (<reflink idref="bib3" id="ref85">3</reflink>) Planning and carrying out investigations (<reflink idref="bib4" id="ref86">4</reflink>) Analyzing and interpreting data (<reflink idref="bib5" id="ref87">5</reflink>) Using mathematics and computational thinking (<reflink idref="bib6" id="ref88">6</reflink>) Constructing explanations (<reflink idref="bib7" id="ref89">7</reflink>) Engaging in argument from evidence (<reflink idref="bib8" id="ref90">8</reflink>) Obtaining, evaluating, and communicating information. From NGSS Lead States (2013).</p> <p>The teacher, Mr. D, explained later that his intention in coming over was to move the students away from trying to get perfect data and to move forward with their analysis. The IS2 observer, Ms. O, had a similar objective, but used a question to direct their attention to the fact that the spikes in the graphs had occurred in the same part of the run each time, despite the students moving everything out of the way, including themselves. S3 now indicated confidence in their ability to obtain the velocity from the data they had. This marked a shift in their activity; they did not change their setup further. The transcript continues in Table 6c.</p> <p>6c Table Fourth ball roll and a student question.</p> <p> <ephtml> <table><thead valign="bottom"><tr valign="bottom"><th>Transcript (Ellipses indicate omissions to reduce repetition)</th><th>Mangle</th><th>Epistemic agency</th><th>Epistemic affect</th><th>NGSS Practices<ext-link href="a" /></th></tr></thead><tbody valign="top"><tr><td>(4<sup>th</sup>ball roll, similar to those in Figure 5</td><td /><td /><td /><td>3. Investigating</td></tr><tr><td>S2: Yeah, it definitely bounced. (laughs) It could definitely be like, the drop.S1: Yeah, that's what it's looking more like. Yeah.(Short off‐topic conversation)</td><td>Attempt at alignment</td><td /><td>Confidence</td><td>3. Investigating: test conceptual model (of motion detector)6. Explaining</td></tr><tr><td>S3: Um, I like this data more.S1: Me too.S3: 'Cause it's like, after (points to sloped part of motion detector data)</td><td>Alignment</td><td>Evaluates quality of data</td><td>Confidence</td><td>3. Investigating4. Interpreting7. Evidence</td></tr><tr><td>S1: Mmhm. We should just go with that.</td><td /><td>Decides which data to use</td></tr><tr><td align="left">(This marks the end of the troubleshooting. Then, after a pause, S2 asks a new question.)</td></tr><tr><td>S2: The only thing I don't get is, why is it straight before it goes off the ramp?</td><td>Lack of alignment</td><td>Spontaneously asks question about meaning of data</td><td>Confusion</td><td>3. Investigating: test conceptual model1. Asking</td></tr><tr><td>S1: 'Cause it's going at a constant velocity?</td><td>Alignment</td><td /><td /><td>3. Investigating6. Explaining</td></tr><tr><td>S2: But isn't it increasing as it goes down the ramp? And then it's like–</td><td>Lack of alignment</td><td>Spontaneously asks question about meaning of data</td><td>Confusion</td><td>3. Investigating:</td></tr><tr><td align="left">(Question from S3 about work to turn in, brief comments back and forth about that.)</td></tr><tr><td>S2: 'Cause like, this isn't getting velocity. It's getting like, how steep the slope should—like, how fast it's coming (unclear). You know what I mean? So like, it should be getting steeper and steeper and steeper and then like, constantly steep. You know what I mean? It should always be like, going down.S1: Yeah.</td><td>Lack of alignment</td><td>Spontaneously asks question about meaning of data</td><td>Confusion</td><td>3. Investigating: provide evidence for, test conceptual model1. Asking7. Evidence</td></tr><tr><td>S3: Yeah. Well, it's flat at the first part because it doesn't register it while it's on the ramp. 'Cause it's (...) too high. But it's not supposed to register while it's on the ramp. Like–S1: Oh, 'cause it's only like, there?S3: –it only gets it coming off the ramp, yeah.</td><td>Alignment</td><td>Student as "more knowledgeable other"</td><td>ConfidenceRelief</td><td>3. Investigating: provide evidence for conceptual model (connects graphical model to real world events)1. Asking6. Explaining7. Evidence</td></tr></tbody></table> </ephtml> </p> <p>5 a (<reflink idref="bib1" id="ref91">1</reflink>) Asking questions (<reflink idref="bib2" id="ref92">2</reflink>) Developing and using models (<reflink idref="bib3" id="ref93">3</reflink>) Planning and carrying out investigations (<reflink idref="bib4" id="ref94">4</reflink>) Analyzing and interpreting data (<reflink idref="bib5" id="ref95">5</reflink>) Using mathematics and computational thinking (<reflink idref="bib6" id="ref96">6</reflink>) Constructing explanations (<reflink idref="bib7" id="ref97">7</reflink>) Engaging in argument from evidence (<reflink idref="bib8" id="ref98">8</reflink>) Obtaining, evaluating, and communicating information. From NGSS Lead States (2013).</p> <p>Note that S2's question in Table 6c came <emph>after</emph> the students were satisfied they had good data and could answer the question posed by the lesson. She appeared to be saying that while the ball was on the ramp, it was accelerating and so should be traveling at a faster and faster velocity, producing a position‐time graph with a steeper and steeper slope. Once it hit the floor and velocity was changing very little (because there was little friction), the graph should have an approximately constant slope. Because the positions were registering as increasingly negative, the velocity and acceleration slopes should both be negative ("go down").</p> <p>S1 appeared to understand S3's explanation, that the detector was aimed low to miss the motion on the ramp. After the ball was off the ramp and in range of the detector, the slope was approximately constant except for the spikes (Figures 4 and 5). At this point, the students had figured out a number of things about how their data were represented (and some things about how the detector worked) and were ready to begin using the clean part of the slope to calculate the answer to the problem, the velocity of the ball immediately after it left the ramp.</p> <p>During this episode, there was evidence for student engagement in at least five of the eight NGSS science practices (NGSS Lead States [<reflink idref="bib24" id="ref99">24</reflink>]). When the students faced material resistance from their setup, they worked to create alignments between their conceptions of the graphical patterns they should be seeing in their data and the patterns they were seeing. They continually exhibited epistemic agency as they asked spontaneous questions about the meaning of their data; suggested, enacted, and evaluated troubleshooting strategies; evaluated what information counted as data and whether they had enough good data to address the question; and on occasion acted as a more knowledgeable other when interacting with each other. They repeatedly considered whether to revise their experimental setup and what the anomalous data meant. Although they expressed confusion and frustration for the first half of the episode, after an interaction with Ms. O, they began to exhibit confidence that they could distinguish the good data and that they had enough of it to calculate a reliable value for the velocity of the ball just after it left the ramp. S1 and S2 were still not satisfied with part of the data representation until S3 took on the role of a more knowledgeable other and explained it to them. At this point S1 and S2 appeared satisfied and S1, in addition, sounded relieved.</p> <p>Although teacher and observer moves were not a focus of the coding, it can be seen from their utterances that Mr. D and Ms. O provided support by asking open questions, using questions to suggest productive directions, and occasionally giving explicit information ("You want it <emph>[to be measured]</emph> as soon as it leaves the ramp"). These interventions also appeared to help with student frustration, suggesting ways they could move forward without, for the most part, being told what action to take. ("One of the things you guys could think about is, are you consistently seeing something like that....").</p> <hd id="AN0188607205-27">Student Reactions to the Episode</hd> <p>The transcript continues in Table 7, as the students reflected on the episode.</p> <p>As S3 worked to generate graphs of their last two runs, the students began articulating how they felt about the experience. Other than S3 trying to create a graph, the students were done with the investigation for the day, so it was not expected there would be evidence for engaging in the mangle or science practices or that they would have much opportunity to exercise epistemic agency. However, there was evidence of their epistemic affect—in this case, their meta‐affect. Starting immediately after the last utterance in Table 6c, the dialog continued.</p> <p>7 Table Epistemic affect immediately after a troubleshooting episode.</p> <p> <ephtml> <table><thead valign="bottom"><tr valign="bottom"><th>Transcript</th><th>Epistemic (meta)affect</th></tr></thead><tbody valign="top"><tr><td>S3: Um, I don't know how to get, um– (clicks around the screen trying to generate a graph)</td><td /></tr><tr><td>S1: I actually dread this class.</td><td>Frustration</td></tr><tr><td>S2: Like, I get up in the morning and I'm like—S1: Yeah. (pause)S2: I just don't learn anything.</td><td>Frustration</td></tr><tr><td>S1: Me neither. I don't know what we're going to do, like when we have a test.</td><td>Anxiety</td></tr><tr><td>(Two of the students give short laughs. S3 finishes constructing the graphs)</td><td>Anxiety</td></tr><tr><td>S2: Like, this helps me kind of understand it, but like, I also need like—S3: —a lesson.S2: Yeah. Like, oh, like figure it out a little bit and then, like, teach us the actual thing.</td><td>Frustration</td></tr></tbody></table> </ephtml> </p> <p>The students' expressions of frustration and anxiety at how they were being asked to construct knowledge were notable. The group's entire affective pathway from the beginning of the troubleshooting episode through the end of their reflection appears to have moved from confusion and frustration to confidence and relief, a positive pathway, but then back to frustration and anxiety. It should be noted that the teacher and observer witnessed the first part of the pathway, where frustration turned to confidence, but not this last, negative turn, in which students were voicing their meta‐affect, and, therefore, they had no opportunity to intervene.</p> <p>Although the nature of the students' meta‐affect was vivid in the video record, the exact source or sources could be debated, as will be discussed below. In any case, the students appeared to be experiencing a decided <emph>lack</emph> of agency in how they were being asked to acquire knowledge. However, it is difficult to gauge how much of the student discontent was a reaction to the specific class session versus discontent with the inquiry approach as a whole.</p> <hd id="AN0188607205-28">Teacher and IS2 Observer Retrospective Interviews</hd> <p>Mr. D was interviewed 3 years later, at the end of the project. He was shown video of the part of the troubleshooting episode in which he had participated, but not the student reflections afterwards. After each of his utterances in the video, the video was paused and he was asked to speculate what had motivated his contribution. This process elicited numerous recollections of his approach that year, as well as articulation of his thoughts about inquiry as a whole. He made it clear that although he valued inquiry, he did not view episodes such as what he was seeing in the video as particularly helpful. Although he did not recall this episode specifically, he did remember that what had motivated him in general by that year was trying to get students not to fixate on the noise in data, but to recognize the good data, see if they had enough of that to answer the question of interest, and then move on. In earlier years of his teaching career, he said, he had wanted students to become deeply acquainted with the tools they were using and how to troubleshoot them because, "once you get out into the field, when your sensor breaks, you gotta' fix it, or your half‐million‐dollar study is shot." However, by the time of the IS2 project, he had become concerned about a tendency to perfectionism he saw in his students' quest for data, especially considering the often faulty motion detectors they had, and wanted to move them past equipment troubleshooting as quickly as possible. He felt that most learning occurs later, during class discussion.</p> <p>Ms. O, the IS2 observer on this day, was also interviewed at the end of the project. Although this was 3 years later, she did recall the specific incident. She had witnessed Activity 2.2 only a few times and said that this episode, in particular, had made an impression. Similar to the teacher, she said she had been concerned that the students had become fixated on getting perfect data. However, she explained, she had wanted the students to engage with troubleshooting not to become deeply acquainted with the tools, but to get them to see that their data were not going to be perfect. She said that with interventions like this, she tends to look at the students' faces to see whether there is some indication of "wheels turning" or whether they are returning blank stares. Here, she looked for evidence this small group was thinking about possible reasons why they might be seeing an imperfect graph and why they were seeing "spikes" in the data. "The fact that they could pinpoint something that was like, 'maybe it's detecting some other motion that we just can't control right now,' that seems like a successful thing to me (...), they were thinking critically." Ms. O had seen what to her was "success" in getting the students to recognize something crucial about collecting real‐world data and she encouraged them, "So try again and (...) see what you notice." She recalled that before she stepped in the second time she had asked herself, "Okay, how many runs am I going to let her discard before I kind of lead her to believe that this is actually useful information that she's seeing here?" After only about a minute, in which the students had conducted two more ball rolls and were about to discard those data, she returned to the group and switched gears, pointing out to them that there was "a section in there that actually is pretty decent and has a nice slope to it," and encouraged them to do only one or two more runs. Therefore, although she did want to engage the students in troubleshooting, she, like the teacher, had the limited class time in mind.</p> <hd id="AN0188607205-29">Lack of Evidence for Engagement in the Mangle After the Troubleshooting</hd> <p>It is reasonable to ask whether conceptual‐material realignments occurred in places other than during the troubleshooting episodes, but the video record for the activity yielded no evidence for this. After the episode described here, the teacher engaged the class in a discussion about ways to analyze their results and together they examined variations in data from across the class. Then students began quietly calculating velocities. The next day the class met, Day 3 of the activity, no video was recorded due to class‐wide technical difficulties, but video evidence about realignments between student conceptions and variations in their data could have been expected on Day 4, when everyone had data and the focus of the lesson turned from data collection and calculation of slope to a deeper exploration of the class data as a whole. Using the coding criteria, the video for this day was examined for evidence of any mention of alignments between student conceptions and feedback from the world, together with evidence of exercise of student agency, but such evidence was not detected until they began designing the next activity. Rather, the focus at the conclusion of this activity was on different procedures to determine the mean and median in the class data, which the students implemented matter‐of‐factly; no questions of a conceptual nature were noted.</p> <p>A shift in activity once students had successfully gathered data was consistent with other observations from across the IS2 project. The most active reasoning appeared to be concentrated during troubleshooting. Once students were confident of their data, observation notes describe physics classes becoming quiet with students calculating velocities and turning in their results.</p> <p>Incidentally, the negative reaction to troubleshooting was also consistent with other observations, although this group gave the clearest articulation. Field notes (including mine) record multiple instances of groups being anxious and frustrated after they had spent more time than they anticipated in their efforts to get clean data. When I tried to complement a group in another class on their methodical and ultimately successful troubleshooting, one of the students, clearly embarrassed, said, "To be perfectly honest, we were just trying to save our (behinds)."</p> <hd id="AN0188607205-30">Summary</hd> <p>Analysis revealed students engaged in at least five NGSS practices (NGSS Lead States [<reflink idref="bib24" id="ref100">24</reflink>]), working to create alignments between their conceptions of what the data patterns should be and what their instruments were telling them, exercising epistemic agency, and working through frustration and confusion to achieve confidence. However, the meta‐affect they expressed immediately afterwards was quite negative, two of them explicitly saying they did not learn anything in this class. The teacher, in retrospect, said he did not view these kinds of episodes as particularly helpful. The IS2 observer said she saw the students thinking critically, which she saw as an indication of success. The most striking result was the contrast between the rich activity observed and the student perceptions that they were not learning anything.</p> <hd id="AN0188607205-31">Discussion</hd> <p>When students are allowed agency in designing their investigations, activities may not go as planned, and this can create challenges for them and their teachers. This case study explores what happened when measuring equipment repeatedly produced unexpected readings in one small group. It asks whether the intellectual work students engaged in while troubleshooting their technical difficulties had disciplinary value and whether they were able to experience their work as meaningful. The video record was coded for student engagement in noticing and repairing misalignments between their conceptual and material worlds, their exercise of epistemic agency, their epistemic affect, and engagement in NGSS science practices. Retrospective interviews with the teacher and IS2 observer gave information about their views of the episode.</p> <p>The discussion of findings is largely organized around the troubleshooting episode to address the first research question, and around the retrospective accounts to answer the second question. However, the affective pathway of the group spanned the troubleshooting and the students' retrospection, and that whole pathway will inform discussion about the second question.</p> <hd id="AN0188607205-32">The Disciplinary Value of an Episode of Troubleshooting Equipment</hd> <p>The 8‐min troubleshooting episode was rich with disciplinary activity in terms of students noticing and repairing misalignments between their conceptions and their data, engaging with multiple science practices, and exercising agency in making decisions and evaluating the quality of their data. In short, the students appeared deeply engaged in active reasoning and creative problem‐solving, behaving much as real scientists do. A question is what learning might have been in this context, and how it may have differed from what the students and teacher were ready to recognize as the learning goals for the lesson.</p> <hd id="AN0188607205-33">The Nature of "Learning" in the Context of Technical Troubleshooting</hd> <p>If the students were recognizing and repairing misalignments between their conceptions and their data, this certainly sounds like learning, although they appeared not to recognize it as such. This may be because the conceptual‐material alignments these students were exploring that day were not so much focused on their conceptions of velocity as on their conceptions of how velocity could be detected and represented by their instruments. In the NGSS standards, disciplinary core ideas involving motion and stability are associated with multiple science practices (NGSS Lead States [<reflink idref="bib24" id="ref101">24</reflink>]). It is plausible, though, that phenomena targeted in lessons, and conceptions about those phenomena, are more salient to students than the science practices they are engaging in. The phenomenon explored here was suggested in the NGSS performance expectation for Newton's second law of motion, making use of data graphs of position or velocity as a function of time (NGSS Lead States [<reflink idref="bib24" id="ref102">24</reflink>], 94). However, the students were not yet investigating Newton's law directly, but becoming familiar with real‐world velocity data in graphs while planning and carrying out an investigation, among other science practices. Because the alignments they were making were not directly focused on their conceptions of velocity, what they were doing may not have seemed to them like "real science."</p> <p>As Pickering ([<reflink idref="bib27" id="ref103">27</reflink>]) has described, when actually doing physics—as opposed to learning what has already been discovered in physics—concepts include what the instruments are measuring and how they do the work of measuring. The teacher, on the other hand, had decided to reduce a focus on the function of the instruments as taking students away from the physics content. However, looking at the videos using the mangle as a lens, it appears that rich conceptual‐material alignments were continually being made concerning the function of those instruments. Even after S2 realized that the motion detector detected unmoving objects (because it actually detected position and recorded time), she asked, "Why is (the graph) straight before it goes off the ramp?... It should be getting steeper and steeper" because it was accelerating downward. She knew how the graph of the motion she had observed <emph>should</emph> look, and this helped her recognize a remaining misalignment between her conception of what the detector was detecting and what it was actually detecting at that point (not the ball).</p> <p>If uncertainty gives rise to science practices, as postulated by Manz ([<reflink idref="bib18" id="ref104">18</reflink>]), it is worth noting that even when technical troubleshooting seems to distract from the lesson focus, by its nature, it is a response to uncertainty in an investigation, a sense that something is wrong without knowing exactly what. Perhaps it is not surprising that student troubleshooting would give rise to a large number of practices in addition to the one explicitly targeted by the activity sequence. But if the students learned something about science practices, they did not appear to recognize this.</p> <hd id="AN0188607205-34">The Form This Learning May Have Taken</hd> <p>Teachers may think that because students have experienced something and done something, they have gained usable knowledge. However, it is possible that the learning was implicit. Implicit learning is learning that a student may be unaware of engaging in or that takes place without their conscious intention to learn (Jiménez [<reflink idref="bib15" id="ref105">15</reflink>]; O'Brien‐Malone and Maybery [<reflink idref="bib25" id="ref106">25</reflink>]; Seger [<reflink idref="bib29" id="ref107">29</reflink>]). This kind of learning can lead to knowledge that is tacit, not yet put into words (Gourlay [<reflink idref="bib12" id="ref108">12</reflink>]), or knowledge that students do not even know that they know (Collins [<reflink idref="bib4" id="ref109">4</reflink>]). Implicit and explicit learning may be mixed (Jiménez [<reflink idref="bib15" id="ref110">15</reflink>]). It is plausible that in the episode analyzed, implicit emergence of science practices occurred as a byproduct of an explicit focus on getting the instruments to work. If so, in such situations an intervention might help students become explicitly aware of practices that have emerged and avoid the perception that what they are doing is not worthwhile.</p> <hd id="AN0188607205-35">Aspects of the Activity That Supported Students Taking on Roles of Epistemic Agents</hd> <p>The episode occurred at a point in the instructional sequence where scaffolds had begun to be faded, but this was not yet an open investigation. Some, but not all, of the design decisions were left to students. In this investigation, one objective was to foster the need to identify dependent and independent variables and constants, and the stated goal was to collect data with which they could calculate the velocities. In this respect, the final knowledge products they were being asked to construct were expected/canonical. This means that once students were doing what they thought they were supposed to be doing, successfully collecting data, they were acting with what Miller et al. ([<reflink idref="bib22" id="ref111">22</reflink>]) describe as <emph>pseudoagency</emph>. It was when students were engaged with the mangle and trying to salvage their investigation that they appeared to be acting with true agency. At these times, they were in a territory where the given procedures were not working, the data patterns they were seeing were not in alignment with their conceptions of what the motion detectors should be picking up, and they had to revise their conceptions, their procedures, or both, with no step‐by‐step procedures to guide them. They were acting as epistemic agents as described by Stroupe ([<reflink idref="bib37" id="ref112">37</reflink>]), taking responsibility for shaping the knowledge and practice of a science community, making and verifying knowledge claims, asking their own questions, and to some extent, directing the course of their investigation.</p> <p>Manz ([<reflink idref="bib18" id="ref113">18</reflink>]) has noted a need to balance disruption and focus, and Mr. D and Ms. O endeavored to do so. Although they were concerned about time, they each took a moment to scaffold deeper student reasoning before helping the students refocus on the good data and move on. In addition, Ms. O indicated to the students that their ideas "counted" ("If you could make a prediction about what happened there, what were you thinking?") and that they had agency ("Try a few different methods"), although the message that their activity was valid scientific practice was not rendered explicitly.</p> <hd id="AN0188607205-36">The Perceived Value of the Troubleshooting Episode</hd> <p>It had been my impression that students in inquiry classes often did not value their troubleshooting, especially when it involved digital instruments, but I was surprised by the vehemence of the student responses here. Early rounds of coding had focused on the portion of video ending with the students expressing confidence in their data, and it was not until looking back at the video record with epistemic affect and meta‐affect in mind that the importance of the student utterances in the latter part of the video became clear. This motivated setting up the retrospective interviews with the teacher and IS2 observer even though substantial time had passed. The limited value the teacher said he now placed on this kind of activity was also a surprise, given his enthusiastic and longstanding embrace of inquiry activities.</p> <hd id="AN0188607205-37">Student Affect and Their Views of Their Troubleshooting</hd> <p>Manz et al. ([<reflink idref="bib19" id="ref114">19</reflink>]) argue that classroom science investigations should be approached such that practice and content understanding are interrelated and students experience their work as meaningful. Even though this investigation was designed for the content to be interrelated with science practices, these students clearly did not experience their work as meaningful. There are several possible explanations. One is that they might not have learned anything and needed a different lesson. Another is that they might have needed help rendering their new knowledge explicit. Or perhaps they were aware of learning, but frustrated that they were not engaging in the kind of learning they valued, and needed support to appreciate how this fit into the overall learning objectives. Or perhaps the main problem was their unhelpful affective pathway and they needed instructional attention with respect to epistemic affect as described by Jaber and Hammer ([<reflink idref="bib14" id="ref115">14</reflink>]).</p> <p>The first possibility is one that goes beyond the scope of this study. However, even if the students had learned nothing new, it is unlikely this was the only factor at work, given that frustration at troubleshooting was observed more widely than this in the project and has been noted in the literature (Seroy et al. [<reflink idref="bib30" id="ref116">30</reflink>]). The second and third possibilities have been discussed above (e.g., explicitly noting their engagement in practices), but the fourth issue, about an unhelpful affective pathway, deserves a closer look.</p> <p>DeBellis and Goldin ([<reflink idref="bib8" id="ref117">8</reflink>]) describe these pathways as feelings leading to feelings about feelings. In the present case, the students' affective pathway during the troubleshooting itself appeared positive, leading from confusion and frustration to confidence and relief at their success. But as they reflected immediately afterward and articulated their feelings about the experience, their pathway took a nosedive; their meta‐affect was one of pronounced anxiety about how they were being asked to acquire knowledge.</p> <p>In the literature, a concern is that students will give up or not be able to find a solution if their affect is negative. DeBellis and Goldin ([<reflink idref="bib8" id="ref118">8</reflink>]) noticed instances when someone could manage negative feelings to get the job done, as when a meta‐affect allowed someone experiencing frustration to reframe it as challenging. In the present instance, the students' frustration did not appear to interfere with their problem solving. Partly this may be because Mr. D and Ms. O helped them manage frustration by suggesting other things they could try. Because they each suggested more than one possibility, the students were allowed agency in what they chose. Although the students may have experienced some of this as pseudoagency, they did exhibit confidence when stating their choices of how to handle the uncertainty and where to go next. Therefore, I would argue that in the moment, and with the support they received, they were able to handle their frustration and were motivated and able to find answers. However, their confidence in their <emph>solution</emph> did not translate into confidence in their <emph>acquisition of usable knowledge</emph>, at least in terms of their ability to function on a test.</p> <hd id="AN0188607205-38">Teacher and IS2 Observer Views of the Troubleshooting</hd> <p>There were some differences in the perspectives of Mr. D and Ms. O. Mr. D, a teacher well experienced teaching inquiry‐based classes, was responsible for the content coverage of the entire course during the set time frame of the school year and, like his students, was frustrated with school equipment that was often faulty. Therefore, he wanted his students to realize they just needed "good enough" data to get a reasonable value for the velocity. Through these activities, it was expected they would become more familiar with recognizing the relationship between slope in a position/time graph and velocity, to prepare them for exploring acceleration in a later activity. If he did not see their troubleshooting dealing with their equipment as supporting this goal, or if he anticipated that the conceptual links would happen mostly in class discussion after good data had been gathered, his feeling that their current effort was not what he was really interested in could have communicated itself to the students. Because the focus of the entire activity sequence was on the practice of planning and carrying out investigations and this had been explicitly articulated to the students, he may not have noticed their engagement in additional practices or may have felt that explicit discussion about those was not sufficiently important at this time.</p> <p>Ms. O, who, as a project observer, was not responsible for content coverage, had a more positive view of the troubleshooting. When the students realized there might be factors they could not control in their real‐world data collection, Ms. O saw this as something successful coming from the activity. She though, like Mr. D, was concerned about the time.</p> <hd id="AN0188607205-39">Possible Remedies</hd> <p>Manz and Suárez ([<reflink idref="bib20" id="ref119">20</reflink>]), in a year‐long teacher workgroup, documented strategies that arose among elementary science teachers for dealing with the uncertainty they intentionally introduced into their lessons. Many of these strategies bear similarities to those recommended in the IS2 materials. Of particular interest here is a strategy Manz and Suárez used with the teachers during their professional development workshop: to explicitly reflect on what science practices they had just engaged in. This might be a useful strategy to use with students also, especially for someone such as S2, who said she did not learn anything in this class. However, to lead such a discussion, the teacher would first need to be aware of those practices having been enacted, which may mean needing support to know how to notice the practices in this context.</p> <hd id="AN0188607205-40">Teacher Noticing and Seeds of Mature Science</hd> <p>Noticing science practices as they arise in student activity is reminiscent of Hammer ([<reflink idref="bib13" id="ref120">13</reflink>]) noticing "seeds of mature science." Hammer argued that the beginnings of science in one student may be very different from the beginnings of science in another. Therefore, teachers should not specify, based on a particular model, what should be seen in students' work, but look for any productive aspects of students' work and then try to support what is found. The greater the teacher's awareness, the greater the chance of discovering something of value. In inquiry classes, I suggest it is important not only for teachers to learn to recognize the mangle when it occurs, but also to be aware that multiple science practices can be elicited, and that these may need to be rendered explicit to help students see the validity and importance of their work.</p> <hd id="AN0188607205-41">Ideas for How to Scaffold Students In Rendering Their Learning Explicit</hd> <p>Although a discussion for students to identify science practices they have just engaged in could be very helpful, a challenge for the teacher is that when things have "gone wrong," the activity may already have taken longer than anticipated, and carving out a few minutes at the end of class for closure may be especially difficult. When observing in inquiry classes with a time crunch after technical challenges, I have occasionally tried something less time intensive: making a quick comment to an individual student or group that has just engaged in troubleshooting to let them know that what they had just done was real science and that they had behaved as professional scientists do. My purpose was to dignify and validate the student actions when it may have seemed to them that they were failing at the activity. The few times I have tried this, it resulted in furrowed faces breaking into smiles. A future study might explore quick interventions such as this in terms of effect on both student attitudes and on their understanding of the nature of science. For example, a comment such as, "I notice you engaged in (such and such) science practice today," would not ask a student to mimic a practice, but would point out practices in which the student had already, perhaps spontaneously, engaged.</p> <p>Another possible method is something we tried in later revisions of the IS2 materials, to add prompts for students to write down what problems they had and what they did to try to address those problems, reminiscent (on a smaller scale) of Crismond and Peterie's ([<reflink idref="bib6" id="ref121">6</reflink>]) troubleshooting portfolios. This could be useful for any engagement in the mangle, whether troubleshooting equipment is involved or not. Moving descriptions of experimental results to the penultimate section of reports and reserving the final section for articulating remaining questions and describing strategies the students developed to deal with the unexpected could be useful for all students, but especially so for students whose designs yielded disappointing results.</p> <p>All of this is not to argue for deliberately increasing time spent on troubleshooting. The argument I am making is that when unexpected problems arise, it may be easy for both students and teachers to become focused on the barriers to the extent that they do not recognize, or ever explicitly acknowledge, the resourcefulness and active reasoning the students have exhibited and the ways in which they were behaving as scientists do.</p> <hd id="AN0188607205-42">Deciding When to Intervene (and When to Get Students to Move On)</hd> <p>Manz and Suárez ([<reflink idref="bib20" id="ref122">20</reflink>]) extensively discuss the difficulty of deciding when to intervene and how. On the last day of professional development in their study, their teachers were still wrestling with the question. What the present study can offer is an example of one such decision and the thinking behind it. Because Ms. O had appeared comfortable during the episode with this decision, she was asked about it in her interview. First, she had a clear articulation of her goal for the activity: she was hoping these students would gain awareness that some noise in their data might be something they could not control. Once she saw the students reasoning in a productive direction toward this goal, she felt comfortable becoming more directive by encouraging them to focus only on the good data to see if they had enough of it. This shift from open questioning to a more directive approach occurred only about three and a half minutes into the episode (the second group of gray bar codes in Figure 3), suggesting that this approach could be efficient with respect to class time.</p> <hd id="AN0188607205-43">Implications</hd> <p></p> <hd id="AN0188607205-44">Theoretical Implications</hd> <p>The theoretical framework used here considered students' activity in terms of their engagement with uncertainty and the mangle of practice, their exercise of epistemic agency in resolving these uncertainties, the emergence of multiple science practices, and their epistemic affect during and after the activity. The literature is rich with two‐ and three‐way links between these concepts (Davidson et al. [<reflink idref="bib7" id="ref123">7</reflink>]; Jaber and Hammer [<reflink idref="bib14" id="ref124">14</reflink>]; Manz and Suárez [<reflink idref="bib20" id="ref125">20</reflink>]; Manz et al. [<reflink idref="bib19" id="ref126">19</reflink>]; Stroupe [<reflink idref="bib37" id="ref127">37</reflink>]; Zivic et al. [<reflink idref="bib41" id="ref128">41</reflink>]). In the present study, all four aspects were deeply intertwined. Somewhat surprisingly, although the students exercised agency, they did not appear to experience themselves as epistemic agents, and although multiple science practices emerged and the students were successful with their activity, they did not think they had done anything of value. Rather than their meta‐affect preventing them from experiencing success, I suggest it is equally, if not more, plausible that it was the other way around—their lack of awareness of having engaged in anything useful and their perception of a lack of epistemic agency either led to or amplified their negative meta‐affect. This argues for the importance of looking at all four aspects. Before I returned to the data to examine the students' retrospective feelings about how they were being asked to create knowledge, the entire activity appeared to be a success story.</p> <p>A theoretical issue only touched on here, but that could bear further exploration, is the possibility that inquiry stages may look different during technical troubleshooting (and different from the troubleshooting cycle described by Sullivan [<reflink idref="bib38" id="ref129">38</reflink>], in the context of debugging a program). For instance, the stages used in the teacher materials: design, collect, analyze, explain, might become design/revise, attempt collect, analyze/evaluate, attempt explain. In the attempt explain stage, rather than proposing models of the target phenomenon, students may be proposing and testing models of how their instruments work. In the teacher materials, the original stages were designed into the instructional plan, with a half hour or more allowed for design, up to two periods to collect, and a period or more to analyze and explain. However, the stages observed during the technical troubleshooting ranged from 2 s to a minute in length and could easily be missed in the classroom, even by a teacher very experienced in inquiry. In fact, they were missed by this researcher until a second round of video analysis. This could have practical implications. If teachers were made aware of this difference in pace, it could help their noticing, and open up possibilities for reframing the activity for their students.</p> <hd id="AN0188607205-45">Practical Implications and Next Steps</hd> <p>The idea that including scientific uncertainty and providing room for students to act with epistemic agency can lead to the emergence of science practices, as discussed in Manz ([<reflink idref="bib18" id="ref130">18</reflink>]), is supported by the present findings. What has been less often argued is that high school science students engaging successfully in inquiry may need to have the practices they have just engaged in, and the ways they have exercised agency, rendered visible to them.</p> <p>If implicit learning through the mangle can occur as a seeming distraction from acquiring science content, it makes sense that having students leave that investigation (or that course) without becoming clear on the learning that has occurred will not support a sense of agency or confidence in their own knowing. Especially at a point in their educational journey when content coverage is very important to both teachers and students who are preparing for college entrance exams, it may be crucial to explicitly point out the nature and importance of this less visible learning. The results of this study suggest the importance of research to (a) determine whether and when engagement with the mangle produces implicit learning of practices in other classroom contexts, and, if it does, (b) explore whether engaging students (and perhaps teachers) in explicit discussion will support their making connections between their own activity and the practices of science, along with an appreciation of the validity and epistemic value of their work. Because this was an analysis of a single small group, further research might evaluate the typicality and extent of student/teacher frustration levels with inquiry investigations that involve equipment troubleshooting, or other engagement with the mangle of practice if it appears to pull focus away from content objectives. If this issue is widespread, it could be fruitful to further investigate how to resolve frustration levels and improve students' sense of epistemic agency without imposing additional time demands on the teacher.</p> <hd id="AN0188607205-46">Limitations</hd> <p>No claims of typicality can be made from this type of study. All new analysis presented here is primarily the work of a single author, although it was discussed with the IS2 team both early and late in the analytical process. It is hoped that enough transcript data are presented for the reader to draw their own conclusions. The episode chosen for in‐depth analysis involved a single group of students, therefore, the results can best be described as an existence demonstration of phenomena that may be overlooked in inquiry classrooms and that can suggest areas for further research, as described above.</p> <hd id="AN0188607205-47">Conclusion</hd> <p>Allowing students agency in designing an experimental setup within an inquiry activity can "promote the development of the habits of mind (scientific abilities) that are an important part of scientific practice" when properly scaffolded (Etkina et al. [<reflink idref="bib10" id="ref131">10</reflink>], 54), while exposing them to the uncertainty central to scientific activity (Manz et al. [<reflink idref="bib19" id="ref132">19</reflink>]). Scientists can spend considerable time in the professional laboratory troubleshooting their instruments, engaging in a "mangle of practice" (Pickering [<reflink idref="bib27" id="ref133">27</reflink>]). However, a question arises as to the disciplinary value of time taken up by this in the classroom, especially if focus is being pulled away from target phenomena.</p> <p>In the rather technical process of troubleshooting motion detectors during a high school physics investigation, the student group focused on here was engaged in several NGSS science practices besides planning and carrying out an investigation: asking questions, interpreting data, constructing explanations, and occasionally arguing from evidence (NGSS Lead States [<reflink idref="bib24" id="ref134">24</reflink>]). With respect to the practice of planning and carrying out investigations in particular, they were evaluating and re‐evaluating their design, collecting data to identify failure points in this design, deciding the accuracy of data they needed, and using evidence to evaluate their conceptual models of how the motion detector worked to inform their design iterations. They were engaging in many of the practices of real science as they sought to create alignments between their conceptual and material worlds. The most active reasoning and evidence for epistemic agency for this group was observed during their troubleshooting episode.</p> <p>However, this study suggests that students may need to be scaffolded if they are to experience troubleshooting their instruments as an exercise of their agency rather than as defeat. The author heartily endorses Stroupe's ([<reflink idref="bib37" id="ref135">37</reflink>]) suggestion to explicitly reframe such moments in terms of the mangle. But this requires the teacher to recognize the mangle when it occurs in the context of technical troubleshooting and understand its value. It also requires being able to make on‐the‐spot decisions about when to move on. It means, at the end of a frustrating classroom experience of troubleshooting uncooperative laboratory equipment, being explicit about the ways in which the students were acting as true scientists.</p> <hd id="AN0188607205-48">Acknowledgments</hd> <p>The author wishes to thank the IS2 team members who participated in the earlier videotape analysis and provided feedback on the present study: Dan Damelin, Natalya St. Clair, Cynthia McIntyre, and Brandi Ediss. I also extend thanks to the teacher and InquirySpace observer who so generously shared their thoughts afterwards, and to all of the teachers and students who consented to be videoed as part of the project. This material is based upon work supported by the National Science Foundation under Grant Nos. IIS‐1147621 and DRL‐1621301. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.</p> <hd id="AN0188607205-49">Conflicts of Interest</hd> <p>The authors declare no conflicts of interest.</p> <hd id="AN0188607205-50">Data Availability Statement</hd> <p>The data that support the findings of this study are available upon reasonable request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.</p> <p>GRAPH: Supporting Information for Troubleshooting.pdf.</p> <ref id="AN0188607205-51"> <title> References </title> <blist> <bibl id="bib1" idref="ref18" type="bt">1</bibl> <bibtext> Albert, D. R. 2020. " Constructing, Troubleshooting, and Using Absorption Colorimeters to Integrate Chemistry and Engineering." 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NARST Conference, Baltimore, MD, United States. https://narst.org/sites/default/files/2019‐08/2019_Program_0.pdf.</bibtext> </blist> <blist> <bibtext> Stephens, A. L., N. St. Clair, B. Ediss, T. Farmer, and D. Damelin. 2020. Small Group Reasoning About Unexpected Sensor Readings When Scaffolded (or not): One Physics Lesson, Four Teachers [Paper presentation]. NARST Conference, Portland, OR, United States. (Conference canceled). https://narst.org/sites/default/files/2021‐01/NARST%202020%20Conference%20Program%20Book%20‐%20updated%20v2.pdf.</bibtext> </blist> <blist> <bibtext> Stephens, A. L., N. St. Clair, B. Ediss, and H. Lee. 2020. " Scaffolding a Lesson With Noisy Data: One Physics Lesson, Two Teacher Approaches." In The Interdisciplinarity of the Learning Sciences, 14th International Conference of the Learning Sciences (ICLS) 2020, edited by M. Gresalfi and I. S. Horn, 4, 2301 – 2304. 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  Data: Troubleshooting as an Inquiry Activity: Recognizing and Supporting the Mangle in the Classroom
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  Data: English
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  Data: <searchLink fieldCode="AR" term="%22A%2E+Lynn+Stephens%22">A. Lynn Stephens</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-4343-340X">0000-0002-4343-340X</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Science+Education%22"><i>Science Education</i></searchLink>. 2025 109(6):1509-1530.
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  Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
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  Data: Y
– Name: Pages
  Label: Page Count
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  Data: 22
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  Label: Publication Date
  Group: Date
  Data: 2025
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  Label: Sponsoring Agency
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  Data: National Science Foundation (NSF), Division of Information and Intelligent Systems (IIS)<br />National Science Foundation (NSF), Division of Research on Learning in Formal and Informal Settings (DRL)
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  Data: 1147621<br />1621301
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  Data: Journal Articles<br />Reports - Research
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  Label: Education Level
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  Data: <searchLink fieldCode="EL" term="%22Secondary+Education%22">Secondary Education</searchLink><br /><searchLink fieldCode="EL" term="%22High+Schools%22">High Schools</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Troubleshooting%22">Troubleshooting</searchLink><br /><searchLink fieldCode="DE" term="%22Inquiry%22">Inquiry</searchLink><br /><searchLink fieldCode="DE" term="%22Science+Education%22">Science Education</searchLink><br /><searchLink fieldCode="DE" term="%22Science+Process+Skills%22">Science Process Skills</searchLink><br /><searchLink fieldCode="DE" term="%22Secondary+School+Science%22">Secondary School Science</searchLink><br /><searchLink fieldCode="DE" term="%22High+School+Students%22">High School Students</searchLink><br /><searchLink fieldCode="DE" term="%22Science+Activities%22">Science Activities</searchLink><br /><searchLink fieldCode="DE" term="%22Physics%22">Physics</searchLink><br /><searchLink fieldCode="DE" term="%22Science+Projects%22">Science Projects</searchLink><br /><searchLink fieldCode="DE" term="%22Epistemology%22">Epistemology</searchLink><br /><searchLink fieldCode="DE" term="%22Theory+Practice+Relationship%22">Theory Practice Relationship</searchLink><br /><searchLink fieldCode="DE" term="%22Learner+Engagement%22">Learner Engagement</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1002/sce.21979
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  Label: ISSN
  Group: ISSN
  Data: 0036-8326<br />1098-237X
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Although there is a push to provide more student agency in science classrooms, teachers and students may become frustrated when inquiry activities and equipment do not work as planned--teachers because of the time crunch to "cover" topics and students because of the perceived lack of value in activities that are "off task." In classroom implementations of a data-rich high school physics activity sequence as part of the InquirySpace 2 (IS2) project, numerous episodes of equipment troubleshooting were observed. Teachers questioned whether the time spent had disciplinary value. Students expressed concern regarding what, if anything, they were learning. This qualitative case study of one such episode considers students' activity in terms of their engagement with the "mangle of practice" and misalignments between their conceptual and material worlds, their exercise of epistemic agency in recognizing and repairing those misalignments, and their epistemic affect during and after the activity. Video analysis revealed all three aspects deeply intertwined with evidence of student engagement in multiple science practices. The students expressed their feelings about the episode immediately afterward and the teacher and IS2 observer when interviewed much later, at the end of the project. One reason for the negative perceptions of teacher and students may be that the alignments being explored were related to the instrumentation more than to the target phenomenon. This study argues that in such situations, students may not recognize or value science practices that emerge, and may need explicit support to reframe their activity as valid scientific practice.
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  Data: 2025
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  Data: EJ1486526
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        Value: 10.1002/sce.21979
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      – SubjectFull: Inquiry
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      – SubjectFull: Science Education
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      – SubjectFull: Science Process Skills
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      – SubjectFull: Secondary School Science
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      – SubjectFull: High School Students
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