Implementing

Modeling Discourse Management

In High School Physics

An Action Research Project

By John Crookston

July 17, 2006

7:30 pm

PSH 356

Abstract

Modeling discourse management is a second-generation classroom management technique developed to augment first generation Socratic modeling. Socratic modeling promotes student discourse through Socratic dialogue in which the teacher leads students to a deeper understanding through persistent questioning. Modeling discourse, also referred to as discourse management, is a classroom management technique that promotes student discourse through “seeding” and the creation of a learning community. Seeding is a questioning technique where the teacher seeds small collaborative groups with a question or hint and a learning community is where knowledge is socially constructed. Discourse management has been found to enhance student understanding, problem solving skills, and student views of science in regular and honors university classes where it has been tried. This action research project chronicles a two-year effort to implement discourse management in the high school setting. The implementation was designed to promote richer student-to-student discourse, improve student engagement, change student views about learning and science, and enable the teacher to function and be perceived more as facilitator of learning and less as an authority. A contrasting alternatives survey was designed to measure the use of discourse management techniques. Results indicate some success at using modeling discourse management and point to the need for further investigation.

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Context

Forest Hills High School is a three-year public high school located in the rural community of Sidman, Pennsylvania. The Forest Hills School District is located ten miles northeast of Johnstown and both communities are situated in west-central PA about 90 miles east of Pittsburgh. The high school’s seven hundred students are 99.1% Caucasian, 0.7% Black, and 0.2% Hispanic and 36.4% of the students come from economically disadvantaged households. In 2000-2001, 70% of the graduates intended to enroll in post-secondary degree programs, 4% in non-degree programs, 23% intended to seek employment and 3% intended to join the military. In 2005, the high school made adequate yearly progress as defined by the No Child Left Behind (NCLB) law. The high school follows a 4 x 4 block schedule with regular classes running 80 minutes a day for eighteen weeks. I teach Physics 1 on this schedule with class size ranging from 14 to 28 students. The physics students are typically college bound, and have passed Algebra II and Chemistry 1 with at least a “C” average. On average my Physics 1 classes are 40% female, 60% male and 65% juniors, 35% seniors. I also teach AP Physics C Mechanics, and Conceptual Physics.

Historical Background

In 1999, after thirteen years of teaching high school physics, I began moving away from traditional physics instruction - lecture, problem solving, cookbook verification labs - because of a growing realization that what I thought I was teaching was not what students were learning. Students often missed the point of what I told them in lecture. My presentations of definitions, facts and know how were usually rote memorized with little more than superficial understanding. Showing students how to solve problems usually resulted in many students parroting what I did when they solved similar problems. As a consequence, students viewed successful problem solving as what mattered most in physics. With each additional chapter, a new set of problems that could be solved using some additional new equations eventually gave students a very fragmented view of physics. At its worst, this fragmentation was most evident when students tried to solve novel problems; many could not solve them and claimed they had never worked on these kinds of problems. Fragmentation was also evident during reviews for exams; students blindly searched for the right equation in an attempt to get answers to problems done in the earlier part of the course. Instead of learning physics as a unified and coherent body of knowledge, students were learning how to select and manipulate formulas to solve problems with only a limited understanding of the underlying concepts on which the solutions were based. My departure from traditional instruction began in the summer of 1999 when I took a month long Modeling Workshop in teaching mechanics at the University of Maryland.

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Conceptual Framework

The Modeling Method of physics instruction is a research-based reform effort built on the premise that active student involvement will increase conceptual understanding (Wells, Hestenes and Swackhammer, 1995, Desbien 2002). It is based on the constructivist idea that students construct knowledge through interactions with each other and the instructor (Piaget, 1964, 1970 Vygotsky, 1962, Desbien, 2002).

The Modeling Method has students work in small cooperative groups to determine physical relationships with minimal guidance from the teacher. Typically, students work through a modeling cycle in which they design and perform experiments, use graphing calculators or computers to collect and analyze data, formulate functional relationships between variables, and evaluate “fit” to data. Results are then summarized on dry-erase white boards using diagrams, graphs, derived equations and written statements of uncovered relationships. In the post-lab analysis white boards are shared in a large-group format for teacher and peer feedback. During these white board discussions, students are expected to justify their conclusions and, with practice, develop critical thinking and peer-questioning skills. According to David Hestenes, Director of the Modeling Workshop Project at ASU, the primary role of the teacher during white board discussions is to facilitate and promote scientific discussions among the students.

The modeling approach is taught using one of two classroom management strategies: Socratic Modeling (the original program most teachers are exposed to in their first modeling workshop) and Modeling Discourse Management (DM), a more recent and more “radical” (social constructivist) implementation of the modeling method. Dwain Desbien, inventor of DM, has produced well-documented evidence of the effectiveness of DM in elevating the overall level of scientific discourse in University physics classrooms where it has been tried.

Discourse Management is a comprehensive classroom management strategy comprised of seven components:

Deliberate creation of a “learning community” Explicit need for the creation of models in science Creation of shared inter-individual meaning Seeding Intentional lack of closure Inter-student discussion Formative evaluation

Seeding, as described Desbien, is the primary technique for introducing new ideas into class discussion. Seeding involves two interrelated activities: planting and questioning. The first activity happens when the teacher plants an idea, concept or challenge with a small collaborative group of students. The group works out the details and gains ownership of the seeded idea and then brings that idea to the larger learning community. Thus, groups of students instead of an authority figure, introduce ideas to the whole class. The second activity happens when the teacher questions a small collaborative group to guide the groups’ thinking. The group can then bring its answer to the teacher-supplied question to the learning community.

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Literature Review

The single most important factor that determines the success of the Modeling Method is the ability of the teacher to manage and raise the level of scientific discourse between students during class discussions (Hestenes talk). Adapting white board discussions to one’s own unique strengths has proven to be an enduring challenge for teachers (Lattery and Schmitt, 2004). More than a few modeling teachers share the ongoing frustration of knowing the potential of the Modeling Method yet continually falling short of a more successful implementation. Desbien believes this problem centers around classroom management (Desbien, 2002).

Modeling Discourse Management is an approach that focuses on classroom management strategies to improve learning. The first order of business is the deliberate creation of a learning community in which students have access to and can appropriate a shared language to communicate with one another in such a way that meaningful learning occurs. One of the hallmarks of this kind of learning community is that shared language must be negotiated through inter-student discourse and it is the discourse that enables all participants in the community to engage in the activities of the community (Tobin, McRobbie, and Anderson, 1996).

In order to form classroom communities which function more like those of scientists and mathematicians, students need to be given opportunities to engage in authentic practices of scientists and mathematicians and they need to be given opportunities to engage in the necessary discourse practices routinely used by the scientific community (Roth and Roychoudhury, 1993).

Raising the level of student discourse also necessitates a change in student epistemological beliefs about science, learning, and the learning environment. Progress is made when students begin to view themselves more as creators of their own understanding and less as collectors of information. This social constructivist approach is dependent on a change in the roles of both students and the teacher, and students will only change roles in a significant way when their beliefs about those roles change. Learning and teaching that focuses on the dynamic interactions among the members of a community of knowers [learners] changes the classroom talk from that of information dissemination by the all-knowing teacher to one of a culture of learning structured by student independence [and inter-dependence] and teacher [functioning] as co-inquirer and learner (Roth and Bowen, 1999).

Pilot Study – First Cycle of Action Research – Spring 2005

Ideally, for DM to be most effective a teacher should begin using components on the first day of class. The three-week pilot study was conducted midway in the second semester of the 2005 – 2006 school year as a requirement for an online Foundations of Action Research course taken through the University of Montana. Because of time constraints, full adoption of DM was not a practical option at that point. I decided to narrow the pilot to the use of seeding. Students had already done quite a bit of modeling as previously described so I thought seeding was the one DM technique I could introduce into my teaching without having to make wholesale changes in how I teach or how the class was functioning at that point.

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My goal in the pilot study was to use seeding to increase the level of scientific discourse among students. This ties into my larger goal of getting my physics classes to function more as a community of learners where students create new knowledge through shared experience and student dialogue. These goals are consistent with my educational beliefs that students should be given frequent and challenging opportunities to think for themselves and take ownership of their learning in a classroom structured to allow these things to happen.

The Problem

I have been dissatisfied with my efforts to elevate the quality of student discourse during white board discussions. According to David Hestenes, the single most important factor that determines the success of the Modeling Method is the ability of the teacher to manage and raise the level of scientific discourse among students during white board discussions. I have grown increasingly frustrated with knowing the potential of the Modeling Method yet continually falling short of a more successful implementation that I, like Desbien, believe centers around classroom management issues.

Adaptation of white board discussions to my own unique strengths has been a long-term challenge:

I have had mixed success keeping students engaged during white boarding. When discourse is more of an exchange between myself and a student or a group of students for more than a brief amount of time, I notice the overall level of engagement of many students tends to drop.

I try hard not to come across or be viewed as the authority on content during white board discussions, a central tenant of modeling. I tend assume this role to keep things moving along when student discussion bogs down or hits a snag.

I struggle to have students change their view and practice of learning from passively collecting information to actively creating their own understanding. I believe students who do not “crossover” function poorly in a modeling classroom.

I have not spent enough time and have not been consistent in establishing and maintaining classroom norms and expectations for student discourse during white board sessions.

Focus Question

Can the discourse management technique of seeding, be used to improve scientific discourse among students during small group and whole class (white board) discussions?

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Sub Questions1. Can seeding small cooperative groups keep students more actively engaged

during whiteboard discussions?2. Can seeding small groups help promote student-to-student discourse about

science?3. Can seeding enable me to function more as a facilitator of learning and less as an

authority on content and ideas?4. Can seeding help students change their view of learning from collectors of

information to creators of their own understanding?

Implementation – Spring 2005Method

I conducted the three-week pilot in my third period Physics 1 class of 17 males and 10 females. The highest level of completed or concurrent math ranged from algebra II to trigonometry to calculus, and the highest level of completed or concurrent science ranged from chemistry I to college in high school chemistry to AP biology. This academically diverse class had been taught physics using the modeling approach for several weeks, so the class had experience using whiteboards in small and large group settings.

To implement seeding for an activity, I first formulated an agenda of the major ideas (discussion points) and goals for the activity. I seeded small groups in a strategic manner to help set up, frame and orchestrate the white board discussion that followed. To seed strategically, I relied on my prior knowledge of each group’s strengths, weaknesses, and patterns of interaction, both within the group and with the rest of the class during whiteboard discussions. I used my knowledge of each group to seed them to their ability level, strengths, and patterns of interaction

After reading Desbien’s narrative of how to use the seeding technique in a ball-drop activity, my first attempt involved seeding small groups during the post-lab analysis of a constant motion lab to see if it was something I could actually do. My first attempt exceeded my expectations and is included as a narrative in Appendix A.

Using Desbien’s dissertation on DM as a resource, I created and administered a Likert-Scale survey (Appendix B) to learn about students’ views and perceptions of whiteboard discussions. On the advice of my validation team I also constructed and administered a follow-up ten-question survey (Appendix C) of students’ perceptions and views of all the activities in a modeling cycle. I recruited the Director of Curriculum, who has done action research, to observe my class on three occasions when the seeding technique was employed.

Encouraged by the success of my first attempt, my second attempt at seeding was more ambitious. It involved giving small cooperative groups hints, questions or explanations during three post-lab analysis sessions of a multi-part paradigm lab on uniform acceleration. The groups of students (three students per group) were preparing their lab results for presentation to the whole class when seeding took place. I also took digital photographs of each group’s whiteboard after the conclusion of each discussion. Finally, with the help of my validation team, I put together and administered a nine-question follow-up survey of student’s views of the value of seeding and discourse (Appendix D).

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Data Collection - Triangulation Matrix

Sub Question Data Source 1 Data Source 2 Data Source 3

Student 3/1 Journal Survey questions Peer observationengagement 12 and 18

Promotion 3/1 Journal Survey questions Peer observationof discourse 33, 36, 39, 51

Facilitator vs. 3/1 Journal Peer observation Follow-up Surveyauthority questions 5, 6, 8

Student views Survey questions Peer observation Follow-up Surveyof learning 63, 58 questions 5, 6

Results and Analysis

Student Engagement

There is evidence that seeding increased student engagement during small group work and whiteboard discussions. In the constant velocity lab I seeded groups with questions like, “What would happen to your data and graph if your car were moving faster?…slower?…not moving?” I found myself providing far less input to draw out meanings of slopes and other key ideas in the subsequent whiteboard discussion.

Student responses to surveys (Appendix B and D) also support the theme of increased engagement:

89% - agreed they listen to and consider alternative points of view 81% - disagreed they don’t pay much attention during whiteboarding 77% - found seeding small groups to be “very valuable” 80% - seeding helped when groups reached an impasse

Promotion of Discourse

There are three pieces of evidence that seeding small groups helped promote the frequency and fluency of discourse about science. The first piece is a narrative account of the constant velocity lab discussion (Appendix A). This whiteboard session progressed with minimal input from me. The second piece comes from the Likert-scale survey (Appendix B2):

78% - agreed student-to-student dialogue was the dominant mode of discussion 78% - agreed student-to-student interaction was the focus. 19% - agreed teacher-to-student dialogue was the dominant mode of discussion. 30% agreed and 41% disagreed student-to-teacher dialogue was the dominant mode of

discussion.

Other survey responses also indicate student-to-student discourse was frequent.

The third piece of evidence that supported promotion of discourse is the following peer observation (Appendix E):

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“As I observed your classes, I could definitely see that you had a plan in mind in regards to which groups you wanted to share their whiteboards with the rest of the class.  You moved around to each group, asking pointed questions, guiding their thinking, giving hints as to the next step, and also subtly implying to specific groups to be ready to explain the group's thinking on the whiteboard.  You knew each group's strengths and weaknesses, level of achievement, and patterns of interaction with the rest of the class.  It was obvious to me as I watched you interact with each group which groups you would call upon to share their whiteboards with the whole class.  As you called upon each group, the groups shared willingly, were comfortable with the sharing process, and were not afraid to make mistakes.  Groups listened attentively and quietly conferred with group members regarding changes to their group's whiteboard based on the previous group's whiteboard presentation.” 

Facilitation and Authority - Success in the Constant Velocity Lab

There is evidence to support the theme that seeding enabled me to function more as a facilitator and less as an authority on content and ideas. My journaling of the constant velocity lab again indicates I was able to use seeding to help set up, frame and orchestrate not only the small group work but also the subsequent whiteboard discussion. This orchestration is what made my role of facilitator possible. Other evidence included the following peer observation:

“I can definitely see the benefit of seeding.  The instructor can entice students to participate by "setting up" a collaborative group to answer according to the lesson's goals and objectives, but also according to the group's needs as well, reinforcing strengths and scaffolding weaknesses to ensure all groups participate, grow, and achieve.” 

Facilitation and Authority - Difficulties in the Uniform Acceleration Lab

I was more successful at seeding in the constant velocity lab than I was in the multi-part uniform acceleration lab. I attribute this to poor organization of the second and third parts of this four-part lab. Part two involved having students use Graphical Analysis for the first time, and I found myself showing each group how to generate a velocity-time graph from the slopes of tangent lines on the original position-time graph. Students took advantage of not knowing what to do. As the peer observer in her second observation points out, they waited until I came to them to begin their work:

“I did observe, however, that some groups waited until you came to them to begin their work.  It seemed they were relying on you to get them started and direct their work.  Not many students took notes or were careful to record your expectations as you outlined the groups' tasks in the beginning of class.  They seemed to know that if they weren't on the right track, you would automatically "help" them get where they needed to be.  During my first observation, it was definitely noticeable that some groups waited for you to come to them and get them started.  These same groups continued to rely on you to "hold their hand" throughout the entire lab, not really trying to figure it out on their own.  During the third observation, you pointedly demanded they do it on their own and the students did.”

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It is now clear to me that seeding more complicated activities requires additional planning. Once the class and I got past the hurdle of how to use the software, I was able to seed one group in a significant way for the subsequent whiteboard discussion. This seeding involved guiding the group in determining the meaning of the slope on their newly obtained velocity-time graph. According to the peer observer (Appendix E), I spent over five minutes with this group. At the end of the seeding the group felt confident they could explain the meaning of the slope during the ensuing whiteboard session. The group was able to accurately share, in their own words and with confidence, what I had guided them through. This group was comprised of three females and two of them had been struggling with the underlying math concepts of the course. I watched the class reaction to this “slower” group as they gave their presentation. Everyone was listening to what this group had to say and hearing their explanation of the meaning of the slope on a velocity-time graph seemed to have significant impact. It was evident the entire class understood the group’s detailed explanation that the slope on a velocity-time graph represents acceleration. In many ways the class had been messy and at times chaotic, as the peer observer pointed out, but solid learning emerged in spite of it all. My reflection on this day: I was too eager to help the small groups to compensate for poor planning and lack of organization.

I had some interesting Likert-survey (appendix B2) responses about student views of my role:

48% - agreed they question ideas shared by the students. 22% - agreed they question ideas shared by the teacher.

81% - agreed what students say during discussions is important

44% - agreed what the teacher says is important

69% - agreed the teacher avoids being the leader of discussions

52% - agreed the teacher observes the discussions and has minimal involvement.

56% - agreed the teacher is the ultimate authority,

67% - agreed the teacher is the authority on the correctness of ideas

81% - agreed the teacher takes the lead when the discussion bogs down

Overall, I believe the class was in a transitional stage of their view of me. Roughly speaking, about half the class viewed me as a facilitator and around two-thirds viewed me as the authority on ideas. Responses to questions five, six, and nine on the follow-up survey (Appendix D) indicate many students wanted me to clearly indicate when work was right or wrong. One student wrote she didn’t “like tip-toeing around the answer - plainly say what’s right and wrong”. Another student wrote, “It’s like kindergarten where everyone’s told they’re ok. If it’s wrong, it’s wrong - let it be known

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and just show how to fix it.” Many students also commented discussions could be more effective if the correct answers were summarized at the end of the discussion.

Conclusion - First Cycle

Seeding small groups helped keep students engaged, promoted student discourse, and enabled me to function more as a facilitator of student learning. However, seeding alone was not the only factor. The class and I had been modeling for several weeks prior to the pilot and students were already adapted to this style of learning. I think seeding did aid student learning in significant ways. However, I believe the biggest obstacle to greater success stems from the fact that the students, not surprisingly, are what Jack Whitehead calls living contradictions. In terms of their attitudes about learning 40% of the students view themselves as passive collectors of information despite the fact that 74% percent view themselves as active creators of their own knowledge. Peer observations agree with this:

“I believe one of the biggest hurdles an instructor must overcome is convincing students that they must do the thinking and the "working through" part of constructing knowledge.  Students are so used to the instructor giving them the information and then reciting said information back to pass "the test" that they don't see the point of finding out things on their own.  Students want instructors to give them the information so they can pass the test and move on.  The type of instructional strategies that you are experimenting with will change the culture of school, which takes much time, energy, planning, and conviction”.

Using more components of discourse management in conjunction with seeding might be a way to overcome the shortcomings of the pilot study and the hurdles mentioned above.

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Second Cycle of Action Research – Spring 2006

Focus Question

In addition to seeding, can using DM components of creation of a learning community and making explicit the need for the creation of models in science improve scientific discourse among students during small group and whole class (whiteboard) discussions?

Sub Questions

1. Can the creation of a learning community result in greater student engagement during whiteboard discussions?

2. Can the creation of a learning community enable me to function more as a facilitator of learning and less as an authority on content and ideas?

3. Can the creation of a learning community help students change their view of learning from collectors of information to creators of their own understanding?

4. Can making explicit the need for the creation of models improve student views about science?

5. Can teacher effectiveness using discourse management be measured?

Expected Results

I expected that once I established the culture of a learning community in my classroom and made explicit the need for the creation of models in science, students would respond more fully to the modeling approach. As a result, I hoped to see an improvement in the level of student discourse, overall better performance and improved attitudes about science.

Implementation – Spring 2006Method

I decided to focus on the DM components of creation of a learning community and making explicit the need for the creation of models in science. I chose these two components based on Desbien’s assertion they must occur first in order to get DM up and running in a classroom. Creating and nurturing a learning community involves, among other things, establishing classroom norms for how everyone will function in a modeling classroom where DM is used. Making explicit the need for the creation of models helps establish the guiding principle for the modeling cycles that form the backbone of the course. I started my research at the beginning of the course by attempting to follow Desbien’s step-by-step procedure for how he initiates a learning community in his classroom.

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In the early stages of organizing the class into a learning community, the activities are designed to encourage students to interact in a noncompetitive manner. To create this atmosphere without the pressure of “learning physics” at the same time is critical to encouraging the greatest number of students to be both involved in the discourse and prepared to be contributing members of the class (Beane, 1995).

Day One – Making Airplanes – an Unanticipated Outcome

The course began with a community building activity of having small groups of students create instructions on how to make a paper airplane. Each group was told to create instructions on how to make a paper airplane on the paper provided. Students were also told to decide for themselves what that means and act accordingly. All groups decided to actually build an airplane and wrote the instructions as it was built. Once the groups were finished, the built airplanes were given identifying numbers, collected and moved to an out of site location. The instructions were collected and redistributed to other groups who were told to use them to construct an airplane. As the instructions were being passed out to other groups, the class was told to follow them exactly as written. Where the instructions were unclear the groups had to interpret as best they could. As the groups began building the airplanes, I passed among them looking for certain words or phrases in the instructions and seeding questions about how the words in the instructions could be interpreted differently. The intent of this seeding was for students to see how the instructions could be interpreted differently and then create paper “airplanes” that in no way resembled what the creators of the instructions intended. Next, the class was brought together in a circle for their first in-the-round discussion of the activity without the use of whiteboards.

I used the first discussion to establish the pattern for the future. The class was told to move the desks into a circle with nothing inside it. I explained this would be the standard mode for class discussions. Students were given two basic rules for discussion: only one person could talk at a time, and evaluation of each other’s work must be done in a positive manner. I went on to say I would remain outside the circle during the discussion and for the most part I would not participate. To join the discussion, I would have to take a position in the circle. I then wrote the following questions on the front board:

What were the difficulties in making the paper airplanes? What words were ambiguous? What assumptions had to be made?

All groups had actually built an airplane as they wrote the instructions. As a result, the instructions were very explicit and detailed which left little room for interpretation by the group that built the airplane from the instructions. This unanticipated turn of events left the class with little to talk about and made it difficult to get to the point of the activity. I had to intervene with questions and comments and basically lead the class to see why they were given the activity, as they were not getting there on their own. In short, the activity was a bit of a flop.

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The purpose of the activity was to have students realize the importance of shared meaning and bring out two ideas the class needed to be mindful of when having discussions: terms need to be defined and agreed upon by the class and pictures are often better than words. According to Desbien, the paper airplane activity is designed to bring this to students’ attention in a memorable way.

At the end of the first day the students were given the following questions to ponder and answer with their own ideas as a page-long assignment:

What is reality? What is science? Is science reality?

Day Two – Reality and Science – Moving Deeper into Uncharted Waters

The second day began with students working in small groups to pull together answers to the homework questions. Unlike Desbien, I made no attempt to seed questions to any groups while they created their whiteboards. I was more interested in what the students were thinking than in steering them in a certain direction. When the whiteboards were done, the class came together for discussion in a circle. I reminded students to hold their white boards so other groups could see them at all times, and I emphasized that a goal of discussion was to reach consensus, explaining what I meant by consensus. I asked one group to present their ideas and let the discussion flow from that point. For those who participated, the discussion was often intense and many different points of view were presented. Like Desbien, I frequently had to intercede and refocus the discussion.

The goal is to have students come to the realization that no explanation [about science and reality] is complete. A secondary goal is to have students realize that how they describe something depends on their own experiences.

I was a bit overwhelmed by how the discussion progressed. The class was all over the place in their thinking and I was at a loss for what to do about it. Like the first day, there were very few agreed upon ideas that could be summarized. I was frustrated that I could not pull things together and give the class a sense of closure, but I now think this was one of the points of the activity. I gave no assignment for the third day and afterwards tried to figure out what to do next. After two days of frustration and false starts, I felt like I was in deep uncharted waters and going down for the second time.

Reflection on Day Two:

The range of views about science and reality surprised me. I was more surprised that many students held conflicting and overlapping views about the two and didn’t seem aware of having such views or able to sort them out during the whiteboard discussion with their peers. I was very concerned that the activities of the first two days were hindering rather than helping the formation of a learning community. I sensed the less talkative students might have been overwhelmed by the reality versus

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science topic and the ease with which their more talkative peers where able to participate. I was concerned about students getting the impression that class discussions were going to be unfocused, intimidating and chaotic occasions in which they would be reluctant to participate. In hindsight, a short formative assessment like a minute paper at the end of class might have given me a better read of the class than my follow up speculative journaling.

Day Three – Finally Some Progress - Naïve Realism versus Scientific Realism

Because of my concerns that the learning community was not forming as it should and because of students’ conflicting and overlapping views about science and reality, I decided to continue this discussion for another day. I constructed a list of contrasting alternatives (Appendix F) derived from the dimensions of Halloun’s Views About Scientific Thinking (VASS) taxonomy to provide more focus for student thought and discussion. I was hoping the list would serve as a springboard for discussion and help create a safe place for learning where students would be willing to take risks. More students participated in this discussion than in the previous reality versus science discussion. The list of contrasting alternatives provided students with a scaffold and the tone of the discussion was more open, relaxed and productive. In contrast to the day before, I felt progress was made in forming the learning community and in helping students clarify their views of science and reality. The discussion wrapped up with a short presentation on scientific realism (Appendix G).

Day Four – Making Explicit the Need for Creating Models –Things Start to Gel

The idea of a model was introduced to the class through an activity called “What’s Inside the Box?” At the start of class each group was given a piece of graph paper and a sealed textbook-sized box containing a marble that rolled around the inside of the box. The class was instructed to use the marble to determine what was in the box and draw a representation on the sheet of same-sized graph paper. The groups where given about twenty minutes to move the box around in any orientation and listen as the marble rolled over or around the various objects glued to the inside surfaces of the box. Each box had a unique configuration of objects inside. When finished, each box was opened and the group’s representation was put on the document camera and compared to what was actually inside the now opened box. At this point I presented the following:

What scientists really do is build models of reality. Let’s call what’s inside the box reality and what’s drawn on the graph paper a model or representation of that reality. Models in science are representations of the structure of reality much like the graph paper sketch represents the structure of what’s inside the box. A model built by scientists has similarities to the object or system it represents but certain details are missing. Many groups found some object or structure, but the details of the exact shape or size were missing or some structures were missed altogether. This activity is very similar to what scientists do when they build models, except they cannot open the box (reality) to check how well the model represents it. Not being able to open the box of reality to verify a model, scientists gather evidence to build, test and verify models. This is

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what we will do in this course – build and verify models that represent the structure of reality and form the basis of science.

At this point I asked the class if they would like to try the activity again with a different box. Everyone wanted a second chance. After repeating the activity, the boxes were opened and the models were compared to reality. Students were both amazed and disappointed: sketches still lacked detail and many still entirely missed some of the objects or major features of the inside of the box. The class ended with a summary of important ideas about scientific models (Appendix H). I felt the immediate goal of making explicit the need for creating models had been achieved:

By the end of the class, students had developed the idea that science is about creating models and scientists continuously create models because no one model is ever complete. Because of their participation in creating it, students had developed ownership of the idea that scientific models are the basis of science.

I was also making progress as well on the larger goals of forming a learning community which functions through the creation of shared meaning.

Day Five – Scientific Claims

Being able to determine whether or not a claim is scientific is, in my opinion, one of the hallmarks of science literacy. I felt a discussion of what makes a claim scientific was appropriate at this point in the development of a scientific learning community. The class was given a worksheet of seven statements (Appendix I) and instructed to work in small groups to determine if the statements were scientific claims and to explain their reasoning. As the groups worked, I seeded them with previously worked out questions (Appendix J) to help stimulate their thinking. Depending on the claim, the seeded questions were either general (for claims 1, 4-6), or very specific (for claims 2, 3, 7). I seeded the general questions initially to all the groups early in their work. Later, after monitoring each group’s progress, I seeded the more specific questions only to those groups that I had decided would be assigned that claim to whiteboard. Each group was then assigned a claim to whiteboard and told to include the statement, whether or not it is a scientific claim and their justification. While they prepared their whiteboards, I made a general announcement that each group needed to be prepared to defend their reasoning once we formed the circle. Once in the circle the groups presented their work in the order of the worksheet. The discussion was relaxed and for the most part focused and productive, but there were a couple of rough moments in discussing claims 2 and 6. These were moments when competing ideas were being argued back and forth. I was outside the circle, listening as the talk went back and forth and hoping the class would self-regulate and reach consensus. They could not reach agreement and for a few moments I left them remain in this state of tension. The class was at an impasse. I intentionally let the moment linger then I reminded them that one goal of discussion was

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for them to reach consensus. I told the class to move on. The class progressed through discussing the remaining claims and points emerged that proved helpful when we returned to the earlier impasse. I ended the session with a handout (Appendix K) and short presentation on terms and concepts related to science and the scientific method.

Reflection on Day Five:

I was concerned the discussion would lack focus and become either chaotic or intimidating to the point of being nonproductive. This did occur somewhat during the discussion of claims 2 and 6, but it did not get out of hand as it had in the science versus reality discussion of Day Two. I had anticipated that claims 2, 3 and 6 would be more difficult for students so beforehand I designed questions to seed to the groups that would whiteboard these claims. As in the pilot action research a year earlier, I was becoming more aware of the value of strategically seeding the small groups as a way to set up and orchestrate the subsequent whiteboard discussions of the learning community.

Data Collection -Triangulation Matrix

Sub Question Data Source 1 Data Source 2 Data Source 3

Engagement Journal Surveys* Audio taping

Frequency & Journal Surveys* Audio tapingFluency

Facilitator vs. Journal Surveys* Audio tapingAuthority Role

Views of learning Journal Surveys* Audio tapingAnd Science

Teacher Journal Surveys* Audio tapingEffectiveness

* Three surveys were used:

The Likert-scale (LS) survey on discourse management used in 2005 A new contrasting alternatives (CA) survey on discourse management

(Appendix L) The VASS survey

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Results and Analysis

Student engagement

First, there is mixed evidence from the CA survey that the formation of the learning community did help student engagement during whiteboard discussions. I decided to use student perceptions of how student-centered the discussions were as a measure of student engagement. Thus, the degree to which the students responded that the discussions were student-centered is an indicator of student engagement. The following items from the DM survey indicate student views.

Student-centered versus Teacher-centered itemsTrad  Mixed DM Trad Mixed DM

Question 1 2 3 Total Percent Percent Percent2 6 1 6 13 0.46 0.08 0.465* 4 5 4 13 0.31 0.38 0.316 0 11 2 13 0.00 0.85 0.15

8** 8 1 4 13 0.62 0.08 0.3115* 5 4 4 13 0.38 0.31 0.3125** 3 1 9 13 0.23 0.08 0.6926 1 5 7 13 0.08 0.38 0.54

 totals 27 28 36 91

91 91 91

percent 0.30 0.31 0.40

The DM column shows the number of students who responded favorably to discourse management (a collapsed score of three on an item):

Q2 46% - dominant mode of discussion is student-to-student dialogue versus 46% - teacher-to-student / student-to-teacher dialogue.

Q5 31% - focus is on the students’ ideas versus 31% - focus is on teacher’s ideas, with 38% mixed.

Q6 15% - the students run discussions with 85% mixed. Q8 31% - discussion evolves naturally from student dialogue versus

62% - teacher intervenes to maintain focus. Q15 31% - important part of discussion is what the students have to say versus

38% - what the teacher has to say.

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Q25 69% - teacher intervenes with a brief question or comment versus 23% - teacher takes the lead when discussion bogs down with 8% mixed.

Q26 54% - understanding is negotiated by student-to-student dialogue versus 8% - the teacher determines understanding with 38% mixed.

Teacher Function and Perceived Role

Second, there is evidence that the formation of the learning community enabled me to function more as a facilitator and less as an authority on content and ideas. I used students’ perceptions of how knowledge is constructed and how the correctness of ideas is determined as a measure of facilitation and authority. The more students view knowledge as being constructed by discourse as opposed to direct instruction indicates my functioning more as a facilitator. The degree to which students view the correctness of ideas being determined through reasoning based on empirical evidence or logical argument indicates I am functioning less as an authority in these areas and the discourse in the learning community is doing this job.Authority (Knowledge)

Trad  Mixed DM Trad Mixed DMQuestion 1 2 3 Total Percent Percent Percent

9 1 5 7 13 0.08 0.38 0.5416 2 6 5 13 0.15 0.46 0.3823 2 7 4 13 0.15 0.54 0.31

 totals 5 18 16 39

39 39 39

percent 0.13 0.46 0.41

Authority (Correctness)Trad  Mixed DM Trad Mixed DM

Question 1 2 3 Total Percent Percent Percent18 3 2 8 13 0.23 0.15 0.6221 1 2 10 13 0.08 0.15 0.77

 totals 4 4 18 26

26 26 26

percent 0.15 0.15 0.69

The DM column shows the number of students who responded favorably to discourse management:

Q9 54% - knowledge is constructed by students versus 8% - presented by teacher with 38% mixed

Q16 38% - new understanding comes from student discussion versus 15% - comes from teacher input with 46% mixed

Q23 31% - knowledge is constructed through student dialogue versus 15% - comes from the teacher with 54% mixed

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Q18 62% - authority on the correctness of ideas is reasoning supported by evidence versus 23% authority on correctness is the teacher.

Q21 77% - correctness of the ideas is decided by logical argument rooted in experimental evidence versus 8% correctness is decided by the teacher.

Collectors and Creators of Information

Third, there is mixed evidence that the formation of the learning community helped students change their view of learning from collectors of information to creators of their own understanding.

Collectors versus CreatorsTrad Mixed DM Trad Mixed DM

Question 1 2 3 Total Percent Percent Percent1 4 7 2 13 0.31 0.54 0.154* 3 3 7 13 0.23 0.23 0.5424 6 2 5 13 0.46 0.15 0.3827* 4 2 7 13 0.31 0.15 0.5429 4 2 7 13 0.31 0.15 0.54

 totals 21 16 28 65

     percent 0.32 0.25 0.43

The DM column shows the number of students who responded favorably to discourse management:

Q1 31% - collectors of information, 54% mixed, 15% creators of understanding. Q4 54% - discussions increase understanding

23% - discussions leave them confused with 23% mixed Q24 38% - listen to and consider alternative points of view given by others

46% - don’t pay much attention to what others say. Q27 54% - understand what has been discussed versus 31% are confused. Q29 54% - best part of discussions is working together to figure things out versus

31% - best part is the summary of what was discussed at the end.

Overall, the composite percents indicate one fourth of the class holds mixed views. About one third of the class view themselves as collectors of information and 43% view themselves as creators of information. Force Concept Inventory (FCI) scores are all below the Newtonian Threshold. This is due to not covering enough material for the class to do any better. The VASS scores indicate 9 out of 13 students have a folk profile. This indicates that making explicit the need for the creation of models and spending several days at the beginning of the course discussing nature of science themes had no lasting effect on students’ views about science.

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Models and Views About Science

Fourth, there is no evidence from the VASS that making explicit the need for the creation of models improved students’ views about science.

S2 05-06   FCI DMSurvey VASS FCI Totals VASS ProfilesStudent 5/31/2006percent 6/1/2006 5/31/2006Thresholds 2005-6 EP>92 1

1 11 0.37 30 57 Mastery >0.80 0 HTP 83-92 12 9 0.30 57 75 Newtonian >0.60 0 LTP 73-82 23 13 0.43 33 69 Below <0.60 13 FP <73 94 7 0.23 42 485 11 0.37 60 1026 5 0.17 21 457 11 0.37 36 758 5 0.17 42 579 13 0.43 60 90

10 6 0.20 36 3911 11 0.37 39 6612 8 0.27 45 5713 8 0.27 63 69

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FCI scores are all below the Newtonian Threshold of 60%. This is due to not covering enough material for the class to do any better. The VASS scores indicate 9 out of 13 students have a folk profile. This indicates that making explicit the need for the creation of models and spending several days at the beginning of the course discussing nature of science themes had no lasting effect on students’ views about science.

Teacher Effectiveness

Fifth, there is, with one exception, evidence of overall teacher effectiveness in attempting to implement components of discourse management. Many of these items would be measures of teacher effectiveness for any classroom management approach. However, in a social constructivist classroom, they are essential for the formation, nurturing and maintenance of a learning community. Effectiveness Items

Trad Mixed DM Trad Mixed DMQuestion 1 2 3 Total Percent Percent Percent

11 3 2 8 13 0.23 0.15 0.6212 0 3 10 13 0.00 0.23 0.7713 0 2 11 13 0.00 0.15 0.8517 6 5 2 13 0.46 0.38 0.1520 3 2 8 13 0.23 0.15 0.6227 4 2 7 13 0.31 0.15 0.54

 totals 16 16 46 78

     percent 0.21 0.21 0.59

The DM column shows the number of students who responded favorably to discourse management:

Q11 62% - classroom atmosphere is supportive versus 23% competitive. Q12 77% - teacher treats everyone the same versus 0% shows favoritism with

23% - mixed. Q13 85% - differences over the meanings of ideas are resolved versus

0% - unresolved with 15% mixed.

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Q17 46% - conflicting ideas turn into conflict between students versus 15% - lead to greater appreciation for how others think with 38% mixed.

Q20 62% - similarities/common items quickly noted - attention turns to differences/deeper meanings versus 23% lots of repetition.

Q27 54% - understand what has been discussed versus 31% are confused.

I believe the response to question 17 was due to the personal dynamics between a student with conservative political views and students with more liberal views. Political arguments among the students where often in progress as they walked into class. It was clear from these discussions that students’ differences were both political and personal. I think some of these dynamics carried over into how students answered question 17. To the students’ credit, the whiteboard discussions never became polarized along personal or political dimensions, but I think the response to question 17 was influenced by these debates. The composite 59% rating of overall teacher effectiveness would be higher if question 17 were removed.

What changed in 2006?

In comparing the results of the Likert-scale (LS) survey to those of the contrasting alternatives (CA) survey, the CA survey appears to have provided a more reliable read of the 2006 class than the LS survey provided for the 2005 class. Halloun states that CA surveys resolve the risk of interpretation mismatch between surveyor and respondent often found in LS surveys. Table 1 below includes several of the two alternatives associated with one CA statement. Each pair were originally listed as two separate items on the LS survey and later combined into one contrasting alterative item on the CA survey. Some of tabulated data of the 2005 students revealed contradictory positions on Likert statements dealing with the same issue. Halloun’s study showed that LS surveys can be misleading, even when all possible viewpoints are offered in separate questions, and that the CA format is significantly more reliable. In the CA format, a student’s response has to be stated for one alternative by comparison to the contrasting one and not in the absolute sense. This comparison is not made possible with the LS format where there is no point of reference relative to which students can state their position.

Table 1 Contrasting Alternatives 2005 LS 2006 CA

The focus is on student ideas. 81% agree 31% The focus is on teacher ideas. 56% disagree 31%

Mixed view NA 38%

View themselves as collectors of information. 44% agree 31% View themselves as creators of understanding. 74% agree 18%

Mixed view NA 51%

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What students say is most important. 81% agree NA What teacher says is most important. 44% agree NA

Teacher leads when discussion bogs down. 81% agree 23% Teacher has minimal involvement in discussion. 52% agree 69%

Mixed view NA 8%

The percentages in all four pairs add up to over 100%. Consider the first pair. When the focus of discussion can only be on student or teacher ideas, it is inconsistent for 81% of the students to agree the focus is on student ideas and 56% of students to disagree the focus is on teacher ideas. For consistency the two percentages should match and since they do not, the reliability of the two statements taken together is questionable. The remaining pairs of statements also show inconsistencies because there is no way to account for respondents who share both views. By design, the CA format captures the range of intermediate responses and therefore gives a more complete and reliable read.

Interpreting the VASS

Vass results separate students into four profiles: expert, high transitional, low transitional, and folk. Profiles have predetermined cutoffs. According to Desbien, reliabilities for the VASS have been found to be relatively low. The Vass is used here for simply making comparisons between distributions of students in the four profiles and distributions of student’s scores on the CA survey. To this end, the results of the CA survey were tabulated in the same manner as the results of the VASS. Collapsing results form a 5-point scale to a 3-point scale and adding the expert views (3’s) yields a number that determines a student profile.

DMSurvey VASS Totals VASS Profiles6/1/2006 5/31/2006 2005-6 EP>92 1

30 57 0 HTP 83-92 157 75 0 LTP 73-82 233 69 13 FP <73 942 4860 10221 4536 7542 5760 9036 3939 6645 5763 69

The Vass scores were plotted versus the DM scores. The DM survey is the 2006 CA survey. The above graph shows a possible correlation between scores on the CA survey and having a particular VASS profile. Three of the four students with profile

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scores above the folk level of 73 have the highest DM survey scores. Eight of the nine students with a folk profile scored below 50 on the DM survey. There are inconsistencies. The one remaining student above the folk profile had a low transitional profile (LTP) of 75 and a DM score below 40. One of the 9 students with a folk profile of 69 had the highest DM survey score of 63. Despite the small population and these inconsistencies, it can be said the DM survey (CA survey) with additional refinement and testing shows promise as a possible instrument to measure the use of discourse management.

Using the VASS

The question of whether VASS profiles can be used by teachers to identify students who will struggle with modeling and scientific discourse is worth consideration. Halloun states that students with folk profiles are primarily naive realists and passive learners while students with expert profiles are scientific realists and critical learners. Most students are a mix of expert and folk views and reside somewhere along a continuum of the four profiles. Halloun has reported the profile distribution among high school students to be 31% folk, 36% low transitional, 25% high transitional and 8% expert. Knowing the profile distribution of students at the beginning of a course would provide teachers with information that could be used for planning instruction that considers where the students are coming from. Specifically, physics teachers whose students have previously taken chemistry or biology could use the chemistry or biology version of the VASS at the start of instruction. The results could be used to help place students in collaborative groups, making sure that every group has at least one student with a profile other than folk. As a follow up, the physics version of the VASS could be used at the end of instruction to measure changes in student views about science that may have occurred during the course.

Conclusion - Second Cycle

Creation of a learning community did result in greater student engagement during whiteboard discussions. Seeding questions enabled me to function and be perceived more as a facilitator of learning and less as an authority on content and ideas. The learning community experience of building consensus through shared meaning helped some students change their view of learning from passive collectors of information to active creators of their own understanding. Making explicit the need for the creation of models did not appreciably change student views about science. Teacher effectiveness using discourse management may be measurable with further development of a discourse management survey using a contrasting alternative format similar to the VASS.

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Professional Value

This action research project has been personally and professionally challenging as well as rewarding. In doing the 2005 and 2006 cycles of action research, I have started a new phase in my professional life that has significantly changed my view of teaching and my teaching practice. I spend more time thinking and reflecting on what I do in the classroom and whether or not my actions are in line with my personal and professional values. I chose to do action research on discourse management because I was frustrated by my inability to raise the level of student discourse about science. I want students to function at a higher level in my classroom. I hope what I have learned about doing action research and using discourse management will benefit my students and possibly other teachers who also struggle to improve their teaching of modeling. I highly recommend teachers try doing classroom action research in an area of their practice where they experience a concern that their educational values and beliefs are being denied. I got started in action research by looking at an area of my teaching that concerned me and quickly came up with ideas for research. The project has not been easy, but it has been rewarding and beneficial. I have benefited personally and professionally form my efforts and my students have and will be provided with better instruction as a result of my work. I plan to do future cycles of implementing discourse management starting in the fall of 2006.

Implications for the Future

Implementing a new style of modeling has been a make or break proposition for me. I have worked for a long time to improve my use of modeling and frankly I was at the point of abandoning it altogether until I was exposed to Desbien’s work. I was not very good at Socratic modeling and the pace at which I progressed through the units was such that I considered shifting to more traditional instruction. Efforts to change how I teach have been fraught with false starts, missed opportunities and unanticipated outcomes. Discourse management coupled with the reiterative systematic reflection of action research have provided me with both a model of instruction and a model for improving instruction that I can use to improve my practice so it moves in the direction of my personal and professional values. What follows is a short list of things I will strive to accomplish in the future.

I will to continue to develop the discourse management survey until it is a reliable tool for measuring the use of modeling discourse.

I will to give incoming students the chemistry version of the VASS and use the results to distribute the highest scoring students among the small groups in my class. The physics version of the VASS will be given at the end of instruction to measure changes in student views about science. The VASS results and DM survey results will be used to improve instruction and refine the DM survey.

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I would like to try Fishwild’s approach of incorporating nature of science activities throughout a physics course. This involves student journaling which might help students with changing their views about science and bring to the fore the need to work from the perspective of building models.

I am interested in having students maintain a reflective journal about what they learn. I think journaling would help them consolidate what is learned in class and be a personal record of student progress.

I will refine my use of the seeding technique in order to strategically tailor seeds to each group’s strengths in such a way that all the groups’ contributions to discourse compliment one another and balance out during the whiteboard discussion. Then groups will be on a level playing field, so to speak, and contribute to the discussion so that no group tends to dominate or intimidate.

References

Beane, J.: 1995, Curriculum Integration and the Discipline of Knowledge, Phi Delta Kappan, 76, 616-622.

Desbien, D.: 2002, Modeling Discourse Management Compared to Other Classroom Management Styles in University Physics, Dissertation at Arizona State University, http://modeling.asu.edu/modeling/ModelingDiscourseMgmt02.pdf.

Fishwild, J.: 2005, Modeling Instruction and the nature of Science, Unpublished Thesis, JEF@oregon.k12.wi.us

Halloun, I.: 2001, Student Views About Science A Comparative Survey Monogram, Educational Research Center, Lebanese University, Beirut, Lebanon, http://cresmet.asu.edu/cgi-bin/cpublications.pl

Halloun, I.: 2004, Modeling Theory in Science Education, Kluwer Academic Publishers, http://cresmet.asu.edu/cgi-bin/cpublications.pl

Halloun I,& Hestenes D.: 1998, Interpreting VASS Dimensions and Profiles for Physics Students. Science & Education. 7(6) 553-577, http://cresmet.asu.edu/cgi-bin/cpublications.pl

Halloun I,& Hestenes D.: 1987, Modeling Instruction in Mechanics, Am. J. Phys., 55, 455-462, http://cresmet.asu.edu/cgi-bin/cpublications.pl

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Hestenes, D.: 1996, Modeling Methodology for Physics Teachers: Proceedings of the International Conference on Undergraduate Physics Education, http://modeling.asu.edu/modeling/ModMeth.html

Hestenes, D.: 1987, Toward a Modeling Theory of Instruction, Am. J. Phys., 55, 440-454,

http://modeling.asu.edu/R&E/Research.html

Lattery, J, & Schmitt, M.: ????, Faciltating Discourse in the Physics Classroom:A Compilation of Quotes from Experienced Modelers, Unpublished Paper, http://modeling.asu.edu/Projects-Resources.html

McNiff, J, Lomax, P, & Whitehead, J.: 2003, You and Your Action Research Project, 2nd Edition, RoutledgeFalmer, NY, 59-60.

Piaget, J.: 1964, Part I, Cognitive development in children: Piaget development and learning, Journal of Research in Science Teaching, 2, 176-186.

Piaget, J.: 1970, The Child’s Conception of Movement and Speed, Translated byHolloway and Mckenzie, Routledge and Kegan, London.

Wells, M, Hestenes, D, & Swackhamer, G.: 1995, A Modeling Method for High School

Physics Instruction. American Journal of Physics, 63, 606-619. http://modelingnts.la.asu.edu/pdf/ModelingGames.pdf

Vygotsky, L.: 1962, Thought and Language, Cambridge, Ma, MIT Press.

Wendel, P.: 2003, Resistance to Whiteboarding, http://modeling.asu.edu/listserv/WB_resistance03.pdf.

Yost, D. (2000). Whiteboarding: A Learning Process. http://modeling.asu.edu/modeling/Whiteboarding_DonYost03.pdf

Yost, D., Groeshel, G., & Hutto, S. (2002) Whiteboarding Is a Tool, a Learning Experience. http://modeling.asu.edu/listserv/wb_ALearningExper_02.pdf.

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Appendix A

Monday, March 07, 2005 5:49 PM

Seeding is something I recently tried on March 1st with 11th and 12th-grade students who were preparing whiteboards in the Unit 2 Paradigm (Dune Buggy) Lab. During small group time when they were preparing whiteboards of their results I seeded groups with questions like, "What would happen to your data and graph if the car was moving faster?..slower?...not moving?......was turned around and moving in the opposite direction?" and so on.   I asked these questions knowing that many groups had decided to graph distance (the group's independent variable, based on their experimental design) on the horizontal axis and time on the vertical axis.  The groups were given additional time to work out the answers to these questions before whiteboarding began. This lead to some interesting discussion of what the slope told us about the car.   Groups that graphed time versus distance had no trouble telling the class their slope told how much time the car traveled a unit distance of a meter or centimeter.  They could also easily articulate that their graph would become steeper (the car would take more time to travel the same unit distance) if the car were moving slower and less steep (the car would take less time to travel the same unit distance) if the car were moving faster.  Groups that had controlled the time and graphed distance versus time then presented their analysis and take on the same questions.  IMHO, the seeding of questions helped make the whole class discussion more lively and engaging, and I found myself having to provided less input in terms of having to guide and focus the discussion and draw out meanings of slopes and other main ideas.  The students were doing more of this on their own.  What I think I've learned from this is that seeding can be used to help set up, frame and orchestrate not only small group work, but more importantly the subsequent whole class discussion.   I feel my one-time experience with Dwain Desbien's technique of seeding small groups with questions (conjectures, if you will) helped elevate the level of discourse and I plan to do a three-

28

week action research pilot on seeding techniques as a requirement for a Foundations of AR course I am taking at Montana State University.

Appendix B PHYSICS FEEDBACK SURVEY II

DIRECTIONS: For each of the following items, please read the statement, and indicate (on the scantron answer sheet) the answer that describes how strongly you agree or disagree.

A: Strongly disagree B: Somewhat disagree C: Neutral D: Somewhat agree E: Strongly agree

1. During whole-class (white board) discussions knowledge is constructed and shared through dialogue.(7)

2. During whole-class (white board) discussions I listen to and consider alternative points of view.(12)

3. During whole-class (white board) discussions the teacher avoids being the leader of the discussion.(16)

4. During whole-class (white board) discussions new knowledge comes mostly from the teacher.(17)

5. During whole-class (white board) discussions I don’t pay much attention to what goes on.(18)

6. During whole-class (white board) discussions the teacher is the ultimate authority.(26)

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7. During whole-class (white board) discussions new knowledge is created when students confront their own beliefs and modify or abandon them.(31)

8. During whole-class (white board) discussions what students have to say is the important part of the discussion.(32)

9. During whole-class (white board) discussions student-to-student dialogue is the dominant mode of discussion.(33)

10. During whole-class (white board) discussions student-to-teacher dialogue is the dominant mode of discussion.(36)

11. During whole-class (white board) discussions the teacher mostly observes the discussion and has minimal involvement.(37)

12. During whole-class (white board) discussions I question ideas that are shared by fellow students.(38)

13. During whole-class (white board) discussions teacher-to-student dialogue is the dominant mode of discussion.(39)A: Strongly disagree B: Somewhat disagree C: Neutral D: Somewhat agree E: Strongly agree

14. During whole-class (white board) discussions teacher-to-student dialogue is the dominant mode of discussion.(39)

15. During whole-class (white board) discussions the teacher’s ideas are the focus of the discussion.(40)

16. During whole-class (white board) discussions I question ideas that are shared by the teacher.(41)

17. During whole-class (white board) discussions what the teacher says is the important part of the discussion.(46)

18. During whole-class (white board) discussions student-to-student interactions are the focus of the discussions.(51)

19. During whole-class (white board) discussions the focus is on the students’ ideas.(54)

20. During whole-class (white board) discussions the focus is on the teacher’s ideas.(57)

21. During whole-class (white board) discussions my view of my own learning is that I am mostly a collector of information.(58)

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22. During whole-group (white board) discussions my view of my own learning is that I am a creator of my own understanding.(63)

23. During whole-group (white board) discussions the teacher assumes the role of authority when it comes to the correctness of the ideas being discussed.(65)

24. During whole-group (white board) discussions the teacher takes the lead in the discussion to keep things moving along when the discussion bogs down or hits a snag.(67)

25. During small-group (white board prep) discussions the teacher “seeds” ideas, hints or questions to small groups for them to work on and then bring to the whole class during white board discussions.(74)

25. I have responded to this survey to the best of my ability.(75)

Appendix B2MODELING DISCOURSE SURVEY RESULTS – March 2005

DIRECTIONS: For each of the following items, please read the statement, and indicate (on the scantron answer sheet) the answer that describes how strongly you agree or disagree.

A: Strongly disagree B: Somewhat disagree C: Neutral D: Somewhat agree E: Strongly agree

1. During whole-class (white board) discussions knowledge is constructed and shared through dialogue.(7)

1 2 1 8 15 4.26*2. During whole-class (white board) discussions I listen to and consider alternative

points of view.(12)1 2 0 10 14 4.26

3. During whole-class (white board) discussions the teacher avoids being the leader of the discussion.(16)

2** 2 4 8 10 3.854. During whole-class (white board) discussions new knowledge comes mostly from

the teacher.(17)3 8 5 9 2 3.04

5. During whole-class (white board) discussions I don’t pay much attention to what goes on.(18)

15 7 2 2 1 4.07

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6. During whole-class (white board) discussions the teacher is the ultimate authority.(26)

1 5 6 6 9 2.377. During whole-class (white board) discussions new knowledge is created when

students confront their own beliefs and modify or abandon them.(31)2 0 3 8 14 4.37

8. During whole-class (white board) discussions what students have to say is the important part of the discussion.(32)

0 2 3 12 10 4.009. During whole-class (white board) discussions student-to-student dialogue is the

dominant mode of discussion.(33)0 1 5 13 8 4.04

10. During whole-class (white board) discussions student-to-teacher dialogue is the dominant mode of discussion.(36)

2 9 8 8 0 3.1911. During whole-class (white board) discussions the teacher mostly observes the

discussion and has minimal involvement.(37)2 4 7 12 12 3.30

12. During whole-class (white board) discussions I question ideas that are shared by fellow students.(38)

2 2 10 10 3 3.37A: Strongly disagree B: Somewhat disagree C: Neutral D: Somewhat agree E: Strongly agree

13. During whole-class (white board) discussions teacher-to-student dialogue is the dominant mode of discussion.(39)

5 10 7 5 0 3.5614. During whole-class (white board) discussions the teacher’s ideas are the focus of

the discussion.(40)4 10 7 4 2 3.37

15. During whole-class (white board) discussions I question ideas that are shared by the teacher.(41)

4 7 10 6 0 2.6716. During whole-class (white board) discussions what the teacher says is the

important part of the discussion.(46)3 7 5 5 7 2.74

17. During whole-class (white board) discussions student-to-student interactions are the focus of the discussions.(51)

0 2 4 13 8 4.0018. During whole-class (white board) discussions the focus is on the students’ ideas.

(54)0 2 3 10 12 4.19

19. During whole-class (white board) discussions the focus is on the teacher’s ideas.(57)

6 9 9 3 0 3.6720. During whole-class (white board) discussions my view of my own learning is that

I am mostly a collector of information.(58)1 4 10 9 3 2.67

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21. During whole-group (white board) discussions my view of my own learning is that I am a creator of my own understanding.(63)

1 2 4 13 7 3.8522. During whole-group (white board) discussions the teacher assumes the role of

authority when it comes to the correctness of the ideas being discussed.(65)1 5 2 10 8 2.33

23. During whole-group (white board) discussions the teacher takes the lead in the discussion to keep things moving along when the discussion bogs down or hits a snag.(67)

0 4 1 13 9 2.0024. During small-group (white board prep) discussions the teacher “seeds” ideas,

hints or questions to small groups for them to work on and then bring to the whole class during white board discussions.(74)

1** 0 1 4 20 4.6125. I have responded to this survey to the best of my ability.(75)

* Modeling Discourse Score (weighted average obtained by multiplying the results by a discourse weighting factor (DWF) of 1-5, 1 being the lowest DWF (least favorable for discourse) to 5 being the highest DWF (most favorable for discourse).

**Had 26, not 27 responses.Appendix C Student Feedback Survey – Physics ID #______________ Date_______________

1. Compare the workload in this class to that in other science classes you have taken.a. much greaterb. somewhat greaterc. about the samed. somewhat lesse. much less

2. Compare the workload in this class to that in other classes you are taking this year.a. much greaterb. somewhat greaterc. about the samed. somewhat lesse. much less

3. Compare the level of difficulty of material in this class to that of other science classes you have taken.

a. much more difficultb. somewhat more difficultc. about the samed. somewhat less difficulte. much less difficult

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4. Compare the level of difficulty of material in this class to that of other classes you are taking this year.

a. much more difficultb. somewhat more difficultc. about the samed. somewhat less difficulte. much less difficult

5. Whiteboarding homework problems helps me understand the concepts better.a. strongly agreeb. agreec. neither agree nor disagreed. disagreee. strongly disagree

6. I find myself struggling with the math required for this class.a. strongly agreeb. agreec. neither agree nor disagreed. disagreee. strongly disagree

7. Please compare the Modeling style of labs to the other kinds of labs you've had in your previous science classes. How are they different? How are they similar?

8. Please comment on your attitude towards each kind also - which kind do you prefer, and why?

9. When we do Modeling labs, we follow a series of steps in the process: first, we have a PRE-LAB DISCUSSION, then you DESIGN THE LAB, then you actually DO THE LAB, then you ANALYZE THE LAB in your groups, then you PREP WHITEBOARDS on what you’ve learned, then you do GROUP PRESENTATIONS and we have CLASS DISCUSSIONS about the findings where we try to reach agreement, then we have a POST-LAB DISCUSSION, then you do a short LAB WRITE-UP and then you use what you learned in HOMEWORK.

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Which of these steps do you feel you get the most out of, in terms of learning the new concepts? Which step(s) is/are most valuable and effective? Explain.

10. What do you LIKE about this style of lab?

What do you DISLIKE about it?

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Appendix D

Student Follow Up Survey Student ID#___________ Date ___________

1. What do you see as the qualities of a good physics student or the strategies that work best for you to help you learn physics?

2. Evaluate the typical class activities as to their value as learning experiences for you personally...i.e. labs, whiteboard preparation, teacher “hints” “ questions” “explanations” during whiteboard preparation, whiteboard presentations, whole class discussions, group problem solving, etc....

3. What part of the modeling cycle is the most likely to cause that "light-bulb experience" for you?

4. At what point do you typically grasp what the model is? Small group discussion? Whole group work? At home doing homework problems? On review day the day before the test?

5. What is it about the discourse that works (or not) for you?

6. What would make discourse more effective?

7. How valuable or necessary is an occasional teacher "hint", “question” or “explanation” (i.e., small group seeding) in your opinion?

8. What happens in the group after the teacher seeds a question and then moves on?

9. Do you have any ideas for how to change the discourse in small groups to make it more productive?

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Appendix E

Summary and Conclusion - Mr. Crookston’s Physics Class Observations - April 15, 2005Vanessa Sral, Director of Curriculum and Instruction

As I understand seeding (primary technique for introducing new ideas into class discussion), the instructor uses questioning and planting to guide a collaborative group's thinking and white board responses with the eventual outcome of sharing the group's constructed knowledge with the other groups. 

As I observed your classes, I could definitely see that you had a plan in mind in regards to which groups you wanted to share their whiteboards with the rest of the class.  You moved around to each group, asking pointed questions, guiding their thinking, giving hints as to the next step, and also subtly implying to specific groups to be ready to explain the group's thinking on the whiteboard.  You knew each group's strengths and weaknesses, level of achievement, and patterns of interaction with the rest of the class.  It was obvious to me as I watched you interact with each group which groups you would call upon to share their whiteboards with the whole class.  As you called upon each group, the groups shared willingly, were comfortable with the sharing process, and were not afraid to make mistakes.  Groups listened attentively and quietly conferred with group members regarding changes to their group's whiteboard based on the previous group's whiteboard presentation. 

I did observe, however, that some groups waited until you came to them to begin their work.  It seemed they were relying on you to get them started and direct their work.  Not many students took notes or were careful to record your expectations as you outlined the groups' tasks in the beginning of class.  They seemed to know that if they weren't on the right track, you would automatically "help" them get where they needed to be.  During my first observation, it was definitely noticeable that some groups waited for you to come to them and get them started.  These same groups continued to rely on you to "hold their hand" throughout the entire lab, not really trying to figure it out on their own.  During the third observation, you pointedly demanded they do it on their own and the students did. 

I can definitely see the benefit of seeding.  The instructor can entice students to participate by "setting up" a collaborative group to answer according to the lesson's goals and objectives, but also according to the group's needs as well, reinforcing strengths and scaffolding weaknesses to ensure all groups participate, grow, and achieve. 

I believe one of the biggest hurdles an instructor must overcome is convincing students that they must do the thinking and the "working through" part of constructing knowledge.  Students are so used to the instructor giving them the information and then reciting said information back to pass "the test" that they don't see the point of finding out things on their own.  Students want instructors to give them the information so they can pass the test and move on.  The type of instructional strategies that you are experimenting with will change the culture of school, which takes much time, energy, planning, and conviction.  

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Appendix F Halloun’s VASS Taxonomy

A short survey on science (CA) Name______________________Period_____ Date____________

Epistemology

1. Science is:a. A collection of particular empirical (observable or experienced) facts about

physical realities (real systems or phenomena).b. A logically consistent (coherent) body of knowledge about patterns in physical realities.

2. A given pattern is defined by:a. A comprehensive similarity in all possible features that may actually be common to all

concerned realities.b. A limited number of primary aspects (essential features) common to a variety of physical

realities.

3. Primary aspects of physical realities, and especially explanatory or causal (cause and effect, not casual) aspects:

a. Are by necessity exposed directly to our senses or are detectable through instruments.b. Need to be arrived at by reasoning from evidence (inferred from certain observations).

Methodology

1. Natural patterns:a. Are usually unveiled by careful investigation of physical realities.b. Are discovered accidentally through direct perception of physical realities.

2. Scientists:a. Use a single method governed by a particular theory to investigate a given physical

reality from one perspective.b. Use a variety of methods and rely on a variety of theories to investigate a given physical

reality from different perspective.

3. Mathematics is used by scientists:a. For processing information efficiently.b. For number crunching.

Viability

1. Scientific concepts (concepts, laws, models):a. Are by necessity inherent (already present) in physical realities.b. Are invented by scientists to represent physical realities.

2. Scientific concepts (concepts, laws, models):a. Are corroborated (supported or made certain) with reliable evidence form the empirical

(observable or experienced) world.b. Are faithfully accepted form particular scientific authorities.c.

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3. Scientific knowledge:a. Is approximate (not quite reality), tentative(not fully worked out or developed) and

refutable (can be proven wrong).b. Is exact (agrees with reality), absolute (fully worked out) and final (cannot be altered or

changed).

1 2 3 4 5 (a>>b) (a>b) (a=b) (a<b) (a<<b)

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Appendix G Adapted from Halloun’s VASS Taxonomy

Scientific Realism

EPISTEMOLOGY

1. Science… Is a logically consistent (coherent) body of knowledge about patterns in physical

realities (systems)

2. Patterns… Are defined by a limited number of essential features common to a variety of physical

systems.

3. Primary (explanatory or causal) aspects… Need to be arrived at by reasoning from evidence.

METHODOLOGY

4. Natural patterns… Are usually unveiled by careful investigation.

5. Scientists… Use a variety of methods and rely on a variety of theories to investigate a given

physical reality form different perspectives.

6. Mathematics… Is used by scientists for processing information efficiently.

VIABILITY

7. Scientific concepts… Are invented by scientists to represent physical realities. Are corroborated with reliable evidence from the observable world.

8. Scientific knowledge… Is approximate, tentative and refutable. Is incomplete. Is in a constant state of change and evolution.

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Appendix H

Introduce the idea of a model…

A model is the representation of structure…

It includes graphs of variables, relationships between variables, equations, and a variety of representational tools.

A model has similarities to the physical reality it represents, (object, system, phenomena), but certain details are missing (the focus is on the bare essentials or essence of the situation).

Scientists continually create, revise and refine models because no model is ever complete.

Scientific models do not explain reality, they only represent reproducible patterns that anyone can observe.

Science is about creating models, rather than discovering absolutes.

Scientific models are the basis of science and models have limitations…

It is important to communicate these limits so others understand when a model is used appropriately.

Reminder:

There is not “right answer” to a question……the answer developed depends on the model used.

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Appendix IScientific Claims? Name________________________

Period____ Date_______________

Directions: Which of the statements below is a scientific claim? Explain your reasoning.

1. The alignment of the planets in the sky determines the best time for making decisions.

2. Intelligent life exists on other planets somewhere in the universe.

3. Most people stop for red lights.

4. No material object can travel faster than the speed of light.

5. Atoms are the smallest particles of matter.

6. The universe is surrounded by a second universe, the exist of which cannot be detected by scientists.

7. Albert Einstein was the greatest physicist of the 20th century.

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Appendix J

Scientific Claims – Seeding Questions

General Questions

1. How would you go about checking out whether or not this claim is scientific?2. How would you check the validity of this claim?

Intelligent life exists on other planets somewhere in the universe. (Claim 2)

1. How could this claim be proven correct?2. Is there a way to prove this statement incorrect if no life is ever found?3. If you searched for a long time and never found intelligent life…

a. Would you have proved it exists “around the next corner”?b. Would you have proved it does not exist “around the next corner”?c. Would you have not proved it does not exist “around the next corner”?

4. Can this claim be proven false?

Most people stop for red lights. (Claim 3)

1. What do we study in science?2. What do we study in the life sciences?3. What do we study in the physical sciences?4. What branch of science would study whether or not people stop at red lights?

No material object can travel faster than the speed of light. (claim 4) Atoms are the smallest particles of matter. (claim 5) The universe is surrounded by a second universe, the exist of which cannot be

detected by scientists. (claim 6)

1. Has this claim been proven?2. Has this claim been proven wrong?

Albert Einstein was the greatest physicist of the 20th century. (claim 7)

1. If Einstein was not the greatest scientist, how would you know?2. If someone else was greater, how would you know?3. What is the basis of this claim?

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Appendix K

Scientific Method … An orderly method of gaining, organizing, and applying new knowledge about the

natural world.

Facts… Revisable ideas about the world that are the result of close agreement among

competent observers of the same phenomenon. Facts are not absolute; they can be revised or changed. Facts are interpreted by scientific theories.

Scientific Hypothesis… A reasonable explanation of an observation that is not fully accepted as “factual”

or “correct” until tested over and over again by experiment. An educated guess not yet proven by experiment. Hypotheses in science are changed or abandoned if they are contradicted by

experimental evidence.

Scientific Law or Principle… A general statement about the relationship between natural quantities that have

been tested over and over again and have not been contradicted. If a scientist finds evidence that contradicts a law or principle, it must be changed

or abandoned.

Scientific Theory… A synthesis of a large body of information that includes well-tested and verified

hypotheses and predictions about certain aspects of the natural world. Scientists use the word theory differently: in everyday speech a theory is the same

as a hypothesis – a supposition that has not yet been verified. Theories of science are not fixed; they undergo change and evolve as they go

through stages of redefinition and refinement. Theories are modified as new and conflicting evidence is gathered. Refinement of theories is strength of science, not a weakness. Scientists change

their minds when (1) confronted with solid experimental evidence to the contrary or (2) when a conceptually simpler hypothesis forces them to a new point of view.

The criterion of a theory is not whether it is true or untrue, but rather whether it is useful or not useful.

A theory is useful even though the ultimate causes of the phenomenon it deals with is unknown ( e.g. the classical theory of gravity ).

The common misunderstanding of what a scientific theory is often shows up in conversation when someone says, “But it’s not a fact, it’s only a theory.” Many people have the mistaken notion that a theory is tentative or speculative while a fact is absolute.

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Cardinal Rule of Science… All hypotheses or claims must be testable. A scientific claim or hypothesis must have the capability of being tested so that it

is not correct (possibly wrong). Scientific claims or hypotheses must link to a general understanding of the natural

world. If a claim or hypothesis has no test for possible wrongness, then it is not

scientific.

The Possible Rightness or Wrongness of Ideas… Is generally misunderstood. Is not generally a criterion (a requirement) of other disciplines. It is a prerogative of science to embrace only ideas that can be tested and to

disregard the rest. Ideas that can’t be tested are not necessarily wrong – they are simply useless

insofar as advancement of scientific knowledge is concerned. Ideas must be tested and verified by other scientists – in this way science tends to

be self-correcting.

Appendix LModeling Discourse Management Survey

John Crookston1 2 3 4 5

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(a>>b) (a>b) (a=b) (a<b) (a<<b)

1. My view of my own learning is that: a. I am a collector of information.b. I am the creator of my own understanding.

2. The dominant mode of discussion is:a. Teacher-to-student / student-to-teacher dialogue.b. Student-to-student dialogue.

3. I question the ideas and arguments:a. of fellow students.b. of the teacher.

4. White board discussions: a. Increase my understanding.b. Leave me confused.

5. The focus during discussion:a. is on the teacher’s ideas.b. is on the students’ ideas.

6. Discussions:a. Are run by the students.b. Are run by the teacher.

7. The validity of ideas:a. Depends on logical argument rooted in experimental evidence.b. Depends on what the teacher says.

8. The teacher:a. Intervenes to keep the discussion focused and on track.b. Has minimal involvement, the discussion evolves naturally from student

dialogue.

9. Knowledge is:a. constructed by the students.b. presented by the teacher.

10. Sharing my ideas:a. Helps me learn.b. Helps others learn.

1 2 3 4 5 (a>>b) (a>b) (a=b) (a<b) (a<<b)

11. The classroom atmosphere is:

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a. Competitive.b. Supportive.

12. The teacher:a. treats everyone the same.b. shows favoritism.

13. Differences over the meanings of ideas:a. Go unresolved.b. Are resolved.

14. When differences over the meanings of ideas are resolved:a. The differences are resolved by the teacher.b. The differences are resolved through student-to-student dialogue.

15. The important part of discussion:a. Is what the teacher has to say.b. Is what the students have to say.

16. New understanding: a. Comes from student discussion .b. Comes from teacher input.

17. Conflicting ideas:a. Turn into conflict between students or groups of students.b. Lead to greater appreciation for how others think.

18. The authority on the correctness of ideas is:a. Sound reasoning supported by evidence.b. The teacher.

19. My ideas about physics:a. Are brought into question when I hear the ideas and arguments put forth by

other students.b. Are abandoned when I hear the ideas and arguments put forth by the teacher.

20. During white board discussions:a. There is a lot of repetition.b. Similarities and common items are quickly noted and attention then turns to

differences and deeper meanings.

1 2 3 4 5 (a>>b) (a>b) (a=b) (a<b) (a<<b)

21. The correctness of the ideas being discussed:

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a. Is decided by the teacher. b. Is decided by logical argument rooted in experimental evidence.

22. The pace is such that:a. I become bored. b. I cannot keep up.

23. Knowledge: a. is constructed through student dialogue.b. comes from the teacher.

24. During white board discussions:a. I listen to and consider alternative points of view given by others.b. I don’t pay much attention to what others say.

25. The teacher intervenes:a. With a brief question or comment that helps student discussion remain

focused and on track.b. By taking the lead when student discussion bogs down or hits a snag.

26. A common understanding of what is being discussed : a. is negotiated by student-to-student dialogue.b. is determined by the teacher.

27. When a white board session is finished:a. I understand what has been discussed.b. I am confused.

28. The difficult part of discussions is:a. Following the conversation.b. Reading the whiteboards.

29. The best part of discussions is: a. The summary of what was discussed at the end.b. Working together to figure things out.

30. I have answered the questions in this survey:a. To the best of my ability.b. Without thinking seriously about them.

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