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Student misconceptions in science are common and may be present even for students who are academically successful. Concept inventories, multiple-choice tests in which the distractors map onto common, previously identified misconceptions, are commonly used by researchers and educators to gauge the prevalence of student misconceptions in science. Distractor analysis of concept inventory responses could be used to create profiles of individual student misconceptions which could provide deeper insight into the phenomenon and provide useful information for instructional planning, but this is rarely done as the inventories are not designed to facilitate it. Researchers in educational measurement have suggested that diagnostic cognitive models (DCMs) could be used to diagnose misconceptions and to create such misconception profiles. DCMs are multidimensional, confirmatory latent class models which are designed to measure the mastery/presence of fine-grained skills/attributes. By replacing the skills/attributes in the model with common misconceptions, DCMs could be used to filter students into misconception profiles based on their responses to concept inventory-like questions. A few researchers have developed new DCMs that are specifically designed to do this and have retrofitted data from existing concept inventories to them. However, cognitive diagnostic assessments, which are likely to display better model fit with DCMs, have not been developed. This project developed a cognitive diagnostic assessment to measure knowledge and misconceptions about Newton's laws and fitted it with the deterministic input noisy-and-gate (DINA) model. Experienced physics instructors assessed content validity and Q-matrix alignment. A pilot test with 100 undergraduates was conducted to assess item quality within a classical test theory framework. The final version of the assessment was field tested with 349 undergraduates. Results showed that response data displayed acceptable fit to the DINA model at the item level, but more questionable fit at the overall model level; that responses to selected items were similar to those given to two items from the Force Concept Inventory; and that, although all students were likely to have misconceptions, those with lower knowledge scores were more likely to have misconceptions. / Doctor of Philosophy / Misconceptions about science are common even among well-educated adults. Misconceptions range from incorrect facts to personal explanations for natural phenomena that make intuitive sense but are incorrect. Frequently, they exist in people's minds alongside correct science knowledge. Because of this, misconceptions are often difficult to identify and to change. Students may be academically successful and still retain their misconceptions. Concept inventories, multiple-choice tests in which the incorrect answer choices appeal to students with common misconceptions, are frequently used by researchers and educators to gauge the prevalence of student misconceptions in science. Analysis of incorrect answer choices to concept inventory questions can be used to determine individual student's misconceptions, but it is rarely done because the inventories are not known to be valid measures for this purpose. One source of validity for tests is the statistical model that is used to calculate test scores. In valid tests, student's answers to the questions should follow similar patterns to those predicted by the model. For instance, students are likely to get questions about the same things either all correct or all incorrect. Researchers in educational measurement have proposed that certain types of innovative statistical models could be used to develop tests that identify student's misconceptions, but no one has done so. This project developed a test to measure knowledge and misconceptions about forces and assessed how well it predicted student's misconceptions compared to two statistical models. Results showed that the test predicted student's knowledge in good agreement and misconceptions in moderate agreement with the statistical models; that students tended to answer selected questions in the same way that they answered two similar questions from an existing test about forces; and that, although students with lower test scores were more likely to have misconceptions, students with high test scores also had misconceptions.

Doctor of Philosophy / Department of Physics / Nobel S. Rebello / Conventional wisdom has long advised that students’ learning is best supported by interaction with physical manipulative. Thus, in the physics laboratory, students typically spend their time conducting experiments with physical equipment. However, computer simulations offer a tempting alternative to traditional physical experiments. In a virtual experiment, using a computer simulation, students can gather data quickly, and measurement errors and frictional effects can be explicitly controlled. This research investigates the relative support for students’ learning offered by physical and virtual experimentation in the context of simple machines. Specifically, I have investigated students’ learning as supported by experimentation with physical and virtual manipulative from three different angles-- what do students learn, how do students learn, and what do students think about their learning. The results indicate that the virtual manipulative better supported students’ understanding of work and potential energy than the physical manipulative did. Specifically, in responding to data analysis questions, students who used the virtual manipulative before the physical manipulative were more likely to describe work as constant across different lengths of frictionless inclined planes (or pulley systems) and were more likely to adequately compare work and potential energy, whereas students who used the physical manipulative first were more likely to talk about work and potential energy separately. On the other hand, no strong support was found to indicate that the physical manipulative better supported students’ understanding of a specific concept. In addition, students’ responses to the survey questions indicate that students tend to value data from a computer simulation more than from a physical experiment. The interview analysis indicates that the virtual environment better supported the students to create new ideas than the physical environment did. These results suggest that the traditional wisdom that students learn best from physical experiments is not necessarily true. Thus, researchers should continue to investigate how to best interweave students’ experiences with physical and virtual manipulatives. In addition, it may be useful for curriculum designers and instructors to spend more of their efforts designing learning experiences that make use of virtual manipulatives.

Doctor of Philosophy / Department of Physics / N. Sanjay Rebello / Research has demonstrated that attentional cues overlaid on diagrams and animations can help students attend to the relevant areas and facilitate problem solving. In this study we investigate the influence of visual cues and outcome feedback on students’ problem solving, performance, reasoning, and visual attention as they solve conceptual physics problems containing a diagram. The participants (N=90) were enrolled in an algebra-based physics course and were individually interviewed. During each interview students solved four problem sets while their eye movements were recorded. The problem diagrams contained regions that were relevant to solving the problem correctly and separate regions related to common incorrect responses. Each problem set contained an initial problem, six isomorphic training problems, and a transfer problem. Those in the cued condition saw visual cues overlaid on the training problems. Those in the feedback conditions were told if their responses (answer and explanation) were correct or incorrect. Students’ verbal responses were used to determine their accuracy. The study produced two major findings. First, short duration visual cues coupled with correctness feedback can improve problem solving performance on a variety of insight physics problems, including transfer problems not sharing the surface features of the training problems, but instead sharing the underlying solution path. Thus, visual cues can facilitate re-representing a problem and overcoming impasse, enabling a correct solution. Importantly, these cueing effects on problem solving did not involve the solvers’ attention necessarily embodying the solution to the problem. Instead, the cueing effects were caused by solvers attending to and integrating relevant information in the problems into a solution path. Second, these short duration visual cues when administered repeatedly over multiple training problems resulted in participants becoming more efficient at extracting the relevant information on the transfer problem, showing that such cues can improve the automaticity with which solvers extract relevant information from a problem. Both of these results converge on the conclusion that lower-order visual processes driven by attentional cues can influence higher-order cognitive processes associated with problem solving.

This licentiate thesis describes an investigation of participation and achievement in undergraduate physics courses with a discourse analytical lens. Issues of unequal participation have been a growing concern for the physics education research community. At the same time, these issues have not been explored to any large extent using already developed theoretical tools from fields of social science and humanities. This thesis builds on earlier studies in physics education research but crosses disciplinary boundaries to bring in perspectives from gender studies. The two papers use a discourse theoretical framework to explore what it might mean to participate in physics, whether that is one’s primary subject or not, in courses in electromagnetism and quantum physics. A general conclusion that can be drawn from these empirical studies is that physics courses may often be taught from a narrow physics perspective, and that this may limit the possibilities for identification for many students. For instance, engineering students whose main area was not physics failed to see much significance in studying electromagnetism and then just “studied to pass”. Additionally, students on physics programmes may find that the limited positions in quantum physics which can be characterized as mainly focused on “calculating”, are hard to reconcile with their interest in physics. Using a discourse perspective, I broaden this critique to a discussion of the culture of physics: What does it mean to become a physicist and what physics culture follows from different “productions” of physicists? These results inform continued research in physics education by raising issues of identity and providing critical frameworks for exploring them. They also point to the importance of including broad views of physics in courses. Critically examining participation in physics, this thesis aims at widening the discussion and provide new ways to talk about these issues in physics education research.

Doctor of Philosophy / Department of Physics / Dean A. Zollman / In this study we explored students' transfer of learning in the X-ray medical imaging context, including the X-ray-based computer-assisted tomography (or CAT). For this purpose we have conducted a series of clinical and teaching interviews. The investigation was a part of a bigger research effort to design teaching-learning materials for pre-medical students who are completing their algebra-based physics course. Our students brought to the discussion pieces of knowledge transferred from very different sources such as their own X-ray experiences, previous learning and the mass media. This transfer seems to result in more or less firm mental models, although often not internally consistent or coherent. Based on our research on pre-med students' models of X-rays we designed a hands-on lab using semi-transparent Lego bricks to model CAT scans. Without "surgery" (i.e. without intrusion into the Lego "body") students determined the shape of an object, which was built out of opaque and translucent Lego bricks and hidden from view. A source of light and a detector were provided upon request. Using a learning cycle format, we introduced CAT scans after students successfully have completed this task. By comparing students' ideas before and after teaching interview with the groups of 2 or 3 participants, we have investigated transfer of learning from basic physics and everyday experience to a complex medical technology and how their peer interactions trigger and facilitate this process. During the last phase of our research we also introduced a CAT-scan simulation problem into our teaching interview routine and compared students' perception of this simulation and their perception of the hands-on activity.