Browsing by Subject "Problem solving"

Now showing 1 - 7 of 7
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    The brain is for action: embodiment, causality, and conceptual learning with video games to improve reading comprehension and scientific problem solving.
    (2012-11) Dubbels, Brock Randall
    This experiment compares children's comprehension and problem solving with the same information presented in three different media formats: an embodied video game, a first-person video, and a print narrative. The embodied video game emphasizes interaction and causation, where the player moves the narrative forward by causing change through interaction. According to embodiment theorists, the ability to create knowledge is predicated upon the ability to identify and connect changes, and what causes change in events. Comprehension is measured in this study with the Event-Indexing Model, (EIM). Research on the EIM indicates that identification of causation is often highly correlated to identification of other elements of comprehension, including memory of time, space, objects, and intentions across events. This experiment examines whether media format, which emphasizes embodied interaction and identification of causation, improves comprehension and problem solving. In question 1, this experiment examines whether the embodied video game will lead to superior comprehension and problem solving outcomes compared to the same information presented in a video or a printed text. Question 2 compares comprehension and problem solving when the reading text condition follows playing the game and watching the video. The third question examines the role of causation, which is the ability to identify actions that create changes between narrative events in a text. This dissertation analyzes comprehension and problem outcomes across media: as an embodied video game, a video, or a printed text. Additionally, it examines reading performance across presentation order, and the importance of identification in situation model construction.
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    The effect of functional fixation in problem solving among preschool, second grade, and ninth grade children
    (2014-12) Nehring, Michael Kenneth
    Functional fixedness is a cognitive function whereby an individual becomes fixated on a given function of an object, which prevents the individual from using the object in an alternative fashion to solve a problem (Duncker, 1935/1945). The current study analyzed the effect of functional fixedness on 36 children from three different age groups, preschool, second grade, and ninth grade. The children were presented with a problem solving activity based on a problem used by German and Defeyter (2000), in which they concluded that young children are immune to the effects of functional fixedness. Research conducted by Chrysikou (2006) indicated using an alternative categorization task could reduce the effects of fixation. The current research sought to answer three research question: are children susceptible to the effects of functional fixedness; are there differences in the effect of functional fixedness based on age; and does participating in an alternative categorization task reduce the effect of functional fixedness. The results indicated that children are susceptible to the effects of functional fixedness, when the children use the target object in a typical preutilization function, regardless of age. The results also did not demonstrate a reduction in the effect of functional fixedness after participating in an alternative categorization task.
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    An Empirical Model of Physics Instructors' Beliefs about the Purpose, Actions, and Context of Doing Homework
    (2018-12) Straub, Miranda
    Over the past half century, researchers and curriculum developers studying physics education have created dozens of innovative curricula and educational tools, broadly referred to as research-based instructional strategies (RBIS), to fit almost any classroom situation. However, the rate of adoption of RBIS remains relatively low. A national survey of post-secondary physics instructors in 2012 showed that only half of physics instructors have ever implemented any RBIS in their classrooms, and many of them ceased to do so after implementation difficulties. Why aren’t these effective strategies being implemented at larger rates? Part of removing barriers to RBIS adoption may be understanding what instructors believe about how students learn. In order to answer a small portion of this question, I studied physics instructors’ beliefs about homework. This study is taken up in two parts. First, I analyzed 25 interviews with physics instructors from various types of institutions in Minnesota. The intent of the interviews was to elicit instructors’ beliefs about the role of problem solving in the student learning of introductory physics. I focused on portions of the interviews where instructors spoke about what students should do or learn while they are solving problems independent of instructor assistance (homework). Using analytical methods in line with grounded theory methodology, I performed cycles of vertical and horizontal analyses on these interviews to gain insight into actions, mindsets, contexts, and processes by which students learn physics through doing homework. Six themes regarding homework that emerged from this analysis were: 1) an obligated to do homework, 2) things students should do or not do while they do homework, 3) specific processes students should perform while doing homework, 4) things students should think about or understand while they do homework, 5) mindsets that students should have while doing homework, and 6) working in the context of a group or alone. The second part of the study was to use the themes from the interview analysis to create a survey, which was then sent to physics instructors in the state of Minnesota. I incorporated best practices of survey creation including question ordering, question posing, triangulation, and having both open-ended and fixed-choice responses. I estimate that between 37% and 64% of eligible postsecondary Minnesota physics instructors began the survey, with a completion rate of 88%. Using both the interview analysis and the survey responses, I created an empirical model of physics instructors’ beliefs about homework. There were four main results. First, there is agreement that the goals of doing homework are to learn problem solving and physics principles. Second, homework is seen as necessary for learning physics by a strong majority of instructors, but it is not seen as sufficient for learning. Third, there is a limited number of tasks or actions that instructors believe that students should do while they are solving problems to learn. Fourth, there is evidence that physics instructors fall onto a continuum of beliefs regarding how students should approach solving problems on their homework. On one end of this continuum, instructors believe students should follow an algorithmic process that includes the steps to solving any problem. On the other end of the continuum, instructors believe students should have a more open approach to solving problems where they consider all the tools and principles available to them in order to make decisions about how to solve a problem. These results can inform creators of curriculum and professional development experiences as they try to reach out and connect with instructors and perhaps change their beliefs and practice.
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    Internet computer coaches for introductory Physics problem solving
    (2013-12) Ryan, Qing
    The ability to solve problems in a variety of contexts is becoming increasingly important in our rapidly changing technological society. Problem-solving is a complex process that is important for everyday life and crucial for learning physics. Although there is a great deal of effort to improve student problem solving skills throughout the educational system, national studies have shown that the majority of students emerge from such courses having made little progress toward developing good problem-solving skills. The Physics Education Research Group at the University of Minnesota has been developing Internet computer coaches to help students become more expert-like problem solvers. During the Fall 2011 and Spring 2013 semesters, the coaches were introduced into large sections (200+ students) of the calculus based introductory mechanics course at the University of Minnesota. This dissertation, will address the research background of the project, including the pedagogical design of the coaches and the assessment of problem solving. The methodological framework of conducting experiments will be explained. The data collected from the large-scale experimental studies will be discussed from the following aspects: the usage and usability of these coaches; the usefulness perceived by students; and the usefulness measured by final exam and problem solving rubric. It will also address the implications drawn from this study, including using this data to direct future coach design and difficulties in conducting authentic assessment of problem-solving.
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    The Knowledge Building Approach to Science Education: A Problem-Solving Perspective
    (2019-09) Groos, David
    Science education is reasonably constructed around a vision of authentic scientific practices. Yet, this vision of science is clearly a construct as seen when viewing its changes throughout the last 120 years, as well as viewing it through different theoretical perspectives. While there are diverse descriptions of science and its enactment, going back to Dewey and Peirce, the mission of science is commonly considered to be about the advancement of theory through inquiry where problems serve a central function. Beyond the challenge of constructing an understanding of scientific inquiry as theory development where the diversity in perspectives of scientists is seen as essential, there is the challenge of devising pedagogy and approaches that effectively promote this vision. There are a rich mix of approaches working at solving different parts of this complex problem. One such approach is called, "knowledge building" (Scardamalia and Bereiter, 2006). This approach seeks to scaffold classroom communities such that they develop and grow into a complex community where progressive science-theory improvement emerges. It is considered that these sorts of communities where innovation is the norm have relevance beyond the fields of science and STEM: innovation and knowledge creation is becoming the essential practice of the knowledge age. The knowledge building approach is designed to support the growth of classroom communities that embody the essential nature of progressive scientific inquiry. To effectively support this kind of classroom community development, the unique assets and needs presented by the ever-increasing diversity of thinking and knowing that are emergents of the students' cultures, developmental levels, neurological diversities and iv networks of communities. Overall, this research sought to support and augment classrooms as they strive to grow into classroom communities of scientific inquiry. The research occurred in two stages. It first used philosophical methods to generate a simple, high-level model of problem-solving made possible by Popper's World-3 conception. This conception is a keystone in some epistemologies developed to support approaches aimed at helping students grow in knowledge-innovation practices. The visual problem-solving model that was developed seeks to provide students and teachers with a very simple yet flexible model allowing them to describe, analyze and reflect on the state of their community's knowledge improvement and through this understanding adaptively and effectively respond. The second stage of research utilized hybrid philosophical-empirical methods to develop a framework that describes science in terms of its mission to progressively improve theory through the iterative solving of and subsequent unfolding of new knowledge-problems. These research methods involved an iterative process where promising theories are tested on their ability to describe students' actual online knowledge-building discourse in a satisfying way. In this iterative process, empirical classroom data informed and yet also constrain the theory generation which was informed by diverse theoretical perspectives. These theoretical perspectives included for example, ideas of scientific practices, theories of design such as design thinking and understandings of classroom diversity as represented in the Next Generation Science Standards (NGSS Lead States, 2013) which were intentionally founded upon theories of v culturally responsive pedagogy. The developed framework seeks to scaffold teachers as they design and enact lessons aimed at growing communities of diverse scientists. Taken together, the products of this research seek to provide conceptual structures to aid the students and teachers in classroom communities as they seek to grow into complex communities of scientists.
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    Representation and reasoning for complex spatio-temporal problems: from humans to software agents
    (2014-03) Wetzel, Christopher Baylor
    Success in the real world depends on the ability to reason about space and time. Consider the simple, everyday task of deciding whether to cross a road. If a car is coming, your decision will be based on how wide the road is, how fast you walk, how far away the car is and how fast it is moving. You might also consider structural features of the road; if the car has to turn a corner or go over a speed bump, the car will move slower for a short period of time. Determining whether it is safe to cross requires reasoning about the interaction of these variables.The field of artificial intelligence has developed representations for describing space (e.g., RCC) and time (e.g., interval calculus) but not for describing the interaction between the two. Unsurprisingly, billions of years of evolution have resulted in humans being quite good at it. How they do so is not completely understood. Detailed studies have focused on overly simple problems while studies of complex problems have lacked sufficient detail to build computer models. This thesis describes our investigation into solving problems with significant spatio-temporal components. We focused on the domain of tower defense puzzles, a class of complex spatio-temporal problems that requires the problem solver to use spatial actions (placing guard towers on a map) to maximize a temporal variable (tower active time). We had two objectives. First, using methods from experimental psychology and computational behavioral modeling, we wished to understand how, precisely, humans solved these problems. Humans, unlike computers, are known to be good at solving this type of problem. Our second goal was to construct a computer agent capable of solving this task as well as or better than the best humans.To investigate the relationship of space, time and problem solving, we performed two experiments. The goal of Experiment 1 was to determine how humans solved tower defense puzzles. Experienced tower defense solvers (n=38) were asked to solve a series of novel tower defense puzzles. Interviews and automated data capture tools provided data that were used to answer a set of questions on how humans solved these puzzles. The results showed a tight integration between problem, representation and reasoning. Subjects needed to manipulate space to maximize a temporal value. Rather than represent the space, they represented the goal-relevant opportunities for actions present in the space, known as affordances. Problems were decomposed into sets of goals, each goal was addressed by one or more simple, focused, goal-specific strategies and each strategy was activated by an affordance. An interesting finding was that many subjects treated temporal problems as if they were spatial ones, which we refer to as spatial proxying.The goal of Experiment 2 was to determine how well the discovered strategies worked. Novice (n=10) and experienced (n=10) tower defense solvers were asked to solve a series of novel tower defense puzzles. Results showed that 70% of novice and 40% of experienced subjects used spatial proxying strategies and that these strategies worked surprisingly well. 10% of novice and 60% of experienced subjects used strategies that directly manipulated time. These strategies performed better but frequently created solutions that were counter-intuitive. Our second objective was to investigate computational representations and algorithms capable of creating an agent that performs at or above human levels for this task. Human studies showed that the majority of the "intelligence" of their problem solving process lay in the recognition and representation of spatial affordances. This led to the creation of the Spatial Affordance Query System (SAQS). In this system, spatio-temporal reasoning agents are created declaratively, with the author specifying the strategies the agent knows. The agent and problem map are passed to a solver, which compares the agent's strategy set to the affordances reported by SAQS, which instantiates the applicable strategies. The majority of agents were 5-12 lines of code and the best agent performed at the same level as the best human subjects.
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    Troubleshooting Fundamentals: A Beginner's Guide
    (Information Today, Inc., 2018-07) Carter, Sunshine J; Traill, Stacie
    Libraries have been troubleshooting unexpected problems affecting access to content for as long as libraries have provided online content. Library systems and access models have matured as the volume of content delivered via those systems has grown. Thus, finding and fixing the causes of electronic resource access problems has become a complex, time-consuming, and often specialized task.This article describes three fundamental areas -- content, authentication models, and library systems -- with which a new troubleshooter should acquaint themselves in order to become an effective solver of e-resource access problems.