2 resultados para introductory programming, learning to program, programming pedagogy, collaborative learning, pair-programming

em DigitalCommons@University of Nebraska - Lincoln


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In this dissertation, I use qualitative research methods to study relationships between compositionists and faculty in other disciplines in the context of cross-curricular literacy (CCL) work. Drawing on a two-year CCL project in the biology department, for which I was a participant observer, I argue that compositionists need to attend more carefully to issues that influence day-to-day interactions with disciplinary faculty in order to develop more meaningful CCL relationships. Toward that end, I offer a revisionary approach to cross-curricular literacy work that cultivates complex relationships by delaying consensus and embracing disconnection and disorientation. More specifically, I employ revisionary stance as a discursive strategy to complicate three key concepts in CCL literature and scholarship—expertise, change, and outcomes. I re-vision three texts produced during my time in the biology department in order to illuminate the complexities of negotiating expertise, recognizing change, and pursuing outcomes in CCL contexts. Given the reciprocal relationship between discursive and material change (Lee), I maintain that revision of CCL discourse can inspire revision on a pedagogical level, shaping how compositionists and disciplinary faculty participate in CCL interactions. Thus, a revisionary approach leads me to conceptualize revisionary pedagogy for cross-curricular literacy work. I theorize revisionary pedagogy as a means of fostering pedagogical relationships in CCL contexts, complicating how relationships are framed in traditional Writing Across the Curriculum/Writing in the Disciplines scholarship. The literature advances three main conceptual models of CCL, each of which embraces expertise, change, and outcomes in ways that sponsor potentially problematic relationships between compositionists and disciplinary faculty. I draw on Composition scholars’ rich conceptualization of revision (Jung; Lee; Welch) and pedagogy (Kameen; Qualley; Stenberg) to challenge the litany of next-best models and imagine alternative possibilities for relationships in CCL contexts. Revisionary pedagogy is a means of approaching material circumstances that reconstitutes how compositionists and disciplinary faculty conceive of and participate in CCL relationships.

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Maximum-likelihood decoding is often the optimal decoding rule one can use, but it is very costly to implement in a general setting. Much effort has therefore been dedicated to find efficient decoding algorithms that either achieve or approximate the error-correcting performance of the maximum-likelihood decoder. This dissertation examines two approaches to this problem. In 2003 Feldman and his collaborators defined the linear programming decoder, which operates by solving a linear programming relaxation of the maximum-likelihood decoding problem. As with many modern decoding algorithms, is possible for the linear programming decoder to output vectors that do not correspond to codewords; such vectors are known as pseudocodewords. In this work, we completely classify the set of linear programming pseudocodewords for the family of cycle codes. For the case of the binary symmetric channel, another approximation of maximum-likelihood decoding was introduced by Omura in 1972. This decoder employs an iterative algorithm whose behavior closely mimics that of the simplex algorithm. We generalize Omura's decoder to operate on any binary-input memoryless channel, thus obtaining a soft-decision decoding algorithm. Further, we prove that the probability of the generalized algorithm returning the maximum-likelihood codeword approaches 1 as the number of iterations goes to infinity.