Development of the Heat and Energy Concept Inventory: Preliminary Results on the Prevalence and Persistence of Engineering Students' Misconceptions

BACKGROUND Students frequently hold a number of misconceptions related to temperature, heat and energy. There is not currently a concept inventory with sufficiently high internal reliability to assess these concept areas for research purposes. Consequently, there is little data on the prevalence of these misconceptions amongst undergraduate engineering students. PURPOSE (HYPOTHESIS) This work presents the Heat and Energy Concept Inventory (HECI) to assess prevalent misconceptions related to: (1) Temperature vs. Energy, (2) Temperature vs. Perceptions of Hot and Cold, (3) Factors that affect the Rate vs. Amount of Heat Transfer and (4) Thermal Radiation. The HECI is also used to document the prevalence of misconceptions amongst undergraduate engineering students. DESIGN/METHOD Item analysis, guided by classical test theory, was used to refine individual questions on the HECI. The HECI was used in a one group, pre-test-post-test design to assess the prevalence and persistence of targeted misconceptions amongst a population of undergraduate engineering students at diverse institutions. RESULTS Internal consistency reliability was assessed using Kuder-Richardson Formula 20; values were 0.85 for the entire instrument and ranged from 0.59 to 0.76 for the four subcategories of the HECI. Student performance on the HECI went from 49.2% to 54.5% after instruction. Gains on each of the individual subscales of the HECI, while generally statistically significant, were similarly modest. CONCLUSIONS The HECI provides sufficiently high estimates of internal consistency reliability to be used as a research tool to assess students' understanding of the targeted concepts. Use of the instrument demonstrates that student misconceptions are both prevalent and resistant to change through standard instruction.

Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 2: modelling and optimization

This is the second part of a study investigating a model-based transient calibration process for diesel engines. The first part addressed the data requirements and data processing required for empirical transient emission and torque models. The current work focuses on modelling and optimization. The unexpected result of this investigation is that when trained on transient data, simple regression models perform better than more powerful methods such as neural networks or localized regression. This result has been attributed to extrapolation over data that have estimated rather than measured transient air-handling parameters. The challenges of detecting and preventing extrapolation using statistical methods that work well with steady-state data have been explained. The concept of constraining the distribution of statistical leverage relative to the distribution of the starting solution to prevent extrapolation during the optimization process has been proposed and demonstrated. Separate from the issue of extrapolation is preventing the search from being quasi-static. Second-order linear dynamic constraint models have been proposed to prevent the search from returning solutions that are feasible if each point were run at steady state, but which are unrealistic in a transient sense. Dynamic constraint models translate commanded parameters to actually achieved parameters that then feed into the transient emission and torque models. Combined model inaccuracies have been used to adjust the optimized solutions. To frame the optimization problem within reasonable dimensionality, the coefficients of commanded surfaces that approximate engine tables are adjusted during search iterations, each of which involves simulating the entire transient cycle. The resulting strategy, different from the corresponding manual calibration strategy and resulting in lower emissions and efficiency, is intended to improve rather than replace the manual calibration process.

Effect of Classroom Gender Composition on Students' Development of Self-Regulated Learning Competencies

Success in any field depends on a complex interplay among environmental and personal factors. A key set of personal factors for success in academic settings are those associated with self-regulated learners (SRL). Self-regulated learners choose their own goals, select and organize their learning strategies, and self-monitor their effectiveness. Behaviors and attitudes consistent with self-regulated learning also contribute to self-confidence, which may be important for members of underrepresented groups such as women in engineering. This exploratory study, drawing on the concept of "critical mass", examines the relationship between the personal factors that identify a self-regulated learner and the environmental factors related to gender composition of engineering classrooms. Results indicate that a relatively student gender-balanced classroom and gender match between students and their instructors provide for the development of many adaptive SRL behaviors and attitudes.

Representations of the Human/ Nonhuman Primate Divide: the Influence of Science, Fiction, and Science-Fiction on the Concept of 'Being Human'

For as far back as human history can be traced, mankind has questioned what it means to be human. One of the most common approaches throughout Western culture's intellectual tradition in attempts to answering this question has been to compare humans with or against other animals. I argue that it was not until Charles Darwin's publication of The Descent of Man and Selection in Relation to Sex (1871) that Western culture was forced to seriously consider human identity in relation to the human/ nonhuman primate line. Since no thinker prior to Charles Darwin had caused such an identity crisis in Western thought, this interdisciplinary analysis of the history of how the human/ nonhuman primate line has been understood focuses on the reciprocal relationship of popular culture and scientific representations from 1871 to the Human Genome Consortium in 2000. Focusing on the concept coined as the "Darwin-Müller debate," representations of the human/ nonhuman primate line are traced through themes of language, intelligence, and claims of variation throughout the popular texts: Descent of Man, The Jungle Books (1894), Tarzan of the Apes (1914), and Planet of the Apes (1963). Additional themes such as the nature versus nurture debate and other comparative phenotypic attributes commonly used for comparison between man and apes are also analyzed. Such popular culture representations are compared with related or influential scientific research during the respective time period of each text to shed light on the reciprocal nature of Western intellectual tradition, popular notions of the human/ nonhuman primate line, and the development of the field of primatology. Ultimately this thesis shows that the Darwin-Müller debate is indeterminable, and such a lack of resolution makes man uncomfortable. Man's unsettled response and desire for self-knowledge further facilitates a continued search for answers to human identity. As the Human Genome Project has led to the rise of new debates, and primate research has become less anthropocentric over time, the mysteries of man's future have become more concerning than the questions of our past. The human/ nonhuman primate line is reduced to a 1% difference, and new debates have begun to overshadow the Darwin-Müller debate. In conclusion, I argue that human identity is best represented through the metaphor of evolution: both have an unknown beginning, both have an indeterminable future with no definite end, and like a species under the influence of evolution, what it means to be human is a constant, indeterminable process of change.