Negotiating White science in rural Black America: A case for navigating the landscape of teacher knowledge domains

The purpose of this study was to explore the nature of requisite teacher knowledge for teaching lower-track science students. Using video accounts, student focus groups, and teacher reflections researchers documented missteps, dead-ends, and unfruitful trajectories informed by the teacher’s incoming knowledge and compared these instances to necessary modifications informed by students’ voices and cultural artifacts. Our study revealed the shifting nature of sociocultural and pedagogical content knowledge of the teacher immersed in a context unlike that he experienced as a student. Results showed that teachers of majority backgrounds could learn to teach diverse students with at least moderate success from the perspective of their students. Implications for research and teacher education in diverse settings are discussed.     

Choice of Academic Major at a Public Research University: The Role of Gender and Self-Efficacy

Females are underrepresented in certain disciplines, which translates into their having less promising career outlooks and lower earnings. This study examines the effects of socio-economic status, academic performance, high school curriculum and involvement in extra-curricular activities, as well as self-efficacy for academic achievement on choices of academic disciplines by males and females. Disciplines are classified based on Holland’s theory of personality-based career development. Different models for categorical outcome variables are compared including: multinomial logit, nested logit, and mixed logit. Based on the findings presented here, first generation status leads to a greater likelihood of choosing engineering careers for males but not for females. Financial difficulties have a greater effect on selecting scientific fields than engineering fields by females. The opposite is true for males. Passing grades in calculus, quantitative test scores, and years of mathematics in high school as well as self-ratings of abilities to analyze quantitative problems and to use computing are positively associated with choice of engineering fields.     

Characteristics of SAT Quantitative Items Showing Improvement After Coaching Among Black Students From Low-Income Families: An Exploratory Study

The present exploratory investigation is an extension of a 1985 study that evaluated a Scholastic Aptitude Test preparation program involving black urban students. The present study was conducted to determine if there are identifiable characteristics of quantitative items associated with a susceptibility to coaching. Items showing p-value improvements of. 10 after coaching were compared with items not showing such improvements; comparisons were made in terms of the content, type. format, level of cognitive requirement, and position of the items. Items showing improvement were found across content areas, formats, and type. Findings are discussed in relation to the usefulness and improvement of well-designed supplemental instructional programs that have the potential to affect criterion performance in mathematics     

Relations between intelligence and the development of metaconceptual knowledge

Across two studies, we developed and tested a declarative metacognitive interview to investigate the effects of developmental level and verbal intelligence on children's metaconceptual understanding of processes related to concept use and object categorization. Metaconceptual knowledge developed throughout elementary school, with near ceiling scores for adults. IQ scores correlated positively with metaconceptual interview scores for all groups of children. Study 2 confirmed a relationship between scores on the metaconceptual interview and performance on a Twenty Questions task for which strategic performance was presumed to depend on such knowledge, though metaconceptual knowledge was most important when IQ was lower. Implications for theory development and hypotheses about how metaconceptual knowledge develops are discussed.     

Exploratory Analysis to Identify Concepts,Skills, Knowledge,and Tools to Educate Business Analytics Practitioners

Recent technological advancements in data storage and processing have changed how companies conduct their business. An increasing number of firms have started putting their efforts in extracting information from their databases to improve profitability and reduce costs using quantitative approaches. Thus, the job market has been experiencing a rapidly growing demand for business analytics (BA) practitioners, and universities across the globe are increasingly responding to this newly emerged field by offering both undergraduate and graduate level degrees as well as certificate programs. Thus, this research aims to provide a framework for academic institutions to develop a state‐of‐the‐art master's in business analytics (MSBA) curriculum by identifying concepts, skills, knowledge, and tools (CSKT) that industry seeks in BA practitioners. Our data‐driven methodology utilizes peer institution analysis, indeed.com web scraping, and focus group analysis with mid‐ and senior‐level analytics leaders from major companies. Our contribution to the literature and recommendations to institutions developing MSBA programs are offered at the end.     

Computer systems: Moral entities but not moral agents

After discussing the distinction between artifacts and natural entities, and the distinction between artifacts and technology, the conditions of the traditional account of moral agency are identified. While computer system behavior meets four of the five conditions, it does not and cannot meet a key condition. Computer systems do not have mental states, and even if they could be construed as having mental states, they do not have intendings to act, which arise from an agent’s freedom. On the other hand, computer systems have intentionality, and because of this, they should not be dismissed from the realm of morality in the same way that natural objects are dismissed. Natural objects behave from necessity; computer systems and other artifacts behave from necessity after they are created and deployed, but, unlike natural objects, they are intentionally created and deployed. Failure to recognize the intentionality of computer systems and their connection to human intentionality and action hides the moral character of computer systems. Computer systems are components in human moral action. When humans act with artifacts, their actions are constituted by the intentionality and efficacy of the artifact which, in turn, has been constituted by the intentionality and efficacy of the artifact designer. All three components – artifact designer, artifact, and artifact user – are at work when there is an action and all three should be the focus of moral evaluation.