Search

For the past several years, there has been an increase in the number of job opportunities in the computing field. As a result, many schools and universities are facing a significant increase in the number of students seeking to major in one of several computing disciplines. This increase in the numbers and variety of majors in the computing field poses challenges for higher education institutions in the areas of advising, retention, scheduling, and enrollment management. This paper builds upon prior research documenting the association of personality type and affinity for a computing career, and proposes using personality testing early in a student's university experience by including it as one factor in the advising process. This study employs the Myers-Briggs Type Indicator (MBTI) as a tool to help students select an appropriate computing major better suited for their given personality. This initial exploratory study shows that there is a significant difference in personalities among computing majors, specifically in the area of introversion versus extroversion, and intuition versus sensing. Testing students early, before starting a specific major, allows institutions to provide better advising to students as they choose their major, with the goal of increasing retention, degree satisfaction and completion of the degree.

All curricula for any given academic discipline evolves over time. This is also true for the Information Systems (IS) model curriculum. Curriculum evolution is driven by several factors, such as changes in technologies, industry shifts to meet customer needs, and perceived student deficiencies. One outcome of such factors has been a change in the entry point into the IS major due to the perception that IS majors need a different method of entry from other computing majors [e.g., Computer Science (CS)]. The current entry point for many IS majors is a programming course, often taken by a variety of majors. This paper addresses the question: is there a difference in performance in this initial programming course for students of different majors? More precisely, does major differentiate performance in the first programming course, such as CS1? The data clearly show this is not the case when there is a level playing field. The paper demonstrates that non-computing majors perform as well as computing majors given equal preparation. It is a misconception that changes to the IS curriculum are necessary when based on the belief that IS majors, as compared to other computing majors, need a different entry point. The data presented in this paper suggest the underlying presuppositions for IS curricular changes are misguided--supporting the need for preparation prior to a first programming course.

The most recent Information Systems (IS) Model Curriculum recommendations is IS2010. While the goal of this revision was to update the curriculum from IS2002, the end result was a change in curriculum design philosophy whereby a pre-requisite structure that fostered increasing depth of knowledge was flattened to make the curriculum easier to traverse for the student. At the same time, the number of core courses was reduced from ten to seven by either combining subject matter or eliminating content. This paper examines the usefulness of having perquisites to increase the student's "depth of knowledge" and explores how to analyze the need for those pre-requisites. The data show that five years after the release of IS2010, ABET accredited IS Programs in business schools seem to be embracing the underlying philosophy of IS2010. On the other hand, ABET accredited IS Programs outside business schools continue to embrace the curriculum design philosophy of IS2002. The IS community is now at a critical juncture due to these two differing curriculum design philosophies, both in terms of curriculum content and assessment methods.

General education is more than a list of required courses a student must take to complete their degree. For most universities, general education is the groundwork for the student's university experience. These courses span multiple disciplines and allow students to experience a wide range of topics on their path to graduation. Programming classes, e.g., Introduction to Programming, have not typically been an option as part of a general education course sequence at most universities. This study found that, only half of universities offer any kind of programming course in the General Education (GenEd) Program. The data also show that only two-thirds of institutions offer a computing class of any kind as a general education option. Institutions with ABET accredited Information Systems (IS) programs are significantly lower in both of these categories. This paper demonstrates the reasoning and process for including a programming class as an option in a GenEd Program, thereby showing how a programming class can be used to satisfy the requirements of a general education course. This results in two significant advantages to the computing department and university since the departments expand their reach to many more students, with a potential of increasing the number of majors or minors within the department; and non-computing majors have the opportunity to take courses that have not traditionally been offered in the GenEd Program. The latter results in students receiving a more comprehensive education and exposure to skills in high demand.

The Information System (IS) model curriculum has been advanced by the Association of Computing Machinery (ACM), the Association for Information Systems (AIS), and other associations since the 1970s. The IS2002 and IS2010 curriculum models have been positively received by both academic institutions and industry alike. Each of these models used design principles to help guide the development process; these principles included concepts such as maximizing program flexibility or course sequencing to improve depth of knowledge. The most current undergraduate model (IS2010) that guides university curriculum is nearly 10 years old. In today's IS field, a curriculum should address previous design concepts; plus the environment in which IS professionals work has become even more dynamic and multifaceted. Given these challenges, a new IS model curriculum would benefit by including more programming concepts along with course sequencing. The authors propose a two-course sequence in areas such as computer programming to increase depth of knowledge and keep some program flexibility. Further, the authors recommend: (1) require a minimum amount of programming, (2) require technical infrastructure coverage, (3) allow for specialization, (4) specify sequencing to provide depth, and (5) identify both core competencies and course structure. These recommendations are not a criticism but build a new model with the strengths and knowledge gained in the past 10 years.

Perceptual sensitivity varies from moment to moment. One potential source of this variability is spontaneous fluctuations in cortical activity that can travel as waves.sup.1. Spontaneous travelling waves have been reported during anaesthesia.sup.2-7, but it is not known whether they have a role during waking perception. Here, using newly developed analytic techniques to characterize the moment-to-moment dynamics of noisy multielectrode data, we identify spontaneous waves of activity in the extrastriate visual cortex of awake, behaving marmosets (Callithrix jacchus). In monkeys trained to detect faint visual targets, the timing and position of spontaneous travelling waves before target onset predicted the magnitude of target-evoked activity and the likelihood of target detection. By contrast, spatially disorganized fluctuations of neural activity were much less predictive. These results reveal an important role for spontaneous travelling waves in sensory processing through the modulation of neural and perceptual sensitivity. Timing and position of spontaneously arising waves of activity in the visual cortex predict the sensitivity of visual perception in awake, behaving marmosets (Callithrix jacchus)., Author(s): Zachary W. Davis [sup.1] , Lyle Muller [sup.1] [sup.2] [sup.3] [sup.4] , Julio Martinez-Trujillo [sup.3] [sup.5] [sup.6] , Terrence Sejnowski [sup.1] , John H. Reynolds [sup.1] Author Affiliations: (1) [...]

One of the great strengths of the mouse model is the wide array of genetic tools that have been developed. Striking examples include methods for directed modification of the genome, and for regulated expression or inactivation of genes. Within neuroscience, it is now routine to express reporter genes, neuronal activity indicators, and opsins in specific neuronal types in the mouse. However, there are considerable anatomical, physiological, cognitive, and behavioral differences between the mouse and the human that, in some areas of inquiry, limit the degree to which insights derived from the mouse can be applied to understanding human neurobiology. Several recent advances have now brought into reach the goal of applying these tools to understanding the primate brain. Here we describe these advances, consider their potential to advance our understanding of the human brain and brain disorders, discuss bioethical considerations, and describe what will be needed to move forward.

The Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative has focused scientific attention on the necessary tools to understand the human brain and mind. Here, we outline our collective vision for what we can achieve within a decade with properly targeted efforts and discuss likely technological deliverables and neuroscience progress.

Recent analyses have found waves of neural activity traveling across entire visual cortical areas in awake animals. These traveling waves modulate the excitability of local networks and perceptual sensitivity. The general computational role of these spatiotemporal patterns in the visual system, however, remains unclear. Here, we hypothesize that traveling waves endow the visual system with the capacity to predict complex and naturalistic inputs. We present a network model whose connections can be rapidly and efficiently trained to predict individual natural movies. After training, a few input frames from a movie trigger complex wave patterns that drive accurate predictions many frames into the future solely from the network's connections. When the recurrent connections that drive waves are randomly shuffled, both traveling waves and the ability to predict are eliminated. These results suggest traveling waves may play an essential computational role in the visual system by embedding continuous spatiotemporal structures over spatial maps. Waves of neural activity travel across single regions in the visual cortex, but their computational role is unclear. Here, the authors present a neural network model demonstrating that waves traveling over retinotopic maps can enable short-term predictions of future inputs. [ABSTRACT FROM AUTHOR]

Author(s): Jude F. Mitchell [1]; Gene R. Stoner [2]; John H. Reynolds (corresponding author) [1] A question of long-standing interest to philosophers, psychologists and neuroscientists is how the brain selects [...]