49,965 research outputs found
An Equitable Approach to Academic Progression Advising: To Use an Automated Tool or Not?
This Organizational Improvement Plan (OIP) is concerned with the problem of inequitable access to an automated degree audit tool at a large metropolitan university in central Canada, which is affecting year-to-year progression and timely graduation. Despite the implementation of this tool 17 years ago, it has not been fully adopted, leaving the campus community to navigate degree progression inconsistently and in isolation, with nearly half the students underserved; of particular concern are first-generation students. Stakeholder theory underpins the organizational change management plan, which espouses authentic, transformational, and shared leadership approaches. Following internal and external analyses, it was determined that the institution has the capacity and readiness for change. Using an interpretive paradigm to consider multiple perspectives, four possible solutions are considered. After assessing time, finances, human resources, and impact, the preferred solution is to implement an incremental working group. An inclusive and comprehensive change model and an iterative review cycle comprising immediate and ongoing monitoring and evaluation is proposed for effective implementation. As well, strategic communication for equitable access to information sharing needed for degree progression will enhance the overall student experience and improve administrative efficiencies. The execution of a five-stage change plan will see all academic advisors using the automated degree audit tool by 2025. Successful implementation of this OIP will allow for exploration of other initiatives to improve the student experience using technology and a social justice lens in leadership
Using Counts as Heuristics for the Analysis of Static Models
The upstream activities of software development are often viewed as both the most
important, in terms of cost, and the yet the least understood, and most problematic, particularly in terms of satisfying customer requirements. Business process modelling is
one solution that is being increasingly used in conjunction with traditional software
development, often feeding in to requirements and analysis activities. In addition,
research in Systems Engineering for Business Process Change, highlights the importance
of modelling business processes in evolving and maintaining the legacy systems that
support those processes. However, the major use of business process modelling, is to
attempt to restructure the business process, in order to improve some given aspect, e.g.,
cost or time. This restructuring may be seen either as separate activity or as a pre-cursor
to the development of systems to support the new or improved process. Hence, the
analysis of these business models is vital to the improvement of the process, and as a
consequence to the development of supporting software systems. Supporting this analysis
is the focus of this paper.
Business processes are typically described with static (diagrammatic) models. This paper
proposes the use of measures (counts) to aid analysis and comparison of these static
process descriptions. The proposition is illustrated by showing how measures can be
applied to a commonly used process-modelling notation, Role Activity Diagrams (RADs).
Heuristics for RADs are described and measures suggested which support those
heuristics. An example process is used to show how a coupling measure can be used to
highlight features in RADs useful to the process modeller.
To fully illustrate the proposition the paper describes and applies a framework for the
theoretical validation of the coupling measure. An empirical evaluation follows. This is
illustrated by two case studies; the first based on the bidding process of a large
telecommunications systems supplier, and the second a study of ten prototyping processes
across a number of organisations.
These studies found that roles of the same type exhibited similar levels of coupling across
processes. Where roles did not adhere to tentative threshold values, further investigation
revealed unusual circumstances or hidden behaviour. Notably, study of the prototyping
roles, which exhibited the greatest variation in coupling, found that coupling was highly
correlated with the size of the development team. This suggests that prototyping in large
projects had a different process to that for small projects, using more mechanisms for
communication. Hence, the empirical studies support the view that counts (measures)
may be useful in the analysis of static process models
Can Who-Edits-What Predict Edit Survival?
As the number of contributors to online peer-production systems grows, it
becomes increasingly important to predict whether the edits that users make
will eventually be beneficial to the project. Existing solutions either rely on
a user reputation system or consist of a highly specialized predictor that is
tailored to a specific peer-production system. In this work, we explore a
different point in the solution space that goes beyond user reputation but does
not involve any content-based feature of the edits. We view each edit as a game
between the editor and the component of the project. We posit that the
probability that an edit is accepted is a function of the editor's skill, of
the difficulty of editing the component and of a user-component interaction
term. Our model is broadly applicable, as it only requires observing data about
who makes an edit, what the edit affects and whether the edit survives or not.
We apply our model on Wikipedia and the Linux kernel, two examples of
large-scale peer-production systems, and we seek to understand whether it can
effectively predict edit survival: in both cases, we provide a positive answer.
Our approach significantly outperforms those based solely on user reputation
and bridges the gap with specialized predictors that use content-based
features. It is simple to implement, computationally inexpensive, and in
addition it enables us to discover interesting structure in the data.Comment: Accepted at KDD 201
MITK-ModelFit: A generic open-source framework for model fits and their exploration in medical imaging -- design, implementation and application on the example of DCE-MRI
Many medical imaging techniques utilize fitting approaches for quantitative
parameter estimation and analysis. Common examples are pharmacokinetic modeling
in DCE MRI/CT, ADC calculations and IVIM modeling in diffusion-weighted MRI and
Z-spectra analysis in chemical exchange saturation transfer MRI. Most available
software tools are limited to a special purpose and do not allow for own
developments and extensions. Furthermore, they are mostly designed as
stand-alone solutions using external frameworks and thus cannot be easily
incorporated natively in the analysis workflow. We present a framework for
medical image fitting tasks that is included in MITK, following a rigorous
open-source, well-integrated and operating system independent policy. Software
engineering-wise, the local models, the fitting infrastructure and the results
representation are abstracted and thus can be easily adapted to any model
fitting task on image data, independent of image modality or model. Several
ready-to-use libraries for model fitting and use-cases, including fit
evaluation and visualization, were implemented. Their embedding into MITK
allows for easy data loading, pre- and post-processing and thus a natural
inclusion of model fitting into an overarching workflow. As an example, we
present a comprehensive set of plug-ins for the analysis of DCE MRI data, which
we validated on existing and novel digital phantoms, yielding competitive
deviations between fit and ground truth. Providing a very flexible environment,
our software mainly addresses developers of medical imaging software that
includes model fitting algorithms and tools. Additionally, the framework is of
high interest to users in the domain of perfusion MRI, as it offers
feature-rich, freely available, validated tools to perform pharmacokinetic
analysis on DCE MRI data, with both interactive and automatized batch
processing workflows.Comment: 31 pages, 11 figures URL: http://mitk.org/wiki/MITK-ModelFi
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