152,089 research outputs found
An investigation into the validation of formalised cognitive dimensions
The cognitive dimensions framework is a conceptual framework
aimed at characterising features of interactive systems that are strongly influential upon their effective use. As such the framework facilitates the critical assessment and design of a wide variety of information artifacts. Although the framework has proved to be of considerable interest to researchers and practitioners, there has been little research examining how easily the dimensions used by it can be consistently applied. The work reported in this paper addresses this
problem by examining an approach to the systematic application of dimensions and assessing its success empirically. The findings demonstrate a relatively successful approach to validating the systematic application of some concepts found in the cognitive dimensions framework.</p
Design as conversation with digital materials
This paper explores Donald Schön's concept of design as a conversation with materials, in the context of designing digital systems. It proposes material utterance as a central event in designing. A material utterance is a situated communication act that depends on the particularities of speaker, audience, material and genre.
The paper argues that, if digital designing differs from other forms of designing, then accounts for such differences must be sought by understanding the material properties of digital systems and the genres of practice that surround their use. Perspectives from human-computer interaction (HCI) and the psychology of programming are used to examine how such an understanding might be constructed.</p
The Grammar of Interactive Explanatory Model Analysis
The growing need for in-depth analysis of predictive models leads to a series
of new methods for explaining their local and global properties. Which of these
methods is the best? It turns out that this is an ill-posed question. One
cannot sufficiently explain a black-box machine learning model using a single
method that gives only one perspective. Isolated explanations are prone to
misunderstanding, which inevitably leads to wrong or simplistic reasoning. This
problem is known as the Rashomon effect and refers to diverse, even
contradictory interpretations of the same phenomenon. Surprisingly, the
majority of methods developed for explainable machine learning focus on a
single aspect of the model behavior. In contrast, we showcase the problem of
explainability as an interactive and sequential analysis of a model. This paper
presents how different Explanatory Model Analysis (EMA) methods complement each
other and why it is essential to juxtapose them together. The introduced
process of Interactive EMA (IEMA) derives from the algorithmic side of
explainable machine learning and aims to embrace ideas developed in cognitive
sciences. We formalize the grammar of IEMA to describe potential human-model
dialogues. IEMA is implemented in the human-centered framework that adopts
interactivity, customizability and automation as its main traits. Combined,
these methods enhance the responsible approach to predictive modeling.Comment: 17 pages, 10 figures, 3 table
A review of data visualization: opportunities in manufacturing sequence management.
Data visualization now benefits from developments in technologies that offer innovative ways of presenting complex data. Potentially these have widespread application in communicating the complex information domains typical of manufacturing sequence management environments for global enterprises. In this paper the authors review the visualization functionalities, techniques and applications reported in literature, map these to manufacturing sequence information presentation requirements and identify the opportunities available and likely development paths. Current leading-edge practice in dynamic updating and communication with suppliers is not being exploited in manufacturing sequence management; it could provide significant benefits to manufacturing business. In the context of global manufacturing operations and broad-based user communities with differing needs served by common data sets, tool functionality is generally ahead of user application
How can exploratory learning with games and simulations within the curriculum be most effectively evaluated?
There have been few attempts to introduce frameworks that can help support tutors evaluate educational games and simulations that can be most effective in their particular learning context and subject area. The lack of a dedicated framework has produced a significant impediment for uptake of games and simulations particularly in formal learning contexts. This paper aims to address this shortcoming by introducing a four-dimensional framework for helping tutors to evaluate the potential of using games- and simulation- based learning in their practice, and to support more critical approaches to this form of games and simulations. The four-dimensional framework is applied to two examples from practice to test its efficacy and structure critical reflection upon practice
Bored with point and click?
Computers have the potential to be exploited as one of the most exciting examples of instructional media. Yet designers often fail to realize this potential. This is, in part, due to the limitations of hardware and software and, in part, due to the lack of good theory developed through conclusive research. Good examples of computer-based learning may owe more to the imaginative flair of the courseware designer than they do to the application of explicit design guidelines and good learning theory. This paper will therefore consider a variety of issues that may be blocking theoretical development and draw conclusions for future courses of action. This starts with a statement of the problem, first by considering the macro and micro issues, and then by looking at a recent call for help in ComputerBased Learning Environment (CBLE) design. Next, the contribution of instructional design theories will be presented together with a way forward for investigating the issues. Finally the implications for future progress are presented
Analyzing eye movement patterns to improve map design
Recently, the use of eye tracking systems has been introduced in the field of cartography and GIS to support the evaluation of the quality of maps towards the user. The quantitative eye movement metrics are related to for example the duration or the number of the fixations which are subsequently (statistically) compared to detect significant differences in map designs or between different user groups. Hence, besides these standard eye movement metrics, other - more spatial - measurements and visual interpretations of the data are more suitable to investigate how users process, store and retrieve information from a (dynamic and/or) interactive map. This information is crucial to get insights in how users construct their cognitive map: e.g. is there a general search pattern on a map and which elements influence this search pattern, how do users orient a map, what is the influence of for example a pan operation. These insights are in turn crucial to be able to construct more effective maps towards the user, since the visualisation of the information on the map can be keyed to the user his cognitive processes. The study focuses on a qualitative and visual approach of the eye movement data resulting from a user study in which 14 participants were tested while working on 20 different dynamic and interactive demo-maps. Since maps are essentially spatial objects, the analysis of these eye movement data is directed towards the locations of the fixations, the visual representation of the scanpaths, clustering and aggregation of the scanpaths. The results from this study show interesting patterns in the search strategies of users on dynamic and interactive maps
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