2,513 research outputs found
The Effects of Decomposition Quality and Multiple Forms of Information on Novices’ Understanding of a Domain from a Conceptual Model
Individuals can often use conceptual models to learn about the business domain to be supported by an information system. We investigate the extent to which such models can help novices (i.e., individuals who lack knowledge in the business domain and in conceptual modeling) to obtain an understanding of the domain codified in the model. We focus on two factors that we predict will influence novices’ understanding: (1) decomposition quality: whether the conceptual model manifests a good decomposition of the domain, and (2) multiple forms of information: whether the conceptual model is accompanied by information in another form (e.g., a textual narrative). We hypothesize that both factors will have positive effects on understanding and that these effects depend on whether the individual seeks a surface or deep understanding. Our results are largely in line with our predictions. Moreover, our results suggest that while novices are generally aware that having multiple forms of information affects their understanding, they are unaware that decomposition quality affects their understanding. Based on these results, we recommend that practitioners include complementary forms of information (such as a textual narrative) along with conceptual models and be careful to ensure that their conceptual models manifest a good decomposition of the domain
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Understanding analogical reasoning : viewpoints from psychology and related disciplines
Analogy and metaphor have a long history of study in linguistics, education, philosophy and psychology. Consensus over what analogy is or how analogy functions in language and thought, however, has been elusive. This paper, the first in a two part series, examines these various research traditions, attempting to bring out major lines of agreement over the role of analogy in individual human experience. As well as being a general literature review which may be helpful for newcomers to the study of analogy, this paper attempts to extract from these literatures existing theories, models and concepts which may be interesting or useful for computational studies of analogical reasoning
Design: One, but in different forms
This overview paper defends an augmented cognitively oriented generic-design
hypothesis: there are both significant similarities between the design
activities implemented in different situations and crucial differences between
these and other cognitive activities; yet, characteristics of a design
situation (related to the design process, the designers, and the artefact)
introduce specificities in the corresponding cognitive activities and
structures that are used, and in the resulting designs. We thus augment the
classical generic-design hypothesis with that of different forms of designing.
We review the data available in the cognitive design research literature and
propose a series of candidates underlying such forms of design, outlining a
number of directions requiring further elaboration
Cognition Matters: Enduring Questions in Cognitive IS Research
We explore the history of cognitive research in information systems (IS) across three major research streams in which cognitive processes are of paramount importance: developing software, decision support, and human-computer interaction. Through our historical analysis, we identify “enduring questions” in each area. The enduring questions motivated long-standing areas of inquiry within a particular research stream. These questions, while perhaps unapparent to the authors cited, become evident when one adopts an historical perspective. While research in all three areas was influenced by changes in technologies, research techniques, and the contexts of use, these enduring questions remain fundamental to our understanding of how to develop, reason with, and interact with IS. In synthesizing common themes across the three streams, we draw out four cognitive qualities of information technology: interactivity, fit, cooperativity, and affordances. Together these cognitive qualities reflect IT’s ability to influence cognitive processes and ultimately task performance. Extrapolating from our historical analysis and looking at the operation of these cognitive qualities in concert, we envisage a bright future for cognitive research in IS: a future in which the study of cognition in IS extends beyond the individual to consider cognition distributed across teams, communities and systems, and a future involving the study of rich and dynamic social and organizational contexts in which the interplay between cognition, emotion, and attitudes provides a deeper explanation of behavior with IS
Natural Language Tutoring and the Novice Programmer
For beginning programmers, inadequate problem solving and planning skills are among the most salient of their weaknesses. Novices, by definition, lack much of the tacit knowledge that underlies effective programming. This dissertation examines the efficacy of natural language tutoring (NLT) to foster acquisition of this tacit knowledge. Coached Program Planning (CPP) is proposed as a solution to the problem of teaching the tacit knowledge of programming. The general aim is to cultivate the development of such knowledge by eliciting and scaffolding the problem solving and planning activities that novices are known to underestimate or bypass altogether. ProPL (pro-PELL), a dialogue-based intelligent tutoring system based on CPP, is also described. In an evaluation, the primary findings were that students who received tutoring from ProPL seemed to exhibit an improved ability compose plans and displayed behaviors suggestive of thinking at greater levels of abstraction than students in a read-only control group. The major finding is that NLT appears to be effective in teaching program composition skills
Comprehension of Procedural Visual Business Process Models - A Literature Review
Visual process models are meant to facilitate comprehension of business processes. However, in prac- tice, process models can be difficult to understand. The main goal of this article is to clarify the sources of cog- nitive effort in comprehending process models. The article undertakes a comprehensive descriptive review of empiri- cal and theoretical work in order to categorize and sum- marize systematically existing findings on the factors that influence comprehension of visual process models. Methodologically, the article builds on a review of forty empirical studies that measure objective comprehension of process models, seven studies that measure subjective comprehension and user preferences, and thirty-two arti- cles that discuss the factors that influence the comprehen- sion of process models. The article provides information systems researchers with an overview of the empirical state of the art of process model comprehension and provides recommendations for new research questions to be addressed and methods to be used in future experiments
Toward a Taxonomy of Modeling Difficulties: A Multi-Modal Study on Individual Modeling Processes
Conceptual modeling is an essential activity during information systems development and, accordingly, a learning task faced by students of Information Systems. Presently, surprisingly little is known about how learning processes of conceptual modeling proceed, and about modeling difficulties learners experience. In this study, we integrate complementary modes of observation of learners\u27 modeling processes to identify modeling difficulties these learners face while performing a data modeling task using a modeling tool. We use the concept of cognitive breakdowns to analyze verbal protocols, recordings of learner-tool interactions and video recordings of learners\u27 modeling processes and survey learners about modeling difficulties. Our study identifies five types of modeling difficulties relating to different aspects of constructing conceptual data models, i.e., entity types, relationship types, attributes, and cardinalities. The identified types of modeling difficulties motivate a taxonomic theory of modeling difficulties intended to inform design science research on tool support for learners of conceptual modeling
Knowledge restructing and the development of expertise in computer programming
This thesis reports a number of empirical studies exploring the development of expertise in computer programming. Experiments 1 and 2 are concerned with the way in which the possession of design experience can influence the perception and use of cues to various program structures. Experiment 3 examines how violations to standard conventions for constructing programs can affect the comprehension of expert, intermediate and novice subjects. Experiment 4 looks at the differences in strategy that are exhibited by subjects of varying skill level when constructing programs in different languages. Experiment 5 takes these ideas further to examine the temporal distribution of different forms of strategy during a program generation task. Experiment 6 provides evidence for salient cognitive structures derived from reaction time and error data in the context of a recognition task. Experiments 7 and 8 are concerned with the role of working memory in program generation and suggest that one aspect of expertise in the programming domain involves the acquisition of strategies for utilising display-based information. The final chapter attempts to bring these experimental findings together in terms of a model of knowledge organisation that stresses the importance of knowledge restructuring processes in the development of expertise. This is contrasted with existing models which have tended to place emphasis upon schemata acquisition and generalisation as the fundamental modes of learning associated with skill development. The work reported here suggests that a fine-grained restructuring of individual schemata takes places during the later stages of skill development. It is argued that those mechanisms currently thought to be associated with the development of expertise may not fully account for the strategic changes and the types of error typically found in the transition between novice, intermediate and expert problem solvers. This work has a number of implications for existing theories of skill acquisition. In particular, it questions the ability of such theories to account for subtle changes in the various manifestations of skilled performance that are associated with increasing expertise. Secondly, the work reported in this thesis attempts to show how specific forms of training might give rise to the knowledge restructuring process that is proposed. Finally, the thesis stresses the important role of display-based problem solving in complex tasks such as programming and highlights the role of programming language notation as a mediating factor in the development and acquisition of problem solving strategies
Guidelines for empirical evaluations of conceptual modeling grammars
Conceptual modeling grammars are used to create scripts that represent someone's perception, or some group's negotiated perception, of domain semantics. For many years, researchers have evaluated conceptual modeling grammars to determine ways that they can be improved. One way to evaluate them is to empirically evaluate the strengths and weaknesses of the grammars in terms of their effectiveness and efficiency in generating scripts. A number of researchers have proposed guidelines for the design of empirical research to conduct such evaluations. Although these guidelines have proved useful, further clarification is needed in relation to (1) criteria for evaluating grammar performance, (2) characteristics of grammars that can influence grammar performance, and (3) factors that must be considered when testing the effect of grammar characteristics on grammar performance. We review past conceptual modeling research and provide guidelines for addressing these three issues. We also illustrate how the guidelines would apply to studies that evaluate conceptual modeling grammars from an ontological perspective. Finally, we discuss how the guidelines extend those offered in past research and the implications of our work for future research
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