Exploring Science: The Cognition and Development of Discovery Processes

Howard Greisdorf (Texas Center for Digital Knowledge, University of North Texas, Denton, Texas, USA)

Journal of Documentation

ISSN: 0022-0418

Article publication date: 1 April 2003

306

Keywords

Citation

Greisdorf, H. (2003), "Exploring Science: The Cognition and Development of Discovery Processes", Journal of Documentation, Vol. 59 No. 2, pp. 222-224. https://doi.org/10.1108/00220410310463527

Publisher

:

Emerald Group Publishing Limited

Copyright © 2003, MCB UP Limited


The author of this publication provides a detailed account of how aspects of “real world” science can be observed in laboratory settings (microworlds) for effectively studying the cognitive components surrounding the development of discovery processes. The research reported suggests new avenues for uncovering how children and adults approach the mental heuristics involved in exploration and inquiry. The nine studies reported include descriptions and analyses of children and adults attempting to make discoveries about a variety of systems which, in most cases, consisted of electro‐mechanical devices with keypads that structured how the devices functioned. The focus of these investigations was to uncover “domain‐general, universal, problem‐solving processes” while maintaining the experimental rigor necessary to support sound inferences about human cognition.

The first two chapters establish a grounded approach to the underlying issues engendered by scientific discovery as a problem‐solving process focused mainly on prior work by Herbert Simon. The stated focus of this book is that problem solving in the absence of extensive formal training in a specific domain relies on the use of domain general weak methods for achieving problem resolution leading to discovery. The author refers to five major weak methods including: generate and test, hill climbing, means‐ends‐analysis, planning and analogy. The framework of investigation is weighted heavily on goal directed behavior encompassing a rules‐based structure that the author poses as an scientific discovery as dual search (SDDS) model. The SDDS model acts as a general guideline within which the reported studies are interpreted and are purported to be the types of human behavior utilized in any scientific reasoning task. The major components of the model imply that problem solving leading to discovery takes place in three major domains: hypothesis space, experimental space and evidence space, with a primary focus on prediction (hypothesis formation) and experience (experimentation).

Chapters 3 through 7 outline in full detail the experimental situations and procedures used to test the SDDS model with each chapter crediting the contributing researchers. Diagrams, tables and appendices included in these chapters allow for replication by any researchers seeking to confirm or refute the results reported in these studies. To some degree, this reviewer believes too much detail was included causing the reader to get bogged down in the laboratory methods and procedures, losing focus on the research questions posed and the results obtained. That, however, is a comment not a criticism. Constraints and limitations are well articulated in the reported results including implications for further research.

Chapter 8 acts as a concluding commentary with an excellent table that summarizes the results of each of the nine studies reported. However, considering that five major weak methods for discovery were introduced in Chapter 2, their relation to the main findings stated in Table 8.1 are never clearly explained. For anyone interested in the cognitive aspects of discovery processes, a cursory review of the subheadings in the last 20 pages of this book will help the reader to determine the value of reading the preceding 200 pages. An extensive reference list is provided in support of the reported work, and both subject and author indices are provided to assist the reader.

This book will be enjoyed and valued by a limited audience interested specifically in modeling human problem‐solving behavior as an approach to discovery. Additional breadth of concept would have made inroads for expanded readership by omitting some of the experimental detail and including other supporting and competing frameworks for weighing results. The author admits to being influenced by the work of Herbert Simon and his colleagues and garners his support in the book's foreword. However, comparing the author's SDDS model to other theoretic approaches to problem solving and discovery would have been more enlightening to a broader cross‐section of readers.

Considering that the nine reported studies involved relational knowledge structures, it would have been useful to bring related theoretical perspectives into the discussion. For example, operations on relations as developed by Codd (1990) to include selection, projection, joining, deletion, union, intersection and difference as they relate to the components of the SDDS model and the results obtained from the reported studies; or concepts such as “segmentation” (decomposing complex tasks into smaller segments) and “chunking” (reducing cognitive load to fewer dimensions of representation) while absent from the discussion could also have further enhanced the discussion, conclusions and implications for further investigation (Halford et al., 1994, 1998).

The greatest strength of this work is that the author provides empirical evidence for what has previously been only intuitively obvious: adults and children go about discovery in different ways. While the overall work is noteworthy, the author's concluding comments expose its weaknesses. The approach (laboratory microworlds) is but one way to study scientific discovery, the methods used need to be extended, many questions still remain, and the concept of collaboration in relation to scientific discovery was not part of the investigation.

Until the results reported in this book are expanded and the methods extended, the utility derived from its contents is limited. However, any researcher investigating the behavior of either adults or children involving creative or discovery processes would be remiss if not becoming familiar with this work.

References

Codd, E.F. (1990), The Relational Model for Database Management: Version 2, Addison‐Wesley, Reading, MA.

Halford, G.S., Wilson, W.H. and Phillips, S. (1998), “Relational processing in higher cognition: implications for analogy, capacity and cognitive development”, in Holyoak, K. , Gentner, D. and Kokinov, B. (Eds), Advances in Analogy Research: Integration of Theory and Data from the Cognitive, Computational, and Neural Sciences, New Bulgarian University, Sofia, pp. 5773.

Halford, G.S., Wilson, W.H., Guo, J., Gayler, R.W., Wiles, J. and Stewart, J.E.M. (1994), “Connectionist implications for processing capacity limitations in analogies”, in Holyoak, K.J. and Barden, J. (Eds), Advances in Connectionist and Neural Computation Theory, Vol. 2: Analogical Connections, Abex, Norwood, NJ, pp. 363415.

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