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Edward M. Connelly

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Publication statistics

Pub. period:1984-1994
Pub. count:6
Number of co-authors:4

Co-authors

Number of publications with 3 favourite co-authors:

Paul M. Haas:1
Susan B. VanHemel:1
Michael G. Golden:1

Productive colleagues

Edward M. Connelly's 3 most productive colleagues in number of publications:

Paul M. Haas:2
Susan B. VanHemel:1
Michael G. Golden:1

Calendar

May 20

CTS 2013 - The 2013 Intl. Conf. on Collaboration Techn. and Systems

May 22

Knowing (by) Designing 2013

May 27

13th Intl. Conf. on New Interfaces for Musical Expression

May 19

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Edward M. Connelly

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Publications by Edward M. Connelly (bibliography)

1994

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Connelly, Edward M. (1994): Automated Data Analysis. In: Proceedings of the Human Factors and Ergonomics Society 38th Annual Meeting 1994. pp. 1038-1042.

“Automated Data Analysis (ADA) is a powerful, flexible analysis tool for systematically building performance determinants. ADA is designed to assist analysts in assessing the linkage from system processes to outcomes. It allows for or accounts for the varying conditions during performances and permits formation of complex analyses which extract relevant information from multiple variables while ignoring irrelevant data from the data base. In particular, ADA permits: 1. Focus on selected portions of the performance space, 2. Characterization of the system processes and examination of the relationship between system processes and outcomes, 3. Building analysis variables which can be made simple or as complex as necessary as knowledge of the importance of system processes to outcomes is obtained, and 4. Use of powerful restructured analysis tools.”

1991

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VanHemel, Susan B., Connelly, Edward M. and Haas, Paul M. (1991): Management and Organizational Indicators of Process Safety. In: Proceedings of the Human Factors Society 35th Annual Meeting 1991. pp. 908-912.

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1989

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Connelly, Edward M., Myers, Kent C. and Golden, Michael G. (1989): A Measure of Effectiveness (MOE) Method and Software Aid, with a Case Study of a Soviet Artillery Unit. In: Proceedings of the Human Factors Society 33rd Annual Meeting 1989. pp. 1278-1281.

“A Measure of Effectiveness (MOE) is a criterion. A system that scores well according to the criterion will be accepted as effective, meaning that it achieves what is intended. This seems simple, but in fact well-meaning managers can fail to find an adequate measure, are unclear about what is intended for the system, and may even misidentify the system. The method described here is a means to help avoid common mistakes. With the method, a manager or analyst (a user) builds a model of his or her own effectiveness assessment strategy using specially designed interactive software. The user enters data prompted by the software and views feedback consisting of graphs and ordered lists describing the user's inputs in various ways. Feedback gives the users alternative viewpoints for their inputs. As a case study, an MOE was constructed for a Soviet artillery unit within an attacking regiment.”

1987

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Connelly, Edward M. (1987): Impact of Human Performance on System Performance. In: Proceedings of the Human Factors Society 31st Annual Meeting 1987. p. 620.

“Objectives: The objectives of this symposium are to identify fundamental performance measurement problems and to present theory, methods and application tools for assessing the impact of human performance on system performance. Further, case studies are used to illustrate the methods and tools. Finally, plans for development by government agencies of computer based processors implementing the tools are presented. Scientific Importance: Design and analysis of systems involving human operators have been hampered by the lack of performance based development tools. In order to assess the impact of human performance on system performance, it is first necessary to have a reliable and quantitative means for assessing overall system performance. Second, a means is required for relating human performance to the system performance. When these two types of tools are available and are used, systems can be designed to a prescribed performance standard. The papers in this session address fundamental performance measurement issues (including measurement reliability sensitivity, and discrimination issues), as well as application methods and procedures.”

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Connelly, Edward M. (1987): A Theory of Human Performance Assessment. In: Proceedings of the Human Factors Society 31st Annual Meeting 1987. pp. 629-633.

“Selection of a measure of effectiveness (MOE) (a mathematical function) and using that measure to evaluate performance demonstrations (or exercises, or experimental trials) without first testing the measure, typically results in a disagreement between two ways of assigning effectiveness scores to each performance demonstration are: effectiveness scores assigned directly by the investigator and effectiveness scores assigned by the MOE selected by the investigator. The disagreement often exists even when comparing the rant ordering of the two sets of scored performances demonstrations. A disagreement between the two methods means that one method, possible both, are not correct. The direct assignment of effectiveness scores to each performance demonstration constitutes a test of the MOE. In this paper, we argue that test is typically not conducted and if it were, the MOE (existing untested MOE's) would likely fail the test. We also argue that the investigator should not select an MOE but rather should have an authority (SME) score performance demonstrations and then synthesize an MOE that will pass the test. A method for synthesizing the MOE is presented.”

1984

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Connelly, Edward M. (1984): Transformations of Software Design and Code May Lead to Reduced Errors. In: Shackel, Brian (ed.) INTERACT 84 - 1st IFIP International Conference on Human-Computer Interaction September 4-7, 1984, London, UK. pp. 443-448.

“This research investigated the capability of programmers and non-programmers to specify problem solutions by developing example-solutions and also for the programmers by writing computer programs; each method of specification was accomplished at various levels of problem-complexity. The results, which showed the superiority of using example-solutions with inductive feedback over writing code, suggests that the transformation process provided by the induction might be applied analogously to software development. Considering designs and code in multiple transformed forms may reduce software errors to a level found for example-solutions.”

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