Research institution
Indiana University Bloomington
US
3 researchers0 verified3 linked papers14,091 indexed citations
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2008 · Decision Sciences · 7,969 citations
Technology Acceptance Model 3 and a Research Agenda on Interventions
ABSTRACT Prior research has provided valuable insights into how and why employees make a decision about the adoption and use of information technologies (ITs) in the workplace. From an organizational point of view, however, the more important issue is how managers make informed decisions about interventions that can lead to greater acceptance and effective utilization of IT. There is limited research in the IT implementation literature that deals with the role of interventions to aid such managerial decision making. Particularly, there is a need to understand how various interventions can influence the known determinants of IT adoption and use. To address this gap in the literature, we draw from the vast body of research on the technology acceptance model (TAM), particularly the work on the determinants of perceived usefulness and perceived ease of use, and: (i) develop a comprehensive nomological network (integrated model) of the determinants of individual level (IT) adoption and use; (ii) empirically test the proposed integrated model; and (iii) present a research agenda focused on potential pre‐ and postimplementation interventions that can enhance employees' adoption and use of IT. Our findings and research agenda have important implications for managerial decision making on IT implementation in organizations.
1998 · American Journal of Physics · 6,000 citations
Interactive-engagement versus traditional methods: A six-thousand-student survey of mechanics test data for introductory physics courses
A survey of pre/post-test data using the Halloun–Hestenes Mechanics Diagnostic test or more recent Force Concept Inventory is reported for 62 introductory physics courses enrolling a total number of students N=6542. A consistent analysis over diverse student populations in high schools, colleges, and universities is obtained if a rough measure of the average effectiveness of a course in promoting conceptual understanding is taken to be the average normalized gain 〈g〉. The latter is defined as the ratio of the actual average gain (%〈post〉−%〈pre〉) to the maximum possible average gain (100−%〈pre〉). Fourteen “traditional” (T) courses (N=2084) which made little or no use of interactive-engagement (IE) methods achieved an average gain 〈g〉T-ave=0.23±0.04 (std dev). In sharp contrast, 48 courses (N=4458) which made substantial use of IE methods achieved an average gain 〈g〉IE-ave=0.48±0.14 (std dev), almost two standard deviations of 〈g〉IE-ave above that of the traditional courses. Results for 30 (N=3259) of the above 62 courses on the problem-solving Mechanics Baseline test of Hestenes–Wells imply that IE strategies enhance problem-solving ability. The conceptual and problem-solving test results strongly suggest that the classroom use of IE methods can increase mechanics-course effectiveness well beyond that obtained in traditional practice.
2014 · Proceedings of the National Academy of Sciences · 122 citations
Evolutionary cell biology: Two origins, one objective
All aspects of biological diversification ultimately trace to evolutionary modifications at the cellular level. This central role of cells frames the basic questions as to how cells work and how cells come to be the way they are. Although these two lines of inquiry lie respectively within the traditional provenance of cell biology and evolutionary biology, a comprehensive synthesis of evolutionary and cell-biological thinking is lacking. We define evolutionary cell biology as the fusion of these two eponymous fields with the theoretical and quantitative branches of biochemistry, biophysics, and population genetics. The key goals are to develop a mechanistic understanding of general evolutionary processes, while specifically infusing cell biology with an evolutionary perspective. The full development of this interdisciplinary field has the potential to solve numerous problems in diverse areas of biology, including the degree to which selection, effectively neutral processes, historical contingencies, and/or constraints at the chemical and biophysical levels dictate patterns of variation for intracellular features. These problems can now be examined at both the within- and among-species levels, with single-cell methodologies even allowing quantification of variation within genotypes. Some results from this emerging field have already had a substantial impact on cell biology, and future findings will significantly influence applications in agriculture, medicine, environmental science, and synthetic biology.