One of the principal reasons why Web-based methods are so popular is the fundamental asymmetry of accessibility: What is programmed to be accessible from any Internet-connected place in the world will surely also be accessible in a university laboratory but what is programmed to work locally may most likely not be accessible anywhere else. A laboratory experiment, for instance, cannot simply be turned into a Web experiment by connecting the host computer to the Internet. But any Web experiment can also be used in the laboratory. Consequently, it is a good strategy to design a Web-based study, if possible. As demonstrated later in this chapter, however, the ease with which laboratory studies can be connected to the Web when developed with Internet software carries the danger of overlooking the specific methodological requirements of using Web-based methods. The requirements and associated techniques are outlined in the next section of this chapter; however, some primary advantages of Internet-based assessment must first be stressed.
Web-based methods offer various benefits to the researcher (for summaries, see Birnbaum, 2004; Reips, 1995, 2000, 2002c). Main advantages are that (a) one can test large numbers of participants quickly; (b) one can recruit large heterogeneous samples and people with rare characteristics (Schmidt, 1997); and (c) Web-based methods are more cost-effective in time, space, administration, and labor in comparison with laboratory research. Of course, all advantages of computerized assessment methods (see Drasgow & Chuah, this volume, chap. 7) apply to Web-based assessment methods as well. Methodological analyses and studies reveal that Web-based methods are usually valid (e.g., Krantz, Ballard, & Scher, 1997; Krantz & Dalai, 2000) and sometimes even generate higher quality data than laboratory studies (Birnbaum, 2001; Buchanan & Smith, 1999; Reips, 2000) and facilitate research in previously inaccessible areas (e.g., Bordia, 1996; Coomber, 1997; Rodgers et al., 2001).
Other benefits of Web-based methods are (d) the ease of access for participants (bringing the experiment to the participant instead of the opposite) ; (e) the ease of access to participants from different cultures—for instance, Bohner, Danner, Siebler, and Samson (2002) conducted a study in three languages with 440 women from more than nine countries (but see the discussion about the physical and educational digital divide in access to Web technology); (f) truly voluntary participation (unless participants are required to visit the Web site) ; (g) detectability of confounding with motivational aspects of study participation; (h) the better generalizability of findings to the general population (e.g., Brenner, 2002; Horswill & Coster, 2001); (i) the generalizability of findings to more settings and situations because of high external validity—Laugwitz (2001), for instance, was able to show that a color perception effect in software ergonomics persisted despite the large variance of conditions of lighting, monitor calibration, and so forth in participants' settings; (j) the avoidance of time constraints; (k) the simultaneous participation of very large numbers of participants is possible; (1) the reduction of experimenter effects (even in automated computer-based assessments there is often some kind of personal contact, not so in most Web-based assessments) ; (m) the reduction of demand characteristics (see Orne, 1962); (n) greater visibility of the research process (Web-based studies can be visited by others, and their links can be published in articles resulting from the research); (o) the access to the number of people who see the announcement link to the study, but decide not to participate; (p) the ease of cross-method comparison—comparing results with results from a sample tested in the laboratory; (q) greater external validity through greater technical variance; and (r) the heightened public control of ethical standards.
These are the reasons why 70% of those who have conducted a Web experiment intend to certainly use this method again (with the other 30% who are keeping this option open). "Large number of participants" and "high statistical power" were rated by surveyed researchers who had made the decision to conduct a Web experiment as the two most important benefits (Musch & Reips, 2000).
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