Gender Role Inventory

We describe a newly developed 14-item inventory designed to measure two dimensions – agency and communion – of gender role self perceptions. The Gender Role Inventory (GRI-14) emerges as a conceptual and empirical refinement of the Bem Sex Role Inventory (BSRI; Bem, 1981) offering exceptional utility for electronic-based research while overcoming questions about construct validity and psychometric adequacy inherent in the BSRI. Since its inception, the BSRI has proven a widely used tool for assessing femininity and masculinity in numerous empirical studies and, to a significant extent, has defined the nature of sex role orientation in the research literature. Despite its popularity, however, persistent questions have arisen over whether the BSRI actually measures what it claims to measure (see, for example, Choi & Fuqua, 2003; Hoffman & Borders, 2001). A highly consistent pattern emerging across a range of factor-analytic studies, for example, is (1) a single femininity factor and two or more complex masculinity factors, (2) a tendency toward inconsistent item loading across these factors (e.g., over half of the femininity subscale items do not load on the femininity factor), and (3) an unexpectedly low amount of total variance typically accounted for by the primary factors. Concerns such as these, some argue, point to an “initial lack of theoretically defined dimensions of masculinity/femininity measured by the BSRI” (Choi & Fuqua, 2003, p. 884) while others proposed that the BSRI actually measures constructs such as instrumentality and expressiveness (e.g., Bohannon & Mills, 1979; Moreland, 1978).

Reactance Proneness Assessment

The theory of psychological reactance (Brehm, 1966; Brehm & Brehm, 1981; Wicklund, 1974) has often been called upon to explain the failure of persuasive attempts, and/or the “boomerang effect” in persuasion (Buller, Borland, & Burgoon, 1998; Burgoon, Alvaro, Grandpre, & Voulodakis, 2002; Grandpre, Alvaro, Burgoon, Miller, & Hall, 2003; Ringold, 2002). The theory contends that any persuasive message may arouse a motivation to reject the advocacy. That motivation is called reactance. Reactance may be considered to be an aversive motivational state that functions to reinstate an individual’s perceptions of autonomy. Although initially investigated as a state phenomenon, it has become evident that individuals are likely to vary in their trait propensity to experience reactance. Individual differences in reactance proneness offer a useful means of segmenting target audiences, especially in the context of health communication, because individuals most at risk for various health threats are also the individuals most likely to experience reactance when exposed to persuasive messages about that health risk (e.g., Bensley & Wu, 1991).

Personal Report of Communication Apprhension

The Personal Report of Communication Apprehension (PRCA-24) (McCroskey, 1982) measures communication apprehension. Communication apprehension (CA) first appeared in James McCroskey’s 1970 research note in Communication Monographs. Communication apprehension is defined as the level of fear or anxiety associated with either real or anticipated (oral) communication encounters. McCroskey was interested in a person’s trait or dispositional anxieties across all or most communication situations. Recent investigations have expanded CA to include state-like communication apprehension, or anxiety associated with particular communication contexts and events. The 24-item, Likert-type PRCA instrument is the most popular and valid measure of trait-like CA. It assesses a person’s CA in four separate communication contexts: public, small group, meeting, and interpersonal. Each of these contexts is represented by six items. In filling out the form, an individual indicates the level of anxiety he or she feels about participating in various oral communication situations in one of these four contexts.

Technology Acceptance Model

The Technology Acceptance Model (TAM) (Davis, 1989) measures perceived usefulness and perceived ease of use as predictors of a user’s intent to use computer technology, and their actual usage on the job. The measure first appeared in 1989, in an MIS Quarterly article by Fred Davis and in a coauthored article in Management Science(Davis, 1989; Davis, Bagozzi, & Warshaw, 1989). Extending the Theory of Reasoned Action (Ajzen & Fishbein, 1980) to technology, Perceived usefulness (U) is defined as “the degree to which a person believes a particular system would enhance his or her job performance.” Perceived ease of use (EOU) is defined as “the degree to which a person believes that using a particular system would be free of effort.” ‘Usage intentions’ (BI) was measured through self-predicted future usage and ‘user acceptance’ was measured through self-reported current usage. Although information technology is adopted to improve employee performance, these gains are often lost or diminished by users’ unwilling to accept and use the information system. Davis wanted to understand why users rejected or accepted information technologies, to better predict, explain and increase user acceptance. The TAM model has since become one of the most established models for predicting user acceptance.

Open Source Survey Software

One of the significant advances in software design afforded by the internet has been the open source movement, an effort to collaboratively create software and make it widely and freely available to the online community. Although the open source movement started with Unix-like computer operating systems, it has expanded to include a wide variety of software programs, including tools to publish and analyze online surveys. This article introduces the open source movement and then profiles three leading open source survey programs: php Easy Survey Package (phpESP), PHP Surveyor, and the Moodle course management system.

Web Survey Methodology (WebSM) Portalatform

<div>The chapter describes a Web portal, dedicated to survey research, using modern information-communication technologies, especially the WWW. Although supported by EU since 2002, it provides worldwide visitors information on events (e.g., scientific meetings, calls for papers, projects), software, and literature on the methodology and implementation of Web surveys. The most valuable databases are the bibliography (including over 2,000 entries) and software/services databases (including over 500 entries).<br></div>

Computer-Mediated Communication Research

This chapter asks “what is meant by computer-mediated communication research?” Numerous databases were examined concerning business, education, psychology, sociology, and social sciences from 1966 through 2005. A survey of the literature produced close to two thousand scholarly journal articles and bibliometric techniques were used to establish core areas. Specifically, journals, authors and concepts were identified. Then, more prevalent features within the dataset were targeted and a fine grained analysis was conducted on research affiliated terms and concepts clustering around those terms. What was found was an area of scholarly communication, heavily popularized in education related journals. Likewise topics under investigation tended to be education and internet affiliated. The distribution of first authors was overwhelming populated by one time authorship. The most prominent research methodology emerging was case studies. Other specific research methodologies tended to be textually related such as content and discourse analysis. This study was significant for two reasons. First, it documented CMC’s literature historical emergence through a longitudinal analysis. Second, it identified descriptive boundaries concerning authors, journals, and concepts that were prevalent in the literature.

Measuring Cognitive Load

Cognitive load theory describes learning in terms of a processing system when all too often working memory is overloaded and learning is impeded. Measuring cognitive load is an important component of research in the area of information processing. The design, delivery, and administration of an instrument, as well as its reliability and validity are discussed as a solution to the measurement of cognitive load. A nine-point subjective rating scale ranging from very, very low (1) to very, very high (9) measures cognitive load, defined as the mental effort needed to complete a task. It is a replica of the instrument used by Paas (1992) and Paas and van Merriënboer (1994). The measurement instrument can be used both on paper and on the Web.

Electronic vs. Conventional Surveys

This paper discusses the outcomes of two data collection methods involving questionnaires distributed to members of an organization. One group received a paper survey through the post whilst the second group was asked to complete the survey on-line. The results indicated that although response rates were higher for the on-line group there were no significant differences in the responses of the two groups. These results suggest that for targeted groups of the type involved in this study, either method can be used with confidence but that the on-line method may result in higher return. However, the additional benefits of speed, convenience and cost make the on-line method appealing.

Situational Communication Apprehension Measure

The Situational Communication Apprehension Measure (SCAM) was developed by McCroskey and Richmond (1982, 1985) to measure state communication apprehension in any context. This self-report instrument utilizes a 20-item questionnaire to assess how one person felt during a recent interaction with another. Richmond (1978) has also investigated a person’s dispositional (trait) anxieties and fears associated with specific situations (state). The SCAM, a Likert-type measure of state anxiety, asks survey takers to think about the last time they interacted with someone who held a supervisory role over them. Based on that interaction, respondents rate 20 statements—10 describing positive and 10 expressing negative feelings—on an accuracy scale of 1–7. A mark of “7” indicates the statement describing the situation is extremely accurate; a “1” notes the most inaccurate assessment of the interaction. An individual’s score on the SCAM is determined by summing all the positive statements and then summing all the negative statements. The two sums are then added and subtracted from 80. The score should range between 20 and 140. A score below the lower limit or above the upper limit indicates the respondent has made an error. Because scores on the SCAM are highly dependent on and variable by the particular situation, norms for score ranges, means and standard deviations are hard to define. However, researchers generally accept a score between 39 to 65 as low, 66 to 91 as moderate, and 92 and above as high levels of apprehension.