Pre-testing to Predict Participation in Online Communities

Ana Ramirez Carr, University of Guadalajara, Mexico

Abstract

An instrument was developed to identify computer and Internet self-efficacy levels among faculty in the College of agriculture, veterinary and biology at the University of Guadalajara. The instrument could be useful for pre-testing participation among other Spanish speaking communities. This instrument is based on Bandura's social learning theory (1986). A number of instruments have been developed to measure self-efficacy concepts, but so far none that measure the particular condition that exists in Latin-American countries. The instrument has 17 items that measure judgments about computer and Internet use with a Cronbach’s alpha coefficient of 0.95. To identify trends in adoption, the instrument was used twice with the same community (234 professors), 1998 and 2001. The general mean for this scale (1-5) in 2001 is 3.0, when for 1998 the general mean was 2.6. The items with the highest mean in 2001 were the same for the 1998 results. These are "send e-mail" (3.8) and "find specific information on the Internet" (3.7). Similarly, the two items with the lowest mean for 2001 were the same for the 1998 results: "create a home-page" (1.9) and "use a list-server and chat rooms" (2.1). These indicators are helping us to identify an incremental trend in adoption rate. However, the indicators point toward the idea that this community is more likely to be consumers of the information rather than producers. It also provides us with a direction to invest our efforts in training and campaigning programs if we want to increase our academic presence in the Internet.

Keywords: self-efficacy, adoption rate, trends, Mexico, pre-testing

Introduction

At the University of Guadalajara a science education Web site (www.acude.udg.mx )has been developed. For the last two years, professors have contributed as science consultants. At the moment we are developing a project that would be better described as a natural science museum on the Web for the state of Jalisco, Mexico, for extension purposes. For this project the community of agricultural, veterinary and biological science professors represents our best source of people to contribute to this site.

The use of the Internet by professors is a two-fold question where, on one hand, we want to know the intensity of use of the Web, and on the other hand, we want to know how much, as an academic community, this group would likely participate with contributions for the world via this medium. There is one tool that is helping us in the pre-test stage of the contributions from professors in the College of Agriculture. The tool is an instrument to determine the likelihood that this academic community would contribute. The purpose of this paper is to share this tool with other professionals, and to share the information we found. The fact that the Spanish speaking population in the United States is increasing may make this instrument useful to colleagues in this Web-related community. As well, information about targeting effort for Internet use in Latin-American countries might be of interest.

Theoretical Background

In this paper the use of a self-efficacy instrument based on Bandura's social learning theory (1986) is discussed. Bandura (1986) defined perceived self-efficacy as people’s judgments of their capabilities to organize and execute courses of action required to attain designated types of performances. This concept is also known as efficacy expectancy (Kinzie, Delcourt & Powers, 1994). This concept was developed to explain the effect of self-efficacy, the judgement that each of us has about our own skills and our own decisions to perform an activity, and the performance in practice. According to Bandura, success requires effort and perseverance, so that performance operates partially independent of our skill. This is why self-efficacy is concerned not with the skills one has but with judgments about performance. Bandura explained that self-knowledge about one’s efficacy, whether accurate or faulty, is based on four principal sources of information: (1) authentic mastery experiences; (2) observing the performance of others; (3) verbal persuasion and allied types of social influences which indicate that one possesses certain capabilities; and (4) physiological states from which people partly judge their capability, strength, and vulnerability to dysfunction.

Attitudes toward computers have been found to be significant contributors to prediction of self-efficacy for computer technologies (Kinziee, Delcourt & Powers, 1994; Zhang & Espinoza, 1998), while computer self-efficacy has been found to be significantly related to computer-dependent course performance (Karsten & Roth, 1998). Furthermore, self-efficacy was found to be related to goal level as a contributor to the motivational process that explains and predicts individual performance (Phillips & Gully, 1997). Phillips and Gully reported that what causes people to set higher goals is not measured ability (an objective concept of ability), but rather self-efficacy, a subjective concept of ability, which has a higher correlation. They use a proposed integrated model of individual differences, goal-setting and self-efficacy theories. In their model, learning goal orientation (the belief that abilities are malleable) correlates positively with self efficacy, whereas performance goal orientation (the belief that capacities are fixed and tasks are performed with the intention to perform well) correlates negatively with self-efficacy.

The Instrument

A number of instruments have been developed to measure self-efficacy concepts, but so far none that measure the particular condition that exists in Latin-American countries and specifically focused in computer and Internet use . The instrument has 17 items that measure judgments about computers and Internet use. The instrument was used twice with the same community (234 professors), in 1998 and 2001. After data concerning self-efficacy were collected in 1998, a Cronbach’s alpha analysis was used to estimate the internal consistency reliability of this instrument among all professors who responded, yielding a coefficient of 0.95. According to Mueller (1986), a well-constructed attitude scale may have a reliability coefficient of above .80. On a scale of 1 to 5 where 1 is "not confident" and 5 is "most confident", professors were asked to react to the statement: "My confidence level for performing this task is:" (see Table 1.)

	Table 1. Professors’ judgments of their self-efficacy to use computers for traditional teaching, and for distance learning and teaching.	1998 grand mean: 2.65		2001 grand mean: 3.0
	Items:	Mean	*SD	Mean	*SD
1.	Troubleshoot computer problems	2.92	1.14	3.01	1.06
2.	Install software programs	2.49	1.33	2.68	1.06
3.	Understand computer hardware terminology	3.62	1.07	2.65	1.09
4.	Understand computer software terminology	2.73	1.03	2.82	1.08
5.	Send e-mail (with user friendly software)	3.23	1.49	3.86	1.19
6.	Forward e-mail	3.07	1.56	3.55	1.32
7.	Edit text before forwarding e-mail	2.99	1.45	3.57	1.30
8.	Attach files to a message	2.68	1.45	3.35	1.49
9.	Create a mailing list	2.68	1.40	3.03	1.34
10.	Use a list-server and chat rooms	1.73	1.10	2.12	1.21
11.	Find specific information on the Internet	3.21	1.35	3.69	1.10
12.	Use search engines such as Yahoo	3.20	1.48	3.73	1.22
13.	Understand how the Internet works	3.05	1.24	3.13	1.20
14.	Explain how the Internet information is stored.	2.34	1.19	2.58	1.19
15.	Create a home-page	1.63	.97	1.88	1.09
16.	Download files via Internet	2.28	1.28	2.79	1.50
17.	Explain how information is transmitted on the Internet	2.10	1.09	2.42	1.23

*SD= Standard Deviation

Table 1. Professors’ judgments of their self-efficacy to use computers for traditional teaching, and for distance learning and teaching.

The Spanish version of the instrument is available here (Table 2) for the purpose of sharing the information. The purpose is to encourage practitioners to use this instrument within other communities and create data-bases so we can compare. It is of importance to keep the same wording in any replication studies with other communities. The uses of this replication could be further comparison of self–efficacy levels among communities with similar characteristics in different countries, as well as comparisons across time. The next challenge is how to compare the pre-testing stage to the actual participation in the Web. This is a task that should be addressed once participation is developed and we could measure participation. This measurement should be easily comparable to this pre-test stage.

	Table 2. Spanish version of professors’ judgments of their self-efficacy to use computers for traditional teaching, and for distance learning and teaching, comparing results of 1998 vs 2001.	1998 grand mean: 2.65		2001 grand mean: 3.0
		media	SD	media	SD
1	Resolver problemas en una computadora	2.92	1.14	3.01	1.06
2	Instalar un paquete de software.	2.49	1.33	2.68	1.06
3	Entender terminología de hardware en computadoras	3.62	1.07	2.65	1.09
4	Entender terminología de software en computadoras	2.73	1.03	2.82	1.08
5	Enviar correo electrónico (aún usando software amigable).	3.23	1.49	3.86	1.19
6	Re-transmitir un mensaje en correo electrónico (forward)	3.07	1.56	3.55	1.32
7	Editar texto antes de re-transmitir un mensaje electrónico	2.99	1.45	3.57	1.30
8	Anexar archivos junto con un mensaje electrónico	2.68	1.45	3.35	1.49
9	Crear una lista de direcciones electrónicas	2.68	1.40	3.03	1.34
10	Usar un list-server y chat rooms (conversación de grupo en vivo).	1.73	1.10	2.12	1.21
11	Buscar información específica en Internet	3.21	1.35	3.69	1.10
12	Buscar mecanismos de búsqueda (search engines) como Yahoo e.g.	3.20	1.48	3.73	1.22
13	Entender cómo funciona Internet	3.05	1.24	3.13	1.20
14	Explicar cómo se almacena la información para Internet	2.34	1.19	2.58	1.19
15	Crear una página en Internet (homepage)	1.63	.97	1.88	1.09
16	Obtener archivos (downloading ) vía Internet	2.28	1.28	2.79	1.50
17	Explicar cómo se transmite la información en Internet.	2.10	1.09	2.42	1.23

Table 2. Spanish version of professors’ judgments of their self-efficacy to use computers for traditional teaching, and for distance learning and teaching, comparing results of 1998 vs 2001.

Findings

The self-efficacy mean score for the 1998 survey was 2.65 (SD= .97). Professors felt confident communicating with computer technology (using electronic mail), and as consumers of information (retrieving information over the Internet). However, they did not feel confident disseminating information (creating Web-sites), nor did they feel confident taking active roles in list-serves and chat rooms. Perhaps providing training in these areas would help professors to play active roles and use the Internet more as an educational tool (Pugalee & Robinson, 1998). Scores for the adoption of computers and the Internet in classroom instruction (a dependent variable) tended to increase as the score of computer self-efficacy increased, with a significant moderate positive correlation (.34). In fact, self-efficacy was the variable which had the highest correlation with the adoption of computer use in the first model that was developed in combination with 34 other independent variables. This correlation is similar to that found by Faseyitan and Hirshchbuhl (1992) (.32) between self-efficacy and adoption of computer use by university instructors. In the regression analysis, self-efficacy was one of the predictors (out of four) that explained 18% of the total observed variability in adoption of computers for instruction. Since adults are more likely to be intrinsically motivated (Bandura, 1986) resources to enhance self-efficacy levels would be better directed toward efforts in training (Faseyitan et al., 1996) and availability of support systems, with less emphasis on personal rewards. An effective way to distribute incentives was reported by Faseyitan et al. (1996) In their program, the incentive was provided by funding the purchase of hardware and software after professors participated in training activities.

Computer and Internet self-efficacy was not in the group of variables selected in the discriminant analysis procedures as a predictor of adoption of distance education for learning where a significant low negative correlation (-.20) with the dependent variable “potential to adopt distance education for learning” was found. Nor was it in the group of variables predicting distance education for teaching where a negligible correlation (.07) with the dependent variable “potential adoption of distance education for teaching” was found. In general, there seems to be a lack of connection between computer self-efficacy and preference for distance education ways to deliver or take courses. This might be explained by the fact that past experiences of this audience with distance education activities have been mostly via satellite, fax, or snail mail, with little use of computer mediation. However, it should be taken into consideration that when professors were asked which media they would prefer for distance education learning (if embarked in the future), the Internet was more desired than satellite.

When we compare the results of the 1998 with the 2001 questionnaire, we found that the general mean for this scale (1-5) in 2001 is 3.0, when for 1998 the general mean was 2.6. The items with the highest mean in 2001 were the same for the 1998 results. These are "send e-mail" (3.8) and "find specific information on the Internet" (3.7). Similarly, the two items with the lowest mean for 2001 were the same for the 1998 results: "create a home-page" (1.9) and "use a list-server and chat rooms" (2.1). These indicators provide information that this community is more likely to be consumers of the information rather than producers. It also provides us with direction to invest our efforts in training and campaigning programs if we want to increase our academic presence in the Internet.

Currently we are in the development stage of a project that would be better described as a natural science museum on the Web for the state of Jalisco, Mexico for extension purposes. For this project the community of agricultural, veterinary and biological science professors represents our best source of people to contribute to this site. One quarter of this community (24.5%) has also reported that the software that they would like to learn more about includes Internet-based tools covering topics such as how better to use e-mail, use of Internet, Internet publishing, teaching over the Internet, use of browsers. We trust that the difference in the 1998 and 2001 general means, that went from 2.6 to 3.0 (in a scale from 1-5) , is thanks to a combination of several factors. One of this could be just the natural presence of the Internet over time. The more exposure to something, the more likely it is that one learns more. However, there is little we can do to control time. There are other factors that can be taken into account to encourage participation and that have been acted on. In the College, courses are taught targeting professors and/or students as extra curricular opportunities. Here, professors practice self-selection when it comes to recruitment for these courses, or they respond to invitations to participate in the development of mini-sites. When we ask them to answer the self-efficacy test, these professors score high, in general. On the other hand, when we are developing our mini-sites and have specific needs for expertise, we encounter professors who seem totally unaware of the opportunities the Internet can provide, Then, another approach should be considered. This approach regularly takes more time and resources to get the project done. This is the case of the project for the “Plan de ordenamiento territorial del estado de Jalisco”. (Land Zoning Plan for the Estate of Jalisco) (www.acude.udg.mx/divulga/ordena) where there was a variety of styles of presentation of the materials among the 200 researcher-professors who participated in the project. The Web site was developed with a limited budget. It took a longer than desirable time to put all the available materials in the same format. Another issue has been the users. Target users are at a variety of Internet skills-use levels. If we want decision makers or specialized people to use our Web site where other tools such as Adobe Acrobat Reader are required, or if users are just not computer-oriented, special efforts are needed so the information can get where we want it

Conclusions and Recommendations

The level of awareness about the use of computer technology in the classroom found among professors indicates that there is no need to invest resources to get professors more interested in the use of computers in traditional on-campus teaching. Bypassing the awareness stage would save time and resources in the adoption diffusion process. Programs should be developed to increase professors’ ability to use computers and participate in the Internet. These programs might increase professors’ self-efficacy levels and, as a consequence, professors would set higher goals that require the use of computer skills in academic activities. Showcases or exhibits, seminars, and workshops should be part of the strategy. Professors perceived the access to equipment and telecommunications at work to be limited . In order to reduce these constraints, the University could provide full Internet access for professors who have computers at home. This would be most important for those professors whose courses include the use of computers and telecommunications. If there is interest in promoting Web-based academic presence for extension purposes, the adoption-diffusion process should include a well-implemented awareness program that emphasizes the advantages of education at a distance based on the Internet. This recommendation is based on the lack of connection between computer use and acceptance of education and teaching at a distance. Since half of the professors showed interest in teaching at a distance, administrators in the College of Agriculture in Guadalajara should consider this as an asset in future planning where the Internet is one option. Administrators should encourage professors interested in this form of course delivery by providing opportunities to deliver courses at a distance. In the attempt to enhance adoption of computer technology in the classroom, it is recommended that the administration sponsor special programs to strengthen: (1) professors socializing their knowledge about computers, (2) frequent use of the Internet, (3) planning for more use of computers in the classroom, and (4) computer self-efficacy levels.

Among recommendations: future research regarding self-efficacy should focus on explaining why professors do not feel confident taking active Internet roles such as disseminating information (creating Web-sites), or using list-serves and chat rooms. Focusing research in this area might help to find the means for overcoming professors’ lack of confidence in active participation, and in doing so, help professors to receive the maximum benefit from this technology.

References

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