Design interface can have a large influence on how motivating a software program is. Aside from general guidelines and the incorporation of motivational models such as Keller’s (1987) ARCS or Deci and Ryan’s (1985) suggestions for self-determination, there are cultural considerations. Some general guidelines for motivation in interactive multimedia instruction include suggestions for typography, graphical images, color, animation/audio, integration, and motivation (Heum Lee & Boling, 1999).

Some of the guidelines for typography include consistency in addressing textual cues and signals to the learners, using upper and lower case letters, high contrast between letters and background, etc. Other suggestions include using simple, clear images and graphics for instructional or attention focusing effects rather than simply for the sake of having a graphic, being conservative with color, keeping color consistent, using animations sparingly, and using animation that is consistent with the learning objective. Bradshaw (2000) stated, “Good design is not context neutral-what works well for one content area and audience does not work well for all other content areas and audiences” (p.1).

For example, while it may be considered appropriate to use animals with human like qualities in animation or story lines in the United States, it is not appropriate in other countries, such as Mexico. Few CAI programs are designed to accommodate cultural views. It was suggested by Williams-Green, Holmes, and Sherman (1998) that to do so would enhance the meaningfulness of the learning environment. For example, in Western countries, the orientation is toward higher levels of individuality; weak uncertainty avoidance; small power difference; and femininity. The goal should be to identify cultural values that will impact instructional design decisions and apply the cultural values into the instruction (Williams-Green et al, 1998).

Self Determination

Deci and Ryan (1985) defined self-determination as the experience of choice, or in other words, a perceived internal locus of causality. When self determined, one acts out of choice rather than obligation or coercion. Similarly, there is an issue of learner and program control within the design of software used in CAI. In general, there have been mixed findings regarding learner and program control in CAI. Kinzie et al. (1992) suggested that in order for students to feel that CAI is motivating, the instruction must provide students with the perception that they are in control.

Perceptions of control are important considerations in student motivation because this is related to feelings of competence and self efficacy. In addition, the instruction becomes more meaningful. Learner control has also been linked to higher engagement, perceptions of self responsibility and higher rates of assignment completion (Kinzie et al, 1992).

A higher percentage of students choose to return to learner control rather than program control in follow up sessions (Kinzie et al, 1992). Program control resulted in higher performance in males, but learner control shows non-significant advantages in performance (Kinzie et al., 1991). Contrary to Kinzie et al.’s (1992) findings, Yang and Chin (1996) found that groups under program control performed better on post test, but there was not a significant difference in motivation between the two groups.

Hativa (1989) found that in CAI, students primarily dislike: a) time limits; b) inability to edit work; c) detection of mistakes by computers, d) lack of challenge; and e) competition with class mates that the CAI work enforces. Similarly, Deci and Ryan (1985) found that in regular classroom environments, deadlines significantly diminished subjects’ intrinsic motivation.

Adaptivity

Astleitner and Keller (1995) attempted to show how theories and empirical findings of research on motivation could be integrated in a formal model in order to both describe and predict motivation within the framework of motivationally adaptive CAI. The authors mentioned how most of the design considerations for motivating learners within CAI have been based upon changing levels of difficulty only according to one task performance or to only two dimensions (easy to difficult), and individual learning times were not considered. In addition, animation has been used as a motivator, but it has been used so much that it can become a de-motivator, repeating the same kind of feedback over and over again.

Other problems have been that learning objectives are not clearly stated, which leads to a sense of helplessness among the learners. Shortcomings within CAI were traced back to problems in implementing motivational strategies and failures in distinguishing different levels of adaptivity (Astleitner & Keller, 1995). The authors continued by suggesting that in the past CAI included gimmicks as motivators in the past, rather than specific motivational strategies.

Furthermore, when motivational strategies and tactics were considered, they were not theoretically sound, and if they were, they were not implemented well because of both hardware and software limitations. Another problem identified by Astleitner & Keller (1995) was that motivational strategies within CAI have not been adaptively implemented. In other words, they do not adapt to the learners’ needs at any particular point over an extended period of time.

Astleitner and Keller (1995) wrote: “To develop a model of the learners’ motivational states via computer, a general theoretical framework must first be used to enable the calculation of dynamic and interactional motivational components in a general manner. Second, this global framework has to be specified with differentiated motivational theories and empirical results. Finally, the complete model must be implemented in a computer simulation for predicting motivational states of a learner.”

Conclusion

In sum, research has found that motivation is a factor in CAI in two ways. First, students’ motivation levels going into CAI, influencing the success of the learning experience. Second, CAI can encourage students’ motivation to learn. We found two major themes that surfaced in our review of the literature on the role of motivation in CAI: learner characteristics and the influence of design interface. Learner characteristics include components such as self-efficacy of both the teacher and student, preferences for learning, and the role of gender. Design interface includes elements such as general guidelines, cultural influences, self-determination and adaptivity.

These findings have significant implications for learning in several ways. First, the more efficacious the teachers are in computer use, the more likely they are to use computers in the classroom. The more self-efficacy the student has in computer use, the higher the motivation to participate in CAI on both individual and group bases. Students lower in SES showed greater motivation to learn via CAI, possibly due to the novelty effect. In general, males tend to have greater comfort levels with computer use, mostly due to the socialization process they experience both at home and in school. Boys are given more exposure to computers, and starting at an earlier age, boys are encouraged to use computers more, and view them as an objective tool to conquer.

Knowing all of this, several conclusions can be drawn. First of all, the goal should be to increase the self-efficacy of teachers, and thus increase the likelihood of computer use in the classroom. To do this, in-service training should be provided to teachers. Second, to increase self-efficacy of students, exposure to computers should begin at an early age, and equal encouragement should be given to both girls and boys. Furthermore, students from a lower SES may particularly benefit from CAI. Finally, high achieving students seem to enjoy CAI more than low achieving students, thus may benefit more from CAI.

In general, when designing CAI, it may be helpful to incorporate several elements into the design, including suggestions from Keller’s ARCS model. These include strategies to gain learner’s attention, such as through the use of color and graphics, make the instruction relevant to the goals of the learners, have optimal levels of challenge, so that they have expectations for success, and finally, make the program satisfying. In addition, students prefer learner control to programmed control, so the design should include opportunities for self-determination.

In general, students dislike the following elements in CAI: a) time limits; b) inability to edit work; c) detection of mistakes by computers; d) lack of challenge; and e) competition with classmates. Thus, these components should be reduced from CAI, to increase students’ interest and motivation. In addition to general guideline considerations for design interface, CAI could be more effective at motivating students if cultural considerations were made as well. A program designed in the United States is less likely to be as effective or motivating in a non-western culture, if the designer does not consider differences in cultural values and symbolisms.

Presently, computer aided instruction has many powerful features, mainly its capacity to individualize instruction (Ross and Schulz, 1999). However, research by Astleitner and Keller (1995) stressed that CAI needs to be adaptive, so that the motivational strategies change with the evolving needs of the student. Currently, CAI can act as a motivator for students to learn, but at the same time, students’ levels of motivation influence learners’ attitudes towards and success in CAI. The suggestions made earlier may be applied to make CAI more motivating, as well as to encourage a change in attitudes in learners, so that they are more willing to participate in CAI.

Success in CAI would mean that students are eager and enthusiastic to participate in CAI, and that CAI further increases students’ motivation to learn. Ideally, CAI would reach out to students of all SES, appeal to both learners in both individual and group settings, and be culturally responsive.

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