Self-Regulation - The Impact of Cognitive Theory on Human and Computer Development - page 39

computer design activity and usage behavior, but none has established self-efficacy as a
predictor of design control mechanisms for RAM and CPU.
Linde et al. (2006) emphasized a lack of interest in technology is not a behavior, but
the effect of a series of behaviors such as component design, testing routine activities, and
information technology monitoring. A clear need exists for investigation of the continuing
perceptions of individuals' self-efficacy for technological and scientific control in develop-
mental behaviors. Linde et al. hypothesized the stronger an individual's self-efficacy and
regularity of developmental behaviors is, the greater the chance of predicting actual funda-
mental development.
Chapman-Novakofski and Karduck (2005) reported the strength of self-efficacy was
true in community-based science and technology education courses where content goals are
to assist science and technology scholars in gaining enough confidence and independence
to modify existing systems to better adhere to preferred functional outcomes. The course
objectives require students to demonstrate self-efficacy to facilitate scholars' management
of the technology, observance of functional limitations, control of CPU speed, and RAM
size research (Chapman-Novakofski and Karduck). A surprising result of the study was in
using self-efficacy to improve the scholars' grasp of the educational intervention, the edu-
cational intervention conversely improved the scholars' self-efficacy (Chapman-Novakof-
ski and Karduck).
An individual's self-efficacy values function to dictate motivation and actions through
cognitive, expressive, and decisional functions; the values also affect individuals' ability
to face difficulties and maintain emotional protection from vulnerability to stress and de-
pression (Bandura and Locke 2003). Bandura and Locke reported the level of self-efficacy
predicts coping developmental behavior independent of anticipatory anxiety; the higher the
level of self-efficacy, the more successful the coping developmental behavior.
Von Ah et al. (2004) described a study of predicting technical developmental behaviors
in college students. The authors determined the college age is a pivotal point in life and
could be a vulnerable time to experiment and try different techniques in developmental
behaviors. Most individuals who attend college enter directly from high school and must
adapt to varying academic workloads, changes in social networks, and other nuances and
idiosyncrasies of the new environment. Because of the transitional nature of college life,
the period is one for new decisions. Von Ah et al. ascertained the stress of trying to adjust
to college life leads students to experiment with independent thinking and decisions made
at this time of young adulthood may have an influence on the status of computer science
and technology development throughout the life cycle. Research indicated the pattern of
experimentation includes engagement in risky practices (Von Ah et al.).
Von Ah et al. (2004) noted the perceived technical threats to scientific and technological
behaviors have a link to technology production activities. The findings were remarkable