Group items tagged

"This review examines that process and the social and other factors influencing the diffusion of Internet/World Wide Web technology. Attributes of Internet technology that differ from those of traditional instructional technologies and that modify the adoption and diffusion process are discussed, as are characteristics of the potential adopters and strategies that contribute to successful technology adoption and integration within an organization. "

"Technology marketers face the ongoing challenge of how to align content touches with their customers' preferences for information sources. Social media heightens this challenge because poorly aligned content can go negatively viral. While technology marketers seek more effective tactics to meet their customers' needs, their customers seek more useful business-to-business (B2B) social media channels that provide them with information that has real value during their decision-making process. One powerful way technology marketers can close this gap is by optimizing social media tactics for each stage in the buyers' technology adoption cycle. These technology adoption patterns lead to safe bets that B2B technology marketers can take for engagement, as long as they follow a customer-driven approach."

"New technology presents risk for many customers. They react differently toward this risk based on their innate characteristics, the wants and needs of their companies, and the behavior of other buyers. The Technology Adoption Life Cycle (TALC) models how different groups of customers adopt to discontinuous innovation at different times. This model helps high-tech marketers build the best strategy for each phase of a product's life. The graphic below shows the markets that develop along the TALC and the types of customers that dominate them."

"The 10 Barriers to Technology Adoption Technology will absolutely change K12 learning. "

The Concerns-Based Adoption Model (CBAM): A Model for Change in Individuals. on The National Academies site, reprinted with permission from the chapter entitled "Professional Development for Science Education: A Critical and Immediate Challenge," by Susan Loucks-Horsley. "The model (and other developmental modesl of its type) holds that people considering and experiencing change evolve in the kinds of questions they ask and in their use of whatever the change is..."

Mentioned in Engaging Faculty thread in Jam as theory that claims to predict who would be willing to adopt a technology.

"Faculty Adoption of Educational Technology Educational technology support plays a critical role in helping faculty add technology to their teaching"

Franziska Zellweger Moser. 2007. EDUCAUSE Quarterly (EQ) Volume 30 (2007). In depth case studies at three highly interesting but very different universities-MIT, Tufts, and Northeastern- based on interviews about the issue of faculty adoption of educational technology.

On EDUCAUSE. Archived webcast (see link, session archive, on this page) "focused on wider campus efforts rather than encouraging faculty to adopt a single tool." -CP

"What is Technology Adoption?"

From Wikipedia, essentially "Diffusion of Innovations is a theory of how, why, and at what rate new ideas and technology spread through cultures." Theory was popularized this theory in his 1962 book "Diffusion of Innovations"

Mentioned in Engaging Faculty thread in Jam as theory that claims to predict who would be willing to adopt a technology.

(PDF) Shea, P. (2007). Bridges and barriers to teaching online college courses: A study of experienced online faculty at 36 colleges. Journal of Asynchronous Learning Networks, 11(2), 73-128. From abstract, "This paper reports on initial findings from a research study of factors that enable and constrain faculty participation in online teaching and learning environments."

Citation provided in Engaging Faculty thread in Jam.

Author posted in Jam sections from his article to highlight some significant differences that might shape adoption of innovation among faculty: Gender - Two differences were identified with regards to gender. First, female respondents were more likely to report that they were motivated to teach online because online teaching accommodated other life needs (such as child care, transportation, and other family needs). Additionally females identified reduced commuting time or hassle as a motivator more frequently than their male counterparts (Tables 3 and 4). Age - With regards to age, more "mature" faculty (those 45 or over) were more motivated by opportunities to experiment with new pedagogy then were younger faculty (Table 5). Younger faculty were more motivated (perhaps unrealistically) by opportunities to demonstrate competencies important for tenure or promotion that they believed online teaching provided (Table 6). Younger faculty also reported being motivated by other material incentives that might be available for online teaching (Table 7) and were more likely to report that online teaching might be a condition of employment as a motivating factor (Table 8). Full-Time/Traditional versus Part-Time/Non Traditional. - Motivational differences were also identified by the employment status of the faculty. Part-time/Non-Traditional faculty (lecturers,instructors, and adjuncts) were over represented as a group that identified the capacity of online teaching to accommodate other life needs as a motivator for online teaching, while Full-time/Traditional faculty (assistant, associate, and full professors) were under represented in this category (Table 9). Part-time faculty were also somewhat more motivated by the possibility that online teaching could provide more free time for other professional activities and reduce commuting time or hassle (Tables 10 and 11). Parttime instructors were also more motivated by the opportunity to teach a new subject area and b

Wiki on EDUCAUSE with ideas on topic.