Profiling Information and Communication Technologies: Guiding the Channel Choices of Technology Leaders

Profiling Information and Communication Technologies: Guiding the Channel Choices of Technology Leaders

J. David Johnson (University of Kentucky, USA)
Copyright: © 2019 |Pages: 27
DOI: 10.4018/978-1-5225-7769-0.ch009

Abstract

Perhaps the most basic decision that educators can make in communicating with students is what communication channel to use. Innovation profiles apply the classic attributes of an innovation—relative advantage, compatibility, complexity, trialability, and observability—to new information and communication technologies to facilitate their successful implementation. Most importantly, as the author demonstrates in applying this concept to distance learning and teaching platforms, technology leaders can analyze technologies a priori to determine potential problems. Profiling the affordances offered by various communication channels will greatly facilitate the work of technology leaders as change agents charged with implementing technologies that confront the numerous challenges facing higher education: retention rates, affordability, and preparing students for the work world.
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Background

Historically, researchers have focused on innovations in terms of their attributes, or perceived characteristics, based on respondents’ subjective judgments, which play a significant role in the diffusion of innovation. For example, Katz (1963) saw the adoption of an innovation as being contingent upon its compatibility, or the degree to which the features of an innovation matched potential adopters. Two decades later, Rogers (1983) developed the most commonly recognized scheme available for examining differing properties of innovations. He identified five perceived attributes of an innovation: relativeadvantage, compatibility, complexity, trialability, and observability.

There should be a conscious weighing of these attributes before implementing innovations. With knowledge of innovation attributes, technology leaders in academe can develop appropriate strategies to facilitate their implementation (Dearing, Meyer, & Kazmierczak, 1994). For example, innovations that are seen as more risky may require higher volumes of persuasive communication in the implementation stage (Fidler & Johnson, 1984). Here we will compare and contrast MOOCs and teaching platforms by profiling their attributes to demonstrate how this approach provides a more nuanced view of innovation implementation (see Table 1 below).

Table 1.
Profiling attributes of information communication technology innovations
AttributesMOOCsPlatforms
Relative AdvantageMuch HypedDepends on Usage
CompatibilityModerate to LowModerately High
AdaptabilityModerateDepends on Implementation
ComplexityModerate to HighVariable
TrialabilityHighModerate
ObservabilityHighLow

Key Terms in this Chapter

Implementation: The routinization of an innovation into the ongoing work of an organization.

Compatibility: The extent to which an innovation “fits” the existing culture and routines of an organization.

Change Agents: Individuals charged with facilitating the adoption and implementation of innovations.

Innovation Attributes: Characteristics (e.g., trialability) of an innovation that can be profiled to determine the likelihood of successful implementation.

Platforms: Software bundles that support a variety of course (e.g., grades) and teaching (e.g., power point slides) related functions.

Adoption: Selection of an innovation perceived as new to the organization for eventual implementation.

MOOCs: Massive open online courses are distance learning courses made available to large numbers of potential students who may or may not be matriculated at the host institution.

Affordances: The underlying properties (e.g., synchronicity) of communication channels.

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