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Technology integration models are frameworks that one can use to guide thinking around the use of emerging technologies in education and as such provide a way to examine the myriad ways stakeholders make decisions pertaining to technology use, adoption, and integration. …. As theoretical constructs, technology integration models empower researchers and practitioners to ask certain questions and to understand technology integration in key ways. Much like the lens of a telescope, these models have great practical value for improving perceptions and guiding inquiry, and it is for this reason that various technology integration models have been posited in recent years as means for understanding technology integration phenomena. Some prominent examples include the Technological Pedagogical and Content Knowledge (TPACK) model, Substitution Augmentation Modification Redefinition (SAMR) model, Replacement Amplification Transformation (RAT) model, Technology Integration Matrix (TIM), Technology Acceptance Model (TAM), and Technology Integration Planning (TIP) model. Each provides different opportunities for understanding and interpreting technology integration efforts. …Rather, it seems that technology integration models are adopted based on convenience and comfort on the part of adoptees without any clear explanation as to why. Furthermore, because the education field is permeated with a general sense of theoretical pluralism, which allows for competing and contradictory theoretical constructs to coexist and enjoy pragmatic use among practitioners and researchers, there does not seem to be a call for adoptees of different models to seek consensus or to reconcile models with one another. As a result, the educational literature does not contain a robust discussion of theory development in this regard, and it seems to be the norm that alternative theories need not compete with one another. Instead, they may be adopted and discarded (Kimmons & Hall, 2016, p.52).

This general lack of theoretical discussion may have serious implications for the credibility and validity of the educational technology field as a site of serious academic endeavor (Selwyn, 2011) and has left us in a strange predicament: though we may believe that theoretical models are good insofar as they are practical, we have not as a field established methods for determining model practicality (and therefore value). Likewise, we have not maturely considered the possibility that some theoretical models may be more appropriate in certain contexts than others. Rather, the flavor of the educational literature in this regard seems to be highly subjective and uncritical, wherein a theoretical model may be adopted for a particular research study, but no justification is provided as to why the model was chosen over alternatives; models themselves are not critically evaluated based upon empirical outcomes. We seem to subjectively choose models and allow those models to dictate how we interpret our findings, rather than using our findings to drive theoretical model development and adoption (Kimmons & Hall, 2016, p. 53).

As practitioners and researchers who have explored technology integration across a number of contexts, we believe that technology integration is a highly complex process that needs to include multiple considerations in order to be successful. For this reason, we embrace theoretical pluralism in the field and contend that various models are appropriate and valuable in different contexts. Technology integration models are very diverse and, like tools in the hands of a carpenter, should be applied in a manner that is contextually appropriate and that properly meshes the model with intended goals. We also believe that technology integration models should serve to guide and simplify, rather than confuse and obfuscate, the process of technology integration. We are therefore frustrated with a lack of clarity regarding model selection (Kimmons & Hall, p.54).

In this chapter, we propose a set of criteria that we believe to be important when weighing the value of any given model. Any model that would truly encompass all pieces and roles of technology integration would be far too complex to apply and remain valuable. Though we believe that no single theoretical model should reasonably be expected to be all things to all people, we also believe that there should be some general framework for model selection that allows us to match a model’s strengths to the value systems of potential adoptees (Kimmons & Hall, 2016, p.54).



The notion of compatibility is derived from Rogers’ (2003) work on the diffusion of innovations and refers to the alignment between a technology integration model’s design and existing educational and pedagogical practices. Some models are created with practitioners in mind and seek to be easily applied, while others threaten to disrupt or alter practice or have no clear bearing on the day-to-day work of educators. This means that models exhibiting high compatibility will likely be welcomed by practitioners for their directedness and ease of implementation, while models with low compatibility would be rejected due to burden of implementation and lack of connection to existing goals and practices Kimmons & Hall, p.54).



The concept of scope emerges from the works of Kuhn (2013) and Papert (1987) and deals with the depth of questioning inherent in a model and the intended purposes for integration. Some models are developed to interrogate fundamental problems of teaching, learning, and educational practice, dealing with the “why” of integration and a global scope, while others take a more technocratic approach, dealing with the “how” of integration and a local scope. Models that exhibit a more global scope may seek to catalyze social reform through effective integration, while those that exhibit a more local scope may focus on improving a single lesson plan (Kimmons & Hall, 2016, p.56).



The concept of fruitfulness is derived from Kuhn (2013), who explains that a good theoretical model should “be fruitful of new research findings . . . [and] disclose new phenomena or previously unnoted relationships among those already known” (p. 75). In this sense, a fruitful technology integration model would be adopted by a diversity of users for diverse purposes and yield valuable results crossing disciplines and traditional silos of practice. In contrast, an unfruitful model would be generally ignored or only be adopted in a manner that promotes siloing and dissuades interdisciplinary practice (Kimmons & Hall, 2016, p.58).

Role of technology

Technology plays different roles in different models. As alluded to in the discussion of scope above, technology can be seen as a means to an end or as an end itself. Some models view technology as a means for achieving socially valuable ends or for improving learning, while other models may treat technology integration itself as the goal. Because technology integration occurs within social contexts wherein attempts at integration may be mandated or expected, some may feel compelled to integrate technology without having a firm understanding of how such integration will meaningfully influence the learning environment. This may compel such adopters to view technology integration as the goal, thereby adopting models that treat technology as an end (Kimmons & Hall, p.59).


Student outcomes

In our current culture of high-stakes testing and mandatory improvement, discernible student outcomes are of great interest (chapter 10), and much of the rhetoric surrounding technology integration focuses on improving student achievement. Yet not every technology integration model includes the incorporation of student outcomes or the expectation that integration will produce discernible impact. Similarly, though some models may allude to student outcomes, they may not give these outcomes a primary role in the technology integration process. On the other hand, some models incorporate student outcomes into their core formulations and encourage adopters to consider these outcomes prior to commencing technology integration.(Kimmons & Hall, 2016, pp.60-61).



Finally, technology integration models vary in their clarity, in terms of both their formulation and their ongoing refinement. Clear models are simple and easy to understand conceptually and in practice, while unclear models are confusing and may be misinterpreted. Reasons for variations in clarity may vary, but some models are clearer because they are simply stated and have limited scope. Others are unclear, because much has been written to refine and extend them. In general, clear models benefit from being easier to explain and utilize, while fuzzier or more confusing models are difficult to explain, or introduce uncertainty(Kimmons & Hall, 2016, pp. 61-62)

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