THE SAMR MODEL

THE SAMR MODEL 

BY: DR. RUBEN PUENTEDURA

WHO IS DR. RUBEN PEUNTEDURA?

Dr. Ruben Puentedura is the Founder and President of Hippasus, a consulting firm based in Western Massachusetts, focusing on transformative applications of information technologies to education. He has implemented these approaches for over twenty-five years at a range of K-20 educational institutions, as well as health and arts organizations. 

He is the creator of the SAMR model for selecting, using, and evaluating technology in education, which currently guides the work of the Maine Learning Technology Initiative, as well as projects in Vermont and Sweden. His current work explores new directions in mobile computing, digital storytelling, learning analytics, and educational gaming, focusing on applications in areas where they have not been traditionally employed. 

INTRODUCTION

The SAMR model, represented as a ladder, is a four-level approach to selecting, using, and evaluating technology in K-12 education.

According to Puentedura (2006), the SAMR model is intended to be a tool through which one may describe and categorize K-12 teachers’ uses of classroom technology (see Fig. 1).

The SAMR Model can be especially powerful during remote and blended learning when integrated classroom technology makes teaching and learning a more seamless experience for educators and students.

DEFINITION

The SAMR Model as a Framework for Evaluating mLearning With the predominance of mobile devices in our lives, it is natural for educators to ask how they could be used to support learning. In exploring the possibilities and reviewing the research, it becomes clear that there are many factors that influence the implementation of mobile devices within the educational context. 

Thus, the proposed definition of mLearning used in this paper is learning that is personalized, situated, and connected through the use of a mobile device (see Figure 1).

THE SAMR MODEL AS A  FRAMEWORK FOR MLEARNING 

Transformational learning activities that are truly personalized, situated, and connected through the use of a mobile device will go beyond merely using a mobile device as a substitute for more traditional tools. The SAMR model provides a framework that can be used to classify and evaluate mLearning activities. Ruben R. Puentedura developed the SAMR model in 2006 as part of his work with the Maine Learning Technologies Initiative (Puentedura, 2006). The model was intended to encourage educators to significantly enhance the quality of education provided via technology in the state of Maine. 

The SAMR Model consists of the following four classifications of technology use for learning activities:

Substitution: 

The technology provides a substitute for other learning activities without functional change.

Augmentation: 

The technology provides a substitute for other learning activities but with functional improvements.

Modification: 

The technology allows the learning activity to be redesigned.

Redefinition: 

The technology allows for the creation of tasks that could not have been done

without the use of the technology.

LET'S BREAKDOWN THE SAMR:

 Fig. 1 Puentedura’s (2006) Substitution, Augmentation, Modification,

and Redefinition (SAMR) model (retrieved from http://www.hippasus.

com/rrpweblog/)

Learning activities that fall within the substitution and augmentation classifications are said to enhance learning, while learning activities that fall within the modification and redefinition classifications are said to transform learning (Puentedura, 2013).

CONNECTION BETWEEN SAMR AND THE MLEARNING DEFINITION. 

Puentedura (2013) notes that learning activities that lie at the modification and redefinition levels of the SAMR framework can transform learning. It is at these higher levels of the SAMR framework that the full potential of learning via a mobile device is realized (Hockley, 2013). After the ten articles included in this review were classified based on the SAMR framework, each article was reexamined to determine whether the mLearning example was personalized, situated, and/or connected (see Table 2). This analysis revealed that every example at the redefinition level of the SAMR model was personalized, situated, and connected. This was not true of examples at the lower levels of the SAMR framework. If learning activities involving a mobile device are purposefully designed to be personalized, situated, and connected, the resulting mLearning activities have the potential to redefine and transform learning.

CONCLUSION AND SUGGESTIONS 

Models such as SAMR have potential for guiding practitioners in their efforts to navigate a complex landscape by seemingly simplifying a multifarious process. At the same time, they also represent teaching with technology in sterile and hierarchical ways that most often serve to misinform and mislead teachers rather than enhance pedagogy and practice. To refocus the conversation regarding K-12 educators’ understanding and use of the SAMR model, our analysis of the SAMR model focused on the absence of context, emphasis on products over processes, and rigid structure. In light of these challenges, the SAMR model may underemphasize the multi-faceted and complex nature of teaching and learning with technology. Instead, it emphasizes the types of technology teachers should use to move themselves up the hierarchical continuum of SAMR, giving primacy to technology rather than good teaching.

Based on our analysis, we offer the following suggestions for how the SAMR model could be more productively used to guide educators’ and researchers’ technology integration efforts. We are not proposing a new framework or altered visual representation of the SAMR model, which is beyond the scope of this paper. Rather, our goal is to present ways in which the SAMR model may be further refined and clarified. First, we propose that the SAMR model be revised or augmented to become context-sensitive. This could include adding context as a formal aspect of the framework, as is the case in the TPACK framework (Koehler and Mishra 2008). Context could also be considered as an implicit part of SAMR, in which case suggestions for how teachers can use the SAMR model based on contextual factors such as appropriate learning outcomes, students’ needs, and school and community expectations can be developed. Doing so supports Zhao and Frank’s (2003) argument for maintaining an ecological perspective when implementing educational technology.

We also suggest redesigning the taxonomic format of the SAMR model to account for the dynamic nature of teaching and learning with technology. Placing more value on higher tasks or levels, as defined through the use of a taxonomic structure, suggests that it is the technology, rather than a teacher’s goals and learning objectives that guide pedagogy and practice (Branch and Merrill 2012). Rather than labeling the types of technology use, practitioners and researchers would benefit from having and using flexible models in which the processes of teaching and learning with technology are central and dynamic (Mishra et al. 2009). A teacher’s choice to substitute one tool for another (i.e., the lowest level in the SAMR model) may be the most appropriate choice given the targeted motivational and learning outcomes, the design of the learning environment, and/or the students in the classroom. In this instance, the teacher’s decision reflects the dynamic and fluid nature of teaching and learning.

REFERENCES:

http://com.appolearning.files.s3.amazonaws.com/production/uploads/uploaded_file/449a37b9-489a-4fb4-9dde-c60ccc02acb2/SAMR_Model.pdf

https://files.eric.ed.gov/fulltext/EJ1036281.pdf

https://www.hippasus.com/team/rrpuentedura.html#:~:text=He%20is%20the%20creator%20of,projects%20in%20Vermont%20and%20Sweden.