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The Substitution Augmentation Modification Redefinition (SAMR) Model: a Critical Review and Suggestions for its Use


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The Substitution, Augmentation, Modification, and Redefinition (SAMR) model is a four-level, taxonomy-based approach for selecting, using, and evaluating technology in K-12 settings (Puentedura 2006). Despite its increasing popularity among practitioners, the SAMR model is not currently represented in the extant literature. To focus the ongoing conversation regarding K-12 educators’ understanding and implementation of technology, we provide a critical review of the SAMR model using theory and prior research. We focus on the absence of context, its hierarchical structure, and the emphasis placed on product over process and conclude with suggestions to guide educators’ and researchers’ technology integration efforts.
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The Substitution Augmentation Modification Redefinition (SAMR) Model
The Substitution Augmentation Modification Redefinition (SAMR) Model: A Critical Review
and Suggestions for its Use
Erica R. Hamilton1, Joshua M. Rosenberg2, & Meta Akcaoglu3
1Grand Valley State University, 2Michigan State University, 3Georgia Southern University
The Substitution, Augmentation, Modification, and Redefinition (SAMR) model is a four-level
approach for selecting, using, and evaluating technology in K-12 settings (Puentedura, 2006).
Despite its increasing popularity among practitioners, the SAMR model is not currently
represented in the extant literature. To focus the ongoing conversation regarding K-12 educators’
understanding and implementation of technology, we provide a critical review of the SAMR
model using theory and prior research. We focus on the absence of context, its hierarchical
structure, and the emphasis placed on product over process and conclude with suggestions to
guide educators’ and researchers’ technology integration efforts.
Author’s final pre-print version of:
Hamilton, E. R., Rosenberg, J. M., & Akcaoglu, M. (2016). Examining the Substitution
Augmentation Modification Redefinition (SAMR) model for technology integration.
Tech Trends, 60, 433-441. 10.1007/s11528-016-0091-y
The Substitution Augmentation Modification Redefinition (SAMR) Model
The complex nature of new digital technologies further complicates the already difficult
task of teaching with technology (Mishra, Koehler, & Kereluik, 2009). Digital technologies, such
as computers, mobile devices, and their software and applications are protean, unstable, and
opaque (Koehler & Mishra, 2008). In other words, digital technologies are ever-changing, not
always predictable, and can take on many forms. For example, users can easily change their uses
of tablet computers and smartphones to support various needs and interests, such as e-reading,
gaming, multimedia consumption and production, as well as communication. Although some
have sought to predict future digital technology, it is not always clear how yet-to-be-developed
hardware and software will be designed or used. As such, this idea supports Koehler and
Mishra’s assertion that both developers and end-users of digital technologies do not always know
nor can they always predict trends and applications of such technologies. Moreover, due to the
opaqueness of design and presentation of digital technologies, those who use digital technologies
may not always understand the inner-workings of the software and devices they use. These
aspects of digital technologies, as explored by Mishra and Koehler, are further complicated when
considering the ways in which digital technologies are (or should be) integrated into K-12
classrooms. In these instances, these aspects are combined with the complexity introduced by
teachers’ contexts, pedagogical choices, as well as their beliefs and motivations, making
technology integration in educational settings more difficult (Hennessy, Ruthven, & Brindley,
2005; Bebell, Russell, & O’Dwyer, 2004).
In an effort to guide educators and researchers in their technology integration efforts,
researchers have developed standards, frameworks, models, and theories that may be used to
inform research and practice around integrating technology into teaching and learning. For
example, the International Society for Technology in Education (ISTE) (2015) developed
standards which exist “to support students, educators and leaders with clear guidelines for the
skills, knowledge and approaches they need to succeed in the digital age” (para. 1). According to
ISTE, these standards have been adopted or adapted by more than fifty percent of states and
territories in the United States and may be used to support K-12 technology integration and
As another example, when educators employ the Community of Inquiry framework
(Garrison, Anderson, & Archer, 1999) they draw upon ideas that computer-mediated teaching
and learning require the existence of three interdependent presences (social, cognitive and
teaching). In the Technological Pedagogical Content Knowledge (TPACK) framework, the work
teachers do is framed by an understanding and application of three kinds of knowledge related to
technology, pedagogy, content; applications of the TPACK framework also help teachers
identify and understand the intersections of these aspects of teacher knowledge as a means of
effectively teaching with technology (Koehler, Mishra, Kereluik, Shin, & Graham, 2014; Mishra
& Koehler, 2006).
Furthermore, Zhao and Frank’s ecological perspective (2003) posits that schools,
teachers, and students are interdependent. “A school exists as a complete unit necessary for
functioning over a long period of time in a hierarchical structure. It is nested in a school district,
The Substitution Augmentation Modification Redefinition (SAMR) Model
which in turn is part of a state educational system that is part of a national education system” (p.
812). Utilizing an ecological perspective enables researchers and practitioners to explain the
dynamic interactions between technology, teaching, and school environments.
Still other prior work characterizes specific aspects of teachers’ and students’ practice,
such as Salomon and Perkins’ (2005) depiction of the effects with, of, and through the use of
technology. This work may be used to help teachers and academics identify how users’
interactions with technologies lead to different cognitive outcomes. Ertmer’s (2005) scholarship
with regard to teacher belief and technology empowers educators and researchers to focus on
beliefs about teaching and technology as a way to more deeply understand how these two may
work in tandem to predict and/or explain individual teacher’s technology uses. These standards,
frameworks, models, and theories are based on systematic (and peer-reviewed) research and
offer ways to inform and guide K-12 teachers’ understanding and uses of technology in teaching.
Puentedura’s (2006) Substitution, Augmentation, Modification, and Redefinition (SAMR)
model is a recent addition to K-12 teacher learning and professional development with respect to
educational technology. According to the ISTE (2015) website, at the 2013 ISTE conference,
only one session out of approximately 800 included the term “SAMR.” The 2014 Conference
program featured 30 workshops and presentations out of approximately 900 total sessions, and
among 1,000 sessions at the 2015 ISTE conference, 44 included “SAMR.”
Despite its increasing popularity among practitioners, the SAMR model is not currently
represented in the extant literature. The purpose of this article is to provide a critical review of
the SAMR model in order to focus the ongoing conversation regarding its use among K-12
educators. In the next section we introduce and explain the SAMR model. Following this, we
provide a critical review of the SAMR model, framed by three challenges. The first centers on
the absence of context, the next on the emphasis placed on product over process, and the third on
the hierarchical structure of the SAMR model.
The SAMR model
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 (Figure 1).
Figure 1. Puentedura’s (2006) Substitution, Augmentation, Modification, and Redefinition
(SAMR) model (retrieved from !
The Substitution Augmentation Modification Redefinition (SAMR) Model
The model encourages teachers to “move up” from lower to higher levels of teaching with
technology, which, according to Puentedura, leads to higher (i.e., enhanced), levels of teaching
and learning. To aid readers’ understanding and to illustrate applications of SAMR, we include
brief descriptions and hypothetical examples we created from content provided on Puentedura’s
At the Substitution level, digital technology is substituted for analog technology, but the
substitution generates “no functional change” (Puentedura, 2014a). For example, in a middle
school math class an instructor chooses to substitute a set of hard copy test review questions for
digital versions. At the Augmentation level, technology is exchanged and the function of the task
or tool positively changes in some way. In a first-grade classroom, for instance, instead of a
teacher-led, whole class read-aloud lesson students instead use hand-held devices to
simultaneously read and listen to individual digital stories. In this case, hand-held devices
augment the reading task. At the Modification level, technology integration requires a significant
redesign of a task. For example, in a secondary science class, an instructor shifts how students
learn about light, from showing a diagram of light traveling to providing an interactive computer
simulation of light with variables students can change. Finally, the Redefinition level is achieved
when technology is used to create novel tasks. For example, instead of assigning a social studies-
based persuasive essay, a fifth grade teacher requires students to create and present their
arguments through individually created and edited videos.
Analysis of the SAMR Model: Three Challenges
The Substitution Augmentation Modification Redefinition (SAMR) Model
Despite its increasing popularity, there is not yet a theoretical explanation of the SAMR
model in the peer-reviewed literature. Moreover, the only reference to its lack of theoretical
explanation we found was in Linderoth’s (2013) blog post, in which the author shared an open
letter to Puentedura, inviting further dialogue and discussion. Puentedura shares his SAMR-
related work--which largely consists of copies of presentation slides--via his website. Within
these web-based materials, there exists limited explanations or details regarding how to
understand, interpret and apply the SAMR the model – in part or whole. Moreover, there are few
connections to theory and prior research, and there is limited qualitative or quantitative evidence
to support the differentiation of the SAMR levels. As a result of this lack of theoretical
explanations or explorations of the SAMR model, both teachers and others involved with
educational technology integration, such as professional development providers and technology
specialists, may be led to interpret and represent the SAMR model in different ways. For
example, results from a recent Google “Images” search provided differing representations of the
SAMR model, such as likening it to various depths of a swimming pool, different types of coffee
drinks, and the life cycle of technology adoption, among others (Figure 2).
Figure 2. Screenshot of a single search “SAMR” Google image search (December 2014)!
Vastly different representations can lead to misunderstandings and confusion, such as
with some of the SAMR depictions highlighted in Figure 2, as they actually reflect inconsistent
interpretations and understandings of the model. For example, in Brubaker’s (2013)
representation of SAMR, the four levels represent different types of coffee-based drinks (e.g.,
The Substitution Augmentation Modification Redefinition (SAMR) Model
black coffee [Substitution]; latte [Augmentation]; caramel macchiato [Modification]; and,
pumpkin spice [Redefinition]). Based on Brubaker’s (2013) interpretation and representation of
the SAMR model an educator could interpret using technology in education as making small
adjustments, just as adding pumpkin spice adjusts the flavor of a cup of coffee. Such
interpretation does not align with how Puentedura defines “Redefinition”.
Another example is Hooker’s (2014) SAMR Swimming Pool 2.0, which is a “remixed”
representation of the SAMR model. Hooker uses the SAMR model to represent students’ uses
and learning with technology and in this model, so that “Redefinition” is represented by a high
dive at the pool, in which students become their own lifeguards and invent the pool rules. This
representation of “Redefinition” suggests that students use technology to guide and facilitate
their own learning and is quite different than making small adjustments to one’s teaching with
technology, as represented by Brubaker’s (2013) visual. These examples demonstrate the
inconsistent ways in which individuals understand and visually represent the SAMR model.
The lack of systematic evidence further complicates how to accurately interpret and apply
the SAMR model. For example, in a recent presentation, Puentedura (2014b) shared Mueller and
Oppenheimer’s (2014) comparative study of students’ taking digital or longhand notes.
Puentedura notes this "switch" as a good example of “substitution.” In his presentation materials,
Puentedura focused on the change in the task (i.e., typing on a computer versus writing longhand
on paper), ignoring the authors’ important finding that this instance of substitution actually
resulted in a negative impact on student learning. In this instance, although Puentedura offers this
study as a positive example of substitution, the researchers’ findings actually argue against
substitution. Despite the larger implied message of the SAMR model, namely that teaching with
technology may be ranked and connected to one of four levels, using technology (even at the
substitution level) is not always better nor is it always necessary, as evidenced in the following
three challenges.
Challenge One: Absence of Context
Context is important in educational research and practice (Berliner, 2002). However, the
SAMR model includes no accommodation for context. As a result, important contextual
components, such as technology infrastructure and resources (Ertmer, 1999), community buy-in
and support (Zhao & Frank, 2003), individual and collective student needs (Lei, Conway, &
Zhao, 2008; Mishra & Koehler, 2006), and teacher knowledge and support for using technology
(Ertmer, Ottenbreit-Leftwich, Sadik, Sendurur, & Sendurur, 2012, Morsink et al., 2011) are not
recognized. We acknowledge there is no one uniform solution regarding integration and use of
educational technology. However, technology integration frameworks that are designed and put
forth without attention to context, such as the SAMR model, often over-generalize their
prescriptions and ignore the complex settings in which this technology integration occurs. For
example, a science teacher in a high-poverty middle school setting aims to create a computer-
supported investigation for her students so that each student could independently investigate a
particular phenomenon during a class period. However, she only has two classroom desktop
computers available for student use. In this instance, although the activity she creates may rank
“higher” on the SAMR ladder, in practice having ten students sit in front of one computer is both
practically and educationally not feasible. The contexts in which educators teach matters and is
an important consideration for any model connected to teaching and learning.
We know from prior research that differences in context contribute to (sometimes vastly)
different educational outcomes (Design-Based Research Collective, 2003; Kelchtermans, 2014).
It is a central tenet of both research and practice and is important for understanding and
The Substitution Augmentation Modification Redefinition (SAMR) Model
explaining motivation (Urdan, 1999), development (Eccles & Roeser, 2011), and teaching and
learning (Tabak, 2013). Berliner (2002) describes educational research as the hardest science
because of the difficulty of obtaining experimental control (more common in many natural
science fields) and the complexity of schools and classrooms. Modifying instruction through
technology is complex and should occur in tandem with teachers’ decisions and plans, which
often shift dynamically based upon noticing and responding to students’ learning within and
across contexts (Sherin & Van Es, 2005).
Context is also a helpful construct for studying the multi-faceted, complex nature of
educational settings (Porras-Hernández & Salinas-Amescua, 2013). Including context in models,
frameworks, and theories directs researchers’ and practitioners’ attention to the broader systems
in which teaching and learning with technology take place. The complex systems in which
teachers work impacts their learning and the decisions they make (Opfer & Pedder, 2011). As a
result, we know that teachers’ learning, pedagogy, and instructional practices as well as students’
learning experiences, are contextual and embedded within complex systems (Opfer & Pedder,
2011). Because SAMR does not acknowledge aspects of context, attempts to connect the SAMR
model to research and teaching practice may be a challenge.
Challenge Two: Rigid Structure
A taxonomy is a hierarchical framework in which categories are arranged in a graduated
order. The SAMR model is structured as a taxonomy that represents technology integration as
belonging to one of four categories. As a result, it dismisses the complexity of teaching with
technology by defining and organizing teachers’ uses of technology in predefined ways. As we
argue previously, there are educational models and frameworks that provide general guidance
rather than prescribe specific practices and assign value to different levels. For example, in
TPACK framework (Mishra & Koehler, 2006), teachers are informed about the necessary
components for effective use of technology in teaching, but no specific activities or practices are
suggested, based on the understanding that every teaching context is unique. Additionally, there
are other frameworks that are descriptive rather than prescriptive, such as descriptions of the
resources and teacher beliefs that serve as barriers to teachers use of technology (Ertmer, 1999).
In the SAMR model the emphasis remains on the levels of technology use teachers should align
themselves with in order to move themselves along the hierarchical continuum of SAMR. This
minimizes the more important focus on using technology in ways that emphasize shifting
pedagogy or classroom practices to enhance teaching and learning (Hennessey, Ruthven, &
Brindley, 2005; Hughes, 2005; Windschitl & Sahl, 2002).
As a taxonomy, the SAMR model represents the idea that teachers more effectively use
technology when they enact modification or redefinition, rather than substitution or
augmentation. For example, a table in one of Puentedura’s (2014a) recent presentations depicts
the idea that using technology in ways aligned with the hierarchical levels in the SAMR model
lead to better learning outcomes (Table 1). The four studies in the table were extracted from
Pearson, Ferdig, Blomeyer and Moran’s (2005) meta-analysis of 20 research articles connected
to specific uses of digital technologies and learning environments to enhance middle school
students’ literacy skills.
Table 1. SAMR levels and effect sizes (additional information added for clarity)
The Substitution Augmentation Modification Redefinition (SAMR) Model
Ligas (2002)
Xin & Reith
Higgins &
Raskind (2005)
Globerson &
Guterman (1989)
In their analysis, Pearson et al. (2005) refrain from a “one size fits all” approach to using
technology in middle-school literacy programs to enhance student learning. For example, the
authors argue that learner characteristics (e.g., students with exceptionalities) are an important
variable when examining outcomes from technology integration. They conclude that although
there exists reason to be optimistic about there is also a need for further research regarding the
use of digital technologies and learning environments to broaden the scope of specific middle
school student interventions and outcomes.
However, these studies are not necessarily representative of all of those in Pearson et al.’s
(2005) meta-analysis: The different effects sizes for the four studies Puentedura selected could
be due to varying population characteristics, measures, and the contexts in which these
interventions occurred. Instead, Puentedura uses four selected studies’ findings from Pearson et
al.’s meta-analysis to argue for a conclusion that may not be supported, namely that the various
levels of the SAMR model lead to “better” or “higher” outcomes. As a result, the effect sizes
from the four selected studies seem to have been chosen to advance the idea that better learning
outcomes are achieved for the modification and redefinition levels of the SAMR model, rather
than through a systematic process of evaluating the impact of different uses of technology. None
of these four studies were originally designed to give agency to technology. Rather, researchers
across all four studies focused on the interactions between learners and technology. For
example, Puentedura aligns Higgins and Raskind’s (2005) effect sizes with the Modification
level. In contrast to the notion that using technology at the modification or redefinition levels
leads to enhanced learning outcomes, Higgins and Raskind (2005) acknowledge that the effects
of technology use depend strongly on the nature of the teachers and students using it as well as
the specific task for which it is being used.
Aligned with the Redefinition level of the SAMR model, Puentedura relies on the effect
sizes reported in Salomon, Globerson, and Guterman’s (1989) study. These authors examined
whether an intellectual partnership (i.e., a student learning through the use of computer software)
could support students’ text comprehension and improve their writing ability. Despite the
positive results (as noted by the authors), the findings point to the positive impact of the
metacognitive-like guidance with which students were provided, not the actual technology itself.
In fact, the authors argue that the technology used in their study was still relatively
underdeveloped and primitive. Thus, one might ask whether similar results could be obtained
with the use of print-based, peer-based, or teacher-based guidance, instead of guidance that is
The Substitution Augmentation Modification Redefinition (SAMR) Model
computer-based. In making these comparisons using Pearson et al.’s (2005) work, Puentedura
(2014b) communicates the belief that technology integration along the SAMR ladder leads to
better results, a conclusion different from Pearson et al.’s (2005) original intentions and/or
Hierarchical representations, often reflected in taxonomies, inevitably depict the top
levels as more desirable than those at the bottom. In some instances, taxonomies may be a useful
construct for supporting understanding of phenomena (Anderson et al., 2001). For example,
teachers often rely on teaching-learning progressions (TLPs) (Alonzo & Gotwals, 2012) to
identify the development of knowledge and skill over time. Similarly, many teachers use
Bloom’s Taxonomy (1956), as well as its revised version (Krathwohl, 2002), to organize and
label teaching and learning using specific categories related to educational objectives.
Taxonomies, however, often reflect a perspective in which teaching and learning are linear
processes and belong to one exclusive category (Hamblen, 1984). Because of the continuous and
reciprocal nature of teaching and learning (Hmelo-Silver & Azevedo, 2006), it is difficult to
label and classify instructional objectives. Therefore such taxonomies, as is the case with the
SAMR model, are deterministic and linear, and are often in direct contrast with the dynamic
processes they seek to represent.
Challenge Three: Product over Process
The instructional design process starts and ends with learning objectives and learning
outcomes (Morrison, Ross & Kemp, & Kalman, 2010; Wang & Hannafin, 2005). However,
within the SAMR model, the technology integration process is simplified because the goal
centers on changing a product (i.e., instructional activity) rather than learning processes. To
illustrate, consider a high school English Language Arts (ELA) instructor who assigns an
interactive research report presentation that students must create using an online tool of their
choice. Focusing on the end product, however, he may inadvertently de-emphasize important
processes inherent to the research process such as supporting students’ understanding of online
presentation tools, the process of identifying, vetting and using reputable research, and the ways
in which students create and share their work with additional audiences. As a result, although
this integration of technology seemingly occurs at a higher level according to the SAMR model,
the process of student learning may not be enhanced, and may, in fact, suffer from the emphasis
on a technology-based product.
A recent definition of instructional technology acknowledges that using technology for
instructional purposes involves a systematic process of design (Reiser, 2012). Therefore, the
complexities inherent to the teaching and learning processes require us to consider education as a
process, rather than education the production of simplistic, independent stand-alone products.
This perspective toward learning as process rather than learning as product has important
pedagogical implications, especially in terms of interactions between the individuals and the
technologies that lead to cognitive changes (Salomon & Perkins, 2005).
From an instructional design perspective, technology plays a role in reaching learning
outcomes, but as long as objectives are reached, one instructional method or tool is not promoted
over others. When integrating technology, the purpose of this integration should be on enhancing
and supporting student learning rather than using a particular technology. In doing so, the
processes associated with teaching and learning remain central, rather than the specific
technology used to support these processes. However, in the SAMR model it appears that the
products, which are associated with the levels of SAMR, remain the focus rather than the
The Substitution Augmentation Modification Redefinition (SAMR) Model
important processes of meeting instructional objectives and achieving learning outcomes (Reiser
& Dempsey, 2012).
To support and extend student learning with technology, educators must seek out and use
flexible and adaptive, vetted frameworks that promote a deeper understanding of teaching and
learning rather than a focus on the affordances or constraints of a given tool (Mishra, Koehler, &
Kereluik, 2009). Within any framework connected to technology integration and/or teaching
with technology, an emphasis must be placed on teachers’ understanding of technology as
important precursors to teachers’ actual use (Inserra & Short, 2012). This requires teachers to
plan for and enact instruction that offers students meaningful technology-based learning
experiences, rather than focusing on “moving up” a hierarchical, techno-centric model.
Despite its increasing popularity, there are challenges to the SAMR model and its
potential applications as identified in the previous sections. Technology and other instructional
tools are intended to play supporting roles in the learning process. In the SAMR model, however,
Puentedura challenges teachers to differentiate their uses of technology(s) as a means of
examining what teachers can (and, perhaps, should) do. As a result, the emphasis is on what and
the type(s) of technology teachers should use to move themselves along the hierarchy, from
substitution and augmentation to modification and redefinition. This movement contrasts with
the more important focus on utilizing technology to emphasize pedagogy and practices that
support, and when possible, enhance teaching and learning (Hennessey, Ruthven, & Brindley,
2005; Hughes, 2005; Windschitl & Sahl, 2002). In its current form, the SAMR model is a task
and technology-focused model. Specifically, our analysis supports the inclusion of contextual
factors that inform teachers’ understanding and uses of technology.
Because the SAMR model has not been critically analyzed in the peer-reviewed
literature, educators involved with educational technology integration sometimes understand and
apply the SAMR model in fragmented ways which further complicates the ways in which the
SAMR model may be understood and applied. For example, in Pepe’s (2014) YouTube video,
SAMR Wheel of Fortune, she explains how the SAMR model is similar to the “Wheel of
Fortune” (in the game show of the same name). In her explanation, Pepe argues that the SAMR
model is not hierarchical but, rather, a fluid model of technology integration. This illustration, of
which many more exist, demonstrates fundamentally different interpretations of the SAMR
Conclusion and Suggestions
Although models such as SAMR have potential for guiding practitioners in their efforts
to navigate a complex landscape by seemingly simplifying a multifarious process, 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 visual representation of the SAMR model,
The Substitution Augmentation Modification Redefinition (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 & 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 &
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, Koehler, & Kereluik, 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 the students in the classroom. In this instance, the teacher’s
decision reflects the dynamic and fluid nature of teaching and learning.
Finally, contrary to what is implied by the SAMR model, we also suggest that technology
integration is neither an educational goal nor is it sufficient on its own to enhance learning
outcomes (Russell, Sorge, & Brickner, 1994). The SAMR model does not attend to these
processes and does not reflect the purposeful, recursive, and systematic process of instructional
design (Reiser, 2012). This is an important and problematic limitation, making it difficult to
suggest possible modifications because of the incompatibility between the SAMR model and the
complexities we know to be inherent to teaching with technology (e.g., Reiser & Dempsey,
2012; Wang & Hannafin, 2005).
With the ubiquity of technology in today’s interconnected world, it is imperative for
teachers to understand how to use technology to promote student learning and achievement (Lei,
Conway, & Zhao, 2008). Specifically, teachers must first understand the relationships between
teaching, technology, and learning to promote student growth and achievement (Koehler,
Mishra, Kereluik, Shin, & Graham, 2014). If they understand these relationships, they will be
better equipped to access and use technology to support and enhance student learning.
Alonzo, A. C., & Gotwals, A. W. (2012). Learning progressions in science: Current challenges
and future directions. New York, NY: Springer Science & Business Media.
The Substitution Augmentation Modification Redefinition (SAMR) Model
Anderson, L. W., Krathwohl, D. R., Airasian, P. W., Cruikshank, K. A., Mayer, R. E., Pintrich,
P. R., ... & Wittrock, M. C. (2001). A taxonomy for learning, teaching, and assessing: A
revision of Bloom's taxonomy of educational objectives, abridged edition. White Plains,
NY: Longman.
Bebell, D., Russell, M., & O’Dwyer, L. (2004). Measuring teachers’ technology uses: Why
multiple-measures are more revealing. Journal of Research on Technology in Education,
37, 45-63.
Berliner, D. C. (2002). Comment: Educational research: The hardest science of all. Educational
Researcher, 31(8), 18-20.
Bloom, B. (1956). Taxonomy of educational objectives (Vol. 1). New York: McKay.
Branch, R. M., & Merrill, M. D. (2012). Characteristics of instructional design models. In R.A.
Reiser & J. V. Dempsey (Eds.). Trends and issues in instructional design and technology
(3rd ed., pp. 8-16). Boston: Pearson.
Brubaker, J. (2013). SAMR: Model, metaphor, mistakes. Retrieved from
Design-Based Research Collective. (2003). Design-based research: An emerging paradigm for
educational inquiry. Educational Researcher, 32, 5-8.
Eccles, J. S., & Roeser, R. W. (2011). Schools as developmental contexts during adolescence.
Journal of Research on Adolescence, 21, 225-241.
Ertmer, P. A. (1999). Addressing first-and second-order barriers to change: Strategies for
technology integration. Educational Technology Research and Development, 47(4), 47-
Ertmer, P. A. (2005). Teacher pedagogical beliefs: The final frontier in our quest for technology
integration? Educational Technology Research and Development, 53(4), 25-39.
Ertmer, P. A., Ottenbreit-Leftwich, A. T., Sadik, O., Sendurur, E., & Sendurur, P.
(2012).Teacher beliefs and technology integration practices: A critical relationship.
Computers & Education, 59, 423-435.
Garrison, D. R., Anderson, T., & Archer, W. (1999). Critical inquiry in a text-based
environment: Computer conferencing in higher education. The Internet and Higher
Education, 2, 87-105.
The Substitution Augmentation Modification Redefinition (SAMR) Model
Hamblen, K. A. (1984). An art criticism questioning strategy within the framework of Bloom's
taxonomy. Studies in Art Education, 26, 41-50.
Hennessey, S., Ruthven, K., & Brindley, S. (2005). Teacher perspectives on integrating ICT into
subject teaching: commitment, constraints, caution, and change. Journal of Curriculum
Studies, 37(2), 155-192. doi: 10.1080/0022027032000276961
Higgins, E. L., & Raskind, M. H. (2005). The compensatory effectiveness of the Quicktionary
Reading Pen II® on the reading comprehension of students with learning disabilities.
Journal of Special Education Technology, 20(1), 31–40.
Hmelo-Silver, C. E., & Azevedo, R. (2006). Understanding complex systems: Some core
challenges. The Journal of the Learning Sciences, 15, 53-61.
Hooker, C. (2014). SAMR swimming lessons. Retrieved from
Hughes. J. (2005). The role of teacher knowledge and learning experiences in forming
technology-integrated pedagogy. Journal of Technology and Teacher Education, 13, 277-
Inserra, A., & Short, T. (2012). An analysis of high school math, science, social studies,
English,and foreign language teachers' implementation of one-to-one computing and their
pedagogical practices. Journal of Educational Technology Systems, 41, 145-169.
International Society for Technology in Education. (2015). ISTE standards. Retrieved from
Kelchtermans, G. (2014). Context matters. Teachers and Teaching, 20, 1-3.
Krathwohl, D. R. (2002). A revision of Bloom's taxonomy: An overview. Theory into practice,
41, 212-218.
Koehler, M. J., & Mishra, P. (2008). Introducing TPCK. In AACTE Committee on Technology
and Innovation (Eds.), Handbook of Technological Pedagogical Content Knowledge
(TPCK) for educators (pp. 3–29). New York, NY: Routledge.
Koehler, M., Mishra, P., Kereluik, K., Shin, T., and Graham, C.R. (2014). The technological
pedagogical content knowledge framework. In J. M. Spector, M. D. Merrill, J. Elen & M.
J. Bishop (Eds.), Handbook of research on educational communications and technology
(pp. 101-111). New York, NY: Springer.
The Substitution Augmentation Modification Redefinition (SAMR) Model
Lei, J., Conway, P. F., & Zhao, Y. (2008). The digital pencil: One-to-one computing for
children. Mawhaw, NJ: Erlbaum.
Linderoth, J, (2013, October 17). Open letter to Dr. Ruben Puentedura [Blog post]. Retrieved
Mishra, P., & Koehler, M. (2006). Technological pedagogical content knowledge: A framework
for teacher knowledge. Teachers College Record, 108(6), 1017-1054.
Mishra, P., Koehler, M. J., & Kereluik, K. (2009). Looking back to the future of educational
technology. TechTrends, 53(5), 48-53.
Morrison, G. R., Ross, S. M., Kemp, J. E., & Kalman, H. (2010). Designing effective instruction.
Hoboken, NJ: John Wiley & Sons.
Morsink, P. M., Hagerman, M. S., Heintz, A., Boyer, M. D., Harris, R., Kereluik, K., . . . Withey,
K. (2011). Professional development to support TPACK technology integration: The
initial learning trajectories of thirteen fifth and sixth grade educators. Journal of
Education, 191(2), 1-18.
Mueller, P.A., & Oppenheimer, D.M. (2014). The pen is mightier than the keyboard: Advantages
of longhand over laptop note taking. Psychological Science, 25, 1159-1168.
Opfer, V. D., & Pedder, D. (2011). Conceptualizing Teacher Professional Learning. Review of
Educational Research, 81(3), 376-407. doi: 10.3102/0034654311413609
Pearson, P.D., Ferdig, R.E., Blomeyer, R.L. Jr., & Moran, J. (2005). The effects of technology on
reading performance in the middle-school grades: A meta-analysis with
recommendations for policy. Naperville, IL: Learning Point Associates.
Pepe, C. [Device Smashing Diva]. (2014, January 3). SAMR Wheel of Fortune [Video file].
Retrieved from
Porras-Hernández, L. H., & Salinas-Amescua, B. (2013). Strengthening TPACK: A broader
notion of context and the use of teacher's narratives to reveal knowledge construction.
Journal of Educational Computing Research, 48, 223-244.
Puentedura, R. (2006). Transformation, technology, and education [Blog post]. Retrieved from
Puentedura, R. (2014a). Building transformation: An introduction to the SAMR model [Blog
post]. Retrieved from
The Substitution Augmentation Modification Redefinition (SAMR) Model
Puentedura, R. (2014b). Learning, technology, and the SAMR model: Goals, processes, and
practice [Blog post]. Retrieved from
Reiser, R.A. (2012). What field did you say you were in? Defining and naming our field. In R.A.
Reiser & J. V. Dempsey (Eds.). Trends and issues in instructional design and technology
(3rd ed., pp. 1-7). Boston, Massachusetts: Pearson.
Reiser, R. A., & Dempsey, J. V. (2012). Trends and issues in instructional design and
technology (3rd ed.). Boston, Massachusetts: Pearson.
Russell, J. D., Sorge, D., & Brickner, D. (1994). Improving technology implementation in
grades5-12 with the ASSURE model. THE Journal (Technological Horizons In
Education), 21(9), 66-70. Retrieved from
journal technological-horizons-in-education
Salomon, G., Globerson, T., & Guterman, E. (1989). The computer as a zone of proximal
development: Internalizing reading-related metacognitions from a Reading
Partner.Journal of Educational Psychology, 81(4), 620-627.
Salomon, G., & Perkins, D. (2005). Do technologies make us smarter? Intellectual amplification
with, of, and through technology. In R. J. Sternberg & D. D. Preiss (Eds.), Intelligence
and technology: The impact of tools on the nature and development of human abilities
(pp. 69–86). Mahwah, New Jersey: Lawrence Erlbaum Associates.
Sherin, M., & van Es, E. (2005). Using video to support teachers’ ability to notice classroom
interactions. Journal of Technology and Teacher Education, 13, 475-491.
Tabak, I. (2013). Lights, camera, learn: When the set is as important as the actors. In R. Luckin,
S. Puntambekar, P. Goodyear, B.L. Grabowski, J. Underwood, & N. Winters (Eds.),
Handbook of Design in Educational Technology (pp. 397-405). New York, NY:
Urdan, T. (1999). The role of context. Bingley, UK: Emerald Group Publishing.
Wang, F., & Hannafin, M. J. (2005). Design-based research and technology-enhanced learning
environments. Educational Technology Research and Development, 53(4), 5-23.
Windschitl, M., & Sahl, K. (2002). Tracing teachers’ use of technology in a laptop computer
school: The interplay of teacher beliefs, social dynamics, and institutional culture.
American Educational Research Journal, 39, 165-205.
The Substitution Augmentation Modification Redefinition (SAMR) Model
Zhao, Y., & Frank, K. A. (2003). Factors affecting technology uses in schools: An ecological
perspective. American Educational Research Journal, 40, 807-840.
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... Nowadays, people use digital devices to look for information on the internet. So, technology has been part of peoples' lives for centuries changing their daily activities, which can be done by using mobile phones, computers, and other devices (Hamilton et al., 2016). In Ecuador, internet use has risen to a 1,5% in 2020 (Alvino, 2021). ...
... The four steps are Substitution, Augmentation, Modification, and Redefinition; they are categorized into two levels enhancement and transformation. The first two levels are enhancements, including Substitution and augmentation; the last two levels are transformation and include modification and redefinition (Aldosemani, 2019;Hamilton et al. 2016). The model is shown in figure 1 bellows The first dimension or step is Substitution; it acts as a direct channel to change the traditional tools into digital ones. ...
... The Augmentation dimension also substitutes technology by allowing teachers and students to use it differently. For example, teachers deliver a task to students, and they have to use technological devices to finish the activity (Hamilton et al., 2016). Teachers need to implement tasks with higher thinking skills using technology for the last two dimensions (Modification and Redefinition). ...
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This article focuses on understanding the perceptions of 31 Ecuadorian teachers and 34 Ecuadorian university students about the Puentedura Substitution, Augmentation, Modification, and Redefinition (SAMR) model in the English class. It has helped teachers integrate technology into their classes. The tool used to evaluate the model consisted of 20 items with 5 questions for each SAMR dimension. The reliability of the model was measured with McDonald's ω (0.94) in a general context and each dimension (S: (ω=0.88), A: (ω=0.82), M: (ω=0.85) R: ω=0.87)). The results on the perceptions of teachers and students were very enlightening to understand how they implement technology in English classrooms before and after the pandemic. They consider the use of technological tools to be beneficial for learning English as a foreign language.
... Original teaching methods had to be discarded, leading to a significant transformation into emergency response teaching (ERT) for teachers without proper planning, implementation, or quality assurance [2]. As a result, ERT was assumed to be just a substitution according to the substitution augmentation modification redefinition (SAMR) model [3]. Students had to adapt their learning, too. ...
... Even if ERT is different from online learning [2], lessons learned from the pandemic may help to develop methods and ways to overcome certain barriers. In addition, an evaluation of possibilities for overcoming barriers in an ERT situation, in which most physical activities were converted into an online substitution, will help reach a higher level within the SAMR model [3]. In general, the presence of barriers requires various stakeholders to perceive and resolve them. ...
... Otherwise, students will experience a mismatch among the three domains. According to the SAMR framework [3], a real transformation must address the creation of new tasks through technology. These new tasks might address pedagogy or content knowledge. ...
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The COVID-19 pandemic forced a transition to digital teaching in higher education institutions (HEIs) as itwas the only safe method for higher education (HE) teaching during the pandemic. However, this crisis emphasized the barriers students face worldwide. For digital HE teaching to survive in the future, these barriers should be overcome. The present paper aimed to systematically identify these barriers and present recommendations to overcome them. For this purpose, a quantitative survey (n = 369) was conducted with students in three countries, and qualitative student statements were analyzed. Possible countermeasures for corresponding barriers are described, and related stakeholders are identified. Thus, the study provided an overview of recommendations for stakeholders to overcome the barriers. The recommendations to resolve most barriers entail offering hybrid formats, adjusting lecture design, and ensuring proper communication.
... Over the last 30 years, technology-supported learning environments have evolved from static, two-dimensional delivery (i.e.., websites and course management systems [CMS]) to dynamic, immersive environments in varying capacities (Huang et al., 2019). Educational technology can move beyond merely sustaining traditional educational practices in digital form (Cuban et al., 2001) or merely augmenting them with functional improvements (Hamilton et al., 2016), ultimately enabling teaching and learning to be transformed in meaningful ways such as how augmented and virtual reality can be used to support learning environments. Another area where technology supports learning is with the use of disciplinary tools or devices that are used by professionals in their respective fields. ...
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... Working with the integration of technology into learning methodology over study process requires strong analysis by looking on how technology enhances and extends studies in general. Relaying on this, we proposed to apply SAMR (Substitution, Augmentation, Modification, and Redefinition) model (Hamilton et al., 2016;Puentedura, 2015) to the course of "Robot Programming Technologies" intended for the first cycle BSc students. It is worth to note here that first steps of inquiry-based learning in this course started in 2018, thus the results, which we showed in this chapter, includes 4 years of IBL based teaching also learning experience. ...
In order to address emerging societal challenges, school education must be radically restructured, adopting a dynamic character to cover and adapt to each student’s academic and social needs. Technology has the means to stand as a valuable facilitator to this end, and teachers should acquire the appropriate pedagogical and technological training to design informal and dynamic environments using technology. In the wake of the above, the aim of the current qualitative research is to define the pedagogical and technological skills for establishing an organized training plan for the teachers of the specific school unit, in matters of inclusive digital education. The needs analysis research was conducted in a Greek primary school and lasted 4 months, involving two fifth grade classes and an integration class in which students with learning difficulties are provided with personalized training for a few hours every day and are separated from their classmates. The study employed non-participatory observation and semi-structured interviews. The study’s findings bring to light misconceptions in teaching methods and entrenched beliefs about the use of technology, highlighting issues related to the need for systematic training of teachers in inclusive digital education. To address these barriers, this work proposes a training plan based on an innovative scenario. The scenario involves the use of informal learning environments by teachers, such as digital museums and digital applications and describes the educational process to be followed during its implementation, so that digital tools are used by teachers in an inclusive way.KeywordsCitizen scienceDigital skillsDigital storytellingInclusive educationNew digital pedagogiesText- based game
This chapter draws upon a critical analysis of two professional accreditation frameworks and the influence these have had on the development of academic staff digital capabilities for teaching and learning. The Advance HE Fellowship ( is an internationally recognised higher education accreditation framework with over 140,000 staff recognised globally. The Certified Member of the Association for Learning Technology (CMALT) ( framework is aligned to technology-enhanced learning (TEL) continuing professional learning development (CPLD) standards and is supported in Australasia by the Australasian Society for Computers In Learning In Tertiary Education (ASCILITE) ( The chapter discusses the extent to which the broader Advance HE Fellowship perpetuates traditional on-campus approaches to teaching and learning and explores how the use of CMALT may help to increase the impact of TEL CPLD across the wider HE sector. This reflection draws upon research into a closer mapping between CMALT and Advance HE frameworks and how this might encourage higher engagement across CMALT as well as Advance HE.
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Gamified flipped learning has become admired in language teaching and learning as a creative and effective way to improve student learning and encourage them to comprehend and process new knowledge. The purpose of this study was to investigate how a gamified flipped EFL classroom affected second-grade students’ vocabulary learning in a private Turkish school. The students were assigned into two groups: experimental and control. There were 20 participants in the experimental group, and 20 in the control group. Teacher reflective journals and structured student interviews were used in this study. Following the treatment of the experimental group, both the control and experimental groups were given a posttest. The results of this study’s experimental group posttest attempted to show that using gamified flipped classrooms improved the experimental group’s mean score, and also had a positive impact on students’ engagement, and increased their motivation toward learning in in-class gamified activities. The key findings of structured interviews were students wanted more interaction inside the videos. They also claimed that they liked the use of hands-on activities in online synchronous classes instead of having only instruction.KeywordsFlipped learningGamificationEFLGamified flipped learningPrimary studentsVocabulary learning
Even if there is no precise definition of hybrid teaching, it is generally referred to as having both face-to-face and remote audiences for the same class of students. Hybrid teaching has peculiar features in the way it integrates technology into educational spaces. This paper aims at understanding how first-year university students approach and take advantage of the features of hybrid teaching. The research has been carried out through a quantitative and qualitative study within a first-year module in Mathematics and Biostatistics at the Bachelor’s degree in Biotechnology at the University of Turin. In this module, students could not only choose whether to attend classes face-to-face or remotely, but they were also supported by an online course with all the useful contents: recording of lectures, presentation of course contents, interactive resources, in-depth materials, and assessment with feedback. Results show a high appreciation of hybrid teaching and its benefits, usefulness, simplicity, high flexibility, facilitation of students’ time management, and fulfillment of learning needs, giving additional value to face-to-face attendance.KeywordsDigital educationHybrid teachingOnline learning
Robotics plays a key role in today’s digital systems. It influences every aspect of human life: daily work, home, industry, transport, aviation, etc. Thus, it is important to raise motivated and gifted generation of young programmers with abilities to create bridges between physical and digital worlds under robotics. Traditional learning in programming of robots cannot meet the needs of students with different capabilities as well as challenges raised by the industry. Inquiry-based learning gives a possibility to pose questions, challenges, and problems for students themselves, thus providing self-realization and self-awareness towards building and improving their abilities. Moreover, the methodology of inquiry-based learning gives well-structured active student-oriented inclusive education in programming of robots. This chapter presents state-of-the-art in programming of robots using inquiry-based learning under inclusive education umbrella. Additionally, the study provides with the application of inquiry-based teaching approaches for the first cycle students with focus on gifted students, their experience of learning; feedback is described in particular sections of this chapter. The evaluation of changes in the abilities of students, who learned programming of robots, which in the long-term period serves as numerical results, is presented in this chapter as well.KeywordsInquiry-based learningRoboticsCritical thinkingStudent-oriented educationGifted studentsReflection
For years, researchers and practitioners alike have searched for meaningful ways to describe or evaluate how technology was being integrated into teaching or to what level. This article will briefly summarize some of the predominant lenses through which to view technology integration and propose a new model for designing meaningfully technology-integrated instruction.
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This study examined the initial learning trajectories of 13 upper elementary teachers as they developed technological, pedagogical, and content knowledge (TPACK) while participating in a 7-month professional development program focused on integrating technology into their classroom practice. The program was collaborative and non-prescriptive: teachers worked on self-chosen summer projects with flexible support from a university-based partner. A descriptive multicase study design was employed to track teachers' learning progressions. Data included interviews, surveys, digital artifacts, and researchers' notes and memos. During the program, teachers developed varying degrees of TPACK. Analyses distilled six initial TPACK learning trajectories.
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Although the conditions for successful technology integration finally appear to be in place, including ready access to technology, increased training for teachers, and a favorable policy environment, high-level technology use is still surprisingly low. This suggests that additional barriers, specifically related to teachers' pedagogical beliefs, may be at work. Previous researchers have noted the influence of teachers' beliefs on classroom instruction specifically in math, reading, and science, yet little research has been done to establish a similar link to teachers' classroom uses of technology. In this article, I argue for the importance of such research and present a conceptual overview of teacher pedagogial beliefs as a vital first step. After defining and describing the nature of teacher beliefs, including how they are likely to impact teachers' classroom practice I describe important implications for teacher professional development and offer suggestions for future research.
Context is an essential aspect of educational research. In this chapter, the authors discuss how context has been avoided or has referred to different constructs among educational technology research, especially among research on the Technological Pedagogical Content Knowledge (TPACK) framework. The authors discuss the descriptive, inferential, and practical implications of the framework for the context of teachers' TPACK advanced by Porras-Hernández and Salinas-Amescua (2013). Then, they exemplify the power of this framework by using it to guide a descriptive study conducted to determine the extent to which the publications included context. They also describe what researchers meant by context as understood through the framework for context. The authors found that context was important but often missing from research about TPACK and that the meaning of context has differed widely. They discuss these findings in relation to the TPACK literature as well as for educational technology research.
In this chapter, we introduce a framework, called technological pedagogical content knowledge (or TPACK for short), that describes the kinds of knowledge needed by a teacher for effective technology integration. The TPACK framework emphasizes how the connections among teachers’ understanding of content, pedagogy, and technology interact with one another to produce effective teaching. Even as a relatively new framework, the TPACK framework has significantly influenced theory, research, and practice in teacher education and teacher professional development. In this chapter, we describe the theoretical underpinnings of the framework, and explain the relationship between TPACK and related constructs in the educational technology literature. We outline the various approaches teacher educators have used to develop TPACK in pre- and in-service teachers, and the theoretical and practical issues that these professional development efforts have illuminated. We then review the widely varying approaches to measuring TPACK, with an emphasis on the interaction between form and function of the assessment, and resulting reliability and validity outcomes for the various approaches. We conclude with a summary of the key theoretical, pedagogical, and methodological issues related to TPACK, and suggest future directions for researchers, practitioners, and teacher educators.