{"id":9272,"date":"2020-02-05T15:06:36","date_gmt":"2020-02-05T15:06:36","guid":{"rendered":"https:\/\/citejournal.org\/\/\/"},"modified":"2020-05-18T18:08:06","modified_gmt":"2020-05-18T18:08:06","slug":"the-picrat-model-for-technology-integration-in-teacher-preparation","status":"publish","type":"post","link":"https:\/\/citejournal.org\/volume-20\/issue-1-20\/general\/the-picrat-model-for-technology-integration-in-teacher-preparation","title":{"rendered":"The PICRAT Model for Technology Integration in Teacher Preparation"},"content":{"rendered":"\n
Teaching technology integration requires teacher\neducators to grapple with (a) constantly changing, politically impacted\nprofessional requirements, (b) continuously evolving educational technology\nresources, and (c) varying needs across content disciplines and contexts. Teacher\neducators cannot foresee how their students may be expected to use educational\ntechnologies in the future or how technologies will change during their\ncareers. Therefore, training student teachers to practice technology integration\nin meaningful, effective, and sustainable ways is a daunting challenge. We propose\nPICRAT, a theoretical model for responding to this need.<\/p>\n\n\n\n
Though these models are commonly\nreferenced throughout the literature to justify methodological approaches for\nstudying educational technology, little theoretical criticism and minimal evaluative\nwork can be found to gauge their efficacy, accuracy, or value, either for\nimproving educational technology research or for teaching technology\nintegration (Kimmons, 2015; Kimmons & Hall, 2017). Relatively few researchers\nhave devoted effort to critically evaluating these models, categorizing and\ncomparing them, supporting their ongoing development, understanding assumptions\nand processes for adopting them, or exploring what constitutes good theory in\nthis realm (Archambault & Barnett, 2010; Archambault & Crippen, 2009;\nBrantley-Dias & Ertmer, 2013; Graham, 2011; Graham, Henrie, & Gibbons,\n2014; Kimmons, 2015; Kimmons & Hall, 2016a, 2016b, 2017). <\/p>\n\n\n\n
In other words, educational technologists seem\nto be heavily involved in what Kuhn (1996) considered \u201cnormal science\u201d without\ncritically evaluating competing models, understanding their use, and exploring their\ndevelopment over time. Reticence to engage in critical discourse about theory\nand realities that shape practical technology integration has serious\nimplications for practice, leading to what Selwyn (2010) described as \u201can\nobvious disparity between rhetoric and reality [that] runs throughout much of\nthe past 25 years of educational technology scholarship\u201d (p. 66), leaving promises\nof educational technologies relatively unrealized.<\/p>\n\n\n\n
Needing a critical discussion of extant\nmodels and theoretical underpinnings of practice, we provide a conceptual\nframework, including (a) what theoretical models are and why we need them for\nteaching technology integration, (b) how they are adopted and developed over\ntime, (c) what makes them good or bad, and (d) how existing models of\ntechnology integration cause struggle in teacher preparation. With this\nbackdrop, we propose a new theoretical model, PICRAT, built on the previous\nwork of Hughes et al. (2006), which can guide student teachers in developing\ntechnology integration literacies.<\/p>\n\n\n\n
Theoretical\nModels<\/h2>\n\n\n\n
Authors frequently use terms such as model<\/em>, theory<\/em>, paradigm<\/em>, and framework<\/em> interchangeably (e.g., paradeigma <\/em>is Greek for pattern, illustration, or model; cf. Dubin, 1978; Graham et al., 2014; Kimmons & Hall, 2016a; Kimmons & Johnstun, 2019; Whetten, 1989). However, we rely on the term theoretical model <\/em>for technology integration models, as it encapsulates the conceptual, organizational, and reflective nature of constructs we discuss.<\/p>\n\n\n\n
Model Purposes and Components<\/h3>\n\n\n\n
A theoretical model conceptually represents\nphenomena, allowing individuals to organize and understand their experiences,\nboth individually and interactively. All disciplines in hard and social\nsciences utilize theoretical models, and professionals use these models to make\nsense of natural and social worlds that are inherently unordered, complex, and\nmessy. Summarizing Dubin\u2019s (1978) substantial work on theory development,\nWhetten (1989) explained four essential elements for all theoretical models: the\nwhat, how, why, and who\/where\/when. First, models must include sufficient variables,\nconstructs, concepts, and details explaining the what<\/em> of studied phenomena to make the theories comprehensive but sufficiently\nlimited to allow for parsimony and to prevent overreaching. <\/p>\n\n\n\n
Second, models must address how<\/em> components are interrelated: the\ncategorization or structure of the model allowing theorists to make sense of\nthe world in novel ways. Third, models must provide logic and rationale to\nsupport why<\/em> components are related in\nthe proposed form. Herein the model\u2019s assumptions generally linger (explicitly\nor implicitly); its argumentative strength relies on the theorist\u2019s ability to\nmake a strong case that it is reasonable. <\/p>\n\n\n\n
Fourth, models must be bounded by a\ncontext representing the who, where, <\/em>and when <\/em>of its application. Models are not\ntheories of everything; by bounding the model to a specific context (e.g., U.S.\nteacher education), theorists can increase purity and more readily respond to\ncritics (Dubin, 1978).<\/p>\n\n\n\n
Many teacher educators adopt technology\nintegration models in anarchic ways or according to camps (Feyerabend, 1975;\nKimmons, 2015; Kimmons & Hall, 2016a; Kimmons & Johnstun, 2019). That\nis, they use models enculturated to them via their own training without\njustification or comparison of competing models. Literature reflects these\ncamps, as instruments are built and studies are framed without comparison of models\nor rationales for choice (cf. Kimmons, 2015b). Each camp speaks its own\nlanguage (TPACK, TIM, TAM, SAMR, LoTi, etc.), neither recognizing other camps nor\nacknowledging relationships to them. <\/p>\n\n\n\n
Whether this disconnect results from theoretical\nincommensurability or opportunism (cf. Feyerabend, 1975; Kuhn, 1996), we advise\ntheoretical pluralism: \u201cthat various models are appropriate and valuable in\ndifferent contexts\u201d (Kimmons & Hall, 2016a, p. 54; Kimmons & Johnstun,\n2019). Thus, we do not perceive a need to conduct \u201cparadigm wars that seek to establish\na single theoretical perspective or methodology as superior,\u201d considering such\nto be an \u201cunproductive disputation\u201d (Burkhardt & Schoenfeld, 2003, p. 9). <\/p>\n\n\n\n
We contend, however, that the field\u2019s ongoing adoption of theoretical models with little discussion of their affordances, limitations, contradictions, and relationships to others is of serious concern, because \u201cno [model] ever solves all the problems it defines,\u201d and \u201cno two [models] leave all the same problems unsolved\u201d (Kuhn, 1996, p. 110). The difficulty with theoretical camps in this field is not pluralism but absence of mutual understanding and meaningful cross-communication among camps, along with the failure to weigh the advantages and disadvantages of competing theories, revealing that educators do not take them seriously (Willingham, 2012). Unwillingness to dialogue across camps or to evaluate critically the underlying theories shaping diverse camps leads to professional siloing and prevents our field from effectively grappling with the multifaceted complexities of technology integration in teaching. <\/p>\n\n\n\n
A Good\nModel for Teaching Technology Integration <\/h3>\n\n\n\n
Kuhn (2013) argued for a structure to\nmodel adoption, with core characteristics identifying certain theoretical\nmodels as superior. These characteristics vary somewhat by field and context of\napplication; theoretical models in this field serve different purposes than do\nmodels in the hard sciences, and teacher educators will utilize models\ndifferently than will educational researchers or technologists (Gibbons &\nBunderson, 2005). <\/p>\n\n\n\n
Kimmons and Hall (2016a) said, \u201cDeterminations\nof [a model\u2019s] value are not purely arbitrary but are rather based in\nstructured value systems representing the beliefs, needs, desires, and intents\nof adoptees\u201d in a particular context (p. 55). Six criteria have been proposed\nfor determining quality of teacher education technology integration models: (a)\nclarity, (b) compatibility, (c) student focus, (d) fruitfulness, (e) technology\nrole, and (f) scope (see Table 1).<\/p>\n\n\n\n
Table 1<\/strong> Six Criteria and Guiding Questions for Evaluating Technology Integration Models for Student Teachers<\/p>\n\n\n\n
Is the model sufficiently simple, clear, and easy to understand, with no hidden complexities?<\/td>\n<\/tr>\n
\n\t
Compatibility<\/td>
Does the model complement\/support existing educational practices deemed valuable to teachers?<\/td>\n<\/tr>\n
\n\t
Fruitfulness<\/td>
Does the model elicit fruitful thinking as teachers grapple with problems of technology integration?<\/td>\n<\/tr>\n
\n\t
Technology Role <\/td>
Does the model treat technology integration as a means for achieving specific pedagogical or other benefits (rather than an end in itself)?<\/td>\n<\/tr>\n
\n\t
Scope<\/td>
Is the model sufficiently parsimonious to ignore aspects of technology integration not useful to teachers, but sufficiently comprehensive to guide their practice?<\/td>\n<\/tr>\n
\n\t
Student Focus<\/td>
Does the model clearly emphasize students and student outcomes?<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n\n\n
First, technology integration models should be \u201csimple and easy to understand conceptually and in practice\u201d (Kimmons & Hall, 2016a, pp. 61\u201362), eschewing explanations and constructs that invite confusion and \u201chidden complexity\u201d (Graham, 2011, p. 1955; Kimmons, 2015). Ideally, a model is concise enough to be quickly explained to teachers and easily applied in their practice \u2014 intuitive, practical, and easy to value. Models requiring lengthy explanation, introducing too many constructs, or diving into issues not central to teachers\u2019 everyday needs should be reevaluated, simplified, or avoided.<\/p>\n\n\n\n
Second, compatibility (i.e., alignment)\nwith \u201cexisting educational and pedagogical practices\u201d (Kimmons & Hall,\n2016a, p. 55) is important. Teachers want practical models that help them\naddress everyday classroom issues with limited conceptual overhead. We\nconcluded the following in an earlier empirical study: <\/p>\n\n\n\n
Teachers find themselves in a world driven by external requirements for their own performance and the performance of their students, and broad, theoretical discussions about how technology is transforming the educational system are not very helpful…. The typical teacher seems to be most concerned with addressing the needs of the local students under their care in the manner prescribed to them by their institutions. (Kimmons & Hall, 2016b, p. 23)<\/p><\/blockquote>\n\n\n\n
Thus, technology integration models should\nemphasize \u201cdiscernible impact and realistic access to technologies\u201d (p. 24)\nrather than broad concepts (e.g., social change) or unrealistic technological\nrequirements (e.g., 1:1 teacher\u2013device ratios in poor communities).<\/p>\n\n\n\n
Third, fruitful models should encourage adoption\namong \u201ca diversity of users for diverse purposes and yield valuable results\ncrossing disciplines and traditional silos of practice\u201d (Kimmons & Hall,\n2016a, p. 58). We intend that technology integration models used to teach\nteachers should elicit fruitful thinking: yielding connections and thoughtful\nlines of questioning, expanding across multiple areas of practice in ways that\nwould not have occurred without the model, and yielding insights beyond the\ninitial scope of the model\u2019s implementation.<\/p>\n\n\n\n
Fourth, technology\u2019s role should serve as a means to an end, not an end in itself \u2014 avoiding technocentric thinking (Papert, 1987, 1990). Though referred to as technology integration models<\/em>, their goal should go beyond integration to emphasize improved pedagogy or learning. The model should not merely guide educators in using technology without a foundation for justifying its use. This means-oriented view should place technology as one of many factors to influence desired outcomes.<\/p>\n\n\n\n
Fifth, suitable scope is necessary for\nguiding practitioners in the what<\/em>, how<\/em>, and why<\/em> of technology integration. While being compatible with existing\npractices, models should also influence teachers in better-informed choices\nabout technology use. As Burkhardt and Schoenfeld (2003) explained,<\/p>\n\n\n\n
Most of the theories that have been applied to education are quite broad. They lack what might be called \u201cengineering power\u201d … [or] the specificity that helps to guide design, to take good ideas and make sure that they work in practice. … Education lags far behind [other fields] in the range and reliability of its theories. By overestimating theories\u2019 strength … damage has been done. … Local or phenomenological theories … are currently more valuable in design. (p. 10)<\/p><\/blockquote>\n\n\n\n
In this way \u201cscope and compatibility may\nseem at odds … models that excel in compatibility may be perceived as\nsupporting the status quo, while models with global scope may be perceived as\nsupporting sweeping change\u201d (Kimmons & Hall, 2016a, p. 57). However, a good\nmodel balances comprehensiveness and parsimony (Dubin, 1978), both guiding\nteachers practically and prompting them conceptually in critically evaluating\ntheir practice against a larger backdrop of social and educational problems. Any\nsuch model should seek to apply to all education professionals broadly while\nfixating on a \u201cpopulation of exactly one\u201d (p. 137). In our context, a model\u2019s\nscope should focus squarely on student teachers, with possible applicability to\npracticing teachers and others as well.<\/p>\n\n\n\n
Finally, student focus is vital for a technology integration model. As Willingham (2012) explained, \u201cchanges in the educational system are irrelevant if they don\u2019t ultimately lead to changes in student thought\u201d (p. 155). Too often the literature surrounding technology integration ignores students in favor of teacher- or activity-centered analyses of practice: perhaps the technology\u2013pedagogy relationship or video as lesson enhancement. \u201cThough some models may allude to student outcomes, they may not give these outcomes … [primacy] in the technology integration process\u201d (Kimmons & Hall, 2016a, p. 61), which may signal to teachers that student considerations are not of primary importance. <\/p>\n\n\n\n
Each of the most popular technology integration models has strengths and weaknesses. To justify the need for a model better suited for the field, we summarize in this section the major limitations or difficulties inherent to seven existing models \u2014 LoTi, RAT, SAMR, TAM, TIM, TIP, and TPACK \u2014 in the context of guiding technology integration for student teachers. This brief summary will not do justice to the benefits of each of these models. Additional detail may be obtained from the previously referenced publications, including Kimmons and Hall (2016a). <\/p>\n\n\n\n
We may be critiqued for providing strawman\narguments against models or ignoring their affordances, but we have chosen merely\nto suggest that these might be areas where each of these models may have\nlimitations for teacher education. Several of these areas have been explored in\nprior literature, whereas others are drawn from our own experiences as teacher\neducators in the technology integration space, briefly summarized in Table 2. Additionally,\nthese critiques may not apply in other education-related contexts (e.g.,\neducational administration or instructional design) and are squarely focused on\nteacher education. Even though we do not provide ironclad arguments or evidence\nfor each claim listed in the subsequent section (doing so would require\nmultiple studies and book-length treatment), voicing these frustrations is\nnecessary for proceeding and for articulating a gap in this professional space.\nIn sum, our goal is not to convince anyone that each enumerated difficulty is\nincontrovertibly true but merely to provide transparency about our own\nreasoning and experiences.<\/p>\n\n\n\n
Table 2<\/strong> Difficulties Using Prominent Models in Teacher Education<\/p>\n\n\n\n
\n\n
\n\t
Model<\/strong><\/th>
Primary Limitations, Criticisms, or Difficulties<\/strong><\/th>
Further Reading<\/strong><\/th>\n<\/tr>\n<\/thead>\n\n
\n\t
LoTi<\/td>
Fruitfulness: Too many levels are provided (seven on a single axis), level distinctions are difficult, and teachers may not agree with hierarchical claims or find value in the hierarchy.<\/td>
Moersch (1995)<\/td>\n<\/tr>\n
\n\t
RAT<\/td>
Clarity: Transformation <\/em>can be difficult for teachers to understand (and is a contested construct). \n Student Focus: Students are implied in pedagogy but are not central.<\/td>
Hughes, Thomas, & Scharber (2006)<\/td>\n<\/tr>\n
\n\t
SAMR<\/td>
Clarity: Level boundaries are unclear (e.g., substitution <\/em>vs. augmentation<\/em>). \n Fruitfulness: Level distinctions may not be meaningful for practitioners. \n Student Focus: Student activities are implied at each level but are not explicit or inherent in each level\u2019s definition.<\/td>
Puentedura (2003)<\/td>\n<\/tr>\n
\n\t
TAM<\/td>
Compatibility: Not education- or learning-focused but is rather focused on user perceptions of technology usefulness (i.e., researcher or administrator focus). \n Fruitfulness: Emphasis on user perceptions and adoption yields little value for teachers. \n Role of Technology: Technology adoption is the goal. \n Scope: Not parsimonious enough to focus on educators and students, but also not comprehensive enough to account for pedagogy, et cetera. \n Student Focus: Students are not included or implied (teacher use only).<\/td>
Venkatesh, Morris, Davis, & Davis (2003)<\/td>\n<\/tr>\n
\n\t
TIM<\/td>
Clarity: Levels are not mutually exclusive (e.g., the same experience may be collaborative<\/em>, constructive<\/em>, and authentic<\/em>) and potentially unintuitive. \n Fruitfulness: Too many levels are provided (25 scenarios between two axes), and levels may not be hierarchical (e.g., infusion <\/em>vs. adaptation<\/em>). \n Scope: May not be sufficiently parsimonious for teacher self-improvement and focuses on overall teacher development (e.g., extensive use) rather than specific instances.<\/td>
Harmes, Welsh, & Winkelman (2016)<\/td>\n<\/tr>\n
\n\t
TIP<\/td>
Clarity: Determining relative advantage is a precursor to the model but is itself not adequately modeled. \n Scope: May ignore other important aspects of practice beyond lesson planning and may overcomplicate the process. \n Student Focus: Students are implied in learning objectives and relative advantage but are not central.<\/td>
Roblyer & Doering (2013) \n (Note: The updated version of this model TTIPP was not reviewed for this paper; Roblyer & Hughes, 2018.)<\/td>\n<\/tr>\n
\n\t
TPACK<\/td>
Clarity: Boundaries are fuzzy, and hidden complexities seem to exist. \n Compatibility: Does not explicitly guide useful classroom practices (e.g., lesson planning). \n Fruitfulness: Distinctions may not be empirically verifiable or hierarchical (e.g., TPACK vs. PCK). \n Scope: May be too comprehensive for teachers (i.e., lacks parsimony for their context).<\/td>
Clarity<\/em>.<\/strong> Many technology integration models are\nunclear for teachers, being overly theoretical, deceptive, unintuitive, or\nconfusing. For instance, SAMR, TIM, and TPACK provide a variety of levels\n(classifications) of integration but may not clearly define them or distinguish\nthem from other levels. Student teachers, thus, may have difficulty understanding\nthem or may artificially classify practices in inaccurate or useless ways. Most\nmodels include specific concepts that may be difficult for teachers to\ncomprehend (e.g., the bullseye area in TPACK, relative advantage in TIP,\nsubstitution vs. augmentation in SAMR, or transformation in TIM and RAT),\nleading to superficial understanding of complex issues or to unsophisticated\nrationales for relatively shallow technology use. <\/p>\n\n\n\n
Recognizing the contextual complexities of\ntechnology integration, Mishra and Koehler (2007) argued that every instance of\nintegration is a \u201cwicked problem.\u201d Although this characterization may be\naccurate, teachers need models to guide them in grappling clearly and\nintuitively with such complexities.<\/p>\n\n\n\n
Compatibility<\/em>.<\/strong> Models we consider incompatible for K\u201312\nteachers emphasize constructs that are impractical or not central to a teacher\u2019s\ndaily needs. TAM, for instance, focuses entirely on user perceptions\ninfluencing adoption, with little application for developing lesson plans,\nguiding student learning, or managing classroom behaviors. Even models\ndeveloped for educators may focus on activities incompatible with teacher needs\n(e.g., student activism in LoTi) or be too theoretical to apply directly to teacher\npractice (e.g., technological content knowledge in TPACK).<\/p>\n\n\n\n
Fruitfulness<\/em>. <\/strong>Models that lack fruitfulness do not lead teachers\nto meaningful reflection, but rather yield unmeaningful evaluations of\npractice. Models with multiple levels of integration, such as LoTi, SAMR, and\nTIM, need a purpose for classifying practice at each level; teachers must\nunderstand why classifying practice as augmentation\n<\/em>versus modification <\/em>(SAMR) or as awareness <\/em>versus exploration <\/em>(LoTi) is meaningful. SAMR has four levels of\nintegration, LoTi has six, and TIM has 25 across two axes (5\u00d75). For teachers,\ntoo many possibilities, particularly if nonhierarchical, can make a model confusing\nand cumbersome if the goal in their context is to help them quickly reflect on\ntheir practice and improve as needed.<\/p>\n\n\n\n
Technology role<\/em>. <\/strong>Some models are technocentric: focused on\ntechnology use as the goal rather than as a means to an educational result. TAM,\nfor instance, particularly focuses only on technology adoption, not on\nimproving teaching and learning. Other models may focus on improving practice\nbut be largely technodeterministic in their view of technology as improving\npractice rather than creating a space for effective pedagogies to emerge.<\/p>\n\n\n\n
Scope<\/em>.<\/strong> Models with poor scope do not balance effectively between\ncomprehensiveness and parsimony, being either too directive or too broad for\nmeaningful application. TIP, for instance, is overly directive, simulating an\ninstructional design approach to creating TPACK-based lesson plans but too\nnarrowly focused to go beyond this. In contrast, the much broader TPACK provides\nteachers with a conceptual framework for synchronizing component parts but without\nconcrete guidance on putting it into practice. To be useful, models should\nignore aspects of technology integration not readily applicable for teachers, but\nprovide sufficient comprehensiveness to guide practice.<\/p>\n\n\n\n
Student focus.<\/em> <\/strong>Most models of technology integration do not meaningfully\nfocus on students, focusing on technology-adoption or teacher-pedagogy goals\nrather than clarity on what students do or learn. Models may merely assume\nstudent presence with pedagogical considerations, but failure to consider\nstudents at the center of practitioner models prevents alignment with student-focused\npractitioners\u2019 needs.<\/p>\n\n\n\n
Summary of theoretical models<\/em>.<\/strong> Many of these models were initially developed for broader audiences\nand retroactively applied to preparing teachers. Others were developed for\nteacher pedagogical practices at a conceptual level without providing sufficient\nguidance on actual implementation. Although many models benefit education\nprofessionals, a theoretical model for teacher education is needed that (a) is\nclear, compatible, and fruitful; (b) emphasizes technology use as a means to an\nend; (c) balances parsimony and comprehensiveness; and (d) focuses on students.\nWe view theoretical models in education opportunistically (\u00e0 la Feyerabend, 1975). Rather than seeking one model for all contexts\nand considerations, we recognize a need to provide teachers with a model that\nis most useful for their concrete practice. While these other models have a\nplace (e.g., TPACK is great for conceptualizing how to embed technology at an\nadministrative level across courses), something is needed with better-tuned\n\u201cengineering power\u201d for teacher education (Burkhardt & Schoenfeld, 2003, p.\n10).<\/p>\n\n\n\n
The\nPICRAT Model<\/h2>\n\n\n\n
As a theoretical model to guide teacher\ntechnology integration, PICRAT enables teacher educators to encourage\nreflection, prescriptively guide practice, and evaluate student teacher work.\nAny theoretical model will explain particular attributes well and neglect\nothers, but PICRAT is a student-focused, pedagogy-driven model that can be effective\nfor the specific context of teacher education \u2014comprehensible and usable by\nteachers as it guides the most worthwhile considerations for technology\nintegration.<\/p>\n\n\n\n
We began developing this model by\nconsidering the two most important questions a teacher should reflect on and\nevaluate when using technology in teaching, considering time constraints, training\nlimitations, and their emic perspective on their own teaching. Based on research\nemphasizing the need for models to focus on students (Wentworth et al., 2009;\nWentworth, Graham, & Tripp, 2008), our first question was, \u201cWhat are\nstudents doing with the technology?\u201d Recognizing the importance of teachers\u2019\nreflection on their pedagogical practices, our second question was, \u201cHow does\nthis use of technology impact the teacher\u2019s pedagogy?\u201d <\/p>\n\n\n\n
Teachers\u2019 answers to these questions on a\nthree-level response metric comprise what we call PICRAT. PIC refers to the\nthree options associated with the first question (passive, interactive, and creative);\nand RAT represents the three options for the second (replacement, amplification,\nand transformation). <\/p>\n\n\n\n
First, we emphasize three basic student roles\nin using technology: passive learning (receiving content passively),\ninteractive learning (interacting with content and\/or other learners), and creative\nlearning (constructing knowledge via the construction of artifacts; Papert\n& Harel, 1991). Teachers have traditionally incorporated technologies offering\nstudents knowledge as passive recipients (Cuban, 1986). Converting lecture\nnotes to PowerPoint slides or showing YouTube videos uses technology for instruction\nthat students passively observe or listen to rather than engaging with as active\nparticipants (Figure 1). <\/p>\n\n\n\nFigure 1<\/strong>. The passive level of student learning in PIC. <\/em><\/figcaption><\/figure>\n\n\n\n
Listening, observing, and reading are essential but not sufficient learning skills. Our experiences have shown that most teachers who begin utilizing technology to support instruction work from a passive level, and they must be explicitly guided to move beyond this first step.<\/p>\n\n\n\n
Much lasting and impactful learning occurs\nonly when students are interactively engaged through exploration,\nexperimentation, collaboration, and other active behaviors (Kennewell, Tanner,\nJones, & Beauchamp, 2008). Through technology this learning may involve playing\ngames, taking computerized adaptive tests, manipulating simulations, or using\ndigital flash cards to support recall. This interactive level of student use is\nfundamentally different from passive uses, as students are directly interacting\nwith the technology (or with other learners through the technology), and their\nlearning is mediated by that interaction (Figure 2). <\/p>\n\n\n\nFigure 2.<\/strong> The interactive level of student learning in PIC. <\/em><\/figcaption><\/figure>\n\n\n\n
This level may require certain affordances of the technology, but potential for interaction<\/em> is not the same as interactive learning<\/em>. Learning must occur due to the interactivity; the existence of interactive features is not sufficient. An educational game might require students to solve a problem before showing the optimal solution or providing additional content, which means that students must interact with the game by making choices, solving problems, and responding to feedback, thereby actively directing aspects of their own learning. The interactive level is still limited, however. Despite recursive interaction with the technology, learning is largely structured by the technology rather than by the student, which may limit transferability and meaningful connections to previous learning.<\/p>\n\n\n\n
The creative<\/em>\nlevel of student technology use bypasses this limitation by having students use\nthe technology as a platform to construct learning artifacts that instantiate\nlearning mastery. Lasting, meaningful learning occurs best as students apply\nconcepts and skills by constructing real-world or digital artifacts to solve\nproblems (Papert & Harel, 1991), aligning with the highest level of Bloom\u2019s\nrevised taxonomy of learning (Anderson, Krathwohl, & Bloom, 2001). <\/p>\n\n\n\n
Technology construction platforms may\ninclude authoring tools, coding, video editing, sound mixing, and presentation\ncreation, allowing students to give form to their developing knowledge (Figure\n3). In learning the fundamentals of coding, students might create a program\nthat moves an avatar from Point A to Point B, or they might learn biology\nprinciples by creating a video to teach others. In either instance the\ntechnology may also enable the student to interact with other learners or additional\ncontent during the creation process, but the activity can be creative without such\ninteraction. In creative learning activities, students may directly drive the\nlearning as they produce artifacts (giving form to their own conceptual\nconstructs) and iteratively solve problems by applying the technology to refine\ntheir content understanding.<\/p>\n\n\n\nFigure 3.<\/em><\/strong> The creative level of student learning in PIC. <\/em><\/figcaption><\/figure>\n\n\n\n
Across these three levels, similar technologies might be used to provide different learning experiences for students. For instance, electronic slideshow software like PowerPoint might be used by a teacher alternatively (P) to provide lecture notes about the solar system, (I) to offer a game about planets, or (C) to provide a platform for creating an interactive kiosk to teach other students about solar radiation. Across these three applications, the same technology is used to teach the same content, but the activity engaging the student through the technology differs, and the student\u2019s role in the learning experience influences what is learned, what is retained, and how it can be applied to other situations. <\/p>\n\n\n\n
This focus on student behaviors through\nthe technology avoids technocentrist thinking (ascribing educational value to\nthe technology itself) and forces teachers to consider how their students are\nusing the tools provided to them. All three levels of PIC might be appropriate\nfor different learning goals and contexts. <\/p>\n\n\n\n
To address the question of how technology\nuse impacts teacher pedagogy, we adopted the RAT model proposed by Hughes et\nal. (2006), which has similarities to the enabling<\/em>,\nenhancing<\/em>, and transforming<\/em> model proposed by our second author (Graham &\nRobison, 2007). Though the theoretical underpinnings of RAT have not been\nexplored in the literature outside of the authors\u2019 initial conference\nproceeding, we have applied it in previous studies (a) to organize understanding\nof how teachers think about technology integration (Amador, Kimmons, Miller,\nDesjardins, & Hall, 2015; Kimmons, Miller, Amador, Desjardins, & Hall,\n2015), (b) to compare models for evaluation (Kimmons & Hall, 2017), and (c)\nto illustrate particular model strengths (Kimmons, 2015; Kimmons & Hall, 2016b).\n<\/p>\n\n\n\n
Like PIC, the acronym RAT identifies three\npotential responses to a target question: In any educational context technology\nmay have one of three effects on a teacher\u2019s pedagogical practice: replacement,\namplification, or transformation.<\/p>\n\n\n\n
Our experience has shown that teachers who\nare beginning to use technology to support their teaching tend to use it to\nreplace previous practice, such as digital flashcards for paper flashcards, electronic\nslides for an overhead projector, or an interactive whiteboard for a\nchalkboard. That is, they transfer an existing pedagogical practice into a\nnewer medium with no functional improvement to their practice. <\/p>\n\n\n\n
Similar replacements may be found in other\nmodels: substitution<\/em> in SAMR or entry<\/em> in TIM. This level of use is not\nnecessarily poor practice (e.g., digital flashcards can work well in place of\npaper flashcards), but it demonstrates that (a) technology is not being used to\nimprove practice or address persistent problems and (b) no justifiable\nadvantage to student learning outcomes is achieved from using the technology. If\nteachers and administrators seek funding to support their technology\ninitiatives for use that remains at the replacement level, funding agencies\nwould (correctly) find little reason to invest limited school funds and teacher\ntime into new technologies.<\/p>\n\n\n\n
The second level of RAT, amplification,<\/em> represents teachers\u2019 use of technology\nto improve learning practices or outcomes. Examples include using review\nfeatures of Google Docs for students to provide each other more efficient and\nfocused feedback on essays or using digital probes to collect data for analysis\nin LoggerPro, thereby improving data management and manipulation. <\/p>\n\n\n\n
Using technology in these amplification\nscenarios incrementally improves teachers\u2019 practice but does not radically\nchange their pedagogy. Amplification improves upon or refines existing\npractices, but it may reach undesirable limits insofar as it may not allow\nteachers to fundamentally rethink and transform their practices.<\/p>\n\n\n\n
The transformation level of RAT uses technology\nto enable, not merely strengthen, the pedagogical practices enacted. Taking\naway the technology would eliminate that pedagogical strategy, as technology\u2019s affordances\ncreate the opportunity for the pedagogy and intertwines with it (Kozma, 1991).\nFor example, students might gather information about their local communities\nthrough GPS searches on mobile devices, analyze seismographic data using an\nonline simulation, or interview a paleontological expert at a remote university\nusing a Web video conferencing service such as Zoom (https:\/\/zoom.us<\/a>).\nNone of these experiences could have occurred via alternative, lower tech\nmeans.<\/p>\n\n\n\n
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