Promoting Adaptive Expertise- A Conceptual Framework for Special Educator

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Teacher Education and Special Education: The Journal of the Teacher Education Division of theSerra T. De Arment, Evelyn Reed and Angela P. Wetzel

PreparationPromoting Adaptive Expertise: A Conceptual Framework for Special Educator

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Article

Introduction

Leaders in the field of special educator prepa-ration identify the need for improved con-ceptions of teacher quality and theoretical frameworks to guide the study of SET [special education teacher] development (Sindelar, Brownell, & Billingsley, 2010, p. 9). Specifi-cally, Sindelar and colleagues (2010) high-lighted the need for teacher preparation models built on theories of change that guide evaluation of teacher candidates knowledge and performance, and overall program effec-tiveness. In the broader field of teacher educa-tion, similar concerns focus on the changing realities of practice for new and continuing teachers, and the need for a conceptual frame-work that embraces those realities as the impe-tus for deepening knowledge, developing adaptive expertise, and sustaining commit-ment to the profession (Darling-Hammond & Bransford, 2005). Adaptive expertise, or the interaction of efficient and innovative uses of knowledge, is described as the gold standard for becoming a professional (Hammerness,

Darling-Hammond, & Bransford, 2005, p. 360). While the development of routine exper-tise is valuable for standard situations, inno-vative problem solving based on novel aspects of the learning context and learners charac-teristics is essential for effective instruction. As innovation and problem solving about individualenvironment interactions is a hall-mark of special education, the development of adaptive expertise is an important concept to understand and incorporate in the design of special education teacher (SET) preparation programs.

To promote the development of adaptive expertise within novice SET, it is necessary to consider what is known about learning and

489578 TESXXX10.1177/0888406413489578Teacher Education and Special EducationDe Arment et al.research-article2013

1Virginia Commonwealth University, Richmond, USA

Corresponding Author:Serra T. De Arment, Department of Special Education and Disability Policy, School of Education, Virginia Commonwealth University, Oliver Hall, 1015 West Main Street, P.O. Box 842020, Richmond, VA 23284-2020, USA. Email: [email protected]

Promoting Adaptive Expertise: A Conceptual Framework for Special Educator Preparation

Serra T. De Arment1, Evelyn Reed1 and Angela P. Wetzel1

AbstractSpecial educators face numerous challenges as their roles change, evidence-based practices increase, educational priorities shift, and accountability grows. How can teacher education for special educators prepare candidates for the realities of practice and promote professional commitment to continuous learning? This article reviews the literature on adaptive expertise, proposes a conceptual framework, and presents implications for special educator preparation to promote cognitive and metacognitve skills and adaptive dispositions that are critical to professional growth and effectiveness.

Keywordsadaptive expertise, special education, teacher preparation

218 Teacher Education and Special Education 36(3)

teaching. Building on 30 years of learning sci-ence, the How People Learn (HPL) frame-work lays the foundation for effective teaching, with relevant applications to teacher development (National Research Council [NRC], 2000). Key components of the frame-work focus on the characteristics of learners, the acquisition and transfer of knowledge, the critical role of environments, and the role of assessment in guiding learning. Understand-ing this complex process is a challenge for all developing teachers, especially as they con-front three major problems in learning to teach: (a) the tendency to assume that they know how to teach based on their experience as learners, (b) the difficulty of using their content knowledge and acting on their peda-gogical knowledge, and (c) the problem of thinking about the complexities of teaching to improve practice (Hammerness et al., 2005). Darling-Hammond and Bransford (2005) pointed to the importance of coherent pro-gram design that helps teacher candidates develop cognitive maps of content and peda-gogical knowledge linked to their students learning and that challenges and builds on their understanding of the teaching and learn-ing process while helping them acquire the tools of practice. Furthermore, program design should provide a context for learning to teach that promotes the development of adaptive expertise through interaction with practitioners about actual teaching, beliefs, and knowledge (Darling-Hammond & Brans-ford, 2005).

Relevance of Adaptive Expertise to Special Educators

While the primary tenet of special education is individualizing educational plans based on the learner in context, changes in the field have also increased the need for SET to build their content knowledge, apply pedagogical knowledge in varied situations, and increase their collaboration with general education teachers and administrators. As the emphasis on evidence-based practices has increased, special educators need to learn and stay

abreast of current research and understand how to incorporate new methods and concep-tual tools into their teaching repertoires (Brownell, Sindelar, Kiely, & Danielson, 2010). Thus, SET need to understand peda-gogical routines that promote learning in the general curriculum and under typical situa-tions; however, their expertise in adapting environments, instruction, and support also requires them to problem solve, experiment, analyze results, and reflect on those adapta-tions with colleagues and families.

Billingsley, Griffin, Smith, Kamman, and Israel (2009) reviewed the challenges that new special educators face, and the primary concerns include the traditional pedagogical roles of special educators as well as the expanded roles of collaborative teaching. Specific challenges are as follows: (a) col-laboration with teachers, parents, paraprofes-sionals, and administrators in inclusive educational settings; (b) teaching in multiple content areas, accessing instructional materi-als, conducting appropriate assessments; (c) addressing student behavior; and (d) under-standing and managing their complex roles that require legal and procedural knowledge, time management, and flexibility. Given the high expectations for novice SET, teacher preparation programs need to reexamine their primary goals, pedagogical content, and processes, as well as formative and summa-tive assessments to ensure that SET candi-dates are prepared to begin their practice with a coherent framework that incorporates the routine expertise of teaching as well as the adaptive expertise that is needed to match the complexity of their roles.

The purpose of this article is to review the literature about adaptive expertise develop-ment to explore the conceptual landscape and operational definitions and to summarize applications to professional preparation across diverse fields. Given that context, implications for designing SET preparation to promote adaptive expertise are discussed to establish a common conceptual frame-work for SET preparation programs and their evaluation.

De Arment et al. 219

Review of Adaptive Expertise Literature

What Is Adaptive Expertise?First conceptualized in 1986, Hatano and Inagaki (1986) distinguished adaptive exper-tise from routine expertise. Routine experts are lifelong learners who increasingly become adept at performing a specific set of skills in response to familiar challenges (Bransford, Derry, Berliner, & Hammerness, 2005; Hat-ano & Inagaki, 1986; Inagaki & Miyake, 2007). Efficiency, made possible by situa-tional characteristics with little to no variabil-ity, allows routine experts to function at a high level in a stable environment (Bransford, 2004); however, routine experts can be lim-ited by inflexibility, overconfidence, bias, and the context of their particular domains (Crawford & Brophy, 2006).

In contrast to routine expertise, individuals with adaptive expertise can not only work

efficiently but also demonstrate the ability to be flexible and innovative in their application of procedural knowledge (Hatano & Inagaki, 1986). The NRC (2000) explained, Experts have varying levels of flexibility in their approach to new situations (p. 31). An adap-tive expert presents a more flexible orienta-tion to problem solving and knowledge construction; whereas, a routine expert tends toward familiar approaches to new situations. Oft cited across the literature, Bransford, Derry, et al., (2005) framed adaptive expertise as a balance between the efficiency and inno-vation (Schwartz, Bransford, & Sears, 2005). Depicted graphically with efficiency along the x-axis and innovation along the y-axis (see Figure 1), the trajectory toward becoming an adaptive expert lies within the optimal adapt-ability corridor whereby innovation and effi-ciency have a positive relationship and roughly an equally important presence in learning. In this view, a routine expert is high

Figure 1. The trajectory toward adaptive expertise balances efficiency and innovation via the optimal adaptability corridor.Source. Reprinted from Bransford, Derry, Berliner, and Hammerness (2005, p. 49) with permission.


in the efficiency dimension but low in the innovation dimension, and an adaptive expert is high in both dimensions, able to select between routine and adaptive approaches, and explain and justify those decisions (Brans-ford, 2004; Crawford, Schlager, Toyama, Riel, & Vahey, 2005; Hatano & Inagaki, 1986; Inagaki & Miyake, 2007).

In addition to the balancing act between efficiency and innovation, adaptive expertise entails critical cognitive skills. Recently, Bell, Horton, Blashki, and Seidel (2012), citing the work of Lin, Schwartz, & Hatano (2005), described adaptive expertise as higher order problem-solving involving knowledge trans-fer across the disciplines (p. 217). More spe-cifically, by responding flexibly to variable contexts, adaptive experts know how to con-structively consider and account for multiple perspectives and potential solutions and mod-ify their existing procedural skills or invent new procedures (Goodnow, Peterson, & Law-rence, 2007; Hatano & Oura, 2003) to meet challenges or problems of practice. Yet, adap-tive experts may tend to miss details (Craw-ford & Brophy, 2006).

Metacognitive awareness is another impor-tant dimension of adaptive expertise whereby individuals actively consider the benefits and drawbacks of efficiency and innovation for a given situation (Bransford, Derry, et al., 2005). Lin, Schwartz, and Hatano (2005) dis-cussed the importance of adaptive metacog-nition in teachers who can respond flexibly to the ever-present variability they encounter in the classroom. For adaptive experts, meta-cognition plays a role in their ability to self-assess and judge when their current levels of understanding are not adequate (NRC, 2000) and in their ability to know when to select an efficient procedure or an innovative one (Crawford & Brophy, 2006). Metacognitive practice also allows for learning to occur dur-ing the process of problem solving (Crawford & Brophy, 2006) as learners actively engage with and assess their own thinking and comprehension.

Finally, dispositional characteristics are thought to play a role in adaptive expertise as well. Adaptive experts understand that

knowledge can be messy and irregular (Crawford et al., 2005) and that discomfort may arise through the course of problem solv-ing, due to having to abandon previously held understandings (Bransford, Derry, et al., 2005). Accordingly, adaptive experts hold [their] theories lightly (Crawford & Brophy, 2006, p. 14) and ask questions as they seek new information with a willingness to replace prior assumptions if necessary (Schwartz et al., 2005). Hatano believed certain individual characteristics, such as curiosity, may influ-ence the development of adaptive expertise (Crawford & Brophy, 2006). Bell et al. (2012) echoed this stating that students who are to become adaptive experts must possess innate motivation to solve problems through innova-tive means. Bransford (2004) explained that adaptive experts enjoy challenges and have a systematic understanding of themselves as learners and problem solvers (p. 6). Other dispositional features of adaptive expertise are thought to be a willingness to think things through and change, a degree of comfort with taking managed risks that may result in mis-takes, and the tendency to seek out feedback from others who may not share similar views (Crawford & Brophy, 2006). Some have described adaptive experts as being more prepared to learn from new situations (Lin, Schwartz, & Bransford, 2007, p. 62) than routine experts and as being willing to ask questions to increase their understanding (Bransford, 2004; Schwartz et al., 2005). Like routine experts, adaptive experts are lifelong learners, but unlike routine experts, adaptive experts are never satisfied with their current levels of understanding and strive not only to work more efficiently but also to work better (Bransford, Derry, et al., 2005; Crawford et al., 2005; NRC, 2000).

Adaptive expertise has relevance across a variety of disciplines, including medicine, engineering, business, and education (e.g., Bell et al., 2012; Bransford, 2007). Adaptive expertise is of particular importance to the development of teaching professionals who face unpredictable and varied circumstances in their daily work with students (Lin et al., 2005). As noted by the NRC (2000), Teachers


are learners and the principles of learning and transfer for student learners apply to teachers (p. 242). Adaptive expert teachers improve in teaching by adapting their known routines to find better solutions to problems of practice (Hammerness et al., 2005). Teachers also need to capitalize on metacognitive strategies to help them cope with the ongoing variability they encounter in their work with students (Lin et al., 2005). Adaptability is thus a sur-vival skill for teachers who know there is no one right way to approach all of the challenges each instructional day.

Crawford et al. (2005) considered the implications of adaptive expertise for teachers and teaching, conceptualizing adaptive exper-tise in terms of adaptive practice:

Instructional practice that is a site of knowledge construction . . . characterized by a stance toward knowledge-building rather that maximizing efficiency in such a way that productive problems and opportunities for knowledge construction are overlooked, removed, or avoided. (p. 4)

Crawford et al. (2005) described a theoreti-cal framework for adaptive expertise com-prised of dispositional characteristics (i.e., understanding the teachers epistemic orienta-tion and disposition) and cognitive/metacog-nitive skills (i.e., understanding the teachers cognitive and metacognitive processes in dealing with problems associated with teach-ing). Specifically, adaptive dispositions entail keeping an epistemic distance between prior knowledge and a current problem of practice, understanding the world as complex without tidy procedures and conclusions, feeling com-fortable acknowledging limits of ones knowl-edge, and wanting to learn, not just apply, knowledge. From a cognitive/metacognitive perspective, Crawford et al. explained adap-tive expertise involves the processes of data-driven forward reasoning, causal reasoning, cognitive flexibility, and self-regulation.

To construct operational definitions and assessment of adaptive expertise in SET prep-aration, we built on the framework of Craw-ford et al. (2005) by parsing out adaptive

dispositions, cognitive, and metacognitive skills. Table 1 summarizes the adaptive expertise literature related to these three dimensions.

How Does Adaptive Expertise Develop?

Understanding how to foster development of adaptive expertise is important to the con-structs value as a tool for promoting growth in learners. Researchers do not yet know for certain when the optimal time is to begin fos-tering adaptive expertise within a learner. Although some consider adaptive expertise as a step after mastery of content knowledge associated with routine expertise, most researchers in the field think adaptive exper-tise can and should develop alongside routine expertise (Crawford & Brophy, 2006). Thus, while learners master content information, they can, and arguably should, develop the dispositions, cognitive, and metacognitive skills that accompany adaptive expertise. Within the context of SET preparation, for example, teacher educators can engage in a deliberate process of scaffolding SET reflec-tive practice while providing instruction that addresses the how-to of routine practice. Thus, faculty create space for novice SET to develop adaptive expertise alongside their acquisition of routine expertise. Bransford (2004), noting that developing adaptive exper-tise is not a quick process, suggested it might be more difficult to teach a routine expert who is set in his ways how to be adaptive than to foster adaptive expertise from the outset of learning within a domain. His advice was to help learners understand themselves as think-ers, problem solvers, and lifelong learners. Teacher educators have the opportunity to set aspiring SET along the trajectory toward adaptive expertise early in their practice by promoting these adaptive habits of mind.

Previous cross-sectional research in medi-cine, education, business, and engineering supports a model for the potential develop-ment of adaptive expertise along the trajec-tory from novice to expert (Barnett &


Koslawski, 2002; Crawford, 2007; Fisher & Peterson, 2001; Varpio, Schryer, & Lingard, 2009); yet, we lack longitudinal empirical studies to demonstrate the process of develop-ment along this trajectory from routine to adaptive expert behaviors (Martin, Petrosino, Rivale, & Diller, 2006). An exception includes Martin and colleagues (2006) longitudinal development model for adaptive expertise

with undergraduate biomedical engineering students (n = 54). Martin and colleagues (2006) examined change in pre- or post-data on an adaptive beliefs survey in relation to performance on adaptive expertise exam out-comes. Each of three course exams included knowledge, innovation, and adaptive expertise items, where adaptive expertise items required students to transfer existing knowledge to a

Table 1. Adaptive Dispositions, Metacognitive Skills, and Cognitive Skills of Adaptive Expertise Derived From the Literature.

Ability to explain decisions and justify outcomes of these processesa,b,c,d

Adaptive dispositions Metacognitive skills Cognitive skills

Maintain an epistemic distance between prior knowledge and model of a case or problem at handb

Willing to abandon previously held understandingse

Willing to replace prior assumptionsf

Holding theories lightlyg

Resisting initial ideas about a problemf

Plasticity of thinkingk

Questioning current levels of expertisej Cognitive flexibilityb

Respond to variability in classroomh

Accounts for multiple perspectivesn

Invent new proceduresm

Balance of efficiency and innovatione,f

An epistemic stance that views the world as complex, messy, irregular, dynamic, and so on.b

Comfort or willingness to reveal and work at the limits of ones knowledge and skillb

Monitoring own learningb

Monitor own comprehensiong

Self-assessj

Systematic understanding of the self as a learnera

Assessing own knowledge statesb

Self-assess thinkingg

Assessing adequacy of current knowledge for solving case at handb,j

Willing to ask questionsf

Willing to take managed risks that may result in mistakesg

Seeking out feedback from others (different others)g

An inclination toward learning rather than merely applying knowledgeb

Never satisfied with current levels of understandingb,e,i

Opportunisticg

Motivation to problem solvej

Curiosityg

Enjoy challengea

Prepared to learn from new situationsf,k

Seeking and analyzing feedback about problem-solving processes and outcomesb

Higher order problem solvingk

Systematic understanding of the self as a problem solver and learnera

Monitoring results and performanceb

Modify existing procedural skillsl,m

Invent new proceduresm

Causal reasoning (develop underlying model or set of contributing factors)b

Data-driven forward reasoning

(hypothesis-based reasoning)b

Higher order problem solvingk

Select routine or adaptive approach based on data & hypothesisg

aBransford (2004).bCrawford, Schlager, Toyama, Riel, and Vahey (2005).cHatano and Inagaki (1986).dInagaki and Miyake (2007).eBransford, Derry, Berliner, and Hammerness (2005).fSchwartz, Bransford, and Sears (2005).gCrawford and Brophy (2006, September).hLin, Schwartz, and Hatano (2005).iNational Research Council (2000).jBell, Horton, Blashki, and Seidel (2012).kLin, Schwartz, and Bransford (2007).lGoodnow, Peterson, and Lawrence (2007).mHatano and Oura (2003).nFisher and Peterson (2001).


novel problem that was not directly taught in the course. The adaptive beliefs survey items relate to four constructs of adaptive expertise (i.e., multiple perspectives, metacognition, goals and beliefs, and epistemology) derived from a review of the literature (Fisher & Peterson, 2001). Results of repeated measures ANOVA indicate knowledge, innovation, and adaptive expertise improved from Exam 1 to Exam 3, and gains in adaptive expertise were preceded by gains in knowledge and innova-tion. Adaptive beliefs survey scores remained stable across the course, and higher pre-survey scores were related to higher adaptive exper-tise performance on Exam 1. Yet, those stu-dents with lower scores on the adaptive beliefs pre-survey demonstrated the greatest improve-ment on the adaptive expertise items from Exam 1 to Exam 3 emphasizing the potential for development of adaptiveness. Further investigations to understand how to promote and assess for routine and adaptive expertise synchronously throughout a program are needed.

Role of the learning environment for promoting adaptive expertise. Cited and elaborated upon by others, Hatano and Inagaki (1986) first proposed three learning environment factors that contribute to the development of adaptive expertise. First, learners must encounter vari-ability (i.e., applying a procedure repeatedly with variations, building in randomness that prompts variations, having to meet changing demands, and applying knowledge flexibly across varied contexts; Bell et al., 2012; Goodnow et al., 2007; Hatano & Inagaki, 1986; Hatano & Oura, 2003). The remaining two factors highlight the importance of con-sidering the influence of the sociocultural context of learning environments, specifically the culture and context in which learners work. Learners will risk applying adaptive strategies rather than a safe strategy when the context does not exert pressure for speedy and correct performance (Hatano & Inagaki, 1986). Furthermore, in a culture that values understanding over performance, learners are more likely to vary their procedures because active experimentation, explanation, and

elaboration are encouraged (Lin et al., 2007). Within this type of learning community, learn-ers may collaborate, learn from one another, and discover innovative approaches that would not otherwise be considered, what Bransford (2004) discussed as distributed expertise.

Lin et al. (2007) reframed Hatano and Inagakis three variability factors as tiers of variability. In the first tier, learners must encounter variability in their environments and be guided to identify the variations. The second tier of variability is related to how the learner applies a procedure with variation. Through exposure to an initial problem fol-lowed by various what if scenarios, Lin et al. (2007) suggested learners can develop smart tools they can then use to generalize across situations. Finally, in the third tier, learners encounter variability of explanation by par-ticipating in the sharing of varied peer and expert perspectives.

Investigations comparing novices and experts do indicate key differences in the vari-ability of professional experience and thought processes that differentiate between not only novices and experts but also routine and adap-tive experts (Barnett & Koslawski, 2002; Crawford, 2007). For example, using a think-aloud interview approach, business consultant experts (n = 12), restaurant managers/owners (n = 12), and undergraduate, nonbusiness stu-dents (n = 12) provided plans of action to address a novel problem scenario. Despite no restaurant experience, business consultants produced significantly more optimal answers for each question, demonstrated more theory-based reasoning, and more often considered multiple perspectives compared with the res-taurant managers and students, who did not differ significantly. Using a similar think-aloud approach, Crawford (2007) investigated the task orientation, efficiency orientation, or innovation orientation, applied by veteran and novice high school biology teachers (n = 13) when presented a hypothetical instructional problem-solving task. Mean percentages of innovation orientation and efficiency orienta-tion codes were compared across veteran teachers with routine expertise, veteran teachers


with adaptive expertise (i.e., previous educa-tion or experience with educational theory and/or research methods and instructional leadership experience), and novice teachers with two to three years teaching experience. Trends in the data indicate routine and adap-tive expert veteran teachers demonstrated a similar percentage of efficiency, or routine, oriented comments; however, adaptive expert teachers expressed more innovation task ori-entation, including high-level analysis and deeper consideration of the provided student data. Evidence suggests the skills learned in the varied professional experience of the con-sultants and veteran adaptive expert teachers may explain these group differences (Barnett & Koslawski, 2002; Crawford, 2007).

Within thoughtfully designed learning environments, teachers can implement instructional techniques to foster adaptive expertise. Schwartz et al. (2005) discussed implications for instruction that leads to adap-tive expertise through the lens of three types

of knowing (Broudy, 1977). They explained that replicative and applicative types of know-ing contribute to the development of routine expertise as learners are assessed based on their ability to transfer knowledge through recall of facts and application of knowledge to familiar circumstances. Through instructor emphasis on interpretive knowing, however, learners are oriented toward preparation for future learning (Schwartz et al., 2005, p. 11). Furthermore, learners need to engage in activ-ities that promote reflection and metacogni-tive thinking (Bransford, 2007), and by emphasizing theory and concepts over spe-cific procedures, instructors can promote innovation backed by justification (Bransford, 2004; Bransford, Derry, et al., 2005). Not only do learners need to be innovative but they also need to understand the reasons behind and cir-cumstances for their innovation.

Complementary to the Hatano-based fac-tors and tiers discussed above, the HPL framework describes the design of learning

Figure 2. The How People Learn framework.Source. Reprinted from Bransford, Darling-Hammond, and LePage (2005, p. 32) with permission.


environments to promote adaptive expertise (Bransford, Darling-Hammond, & LePage, 2005; NRC, 2000). As illustrated in Figure 2, this framework situates learning as taking place within a system of four overlapping environments. The learner-centered environ-ment focuses on what learners bring to the educational setting from their past experience and existing knowledge. Within the knowl-edge-centered environment, learners work to develop new knowledge within a domain through sense-making activities that lead to understanding and future transfer. The assess-ment-centered environment gives learners opportunities for feedback and revision in their learning development. Finally, the com-munity-centered environment provides a foundation for understanding and learning from the perspectives of others. Taken together, these learning environment design considerations help ensure learners capitalize on learning that leads to innovative practice beyond the routine.

Research in undergraduate engineering programs supports the application of the HPL framework to create for students critical learn-ing experiences that target the development of adaptive expertise skills and behaviors during the educational program (Martin et al., 2006; Martin, Rayne, Kemp, Hart, & Diller, 2005; Pandy, Petrosino, Austin, & Barr, 2004). Com-mon to these studies is use of the Star Legacy Cycle (Schwartz, Brophy, Lin, & Bransford, 1999) that involves an engaging challenge-based approach requiring students to (a) review their existing knowledge and generate their own ideas; (b) consider multiple perspec-tives of experts in the relevant field; (c) consult resources, incorporate new knowledge, and revise initial ideas; (d) incorporate formative feedback from peers and instructors; and (e) present the final product. Pandy and colleagues (2004), seeking to increase senior undergradu-ate engineering student (n = 25) adaptive expertise, applied a pretestposttest experi-mental design and compared students factual, conceptual, and transfer of knowledge out-comes and adaptive expertise scores. Students randomly assigned to an HPL group experi-enced a multimedia-based learning module on

biomechanics using the Star Legacy Cycle were compared with those students assigned to the standard lecture group. A calculation of the sum of weighted scores for transfer of knowledge (50%), conceptual knowledge (40%), and factual knowledge (10%) served as the operational definition for adaptive expertise. Similarly, Martin and colleagues (2005) applied an HPL approach using the Star Legacy Cycle to teach and assess one tenet of adaptive expertisethe practice of consulting and evaluating multiple expert viewpointsfor undergraduate bioengineer-ing students (n = 30). In this experimental design, the pretest and posttest included fac-tual knowledge items, assessment of ethical decision making, and an item to measure adaptive expertise where students created and justified a plan of action to address a problem within a novel situation. For both studies, standard lecture students and HPL students demonstrated a similar increase in factual/conceptual knowledge; however, students participating in the HPL learning module sig-nificantly increased on measures of adaptive expertise compared with those in the tradi-tional lecture model (Martin et al., 2005; Pandy et al., 2004). Similarly, findings from Martin and colleagues (2006) longitudinal study of an HPL-based course using Star Leg-acy Cycle modules indicated improvement on adaptive expertise learning outcomes.

Promotion of adaptive expertise in teacher edu-cation. The IRIS (IDEA and Research for Inclusive Settings) Center for Faculty Enhancement provides publicly available IRIS modules (http://iris.peabody.vanderbilt .edu), based on the Star Legacy Cycle, to help prepare general and special educators and other school personnel for practice with stu-dents with disabilities (Smith, et al., 2005). Yet, limited empirical evidence in the litera-ture examines the promotion of adaptive expertise specifically in teacher education (Janssen, de Hullu, & Tigelaar, 2008; Soslau, 2012). Janssen et al. (2008) compared the out-comes from interviews of 16 biology student teachers reflections on positive and negative teaching experiences, including (a) the


content of action plans derived from the reflection, (b) teacher motivation to imple-ment the action plan, and (c) teacher emotions occurring during the reflection. Self-selected positive experiences for reflection more often involved innovative instructional methods, which led to more innovative plans of action when compared with reflection on negative experiences. Furthermore, positive reflections led to greater self-reported motivation to implement action plans and more overall pos-itive emotions. These results support the use of reflective prompts on positive teaching experiences to promote adaptive expertise as innovation seems to lead to further innovation with teachers motivated to act. Soslau (2012) conducted a multiple case study exploring opportunities to promote adaptive teaching expertise through discourse and supervisory styles during conferences following student teaching field experiences. Participants included three undergraduate elementary teacher education students and three univer-sity supervisors each with varied supervision styles based on preassessment inventories. During each of two 8-week field experience placements, the researcher observed two stu-dentsupervisor conferences for each student participant, totaling to 12 conferences. Fol-low-up one-on-one interviews were con-ducted with the student and supervisor after each conference. Results of qualitative analy-sis of interview data suggest a guiding and reflecting supervision style, when compared with a telling supervision style, elicit more discussions of novice problems (i.e., unques-tioned familiarity, dual purpose, context) that hinder the development of adaptive teaching expertise. Yet, supervisors missed 11 of 31 opportunities to use these discussions to pro-mote adaptive expertise by requiring students to discuss and justify the routine elements of teaching practice. These findings have impli-cations for the design and content of reflection and feedback in SET education.

In summary, these investigations suggest educators can help students improve their adaptiveness by providing learning experi-ences that require students to practice the cog-nitive and metacognitive skills and dispositions

for adaptive expertise (Janssen et al., 2008; Martin et al., 2005; Martin et al., 2006; Pandy et al., 2004; Soslau, 2012), even when initial adaptive beliefs are low (Martin et al., 2006). Specifically, the HPL-based Star Legacy Cycle includes opportunities for students to innovate and be efficient. For example, generating ideas based on prior knowledge requires a self-assessment of current understanding of a topic and innovative problem solving; refining ini-tial ideas based on a review of multiple per-spectives and resources allows students to be more efficient in the final outcome. Further-more, reflection on positive teaching experi-ences promotes adaptive dispositions, such as motivation and the cognitive and metacogni-tive skills required to develop innovative new procedures (Janssen et al., 2008). Finally, edu-cators can use feedback structures as opportu-nities for students to become more adept in the cognitive and metacognitive skills of adaptive expertise through discourse and reflection on the routine and variable, contextual aspects of the teaching field experience (Soslau, 2012).

Implications for SET Education

We propose several steps in the application of this conceptual framework to the design and evaluation of SET preparation programs. First, adaptive expertise constructs can be used to examine the congruence, gaps, and relation-ships among the knowledge, skills, and dispo-sitions within professional standards. For example, to what extent does a Council for Exceptional Children (CEC, 2008) knowledge standard provide the critical foundation for related skills and dispositions that are congru-ent with adaptive expertise? Next, we need to identify instructional opportunities throughout SET programs for scaffolding adaptive exper-tise. As we teach core knowledge, do we use the Star Legacy model to ensure engagement, assessment, reflection, and deep understand-ing? Within traditional classroom and field-work experiences, how well do we emphasize the variability in students learning, families priorities, instructional settings, and team functioning? Do we provide a safe learning


environment for experimenting with new methods and examining their effectiveness? When we teach evidence-based practices, how are we emphasizing context, decision making, and understanding as well as technical perfor-mance? Do we provide effective structures for SET candidates to appraise and reflect on the relationships between program standards and their learning experiences? Are we promoting collaboration through direct and supported team learning activities? A final critical step is developing measures of adaptive expertise to support feedback to candidates and faculty and to inform overall program evaluation. To date, the impact of curricular interventions on adap-tive expertise has been isolated to the unit or course level; longitudinal program-level effects on adaptive expertise have not yet been reported. Particularly important in an era of increasing teacher accountability, assessment for longitudinal growth must be carefully scaf-folded for learners at different stages of a pro-gram of study.

Hammerness and colleagues (2005) described adaptive expertise in teaching as creating a balance between efficient use of specific classroom techniques and innovative approaches to instruction. A solid base of effi-cient teaching practices allows teachers to enact innovative approaches that more effec-tively respond to unexpected classroom cir-cumstances or to the unique needs of students who do not respond to routine instruction. Striking a balance between these two dimen-sions has the potential to improve teacher effectiveness and, in turn, student learning outcomes as teachers find successful ways to address day-to-day challenges they encounter.

Learning the efficiencyinnovation balanc-ing act of an effective teacher is no simple task, however. As teacher educators, we must be deliberate in planning for the promotion of adaptive expertise. Prospective teachers need guidance in evaluating their preconceptions about teaching in light of the pedagogical knowledge and skills imparted by their teacher education programs (Hammerness et al., 2005). Experiences embedded in frequent, authentic teaching contexts and opportunities to collabo-rate with and seek feedback from others can

help novice teachers reconcile these competing notions (Darling-Hammond & Hammerness, 2005). Field experiences should be extensive, present throughout coursework, and carefully selected based on relationships developed with schools that share the programs vision of good teaching (Hammerness et al., 2005). Despite acquiring the requisite knowledge, learners do not consistently apply that existing knowledge in novel practice-based situations (Atman, Kilgore, & McKenna, 2008; Greer, De Bock, & Van Dooren, 2009). Beginning teachers must learn how to overcome familiar tendencies and put new knowledge and skills into action in their teaching practice (Hammerness et al., 2005). Furthermore, they need to develop a deep understanding of the complexity and non-routine nature of teaching, and with that, a commitment to self-assessment through meta-cognitive reflection (Hammerness et al., 2005). Case study methods and the development of teaching portfolios can facilitate critical con-nections between theory and practice and help aspiring teachers gain a strong sense of them-selves as learners and problem solvers. In par-ticular, case studies provide preservice SET with the opportunity to assess variability across instructional contexts and seek the perspectives of others in a way that allows them to test ideas and evaluate response in a risk-free, supportive environment. Furthermore, portfolios give teacher candidates structure and space for criti-cal reflection, justification, and evaluation across the preservice program. As teacher edu-cators, we must be accountable for instruction and assessment that emphasize knowledge/efficiency and innovation throughout the edu-cational program and challenge students to reflect on and justify their routine knowledge and practice (Atman et al., 2008; Greer et al., 2009; Mylopoulos & Regehr, 2009). Teacher preparation rooted in these principles of learn-ing can pave the way for the development of adaptive expertise and thus instill the critical skills and dispositions novice SET need to address the inevitable challenges of their future teaching practice.

Heeding the call of Darling-Hammond and Hammerness (2005) for coherence within teacher education programs, we argue that a


conceptual framework of adaptive expertise should be the backbone that undergirds and uni-fies all aspects of the design, delivery, and study of teacher preparation in special education. Whereas the CEC (2008) standards guide the knowledge and skills special educators should possess, adaptive expertise can, and should, be the common thread woven throughout teacher preparation across the coursework and clinical experiences that target particular knowledge and skills. Teacher educators can create this coherence by making the conceptual frame-work explicit to all teacher candidates within the program (Darling-Hammond & Hammer-ness, 2005). In so doing, novice teachers can gain a clear understanding of the broader pur-pose of the preparation program that links their programwide learning experiences beyond the mere acquisition of knowledge and skills. Through consistent, thoughtfully planned activ-ities targeting the development of adaptive expertise such as those outlined above, teacher educators may cultivate within preservice spe-cial educators the adaptive dispositions and metacognitive and cognitive skills that lead to successful teaching. Moreover, the value of developing a teaching practice that successfully balances efficiency and innovation will be made salient for novice special educators. With cohe-sion and salience, we can avoid sending begin-ning SETs into the field who feel only comfortable with the routine and are unprepared for the realities and challenges of practice.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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Author BiographiesSerra T. De Arment is a doctoral student at Virginia Commonwealth University (VCU) whose research

interests include teacher preparation, teacher quality, collaborative teaching, and teacher retention in spe-cial education.

Evelyn Reed, chair and associate professor of the Department of Special Education and Disability Policy at VCU, focuses on special education teacher (SET) development research. She has been the principal investigator for personnel preparation projects emphasizing interdisciplinary collabora-tion, community-engagement, and high-needs environments.

Angela P. Wetzel is director of assessment, Department of Foundations of Education, at VCU School of Education. Her research interests include instrument development, student assessment, and program evaluation as scholarship.

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Promoting Adaptive Expertise- A Conceptual Framework for Special Educator