3.3: Deconstructing Technology-Rich Teaching
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\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)Teacher education has traditionally been informed by a framework comprising the content dimension (what is to be taught or the curriculum) and the pedagogy dimension (how it is taught or instruction). Shulman (1987) suggested teachers’ content knowledge and pedagogical knowledge cannot be developed in isolation, so he proposed “pedagogical content knowledge” (PCK) to describe the capacity of a teacher to organize, explain, and communicate ideas so that students understand the content. The adage commonly applied to education, “you never really understand it until you teach it,” captures the interconnected nature of content and pedagogy; educators better understand content through teaching it and they better understand pedagogy by applying it to teaching problems in their classrooms.
In extending Shulman’s concept of PCK, Mishra and Koehler (2006) observed technology had emerged as a distinct type of knowledge. In adding technological knowledge (TK) to Shulman’s model, Mishra and Koehler recognized computer technology is qualitatively different from pencils and paper and the other long-established print technologies, so it enters the model as a separate type of knowledge. It is reasoned that as digital information technology becomes more familiar, its existence as a separate type of knowledge will decrease. Technological pedagogical content knowledge (TPCK) (see Figure 3.3.1) has become a very useful framework for understanding teaching and learning in the technology-rich school. While TPCK does comprise distinct and isolatable types of knowledge, it is presented as a model that “emphasizes the connections, interactions, affordances, and constraints between and among content, pedagogy, and technology,” and “emphasizes the interplay of these three bodies of knowledge.” (Mishra & Kohler, 2006, p. 125).
Figure \(\PageIndex{1}\): TPCK model (adapted from Mishra & Koehler, 2006)
As a framework useful to inform IT management decisions in school, TPCK identifies seven types of knowledge that can be improved with educators’ increased awareness of new technologies and with their increased knowledge of teaching methods that make use of technology. The state of TPCK within a school community can evaluated from an individual’s perspective and also from the perspective of the entire faculty. Social influences are known to be an important determinate in technology acceptance (Venktah & et al. 2003), so each individual’s TPCK is affected by the group’s TPCK, and the TPCK of influential individuals are particularly important in affecting the group’s TPCK.
TPCK is proposed as a dynamic framework and Mishra and Kohler (2006) anticipated it would change over time. Shulman (1987) did not differentiate books, pencils, paper, and other information technologies into a separate type of knowledge when PCK was first elucidated; he reasoned those were transparent technologies and a stable part of teaching and learning for generations, thus no specific knowledge was necessary to use technology. Given the continued rapid development and diffusion of information and computer technology hardware, software, and network platforms, technological knowledge is anticipated to be an important part of TPCK into the foreseeable future. Further, the nature of the classroom determines how TPCK is defined and instantiated. Mishra and Koehler (2006) observed, “there is no single technological solution that applies to every teacher, every course, or every view of teaching” (p. 1029).
Using TPCK, IT managers can identify and support all aspects of technology in teaching and learning. The model also allows IT managers to identify and clarify the connections between the various types of knowledge. In addition, TPCK facilitates understanding of who must be involved with decisions and who must lead and participate in training, curriculum development, and other professional development activities.
Technological Knowledge
When desktop computers first arrived in schools, leaders found it necessary to provide training and support in the basic operation of the devices. At that time, teachers were unlikely to have access to computers at home and it was unlikely they had been exposed to them during their professional preparation. (In the mid- 1980’s, I was in the minority of my peers enrolled in the teacher education program at out state university who enrolled in the optional “Computers in the Classroom” course offered to undergraduate students; most of my colleagues earned their teaching credentials without any formal experiences with computers.) Simply turning computers on and loading software was the focus of the first computer training for teachers. Software tools such as word processors and spreadsheets were also new, so training sessions introduced educators to the steps of creating, editing, and managing files as well. This reality is also reflected in the goal articulated in the first National Education Technology Plan for the United States which was written in 1996. At the time, educational policy makers sought to address the Technology Literacy Challenge which President Clinton had defined as connecting every classroom to the Internet and ensuring teachers could use it.
In the decades since computers arrived, they have become common household tools and their use is deeply embedded in the higher education courses that are needed to be qualified for almost any position in education. In those same decades, very complex software and network services have been adopted by schools to manage information and provide interaction for educational and business purposes. The result is that educators’ technological knowledge includes that which they must develop and maintain on their own and that which must be developed by IT managers. Part of the screening process for candidates for licensed educators and unlicensed assistants who work directly with students must ensure each who fills one of those positions is capable of operating a computer and common software for professional purposes. Educational professionals arrive at their positions with these skills and maintain them with minimal training throughout their careers. Powering a computer on, logging on to networks, and creating and managing files using locally installed software and cloud-based productivity suites are all tasks educators must be able to accomplish with efficiency, confidence, and independence. In addition, they should be capable of searching and finding credible information on the Internet; this includes multimedia information as well as electronic versions of printed materials. Further, educators should model responsible and ethical use of technology systems and digital media. Finally, educators should be able to adapt to new versions of software and similar upgrades quickly and with little direct instruction.
There are some tools educators should not be expected to use without direct instruction and IT managers must plan for these needs when newly hired educators are “on-boarded” and to support educators during major transitions. The IT systems that require direct instruction include:
- Procedures and credentials for logging on to all systems that are needed by the professional, including local area network, email, and all web services used to manage employment, data, and instruction;
- Instructions for managing rosters and grades through the student information system; these systems are notorious for being “not user friendly,” which can be attributed to the differences between the vocabulary and structures used by designers and programmers and the language and methods used by educators;
- Instructions for posting to the educators’ page(s) on the school web site, the learning management system, social media sites, and other systems for sharing information with both internal and external audiences they are expected to use.
Implicit in this as well is the expectation that educators will be introduced to local policies and procedures relative to acceptable use, procedures to report malfunctioning IT systems, scheduling shared resources, accessing printers, and similar details related to individuals’ use of the specific IT systems installed in the school. On-boarding procedures for new staff must address these aspects of using IT, and changes in how these systems are configured necessitates training for all faculty and staff to ensure efficient and effective use of the new tools.
Content Knowledge
Content knowledge may appear to be the most clearly understood and defined type of knowledge. We all expect, for example, chemistry teachers to understand the concepts, idea, and procedures of chemistry; and this content is found in chemistry textbooks. By successfully completing advanced undergraduate courses in a content area, teacher candidates demonstrate sufficient content knowledge so they understand what they are supposed to teach, including relevant details such as how to recognize when chemistry is being done in an unsafe manner.
The content that future teachers study in their undergraduate courses is developed by those with advanced degrees in the field. Their expertise is assured by the universities granting their degrees, their research, participation in professional organizations, and service to the universities where they are employed. The reality of content knowledge for many educators is becoming more complicated in the digital world, however. Two factors appear to be exerting particularly strong effects on content knowledge as it is experienced in schools.
First, digital technology makes sophisticated information far more accessible than it was in the print-dominated world. For many generations, access to information written by and for professional chemists (for example) depended on access to a research library where the copies of the journals were stored and the professionals who taught at that university could help individuals access and understand that information. Since computer networks have become widely available, access to professional literature (which is now digital) has expanded to every location with an Internet connection and a subscription to a database of periodicals is located. Second, digital information tools are used by individuals, including those with dubious credibility, to distribute information widely. Further, information has become politicized to a greater degree than it was for previous generations, and marginalized and fringe ideas and interpretations of evidence are becoming widely reported and defended.
Together, these factors both afford new opportunities for students and teachers and cause difficulties for those people. Both the affordances and difficulties have implication for efficacious IT managers. These are also the foundation for the pillars of digital learning (Davidson & Goldberg, 2009) (see Table 1.5.1).
In 1644, John Milton composed a pamphlet in which he argues for freedom of expression; areopagitica has been adopted as a term to describe the capacity for individual to compose and distribute any ideas they see fit. Digital tools, especially those called Web 2.0 tools have been interpreted as the realization of areopagetica and students can use these tools to extend and expand the audience of their works. They no longer create solely for their teachers, but they can create for global audiences. This changes the nature of writing and creating for students.
Areopagetica has been adopted by other creators as well, so the vast content available to educators and students includes accurate information from credible sources, fiction packaged as fact, as well as myths, misinterpretations, sarcasm presented as fact. These many variations fill the space between accurate and credible information and purse falsehood. This disparate information led Mark Dueze (2006), a scholar of media and journalism, to conclude the digital media landscape is filled with content creators who “juxtapose, challenge, or even subvert the mainstream” (p. 68) for a variety of reasons.
In a 2016 report on science communication, the National Academies noted a study in which 40% of Americans reported they get science news from Facebook. This contributed to the Committee on the Science of Science and Science Communication (2016) to observe, there are more actors in the media landscape who may, either intentionally or unintentionally, provide inaccurate science information. While today’s science media landscape is likely larger than the declining mass media/newspaper- delivery system of the past, it does not offer clear mechanisms for filtering out false, sensational, and misleading information. More than ever before, citizens are left to their own devices as they struggle to determine whom to trust and what to believe about science-related controversies (p. 4-2).
In the months after the 2016 elections in the United States, the term “fake news” gained in popularity to describe the phenomenon of unverified information in the media. For K-12 educators, navigating and helping students to navigate this emerging information landscape determines the reality of content knowledge. An increasing number of organizations are influencing the contents of recommended curriculum and resources, and this is further complicating content knowledge (CK) for educators. In recent decades, educators’ professional organizations have begun publishing curriculum standards (for example National Council of Teachers of English & International Reading Association, 1996; National Council of Teachers of Mathematics, 2000; NGSS Lead States, 2013). In the 2010, the National Governors Association, initiated the Common Core State Standards, which is an effort to create a national curriculum in the United States. Ostensibly these organizations seek to improve education, but the political nature of governorships makes this a dubious claim; further, educators professional organizations may be motivated to maintain and expand membership rather than affect education.
Textbook publishers also exert strong influences on what is taught. In some jurisdictions, a small number of textbooks are adopted for use by large number of students, publishers approach these areas as mass markets and adopt the strategy of providing the least objectionable content (Johnson, 2006) which allows publishers to sell to the widest audiences with the least potential for offending or alienating large subpopulations so that their media is avoided.
The open educational resource (OER) movement is another factor that is affecting content knowledge in the 21st century school. OER’s are alternatives to textbooks that are published under copyright licenses that allow others to copy, edit, and redistribute the materials without the need to pay the original author or to seek further permission. Typically, an open education resource originates when an expert (often one who teaches undergraduate courses in a field), polishes and details the resources prepared for his or her students, and uploads them to the Internet under the Creative Commons license. An educator who finds the resources and wants to adopt them will download the file, edit it to meet his or her students’ needs, and the focus of the course being taught. The materials derived from an OER source are then made available to the students, and to complete the transaction, the derivative resource is contributed back to the open education community.
Educators and efficacious IT managers are left with the task of providing appropriate access to the vast information sources that are available so they can maintain and update their content knowledge. They provide access to full-text databases for library patrons, they help teachers learn about and design learning activities that give students experience navigating the vast information landscape, and they support educators who participate in OER communities all the while seeking to minimize access to information of dubious credibility.
Pedagogical Knowledge
Of the three individual types of knowledge that contribute to TPCK, pedagogical knowledge is perhaps the most complicated as it is the one with the broadest definition. Relevant technological knowledge is largely defined by the systems available in the school; content knowledge is largely defined by experts who teach the teachers and by textbook and OER publishers. Technological knowledge and content knowledge are clearly bounded and consensus can generally be reached about what constitutes the domain and how it can be improved. Pedagogical knowledge, on the other hand, is defined differently by different scholars and vastly different actions can be called pedagogy. Further, the appropriate pedagogy depends on the goals of the activity as well as the nature of the students and the nature of the curriculum. Pedagogical knowledge is a less clearly understood than other types of knowledge and consensus regarding improvement cannot be easily reached. How pedagogical knowledge is instantiated in the classroom is largely dependent on decisions made by the teacher. Much of the professional discourse on pedagogy, including research and both pre-service and in-service teacher education, differentiates two types of pedagogy. The Standard Model captures one approach to teaching that continues to be supported by various stakeholders. Chris Dede (2010), a scholar from Harvard University, reviewed the many curriculum frameworks that had been produced in the 21st century, and he concluded they demonstrated that educators and education leaders were “systematically examin[ing] all the tacit beliefs and assumptions about schooling that are legacies from the 20th century and the industrial age” (p. 73).
In recent decades, a number of pedagogical models have been presented that call for students to play a more active role in defining curriculum building knowledge, and communicating what they have learned than it typically allowed in instructional pedagogies. While advocates for these many methods differ in the specific details of classroom activity, these methods share the common elements of a curriculum based in complex problems, ample opportunities for social interaction (between teachers and students and among students), students are found articulating their new knowledge, and attending to metacognitive understanding. Advocates for these methods ground their pedagogy in cognitive psychology (rather than behaviorist psychology) and build their rationale around theorists such as Jean Piaget, John Dewey, and Lev Vygotsky.
Instructionism, which is largely used in the Standard Model, is teacher-centered pedagogy, and it has been established that it can be applied with efficacy to the small portion of content that consists of well-known concepts and ideas as well as procedures that can be clearly described. When teachers use instruction, they plan the logical path through the content and they decide when students (either individually or collectively move along). Teachers also measure success by students’ retention of the information and procedures. These methods are grounded in the assumption that learners respond to rewards and punishments; it is reasoned that by rewarding answers and actions that are aligned with expectations (or by punishing those that are not), teachers can promote learning.
Pedagogical knowledge extends beyond understanding the nature of teaching strategies and skill at using those strategies to plan and execute lessons. Educators can approach their work from different perspectives and this affects both what they plan for students and how they present lessons. Douglas Thomas and John Seely Brown differentiate education that teaches about content from education that teaches within the content. When students learn about a subject, they are external to the content and teaching focuses on transferring declarative knowledge and procedures to the learners. Thomas and Brown (2011) suggested this can be mechanistic with “learning treated as a series of steps to be mastered....” (p. 25). When students learn from within the subject, they adopt the methods and approaches of those who work to investigate problems in the field and they produce products similar to those created by workers in the field. This leads to learners developing both explicit knowledge and tacit knowledge, and Thomas and Brown (2011) observed, “the point is to embrace what we don’t know, and continue asking those questions in order to learn more and more....” (p. 38).
Research focusing on learning in informal situations (Lemke, Lecusay, Cole, & Michalchik, 2015) is extending pedagogical knowledge to recognize the role of the learners in the process. Rogoff (1990) described guided participation as a method of informal learning that started with highly-scaffolded modeling and demonstration by mentors early in the experience, but learners assume increasing responsibility for planning, undertaking, and judging the learning products as they develop greater expertise. Caine and Caine (2011) proposed guided experience as a pedagogy that captures the nature of learning that occurs in natural environments, which follows the perception/ action cycle. The perception/ action cycle posits learning is the continuous process of recognizing a situation, interpreting it according to what it is already known, acting, and then adjusting further perceptions according to feedback after acting. Guided experiences are based on three elements:
- Relaxed alertness which find the learners motivated and prepared to learn in a stress-free, but high-expectation, environment.
- A complex experience which finds the learners acting in the same manner as experts rather than learning about what experts know.
- Active processing experience which finds the learners thinking about and making sense of their experiences.
Digital media is also presented as more amenable to guided experience than print. Caine and Caine (2011) even suggest that “technology often plays havoc” with pedagogy designed to transmit knowledge as it “includes student decision making, applying creative solutions to complex and real-life problems, and negotiating with peers and experts” (p. 20). Because more channels of communication, including body language and other movements, are possible with video but nit with text, the nature of the learning that can occur is different when using video media.
Mizuko Ito and her colleagues at the Digital Media and Learning Research Hub seem to have expanded the definition of natural learning as they studied connected learning in young people who comprise the digital generations. That research group observed learning that occurs outside of school tends to be “socially embedded, interest-driven, and organized toward educational, economic, or political opportunity” (Ito, et. al, 2013, p. 6). The students who arrive in today’s classrooms are active and independent learners because of their experiences in the digital world, thus their experiences influence which pedagogies are effective with these populations. Such differences have been recognized by educational scholars for decades, and they led Bereiter (2002) to conclude, “everyday cognition makes more sense if we abandon the idea of a mind operating on stored mental content and replace it with the idea of a mind continually and automatically responding to the world” (pp. 196-7).
As students become more active in creating and communicating new knowledge, basic skills and knowledge can become relevant, so students become motivated to learn the content that is teachable through instruction. As they adopt student-centered methods, many educators are finding a renewed need to include instruction-based methods in their classrooms. This need is less predictable than in instruction and tends to hold the attention of individuals or small groups of students; computer technology and digital media are meeting those needs. Consider the science student who is investigating trajectories of projectiles; she will find it necessary to work with quadratic equations. Using technology, the teacher can direct the student to a lesson reviewing the methods of solving quadratic equations. There is evidence such lessons that include worked examples in which the steps are explicated can be very effective strategies of instruction (Shen & Tsai, 2009). These video lessons can be made available in a learning management system so that students can access them whenever they are needed and can be repeated whenever they are necessary.
It does appear reasonable to conclude that efficacious IT managers will be supporting educators as they create more diverse and flexible learning environments than was necessary for previous generations of learners. The nature of the experiences central to the curriculum will determine the nature of the IT systems that are built and supported. A single approach to using technology in classrooms, or a single type of technology activity will not suffice for learners to participate in the emerging information landscape.
Pedagogical Technological Knowledge
The most efficacious development of pedagogical technological knowledge arises from those situations in which technologists (who obtain and configure test systems) scale up and deploy into production those systems that have been examined by and tested by teachers who identified pedagogical uses. Many of the information technology tools available in schools were developed for audiences and purposes other than education. It is only by investigating emerging technologies and adapting them for teaching that educators gain pedagogical technological knowledge. Those systems that appear to have the greatest pedagogical application with the least consumption of technical resources and the least extraneous cognitive load are those that deserve greatest attention and priority.
Consider social media as an example. Originally developed so that individuals could publish on the Internet (and still widely used for that purpose), many educators have found educationally relevant tasks that can be accomplished through social media, and these can be applied to pedagogical problems in many classrooms. The teacher who finds an excellent solution to a problem in her classroom (perhaps the biology teacher whose students have built an excellent model of a cell) can take a picture of the solution, and post it to a Twitter account. By embedding the feed in her online classroom, the solutions can become part of the resources for all students to use. This exemplifies the adoption of easy-to-use and effective technologies predicted by technology acceptance (Venkatesh et al., 2003).
Other examples of technologies with unexplored pedagogical applications include haptic and full-body motion interfaces (Malinverni & Pares, 2014) which allow for alternatives to keyboard and mouse inputs and for outputs other than printed documents or screen displays. Video games that track motions of bodies have been incorporated into some physical education courses and this is an example pedagogical technological knowledge affecting students’ experiences. Virtual reality, in which technology provides three-dimensional content is another field of developing pedagogical technological knowledge (Ricordel, Wang, Da Silva, & Le Callet, 2017). As these technologies become more fully developed and less expensive, it is anticipated they will become more widely adopted for educational purposes.
Pedagogical Content Knowledge
Just as each content area has its own combination of concepts, ideas, and procedures, each has its own collection of activities that are well-suited to helping students learn that content. In many content areas, the methods used to teach are the lessons the teachers intend to teach. In science classes, for example, laboratory activities in which students plan and set up an apparatus so they can collect data, which they analyze are engaged in methods that teach both the content (the activities are designed to demonstrate important phenomena) and the methods (the activities give experience setting up experiments and analyzing data). Writing courses, also, find the boundaries between pedagogy and content blurred, as the coaching and advice students receive (and give) are intended to improve their writing as they gain experience writing.
Pedagogical content knowledge is an important aspect of on-going teacher education. It has been established that the cognitive and learning sciences are continuing to discover important aspects of pedagogy that were previously unknown and these lead teachers to adopt new methods or adapt their existing practices, so pedagogical knowledge is changing. It has also been established that content is rapidly advancing, so content knowledge is changing rapidly. As a result, the pedagogy used to teach content during a teachers’ preparation is likely to be challenged by new discoveries in the learning and cognitive sciences. The responsibility of supporting teachers’ pedagogical content knowledge falls largely to education professionals and leaders such as department leaders and curriculum leaders, efficacious IT managers will accommodate new demands and needs that are produced as educators continuously redesign and recreate their methods to reflect new discoveries.
Technological Content Knowledge
Technology is affecting how discoveries are made, and even what discoveries can be made, as well as how new knowledge is constructed in many fields. Consider mathematics-rich fields; spreadsheets, statistical software, and graphing calculators have reduced the cognitive demands of manipulating data for recent generations of workers (and students) in those fields. Further, citation management tools and online databases containing the full- text of periodicals has redefined the work of researching in many fields. During a teachers’ professional preparation, he or she will gain experience using the tools employed practitioners in his or her field. In a classroom, many of the same tools will be available and many familiar tools will be replaced by new ones, so teachers must continue to develop and refine their technological content knowledge as it emerges over their careers.
Much technological content knowledge is developed in small and specialized groups, and it is developed to meet very specific goals. A group of math teachers, for example, may develop technological content knowledge around options for graphing functions on mobile devices. As handheld computers have become ubiquitous, students are likely to use many different graphing apps to solve problems. A group of math teachers may plan professional development time to sit with a collection of the problems they typically give to their students, and solve them using the many different devices and applications so they become familiar with the steps for graphing with different software and hardware options. After developing this technological content knowledge, they will be better prepared to both assess and evaluate the choices and support students who may be using different devices. As a result of improved technological content knowledge, tools that are easier to use and more effective are likely to be installed by IT managers and teachers are likely to be more efficacious in helping students use all tools to learn they content they teach.
Technological Pedagogical Content Knowledge
Mishara and Kohler’s (2006) TPCK model differentiates seven different types of knowledge that are relevant to technology- rich teaching and learning. These are useful in deconstructing classrooms into aspects that can be developed and improved in isolation, but efficacious IT managers are cognizant of the fact that these types of knowledge influence each other. A complete framework for understanding teaching requires consideration of and reflection upon all aspects of TPCK; the tools we use (technology), how we use it (pedagogy), and what we teach with it (content) combine to create new and opportunities and challenges in the classrooms.
Efficacious IT managers also recognize that new understandings in one type of knowledge will create permanent and irreversible changes in the others, and that once changes in technology are made, the effects on the others will be permanent and irreversible. Consider IT managers who deploy a learning management system (LMS) so that high school teachers can take advantage of online testing features, resource sharing, and online discussion tools to support face-to-face instruction. Teachers who use that LMS are likely to adopt new approaches to teaching and assessment that are specific for the LMS, but they may find those expand their effectiveness or improve their efficiency so they become a permanent part of his or her practice.
Mathematics teachers can point students to web sites where students can vary the coefficients, exponents, and other constants of functions and the changes are immediately graphed. When I share such sites with students, it is common for one or more to observe, “It is like we were playing with the graphs.” Such a site would affect the content knowledge introduced in the course, as it allows more sophisticated functions to be introduced more rapidly than they are without the technology. These sites also affect pedagogical knowledge of teachers as it introduces play into a topic that is not typically amenable to play and exploration.
It is also likely that those changes which teachers determine to be effective will be immediately adopted, they will exert peer- based social pressure on others to adopt it, and school leaders will exert leader-based pressure all teachers to adopt it. TPCK also provides a framework for ensuring a technological solution is extended and expanded only in those setting where they are appropriate, and inappropriate technology solutions are avoided. While the playful nature of interactive graphing sites can be useful for students who are developing a sense of the nature of graphs and the different effects of each term on the appearance of the graph, but play is unlikely for be effective when teaching students how to interpret graphs.
Efficacious IT managers will recognize the different pedagogical purposes of different technologies. Those who recommend a single tool for every pedagogical problem (or who interpret every pedagogical problem as solvable with a particular technology) are likely to be making decisions and recommendations for purposes other than teaching and learning. Deploying a single technology in every setting is an approach to technology planning that is not supported by leaders who understand TPACK.