Technology in School Classrooms How It Can Transform Teaching and Student Learning Today pdf pdf

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Technology in School Classrooms

How It Can Transform Teaching and

Student Learning Today

Edited by James G. Cibulka and Bruce S. Cooper

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Published by Rowman & Littlefield

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Foreword

NEXT GENERATION LEARNING IN SCHOOL

This book provides an excellent analysis of whether and how digital technologies can transform teaching and learning in classroom settings. The authors collectively provide a multidimensional perspective on how and under what conditions technology can be productively employed by teachers to more effectively meet the challenges presented by a rapidly evolving world.

Civilization today presents a landscape deeply shaped by technologies—transportation, communications, and computing—that place new demands on schooling to prepare today’s students with knowledge and skills not necessary for prior generations (Fishman & Dede, 2016). This challenge has profound implications for teachers and the work of teaching, in terms of both what it means to teach and how one teaches.

I agree with the editors’ stance that the important issue is not the value of digital tools and media as an educational innovation for industrial-era schooling, but their potential role in the emergence of an alternative, next-generation educational model well suited to preparing students for a future quite different than the immediate past.

Recently, in many types of work, advances in computing and in artificial intelligence (AI) have driven shifts in the “division of labor” between technology and people, as new types of tools have taken over the tasks people used to do (Levy & Murnane, 2013). As the chapters in Technology in School Classrooms discuss, these technological advances provide a useful lens for examining how job roles are changing in teaching, as well as how teachers can model for students the division of intellectual labor with technology that they, in turn, will experience when entering the workplace.

The fundamental impact potentially is not technology taking over teaching via AI, but intelligence amplification: technology providing a classroom infrastructure that enables teachers to direct their attention toward the students who need it the most, while supporting more proficient students to continue making progress on their own (Dede & Richards, 2012). Digital technologies can help teachers learn to shift their practice toward this new division of labor, so their classrooms center on “deeper learning” that prepares students for a global, knowledge-based, innovation-centered civilization (National Research Council, 2012; Dede, 2014).

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universal, high-quality professional development in education is in sharp contrast to other professions, such as attorneys and physicians (Dede, Eisenkraft, Frumin, & Hartley, 2016). This shortfall is, in part, responsible for continuing difficulties both in attracting strong people to teaching and in keeping them in classroom instruction more than a few years (Mehta, 2013). Moreover, a few forms of professional development have been studied using strong methods of evaluation and research, so improvement is difficult, given a lack of findings about what strategies are working well and why (Darling-Hammond, Wei, Andree, Richardson, & Orphanos, 2009).

Technology in School Classrooms’ chapters highlight the central role of teachers in classroom learning and also emphasize that using digital media to automate conventional models of professional development cannot be successful in fostering transformations in instruction. Ultimately, shifts in teachers’ practice require professional capacity building in which participants not only learn new skills but also “unlearn” almost unconscious beliefs, assumptions, and values about the nature of teaching, learning, and schooling (Dede & Frumin, 2014).

Professional development that requires unlearning necessitates high levels of emotional/social support in addition to mastering the intellectual/technical dimensions involved. In order for teachers of education to transform from presentational/assimilative instruction to active inquiry-based forms of student learning, teachers must unlearn their own mental models, which include emotional investments developed through decades of being a student receiving traditional instruction and further years of building skills in conventional instruction. Without unlearning, teachers teach as they themselves were taught.

At this point in history, the primary barriers in transforming to a twenty-first-century educational system are not conceptual, technical, or economic, but instead psychological, political, and cultural. Some people oppose any form of educational change that is not fully understood, arguing that traditional schooling was effective for them and that innovators should not “experiment on children.” But the most dangerous experiment we can perform is to keep our current systems of schooling in place, hoping that various small changes and the introduction of new technologies will make up for their shortcomings.

Over time, the disconnect between what society needs and what industrial-age educational models can provide is widening, and cohort after cohort of students has needlessly high rates of failure, creating terrible consequences for those learners and our nation.

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Chris Dede

REFERENCES

Darling-Hammond, L., Wei, R. C., Andree, A., Richardson, N., & Orphanos, S. (2009). Professional learning in the learning profession: A status report on teacher development in the United States and Abroad [Monograph]. Dallas, TX: National Staff Development Council.

Dede, C. (2014). The role of digital technologies in deeper learning. New York: Jobs for the Future. Retrieved from

http://www.jff.org/publications/role-digital-technologies-deeper-learning

Dede, C., Eisenkraft, A., Frumin, K., & Hartley, A. (Eds). (2016). Teacher learning in the digital age: Online professional development in STEM education. Cambridge, MA: Harvard Education Press.

Dede, C., & Frumin, K. (2014 July, 20). Unlearning and mirroring: Transforming instruction. Ed Week (blog). Retrieved from http://blogs.edweek.org/edweek/learning_deeply/2014/07/unlearning_and_mirroring_transforming_instruction.html

Dede, C., & Richards, J. (Eds.). (2012). Digital teaching platforms: Customizing classroom learning for each student. New York: Teacher’s College Press.

Fishman, B., & Dede, C. (2016). Teaching and technology: New tools for new times. In D. Gitomer & C. Bell (Eds.), Handbook of research on teaching (5th ed.) (pp. 1269–1334). Washington, DC: American Educational Research Association.

Levy, F., & Murnane, R. (2013). Dancing with robots: Human skills for computerized work. Cambridge, MA: Thirdway Publications. Retrieved from http://content.thirdway.org/publications/714/Dancing-With-Robots.pdf

Mehta, J. (2013). The allure of order: High hopes, dashed expectations, and the troubled quest to remake American schooling. New York: Oxford University Press.

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Introduction to the Topic— and the Book

James G. Cibulka and Bruce S. Cooper

This book addresses whether digital technologies can transform teaching and learning in America’s P–12 classrooms. Education technology expenditures in the United States continue to grow each year and have now become a major investment for school systems (Schaffhauser, 2016). The federal government has made large investments in promoting education technology, such as through its Preparing Tomorrow’s Teachers to Use Technology Program (PT3).

Yet technology proponents, as well as critics of public school spending and school performance, point to little evidence that digital technologies as currently employed in our schools have met their promise of improving the quality of education in America’s classrooms through new teaching practices and improved performance by students.

Controversy about whether technology is being used effectively by teachers and school administrators is not new. Debates on this question stretch back many decades, prior to the invention of digital technology, but the question of technology’s effectiveness has taken on a new complexion and urgency today. When educational television made its debut in the 1950s, for example, and film and radio before it, these innovations had quite modest objectives. At that time, technologies were conceptualized as supplementing regular instruction (Cuban, 1986, 2001).

Similarly, when computers initially were introduced in classrooms beginning in the 1980s, they were viewed as ancillary tools for teachers to use, often located in a separate learning lab outside the regular classroom. As new technologies were promoted by school boards and administrators, many teachers enthusiastically embraced them. Despite this fact, there have been continuing criticisms that too few teachers were adopting the innovations or were not using them appropriately.

Such concerns appear to have widespread credence. Fishman and Dede (2016) argue that most schools have not achieved a high level of technology integration. These schools operate at Level One (Minimal) or Level Two (Intermediate) rather than Level Three (Extensive).

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Only at Level Three is the technology used by teachers to enable learning that reaches outside the classroom, to “customiz(e) instructional conditions for learners, and to promote collaborative learning approaches.” They describe these classrooms and schools as rare.

TECHNOLOGY AS A DUAL FORCE CHALLENGING

AMERICAN SCHOOLS

For many decades, the fact that American teachers employed technology in their classrooms only at the margins could be viewed as regrettable, but it was hardly central to any overall assessment of the performance of our nation’s schools. However, technology now poses two parallel, and at points converging, challenges to American schools that are qualitatively different from the earlier role that technology played in American schooling.

The first dynamic operates at the societal level due to the emergence of a global economy that is driven by technological changes. These global economic forces are now an important “exogenous” influence on the American school system.

In The Race between Education and Technology, Goldin and Katz (2008) explain that technological change in our broader economy is proceeding faster than the American school system’s ability to adapt. This was not true in the last century, when the American public school system and our nation’s postsecondary system were developing to respond to the challenges of rapid industrialization and mass immigration.

While this educational system came to be regarded as the best in the world and was widely emulated, Goldin and Katz argue that American schools have been unable to respond as effectively to today’s postindustrial global demands rooted in rapid technological change.

They present convincing evidence that these exogenous influences on American schools will or can continue to create negative consequences for the American economy, jobs, and equality unless the American school system produces higher graduation rates, better student outcomes, and more equality of outcomes across student demographic groups. Technology now necessitates better outcomes from our educational system, and the use of digital technology tools in the classroom is one strategy for improving those outcomes.

The excellence movement that evolved from the 1980s onward, with the publication of A Nation at Risk (1983), certainly reflected concerns about the American school system’s ability to compete in a global economy. However, the emergence of the Internet in the 1990s and the resulting digital revolution accelerated these global forces, exerting increased political pressure on the American public school system to perform at higher levels.

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public education, digital technology is also viewed by many as a solution to these very same challenges. Dramatic developments within the field of educational technology are responsible.

Various facets will be discussed in this book. Hardware has evolved to include multiple devices such as laptops, iPhones, and iPads. Education software has grown exponentially, particularly for use in wireless environments. An amazing array of “apps,” produced continuously by tech developers working in a burgeoning tech industry, now purport to assist teachers and students in the classroom. Online sites have been created to curate and rate the quality of these apps.

The advent of digital technology also has spawned new kinds of schools that are entirely technology based, and others that employ “blended-learning” strategies. These ways of organizing learning also exist to some degree in bricks-and-mortar schools, including flipped classrooms.

A growing number of online platforms provide educational content, some of which build lessons based on videos and gaming. “Adaptive” or “personalized learning” has been made possible by advances in education technology. Many online platforms provide open access to specific fields of knowledge and research. Online tools also now support different forms of assessment that can be accessed by students, teachers, and parents.

Online education networks support communities of teachers, students, and parents and serve a variety of specific purposes. For example, some support teacher professional development. In short, the field of education technology, like technology’s influence in business, medicine, journalism, and many other institutions, appears to be growing exponentially.

These advances in educational technology developments have shifted our perception of its potential to drive innovations in the classroom. Xie and Hawk in chapter 1 of this volume point out that the introduction of computers in schools did not begin with this ambitious goal. Their role gradually shifted from emphasizing lower-level skills such as drill and practice to helping students develop more cognitive-based skills.

As these digital technology tools have become more sophisticated and more accessible outside of school, our expectations that they can drive improved schooling outcomes have increased. Not surprisingly then, many education reformers now see technology as a potential solution to the overall failure of the excellence movement to improve the performance of the American school system.

A good example is Paul E. Peterson’s (2010) embrace of technology as a disruptive innovation:

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Critics also point to the lagging performance of American students on international achievement tests like PISA and TIMMS as prima facie evidence of underperforming schools.

Changing Expectations for Student Learning

In this volume, we examine the proposition that digital technology can transform teaching and student learning in American classrooms. We need to think about student learning within an appropriate frame of reference, however. We agree with Fishman and Dede (2016) that a “techno-centric approach” defines technology as a “solution to problems” too narrowly. Student learning should be defined more broadly than performance on standardized tests. The National Research Council’s (2012) consensus framework describes twenty-first-century learning skills as developing students’ advanced knowledge and skills across several dimensions: cognitive outcomes, intrapersonal outcomes, and interpersonal outcomes.

Working from this broader definition of student learning, Fishman and Dede adopt a “socio-technical approach” to digital technology “that views the products of technology use as emerging from interactions among social and organizational structure, people, and tools” (p. 1270). This approach can help us understand whether technology is transforming teaching and student learning. It is also broad enough for us to ask why transformation is, or is not, occurring.

Changing Expectations for Students in Digital Literacy

In addition to the higher expectations for students just discussed, “digital literacy” is now considered essential to their success in the global economy. All students need these technological skills for postsecondary education and to prepare them for whatever careers they will enter, some of which have yet to be invented.

These digital literacy skills fall into at least three areas (Bussert-Webb & Henry, 2016). At the most basic level, students need keyboard skills to operate a computer or other digital device. They also need to learn how to navigate various software apps on the digital device they use. This is a challenge, given the many different apps that developers have put on the market with different design features.

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similar framework adopted by most other states). Digital literacy also includes collaborating with peers in online learning that requires accessing, evaluating, and presenting information.

While today’s students are sometimes described as digital natives, it is not a foregone conclusion that students possess all these skills. There are a range of impediments. Not all schools offer access to digital tools and wireless networks, which may consign some students to the lowest level of digital literacy. Even if schools have digital hardware and software, not all teachers explicitly develop students’ digital literacy in all three skill areas.

Because the Internet is primarily conducted in English, English language learners confront additional challenges in acquiring digital literacy. Students may not have equal access to digital devices and the Internet outside of school. In other words, without explicit school policies and classroom practices to counter these deficits, a “digital divide” may worsen existing inequalities in our current educational system.

Changing Performance Expectations for Teachers

In recent decades, as the education reform movement has adopted more rigorous learning goals for students, including common core standards, in most states, performance expectations for teachers also have been raised. It is worth considering how this context has increased expectations for teachers’ use of technology in their classrooms.

For decades, research has documented that teachers are the most important school-based influence on student achievement with cumulative (although fading) effects: for example, Jackson, Rockoff, and Stager (2014); McCaffrey, Lockwood, Koretz, and Hamilton (2003); Rivkin, Hanushek, and Kain (2005); Rowan, Correnti, and Miller (2002); and Wright, Horn, and Sanders (1997).

In addition, economists (e.g., Hanushek, 2011) have documented wide variation in teacher performance on standardized tests. A widely cited study by Weisberg, Sexton, Mulhern, and Keeling (2009) documented that most teacher evaluation systems failed to capture variations in teacher effectiveness. This work by education economists and reformers spurred federal and state policymakers to require new accountability policies that focus on teachers’ performance.

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Teachers unions have criticized the fairness of using state tests to conduct teacher evaluations. While these federal requirements were rolled back, in part, with the passage of Every Student Succeeds Act (ESSA), many states have continued to keep their high-stakes accountability policies, including teacher evaluation policies, in place.

This political context helps explain current pressures on teachers to improve student test scores. Yet there is no evidence that these policies have incentivized classroom innovations such as technology use. One can consult the annual analyses of technology use in American classrooms conducted by Education Week (2016) since 2002 for some indications. For its 2016 Technology Counts, Education Week conducted a survey of teachers. Many see themselves as technology innovators and risk takers. About a quarter of teachers describe themselves as risk takers who will adopt new technologies as they become available, but another 23 percent say that they will adopt new technologies only after they have been available for a while.

The picture that emerges from their self-reports is that typically they use technology for drills and review rather than to help challenge students with higher-order thinking such as creating new content and helping students using social media to collaborate on projects. Technology continues to serve a supplementary role in their teaching rather than being used to promote inquiry-based learning. Since the Education Week data have documented these practices over many years, it is not clear that high-stakes accountability policies have had any effect on teachers’ cautious embrace of digital technology.

Why are their practices regarding technology use so constrained? In the same survey (Education Week, 2016, June 6), they report that a variety of challenges affect their propensity to adopt new technologies, such as, in the following order, too few digital devices, lack of training, state/district curriculum demands, poor Internet access, insufficient IT support or administrative guidance, software glitches, and classroom management challenges. All these factors no doubt contribute, in part, to teachers’ use, or nonuse, of digital technology in today’s classrooms.

TECHNOLOGY ENTHUSIASTS AND TECHNOLOGY

SKEPTICS

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19). These seeds of a new educational system also are manifested in other reforms such as home schooling and workplace learning.

Technology enthusiasts share a conviction that the forces of change must and can transform schooling in the decades ahead. It is a transformational agenda. The federal government, spanning both Republican and Democratic presidential administrations, has been a strong proponent of this view. The most recent technology plan released by the federal government (U.S. Department of Education, 2016) illustrates a textbook example of the transformational perspective on digital technology:

Technology can be a powerful tool for transforming learning. It can help to form and advance relationships between educators and students, reinvent our approaches to learning and collaboration, shrink long-standing equity and accessibility gaps, and adapt learning experiences to meet the needs of all learners. (p. 1)

Technology skeptics respond that the results of digital technology on teaching practices have been limited and that student achievement gains from investments in technology have been negligible or, at best, mixed. They point to a vast literature documenting the foolhardiness of attempting to change and “rationalize” the educational system with external levers, citing the unintended consequences of high-stakes accountability systems.

Cuban (2013) has studied this issue extensively and points out that technology has not changed teaching practices despite widespread adoption of technology. Accountability systems have done so, he says, but ironically only to reinforce traditional teacher-centered pedagogical practices rather than the student-teacher-centered classrooms that technology advocates celebrate. He argues that there is no one way of teaching that works best for all students, and, moreover, that classrooms remain a poorly understood “black box.” Further, Cuban (2017) has observed it that is very difficult to ascertain whether teachers who claim to have changed their classroom practices on technology use have, in fact, actually done so.

Hence, technology skeptics tend toward caution when discussing technology as a singular influence capable of “disrupting” the status quo. Some researchers have concluded that there is no single medium such as digital media with such power per se. Instead, it is teaching methods and the quality of teaching that must drive any discernible change (Clark & Feldon, 2014).

Some recent research tends to reinforce the views of skeptics. Hattie’s (2009) meta-analysis of the school “effects” literature does not identify technology use as an important predictor of student achievement, although he found considerable variability in research findings.

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explicitly examine teacher behavior and was not designed to measure cause-effect relationships, prompting the authors to acknowledge that the connections between students, computers, and learning are complex.

At times, the debate can be confusing. Collins and Halverson point out that technology skeptics believe education should promote other educational goals for students such as critical thinking and analysis and strong oral and written communication skills (p. 48). Since many technology enthusiasts also endorse these same goals for students, one can get the sense that the two camps sometimes talk past one another.

Clearly, measuring technology’s potential and actual impact is challenging. A study commissioned by the American Federation of Teachers (DeBruyckere, Kirchner, & Hulshof, 2016) examined selected research on effective education technology and summed up the truths and myths surrounding technology with this observation: “Regrettably, we have become saddled with a multiplicity of tools, methods, approaches, theories, and pseudotheories, many of which have been shown by science to be wrong or, at best, only partially effective” (p. 2).

THE FRAMEWORK FOR THIS VOLUME

Given this confusing policy and research environment, the editors asked ourselves how our book could clarify whether digital technologies, notwithstanding their current limited impacts, have the potential to transform teaching and learning in American schools. In trying to capture what exactly is known today about technology’s potential, we have observed that much of the inquiry and research is conducted within specialized subfields whose discourses do not necessarily reach the entire education profession or the broader public.

These subfields cover a range of important topics relative to digital technology in schools. One subfield is learning theory. Unless there is a knowledge base about how digital technologies can promote student learning and engagement, with empirical evidence to support these foundational perspectives on learning, it is unlikely that technology will achieve the efficacious effects enthusiasts promise.

When films were introduced in classrooms, research did document their motivational benefits for students. However, there have been many advances in learning theory and digital technology in recent decades, particularly in the field of cognition. This volume includes a review of these advances with an eye to answering a central question of the book about the potential of digital technologies to advance student learning.

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one chapter focused on the teaching of science to all students, and the second on the teaching of foundational skills to special needs students.

Educational testing and measurement is a subfield that is sometimes overlooked in discussions of education technology’s potential to drive reform at the classroom level. “Assessment technology” is driving dramatic advances in test design and development, test administration, scoring, reporting, and interpretation. Again, this is a potentially vast landscape.

Recent controversies about high-stakes testing used for summative student outcomes have tended to obscure how assessment technology might be used in classrooms to support student learning. Because our primary focus in this book is on classroom teaching and student learning, we commissioned a chapter that charts the formative uses of assessment technology by teachers as well as students.

The earlier discussed subfields correspond closely to subdisciplines within the educational research community that focus primarily on teaching and learning, that is, educational psychology, curriculum and instruction, and educational measurement and assessment. An equally important subfield is the discipline of administrative leadership. In this subfield, there is an emerging empirical knowledge base on effective school-level leadership practices concerning adoption and implementation of digital technology.

School boards must delegate to administrators the task of translating technology investments into improved teaching and student learning. Some of this leadership is provided by district leaders, but the importance of school principals as change agents is now well understood. Accordingly, we have included a chapter in this book to summarize what this literature tells us about effective technology leadership practices.

Education finance also is a subfield that brings a useful body of expertise on costs of digital technologies. School budgeting and finance experts also study how equitably school resources are distributed across different schools, districts, and states. Therefore, education finance casts light on two of the possible barriers to technology use in schools —costs and equitable access. We have included a chapter that helps us understand these resource issues in more detail.

Technology enthusiasts argue that new kinds of schools and new ways of incorporating digital technology into the programs of brick-and-mortar schools are needed. A subfield has emerged to study new forms of schooling such as online schools as well as hybrids of traditional and online instructions known as blended learning and/or technology-focused schools. While research on their effectiveness has not fully caught up within the innovations, we include a chapter that reviews the history of online schooling and blended learning and what we know about their impacts on student learning.

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reform the content and delivery of professional development models. These models both employ technology to deliver professional development in new ways and address how teachers can incorporate technology in their classrooms to enhance student learning. We have included a chapter on what this literature tells us about their potential.

Finally, there is the field of teacher education. What evidence is there that teacher education programs prepare novices to use technology appropriately in the classroom? Are these programs using technology to deliver their programs differently and/or to reach new audiences? A chapter examines what we know about technology preparation in university-based teacher preparation and examines an innovative technology-delivered teacher preparation program that may be a prototype.

Taken together, these subfields can contribute to our understanding of technology’s potential to improve teaching and student learning. They potentially shed light on these specific questions:

What does research in each subfield tell us about the potential of technology innovations as a driver to improve or transform teaching and student learning in schools?

What do these subfields tell us about how widely these technology approaches (e.g., new practices, new schools) are being adopted?

What do they tell us about problems, constraints, and barriers that may impede adoption and effective implementation of technology in today’s classrooms, and how to overcome them?

No one subfield sheds light on all these questions. Taken together, however, they can improve our understanding of technology’s potential to improve teaching and student learning. Whether the emerging evidence from these subfields supports the technology enthusiasts or skeptics is a question we will return to in the concluding chapter.

OUTLINE OF CHAPTERS

In chapter 1, Kui Xie and Nathan Hawk address “Technology’s Role and Place in Student Learning: What We Have Learned from Research and Theories.” After reviewing the changing role of technology in student learning, they explain how technology integration can support teaching and student learning in three major areas of learning theory— human cognition, social learning, and motivation. They also address how technology enables new ways of organizing and delivering learning.

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guide the development of technology-supported professional learning. This will require conceptual shifts from traditional to transformative professional learning.

In chapter 3, Michael Barbour addresses “The State of K–12 Online Learning.” Barbour reviews the history of online learning and defines and classifies K–12 online and blended learning. He reviews research on the effectiveness of K–12 online and blended learning, particularly in relation to “traditional” face-to-face instruction and offers some tentative conclusions on the conditions under which K–12 online learning can be successful.

In chapter 4, Ted S. Hasselbring and Margaret E. Bausch address “Building Foundational Skills in Learners with Special Needs through the Use of Technology.” Technology can assist students with special needs who are being served in general education classrooms to build foundational skills for being successful in life and in the workplace. Technology provides a means of delivering deliberate practice to students with special needs, monitoring their performance, and providing feedback information to teachers.

In chapter 5, Michael Russell addresses “Assessment Technology as a Tool to Strengthen Teaching and Student Learning.” He describes several ways digital technologies can support teachers’ use of classroom assessment. He concludes that digital technologies can improve the efficiency, accuracy, and utility of classroom assessment.

Chapter 6, by John A. Craven III and Tracy Hogan, addresses “Emerging Technologies and Changing Practices in Science Classrooms.” They cite the rapidly changing practices in K–12 science education due to the rapid proliferation of, and demand for, digital technologies. The Next Generation Science Standards (NGSS) released in 2013 have raised learning standards for students. The authors explore how teachers are using emergent technologies to support these new goals and pedagogies within science classrooms across multiple grade levels.

In chapter 7, Lawrence O. Picus addresses “Economic Effects of Technology: Costs and Distribution of Resources to Support Student Learning.” He employs a cost-benefit approach to technology use in schools. Picus presents general cost estimates and reviews trends in technology use. Districts also face challenges in providing equitable access to digital technologies across all areas of the curriculum and at all grade levels.

In chapter 8, James Cibulka discusses “The Role of School Leaders in Leveraging Technology to Transform P–12 Classrooms.” A recently published review of research documents effective technology leadership by school principals. Cibulka concludes that leadership may be an important missing ingredient impeding many schools from fully achieving technology integration.

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technology preparation at education schools. Gallagher describes a new online masters’ program created in 2008 at the University of Southern California’s (USC) Rossier School of Education. She discusses three critical technology-related “outcomes” that all candidates graduating from the program should possess.

In the concluding chapter, James Cibulka draws together the findings and overall conclusions that can be drawn from the chapters. Do they tend to support the technology enthusiasts or the technology skeptics? The reader is invited to keep this question in mind as he or she reads the chapters.

REFERENCES

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Clark, R. E., & Feldon, D. F. (2014). Five common but questionable principles of multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (2nd ed.) (pp. 151–173). Cambridge, UK: Cambridge University Press. Collins, A., & Halverson, R. (2009). Rethinking education in the age of technology: The digital revolution and schooling in

America. New York: Teachers College Press.

Cuban, L. (1986) Teachers and machines: The classroom use of technology since 1920. New York: Teachers College Press.

Cuban, L. (2001). Oversold and underused: Computers in the classroom. Cambridge, MA: Harvard University Press. Cuban, L. (2013). Inside the black box of classroom practice: Changes without reform in American education. Cambridge,

MA: Harvard Education Press.

Cuban, L. (2017). Can technology change how teachers teach? (Part 2). Retrieved from

https://larrycuban.wordpress.com/category/school-reform-policies/technology-use/

DeBruyckere, P. D., Kirchner, P. A., & Hulshof, C. D. (2016). Technology in education: What teachers should know. Retrieved from http://www.aft.org/ae/spring2016/debruyckere-kirschner-and-hulshof

Education Week. (2016). Education Counts 2016: Transforming the classroom. Retrieved from

http://www.edweek.org/ew/toc/2016/06/09/index.html

Fishman, B., & Dede, C. (2016). Teaching and technology: New tools for new times. In D. H. Gitomer & C. E. Bell (Eds.), Handbook of research on teaching (5th ed.) (pp. 1269–1334). Washington, DC: American Educational Research Association.

Goldin, C., & Katz, L. F. (2008). The race between education and technology. Cambridge, MA: The Belknap Press of Harvard University Press.

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Economics, 6, 801–825. Retrieved from www.annualreviews.org

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Chapter 1 Technology’s Role and Place in Student

Learning: What We Have Learned from

Research and Theories

Kui Xie and Nathan A. Hawk

INTRODUCTION

The use of technology in general, and computers more specifically, has increased in both our society and our classrooms. Modern technologies have become more powerful, more accessible, more distributed, and more intelligent. For example, mobile device ownership in the United States has steadily increased over the past ten years, with 90 percent of adults owning a mobile device and 60 percent owning a smartphone (Anderson, 2015).

In addition, the participatory concept of Web 2.0 has reshaped the landscape of the Internet. The media and content on the web have grown substantially. Newer types of technology, such as location aware services, sensor technologies, open platform technologies, cloud computing technologies, artificial intelligence, and argument reality, are changing human experiences. New experiences with the technology are created that involve users being integrated within their real context, that use services for everyday tasks, such as driving directions and targeted marketing, and opportunities exist for greater collaboration with peers and experts around the world. These new forms of experiencing the world increase the authenticity of informal, in-time learning, central to the nonclassroom-based society today and critical to lifelong learning.

The Changing Role of Technology in Student Learning

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McKnight, 2015).

This development was followed by the creation of intelligent tutoring systems, allowing for a tailored individual learning experience. Jonassen (1995) argued that a computer-supported learning system should be used not only as productivity software but also as tools to construct knowledge. With the latter, higher-order, critical thinking can thrive, a necessary component for student learning.

Earlier use of computers in classrooms emphasized devices that were useful for individual and flexible instruction. With the technology infrastructure becoming more and more participatory in nature, the use of learning technologies started to focus on social learning processes, such as collaborative group learning. Research has shown that students perform better and learn more when they learn in groups and in social contexts (Littleton & Light, 1999).

This difference in the learning structure of a classroom is pertinent: whereas previously computers may have been a tool to increase learning efficiency, their use in social learning helps to create new learning environments that emphasize joint meaning making and collective knowledge construction (Cress, Stahl, Ludvigsen, & Law, 2015). The focus on learning is the group and the individual within the group in a collaborative setting, rather than the individual only. Technology has improved and evolved in our classrooms to enable and support this form of learning.

The Evolving Notion of Technology Integration

With the increased presence of computers, mobile devices, and Internet access, the assumption that technology and classroom learning are two separate concepts has been challenged. Learning and technology are becoming interwoven together in classrooms. Collaboration and critical thinking are needed to succeed in today’s world. The need for these skills is reflected in subject-level standards, making collaboration and critical thinking important foci of classroom instruction.

In learning activities that focus on collaboration and critical thinking skills, for instance, problem solving, project-based learning, and collaborative learning, it is often not possible to separate technology from the learning process that takes place in the classroom; technology is fully integrated into the learning process. Technology becomes an integral part of learning as it provides the necessary communication platform and tools and offers cognitive and social tools that enhance student performance and evaluation of learning activities.

Technology Integration Guided by Research and Theories

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design and the integration of learning technologies in classrooms. In the remainder of this chapter, we will define and discuss three major areas where technology plays an important role in students’ learning, including how technology supports human cognition, social learning, and motivation for learning. We will introduce major theories related to these topics, define what learning means under each topic, and illustrate some empirical evidence to show how technology supports learning.

In addition, we will also discuss how technology enables new ways of learning and teaching that would not be possible otherwise, for example, flipped classrooms, virtual learning communities, and massive open online courses (MOOCs). We will conclude this chapter with a discussion about the future trend of technologies and their roles in students’ learning.

THEORETICAL PERSPECTIVES

In technology-supported environments, research and theories address three general perspectives of human learning: the cognitive perspectives focusing on the information processing of the human cognitive system, the social perspectives focusing on the dynamics of social interaction, and the motivational perspectives focusing on the internal and external factors that drive and sustain learning actions. These theoretical perspectives have significant implications for technology-supported teaching and learning.

Cognitive Perspectives of Learning

While earlier research on human learning started with investigating human behaviors in response to contextual stimuli, also called behaviorism, recent research has focused on cognition and cognitive processes of learning, which theorize that human learning involves the mental process of acquiring new, or modifying existing, knowledge. The information processing theory is foundational to the cognitive perspectives of learning. In the human information processing system, three types of memory store and process information differently. Sensory memory receives information from our sensors such as eyes and ears. Working memory holds and manipulates information in active consciousness. Long-term memory stores information for future retrieval. These memory systems vary in capacity and duration of information processing. Information passes from one memory system to another through human learning experiences.

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The cognitive load theory is based primarily on the assumption that working memory is where active cognitive processes take place, but there is a finite load of information that working memory can accommodate. Cognitive load exists in three different categories: a load reflecting the natural complexities of certain information (intrinsic cognitive load), a load unrelated to learning that often occurs with poor instructional design (extraneous cognitive load), and an intentional load resulting from the learning process (germane cognitive load) (Sweller, 2005).

The schema theory describes information processing in the context of long-term memory. A schema describes an information structure with organized categories and specified relationships among these categories. Long-term memory significantly increases the capabilities of working memory, as schemas from long-term memory can be brought to working memory (Paas, Renkl, & Sweller, 2003).

In addition to the study of the human cognitive system, researchers examined a cognitive progress, called metacognition, where learners are aware of their own cognition and control their cognition. Metacognition describes a process where learners monitor and self-regulate their thinking and adapt to the environment.

Implications of Cognitive Learning Theories for Instruction and

Technology

Based upon the cognitive perspectives of learning, cognitive tools have been developed to assist learners in paying attention to stimuli (sensory memory), balancing cognitive load (short-term memory), organizing mental schema for future retrieval (long-term memory), and facilitating self-regulation of cognition (metacognition).

Supporting Attention

Attention is a cognitive process where the human mind focuses on certain external stimuli. Attention facilitates information passing from the sensory register to working memory for further processing. Among many cognitive tools, advanced organizers direct students’ attention to what is important in the coming material, highlight relationships, and provide a reminder about relevant prior knowledge. They can be presented in different forms. For example, Billings and Mathison (2012) created podcasts as a technology-based advance organizer for elementary students to provide a deeper understanding of future content. They found a significant positive effect of these podcasts as advanced organizers on English language learners’ academic performance.

Balancing Cognitive Load

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and germane. The basic principle to promote effective learning is reducing extraneous cognitive load, establishing a balance of intrinsic and germane cognitive load, and keeping overall cognitive load from exceeding the working memory capacity. For example, the cognitive theory for multimedia learning identified principles to guide the design of multimedia (e.g., contiguity, modality, redundancy, and coherence principles) aiming to reduce extraneous cognitive load for learning (see Clark & Mayer, 2016). When appropriately designed and implemented, multimedia materials, such as animations, can aid in learning as information is processed in both auditory and visual channels, reducing the demand for cognitive resources.

In addition, instructional strategies, such as digital games, may help to increase germane cognitive load and reduce extraneous cognitive load. Activities that are presented in various formats help to limit the cognitive load and may also increase relevance of content for students (e.g., Woo, 2014).

Organizing Mental Schema

Successful learning requires the organization and reorganization of mental schema in memory. Cognitive tools have been developed to assist in encoding and organizing information in long-term memory. Chart-based tools, such as concept maps, can aid the human mind in acquiring and retaining new information. They provide useful visual images of the information processing capabilities of the human mind, help to increase propensity for higher-order cognitive skills as well as improve the recall and processing of content-specific questions. For example, Yen, Lee, and Chen (2012) examined students’ learning outcomes and cognitive processing while comparing a text-based versus an image-based concept map. Their results showed that students engaged more in higher-level thinking when using an image-based concept map. Students with image-based concept maps also performed better when completing understanding and creating cognitive activities. Image-based concept maps aided in retention and the formation of new concepts.

Facilitating Self-Regulation of Cognition

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Social Perspectives of Learning

The research on social perspectives of learning focuses on how individuals interact with others to build meaning, solve problems, and learn through cooperation and collaboration. In cooperation, members split the work and combine their individual products to produce a common project, whereas in collaboration, members actively engage with each other to construct new knowledge and produce joint outcomes. Piagetian and Vygotskian theories provide a foundation for understanding social perspectives of learning.

According to Piaget, learning is a process in which individuals construct knowledge through interactions with the environment and their peers, by balancing cognitive activities and achieving equilibration through the processes of assimilation (a process in which new information is brought into one’s existing schema, such as learning to navigate new websites and software) and accommodation (a process in which existing schema are changed to deal with new information or a new situation, such as using computers for another purpose like distance learning).

When cognitive conflicts arise, learners must be able to assimilate or accommodate new information. Piaget’s work has important implications for cooperative and collaborative learning, mainly because of his ideas about peer interactions. Compared to teacher-student interactions, learners in peer interactions generally have equal social status, and thus have equal opportunities to influence one another.

Vygotsky emphasized the importance of sociocultural tools and social interactions inherent around learners. He further detailed internalization and externalization as key components in the learning process. He suggested that peers in groups develop together and optimally because they work within their zones of proximal development, which is a level of competence on a task that an individual could not achieve on his or her own but can master with appropriate support from a more capable peer.

More recent research examined how self-regulated individuals interact with each other in social learning contexts creating a coregulation process, by which individuals help to regulate and scaffold the learning and strategies of other students (e.g., Hayes, Smith, & Shea, 2015). Coregulation occurs interpersonally, primarily through collaboration and scaffolding; learners strive to work within their zone of proximal development.

Implications of Social Learning Theories for Instruction and

Technology

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Enabling Cooperation and Collaboration

Technology has provided the infrastructure and tools to enable collaborative learning. First is computer-mediated communication (CMC; Romiszowski & Mason, 1996), which includes the technologies, interactions, and people that form a process of exchanging information and ideas with the support of networked devices. Various asynchronous and synchronous technological tools have been used in educational contexts to enable the communication and interactions among people at a distance, including e-mail, instant chats, discussion forums, video conferencing, social networks, and virtual worlds. These technologies establish a space for cooperation and collaboration that extend learning opportunities beyond the physical classroom (Xie, DeBacker, & Ferguson, 2006).

Second, technology enables new ways for collaborative learning. Web 2.0 technologies allow users to create artifacts and interact with others in order to enable social collaboration. Wikis, for example, offer a common space for users to construct and edit content in an open-source platform. Cress and Kimmerle (2008) argue that the process of assimilation and accommodation, as initially proposed by Piaget, occurs both internally and externally. Since multiple users can modify wikis, the pages can have additional content (assimilation) or the structure of a page may fully change (accommodation).

This external process along with individual internal process of assimilation and accommodation helps explain the collaborative nature of wikis (Cress & Kimmerle, 2008). Learners are motivated to participate in editing wikis because of the process of cognitive conflicts and the need to arrive at equilibration, per Piaget.

In addition, virtual worlds—computer-based simulated environments—offer users immersive experiences otherwise not possible, constant access, and ample opportunities for developing higher-level cognitive functioning. Second Life, for instance, is a 3D virtual world where users can socialize, connect, and create using free voice and text chat (http://secondlife.com/). Second Life helps support socialization in a group, which further adds to rich learning experiences and networking (Edirisingha, Nie, Pluciennik, & Young, 2009).

Finally, technology enhances interactions in physical spaces. Mobile devices, including interactive (touch) multiuser devices, offer opportunities for synchronous group cognition by affording immense control and interaction in digital environments. For example, the SynergyNet project uses multiuser tablets in classroom settings to encourage interaction. Led through history and math lessons, students interactively discussed clues to a problem either on paper or on an interactive device.

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Supporting Social Collaboration

Technology supports collaborative learning by using different techniques to help students accomplish difficult learning tasks that they would not be able to accomplish on their own. One prominent method is collaborative scripts, which are simply guides for learners about how to structure social interactions that promote effective peer learning (King, 2007). In collaborative learning research, scripts often are embedded within shared, technology-based communication spaces designed for collaborative learning. These scripts are often presented as an instructional guide, collaboration rules, defined social roles (King, 2007), question prompts (Xie & Bradshaw, 2008), worked examples (Tollison & Xie, 2012), and so forth.

With the use of technology, scripts may become more adaptive to collaborative situations. For example, a collaboration script, “I disagree because …” would encourage students to articulate their opinion and provide rationale for their positions. Another type of script, for instance, would define social roles for the group, “Please select one member as challenger, one member as defender, one member as moderator, and one member as summarizer in your group …” Such scripts would encourage group members to raise diverse opinions, argumentations, and reflections.

Scripts effectively externalize the process of collaboration, with the ultimate goal for learners to internalize the process as the scripts gradually fade. When students are placed in contexts where scripts are enabled, and in some cases, where the collaboration process is modeled, they show greater signs of quality of work and of the requisite amount of individual and group cognition necessary (Rummel & Spada, 2007).

Motivational Perspectives of Learning

The motivational perspectives of learning primarily focus on factors that drive and sustain students’ interest and engagement in learning activities. The extant research evidence clearly indicates that motivation in education is a strong predictor for positive learning outcomes. Researchers propose that motivation should also be considered as an educational outcome among the twenty-first century skills (Anderman, Sinatra, & Gray, 2012). Several theoretical approaches to the study of motivation in educational contexts inform teaching and learning.

Self-determination theory distinguishes between types of motivation based on the different drives that provoke action, ranging from intrinsic motivation where a student takes action for the fun or challenge involved in the task to extrinsic motivation where the motive for a student to take an action includes seeking external stimuli or rewards, or avoiding pressure or punishment (Deci & Ryan, 1985).

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ability to cope with challenges (Ryan & Deci, 2000). Although school activities are not necessarily intrinsically motivating to all students, researchers suggest that instructions should be designed to foster greater intrinsic motivation to the extent that they satisfy three innate psychological needs, including autonomy—the need to determine one’s own behavior and to act on one’s own volition; competence—the need to feel successful; and relatedness—the need to relate to others.

Achievement goal theory explains motivation through goal orientations that emphasize the reasons for engaging in academic activities. Two primary reasons related to an individual’s engagement in achievement settings are mastery, with a focus on increasing one’s competence and skills, and performance, with a focus on demonstrating one’s ability often in comparison to others (Dweck & Leggett, 1988). Researchers further distinguished performance goals into a performance-approach (outperform others in a desirable event to show competency) and performance-avoidance goals (avoid demonstration of incompetence in an undesirable situation) (Elliot & Church, 1997).

Studies have reliably shown that students with mastery goals are likely to choose challenging tasks, persist in effort, demonstrate self-regulation, and achieve better outcomes (Greene & Miller, 1996). Students with performance-avoidance goals demonstrate less interest and engagement and show poor academic performance (Xie & Huang, 2014).

Expectancy-value theory proposes that motivation toward achievement-related behaviors can be elaborated through expectancies for success and task values. Expectancies for success are individuals’ beliefs about how well they will do on an upcoming task. They are individuals’ ability judgments against specific learning tasks and are strong positive predictors of learning and achievement (Eccles & Wigfield, 2002). Task values include intrinsic value—how interesting the learning activity is to the student, utility value—how useful the learning activity is to the student, and attainment value— how important the learning activity is to the individual.

Task values describe how a task meets different needs of individuals. They are strong positive predictors of individuals’ active choice to engage in learning behaviors and persistence through learning difficulties (Eccles & Wigfield, 2002). Research found when learners believe that information is valuable and intrinsically meaningful and they have a better chance to succeed in learning tasks, they are more likely to learn and to engage in related behaviors (e.g., Anderman & Wolters, 2006).

Implications of Motivational Theories for Instruction and Technology

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widely used in classrooms for the purpose of intrinsically motivating students, offering a fun activity, and increasing student interest. A player may even become so engaged and absorbed in the activity that he or she loses the sense of effort and gains satisfaction from solving game challenges (Csikszentmihalyi, 1991).

Researchers identified the distinction between the motivation for playing and the motivation for learning in games, and proposed that meaningful game-based learning engagement should be an integrated and continuing process that advances from affective engagement driven by optimal challenge, cognitive engagement situated in playfulness, to potentially game action-based content engagement (Ke, Xie, & Xie, 2016).

Gamification, an area of recent development within education, uses natural game elements and integrates them into nongaming situations, such as scoring systems, points, and digital badges. These elements act as rewards for performance and show mastery of certain goals and content (Ahn, Pellicone, & Butler, 2014). For example, digital badges are achievement certificates players earn after completing game tasks. These badges are generated, recorded, and presented in technology-based gaming environments.

Research suggests that badges may substantially influence extrinsic motivation because learners participate in activities in order to earn badges and compare themselves to other participants. They also purport to affect student behavior and improve motivation because they represent praise and validation of performance and competency. When badges are included and students are openly aware of them, students pursue earning them and spend more time on task (e.g., in online coursework).

Further, as the task difficulty increases, both the effort to earn badges and the overall task motivation may increase (Hakulinen, Auvinen, & Korhonen, 2015). In a study of using digital badges in the classroom, students became less interested in comparing themselves to others and instead focused on the content, and this effect was particularly salient among low-performing students (Abramovich, Schunn, & Higashi, 2013).

TECHNOLOGY ENABLES NEW WAYS OF LEARNING

Infrastructure, engineering capabilities, and overall investments in new, more efficient technology have helped shape the way that we use technological devices in society, and, in turn, enabled new ways of instruction. These technology developments have promoted more independent and adaptive learning. Tools for coordination, collaboration, and communication have advanced, forming a global society of learners. These developments have ultimately led to openness in education and new instructional approaches such as flipped classrooms, virtual communities of learners, and MOOCs.

Flipped Classrooms

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Internet so students can access instructional materials and view content at their own time and pace. Flipped classrooms use the technology available (videos, screencasts, audio lessons, etc.) to deliver traditional “lecture material” to students before and outside of classroom time; this frees up time for in-class interactions and problem-solving activities, which promote in class application of content material (Rotellar & Cain, 2016).

This instructional format allows for differentiated and personal learning, while providing more time for collaborative activities during classroom time. In flipped classes, students are expected to watch the “lecture materials” at home, and be prepared for group discussion and problem solving during class. The in-class activities offer opportunities for social interactions and collaborations that are needed to support active learning and critical thinking.

Researchers suggested several design principles to increase success in a flipped classroom: teachers should provide exposure to materials prior to class, give incentives to prepare for class, and structure assessment, guidance, and appropriate feedback for students. A clear link between the online preclass material and the in-class activities should be established. Finally, teachers should seek to build a learning community where students can interact to build knowledge (Kim, Kim, Khera, & Getman, 2014).

Virtual Learning Communities

With the affordance of learning technologies, virtual learning communities are formed in both formal and informal learning settings. For example, Virtual Math Team (VMT;

http://www.mathforum.org) is a project that supports virtual learning communities within math classes. VMT engages learners in geometry problems through a drawing space and chat environment that help peers negotiate problem solving and goal setting during problem-solving exercises. Students develop math discourse in this computer-mediated environment (Stahl, Koschmann, & Suthers, 2006). Students collaborate on an interesting and challenging math problem using dialogue and propose specific solutions or directions related to the problem. Scaffolding features in VMT could help students develop their critical thinking skills in math and strategy planning for solving problems.

Social network sites have also helped shape collaboration activities for students to promote informal learning and develop group organization. Social network sites typically feature interconnected users, user-generated content, and the interaction between them. Sites that are popular and widely used, including Facebook, LinkedIn, and Twitter, have the potential to transform the type of learning collaboration that occurs, leading to improved learning engagement and offering platforms for building virtual learning communities (Greenhow & Li, 2013).

Technology in School Classrooms How It Can Transform Teaching and Student Learning Today pdf pdf