The Future of Work

Since the turn of the century, a seemingly never-ending series of advocates have told whoever will listen about the changing nature of work in the coming decades. Graphs such as this one I adapted from Levy and Murname (2005) seems to convey the typical message:

the future of work
Expected trends in 21st century work (Adapted from Levy and Murname, 2005)


In general, these advocates predict employers will value different skills than previously.

I cannot disagree that new skills are necessary. I see the work done by people around me (including that in my adult children’s generation, and that in my generation who are into our third decade in the workforce), and I see it requiring different skills than were needed by my parents and their parents. I do think many advocated have missed one important change, however.

Technology is certainly embedded (deeply) in our work. We use computers to interact and to access and process and create information. What I observe that appears missing on much of the literature about “the future of work,” is the important role of humans who are skilled at navigating the space between technology and human affairs.

Consider these examples:

  • A space planner in grocery stores who considers disparate information (some of it explicit, much of it implicit) to decide what products are sold in supermarkets and how much inventory of each product is kept. This individual uses sales information, demographics of store locations, industry trends, and conversations with local managers to plan what goes where on the shelves.
  • The manufacturing professional who designs products and models them on computer screens before building the products and determining their quality. They then understand the technical and human parts of the manufacturing system to ensure the processes become more efficient and produce items that meet customer’s needs.
  • The teacher who makes use of sophisticated graphing tools to allow students to play with graphs to see how they vary depending on the coefficients, constants, and exponents. Those teachers then help students translate the graphs into situations and measurements rather than spending time learning the rules and algorithms of graphing the equations.

Daniel Pink (2005) and others have reminded us the future of work is in the “things” humans can do, but computers cannot. Advocates for coding remind us that the future of work is in the ability to control the IT in our lives. I maintain the future of work lies in the ability to leverage IT to accomplish to tasks relevant to human needs.



Levy, F., & Murnane, R. J. (2005). The new division of labor: how computers are creating the next job market. New York: Russell Sage Foundation.

Pink, D. (2005). A whole new mind: Why right-brainers will rule the future. New York: Riverhead Books.

Organizational Frames

Leaders seek to affect change; they identify those parts of the organization that must become more efficient or more effective. Efficient operation means outcomes and goals are met more quickly by consuming fewer resources. More effective operation means the outcomes are more closely aligned with the intended outcomes.

Leaders also seek to affect transformation change. This means the outcomes or goals are different. Christensen (1997) observes transformation change is often disruptive as the organization must change in a fundamental way, and the tools and methods that were efficient and effective for the previous goals are no longer.

Both leaders and followers will confirm the degree to which change is affected varies according to many variables, and it is very difficult to transfer innovations form one environment to another. Those leaders who are more successful than others seek frameworks to organize the change in their own minds, to focus and refine efforts to affect change, and to help them understand resistance. Bolman and Deal (2008) have developed four organizational frames in their book (entitled Organizational Frames) which has been through several editions.

  • Structural frame includes the tools and methods through which organizations operate. Those parts of the organization within the structure frame are refined to make the organization more efficient or more effective. When transformation change in undertaken, these are often replaced. The structural frame is important for leader to understand as it represents the actions and interactions members of the organization experience on a daily basis.


  • Human resource frame includes those aspects of the organization represented by the individuals who belong within the organization. How the structural frame changes affect how individuals fit into the organization, and leaders must take actions to ensure the human resources are aligned with the goals of the organization. Strong leaders develop the human resources frame to foster this alignment.


  • Political frame includes those aspects of the organization that persuade decision-makers as well as the power to make decisions. While much political influence arises from one’s position within the organization, there are other influences. Especially in the technology-rich landscape in which organizations operate, IT expertise or other specific expertise necessary for emerging pats of the structural frame can increase one’s political powers. Effective leaders are often the individuals who can form coalitions of individuals who have complementary skills and knowledge.


  • Symbolic frame comprises a complex set of beliefs and values about the organization. BY answering the question, “What does it mean to be a part of this organization?” one can get a sense of the symbolic frame. In many ways, the symbolic frame is as much a reflection of the individual as it is a reflection of the organization. If I find that identifying with an organization symbolizes something unacceptable to me, then I am unlikely to continue to be part of the organization.


As leaders, we believe there is agreement between what we perceive to be “the right” direction to our organization in each one of these frames. That is not always true. Dismissing those who disagree with us is the lazy way to approach the work of change; it is also short-sighted and more likely to lead to our failure.

Resistance is often grounded in lack of clarity. By clarifying goals and actions within these frames, leaders can frame their work and their leadership, this be more likely to succeed.


Bolman, L, & Deal, T. (2008). Reframing organizations: Artistry, choice, and leadership (4th ed.). San Francisco, CA: Josey-Bass.

Christensen, C. M. (1997). The innovator’s dilemma. Cambridge, MA: Harvard Business Press.



Technology Acceptance– Understanding Decisions to Use IT

This except is from my book Efficacious Technology Management: A Guide for School Leaders


Technology acceptance model was first elucidated to understand the observation “that performance gains are often obstructed by users’ unwillingness to accept and use available systems” (Davis, 1989 p. 319), and it has been used to study decisions to use (or avoid) technology in many settings. Variations of technology acceptance model have been used to develop and refine both IT systems (hardware and software) and organizational practices that rely on IT systems. It is used to predict and explain both how individuals interact with IT as well as patterns of IT use within groups, and it is used to change perceptions of technology and patterns of technology use.

In 2003, Venkatesh, Morris, Davis and Davis modified the TAM into the Unified Theory of Acceptance and Use of Technology (UTAUT); in this work, the scholars combined eight different theories that predict the decision to use technology into one. According to UTAUT, four factors are positively associated with the use of technology: performance expectancy, effort expectancy, social influences, and facilitating conditions (see figure 2).

  • Performance expectancy is a measure of the extent to which an individual believes technology will affect his or her job performance; it is rooted in efficiency, relative advantage, and outcome expectations. Interventions that lead to increased efficiency or improved outcomes will be more used.


  • Effort expectancy is a measure of the individual’s perceptions of how easy it is to use the technology; users intend to use that technology they perceive to be easy-to-use.


  • Social influences are related to the individual’s perceptions of how others perceive the technology and its use; technology used by others whose opinion matters will be more used.


  • Facilitating conditions include organizational structures that support technology including responsive and effective technical support, adequate replacement plans, access to necessary training, and other supports. More and more highly functioning systems that maintain and provide technology in organizations are associated with increased use of it.


Unified Theory of Acceptance and Use of Technology

Figure 2. Factors directly associated with technology use (adapted from Venkatesh, Morris, Davis and Davis 2003)


It is notable that these factors are associated with ones’ intention to use a technology are based on each individual’s perceptions. In a school, different populations and even different individuals within a population may perceive the same technology differently, and those differences will affect individuals’ intentions to use the technology. Efficacious IT managers will use UTAUT as a theory to explain observed uses of technology and predict interventions that will change those patterns. Changes can be made to affect those factors, and failures to observe the expected changes can be evaluated for either effectiveness or perceptions of the changes.


Davis, F. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly 13(3): 319-340.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425–478.

Educational Design Research: An Emerging Planning Tool

Schools are institutions that leaders seek to improve. They take actions so that operations are more efficient; they take actions so that outcomes are more closely aligned with goals than they currently are. They also take actions so that new goals are achieved.

Whether the improvements are meant to reform operations (make them more efficient or effective for existing goals) or to transform operations (so that new goals are achieved), improvement and change requires planning. Traditionally, leaders approach this work in a familiar manner:

  • Begin by identifying the area of improvement;
  • Design a system that will led to the improvement;
  • Implement the systems;
  • Gather evidence to judge the degree to which the improvement has been realized;
  • Identify a new problem.

Leaders approach these as clearly bounded and linear; it is reasoned that once a step is completed one proceeds to the next. While this approach works well for some systems, many recognize that social systems like schools are far more complex and the planning processes comprise neither well-bounded steps nor linear steps.

In many situations, school leaders seek a sophisticated knowledge of the improvements they undertake:

  • deep understanding of the complex issues they face;
  • to design effective interventions;
  • to understand why their interventions succeeded or failed;
  • to ground all of this in sound theory and existing practice.

Leaders are recognizing the traditional linear models of planning are not amenable to the traditional linear planning. They need more time and structures to understand problems, they must craft interventions to reflect the nuances of their situation, and they need real evidence to understand their work. Educational design research (McKenny & Reeves, 2012) is emerging as a model for those who seek to both reform and transform school operations.

cover of Efficacious Technology Management
Efficacious Technology Management

In my book Efficacious Technology Management: A Guide for School Leaders (which is available under a Creative Commons license and can be downloaded at is include these paragraphs on educational design research:


McKenny & Reeves (2014) captured the dual nature of educational design as a method for designing interventions and a method for generating theory, as they noted it is motivated by “the quest for ‘what works’ such that it is underpinned by a concern for how, when, and why is evident….” (p. 23). They further describe educational design research as a process that is:

  • Theoretically oriented as it is both grounded in current and accepted knowledge and it seeks to contribute new knowledge;
  • Interventionist as it is undertaken to improve products and processes for teaching and learning in classrooms;
  • Collaborative as the process incorporates expert input from stakeholders who approach the problem from multiple perspectives;
  • Naturalistic as it both recognizes and explores the complexity of educational processes and it is conducted with the setting where education is practiced (this is opposed to the pure researcher’s attempt to isolate and control factors, thus simplifying the setting);
  • Iterative as each phase is complete only after several cycles of inquiry and discourse.

Projects in educational design research typically comprise three phases (see figure 7.3), and each phase addresses the problem as it is instantiated in the local school and it is either grounded in or contributes to the research or professional literature. For school IT managers, the analysis/ exploration phase of educational design research is focused on understanding the existing problem, how it can be improved, and what will be observed when it is improved. These discussions typically engage the members of the technology planning committee who are the leaders among the IT managers. Design/ construction finds school IT managers designing and redesigning interventions; this phase is most effective when it is iterative and grounded in the planning cycle described in Chapter 6. Reflection/ evaluation finds them determining if the solution was successful and also articulating generalizations that can inform the participants’ further work and that can be shared with the greater community of school IT managers.phases of educational design researchFigure 7.3. Phases of educational design research (adapted from Ackerman, in press)



Ackerman, G. (in press). Open source online learning in rural communities. In I. Bouchrika, N. Harrati, and P. Vu. (Eds.). Learner experience and usability in online education. Hershey, PA: IGI-Global.

McKenney, S., & Reeves, T. (2012). Conducting educational design research. New York: Routledge.

McKenney, S., & Reeves, T. (2014). Educational design research. In J. Spector, M. Merrill, J. Elen, & M. Bishop (Eds.), Handbook of research on educational communications and technology (pp. 131–140). New York: Springer.


What’s Wrong with Coding?

Coding is a hot topic in my media feeds again… each year when the events designed to increase students’ experience writing code, it appears again. I get it, but I am distressed by educators’ (and philanthropists’) fascination with coding. We are looking to closely at the field of design and are missing the far more important task—manufacturing; or more simply, building stuff.

I recently had a conversation with an individual who brings learners into the space pictured to the right to build projects like that also pictured. He was an engineer before opening this space, and he told the story of his grandfather who used to say, “If you can’t build it, then you are not an engineer.”

As we get our students coding, let’s be sure we help them understand the nature of their work—they are in control of the computer, and it will do what the programs direct. Perhaps, we need a wise grandfather to remind students, “You can’t program it, then you are not a computer user.”

As we get our students coding, let’s also ask them to look at the monitor, mouse, computer case (inside and outside), and the tables, chairs, lights, windows, classrooms (both the physical and the organizational) to predict how they can be improved through good design. Then, let’s give students to tools and autonomy to redesign.


Making Files Accessible

The Americans with Disabilities Act (ADA) was enacted to ensure those who cannot use media (text, audio, and other methods of communicating) have access to the information they need in a format they need. (Of course there are many aspects of life affected by the ADA, but this post focuses on digital media.) Teachers are among the public employees who have an obligation to ensure they materials they use in classrooms are ADA-compliant so they can be used my all.

Exactly what one should do to be ensure works are ADA-compliant can be confusing, especially for those teachers who do not encounter students with this need on a frequent basis. This is further complicated by the kluge of materials that a teacher typically uses—instructional materials come from many publishers (including the teacher) and some are reused (with or without modification) year after year.

Many teachers pay little or no attention to the need to make materials ADA compliant, and they can reasonably argue that it is a low priority if there are no students actively using the features of files that make them compliant. In many cases, the features that make files ADA compliant make them better and more effective teaching materials, so the time needed to ensure files are accessible both supports all learners and ensures quick access if a student arrives who needs the features.

The easiest way teachers can begin to develop a collection of ADA-compliant materials is to use the accessibility checker which is built into Microsoft Office. Run the checker to see a list of errors (things that must be changed) and warnings (things that should be changed) to make the files accessible.

The Lens of Cognitive Load

Educators avoid theory whenever they can, and that is an unfortunate stance as a good theory is very useful when we want to understand what we do and why we do it. Cognitive load theory is an excellent example of a theory that is useful, but little-known and little-used by practitioners.

CLT posits humans have a limited amount of perception, attention, memory, and capacity to process information (which comprise cognition) that can be used for any task. The cognition we have available for any task is used for three purposes:

• Intrinsic cognitive load is used to understand the task; it depends on the nature of the task.
• Extrinsic cognitive load is used to overcome poor design of the task or the tools used to accomplish it.
• Germane cognitive load is that which is available to build new understanding.

Given these definitions, it is reasonable to conclude we seek to maximize germane cognitive load and to minimize extrinsic cognitive load. Ostensibly, it seems those are the only types of cognitive load one can vary. When designing learning environments, we seek to make them easy to navigate and we seek to make our tools easy to use, so more cognition is available for germane purposes. I suggest, however, that recent trends in education are increasing the intrinsic cognitive load of teaching and learning.

Consider a lesson from science in which students are analyzing data they collected in the laboratory. We want students to use germane cognitive load to understand the methods they are using as well as the phenomenon being investigated. When we add elements to the learning task, such as:

• Specifying the standard or proficiency on which they are working, and asking them to be mindful of that as they work
• Adding metacognitive tasks, so students are thinking about their thinking

can add to the intrinsic cognitive load. “Understanding the data we collected” becomes

• “understanding the data we collected and knowing which proficiency we are meeting,” or
• “understanding the data we collected and knowing which proficiency we are meeting, and knowing how I learn about the data.”

While I understand the importance of metacognition and clear objectives, these should play a different role in the classroom than we have been allowing. Clear objectives (and knowing the proficiencies or standards our lessons address) is more important for teachers to understand than for students to understand. The structures teachers use to organize curriculum are certainly of secondary importance to the curriculum itself, so I argue making that explicit to students consumes cognitive load that is better used for other purposes. Likewise, metacognition is most effective when students step back from a learning activity and reflect on it (or better yet a collection of learning activities); to be metacognitive can reduce the cognitive load available to both understand the lesson and understand one’s learning.

Cognitive load theory provides teachers (and curriculum leaders, and anyone else who affects what is taught and how it is taught) a lens with which to understand what happens in classrooms. We have been concerned about minimizing extrinsic cognitive load when making design decisions, but it seems we also need to be aware of how we are expanding our definitions of learning, this interfering with germane cognitive load as well.

Learn more about cognitive load theory:

The Realities of the Digital World

Distracted Mind coverThis review as a PDF file is available: download the review.

A review of The Distracted Mind: Ancient Brains in a High-Tech World by Adam Gazzaley and Larry D. Rosen

by Dr. Gary L. Ackerman | @garyackermanphd

Those familiar with the research on the effects of digital devices in humans (as individuals and as groups) will recognize Adam Gazzaley and Larry D. Rosen, the authors of The Distracted Mind: Ancient Brains in a High-Tech World. Both have contributed to the scientific, professional, and popular literature and media in the field. This book makes a significant contribution to that literature, and it is a work that blurs the boundaries within that literature. The argument is grounded in theory and supported by reference to the scientific research, while it both informs educational practitioners and analyzes products and practices marketed to improve brain health.

When they first evolved, our brains (the feature that differentiates us from other animals) were threatened by jaguars hiding in wait (a character Gazzaley and Rosen introduce to illustrate the nature of our natural environment). Those same brains, and their tendency to perceive and attend to certain aspects of the environment now live in an environment not generally inhabited by jaguars but filled with smartphones and information technology networks. In the prologue, Gazzaley and Rosen note, “It is clear that our interruptive technologies are only going to become more effective in drawing our attention away from important aspect of life… (p. xiii).  From this pessimistic stance towards our devices, Gazzaley and Rosen proceed.

Distracted Minds Explained

Cognition is a goal-oriented activity; we seek to perceive and make sense of information in the environment to make decisions so we achieve our goals. Both internal and external factors distract us and interrupt us from this activity. Digital devices provide “enticing sounds, compelling visuals, and insistent vibrations that tug at our attention while our brains attempt to juggle multiple streams of competing information” (p. 10). As creatures who depend on information and whose brains evolved to understand and share information, the rich information sources we carry in our pockets are both an opportunity and a challenge.

Despite our knowledge that multitasking interferes with performance (we all know that texting while driving can be very dangerous), we continue to allow our devices to distract us. That behavior can be explained by marginal value theory (MVT), which was originally elucidated by biologist Eric Charnov in the 1970’s. Marginal value theory explains the behavior of animals who forage patchy food sources; it also appears to explain humans’ foraging for information on our digital devices.

Marginal value theory posits there is an optimal time that should be spent at a source of food or information. Leaving a source too early results in leaving benefits “ungathered,” while leaving too late results in diminished returns. Once a resource has been depleted (the food is gone or the information is gathered), then one benefits from moving on to another source. Successfully navigating the environment requires a forager negotiate sources and make judgements about the value of separate sources and the time needed to move from one to another. Our digital devices change those dynamics as we carry effectively infinite sources of information and the transit time from one to another is nearly instantaneous as we tap and click from app to web to email to social media.

For about 100 pages (a little less than half of the book), the authors explain how digital technologies interfere with:

  • our ability to select what is sufficiently important to hold our attention;
  • our ability to hold information in our working memory (both the amount of information we can process and the fidelity of our memories);
  • our ability to accomplish goals.

Gazzaley and Rosen do suggest “multitasking” is an inaccurate description of what we do when we try to accomplish multiple goals at once. Human brains are incapable of the parallel processing that allows computers to complete multiple tasks at one time.  Humans task switch; we focus on one task, then focus all of our cognition on another. Each time we switch our attention from one task to another, there is a delay and a loss of fidelity, which explains our decreased performance.

Effects on Humans

Gazzaley and Rosen suggest “three major technology breakthroughs have been monumental games changers in our current lifetime: the Internet, social media, and smartphones” and they define game changers as “technologies that drive our interference-inducing behavior—both internally and externally—and which ultimately aggravate our Distracted Minds” (p. 105). Our digital devices contribute to continuous partial attention and encourage us to task switch which interfere with our capacity to be productive in the work place and successful in academic situations.

In addition to adversely affecting workplace and academic performance, the authors summarize findings that our Distracted Minds can reduce our safety (distracted drivers again being the archetypical example) and have negative effects on our health (digital devices interfere with sleep patterns for example). Further, they summarize findings that the negative effects of the Distracted Mind are exacerbated in diverse populations. For example, Gazzaley and Rosen conclude, “Study after study has indicated that too much technology use, whether it be watching television, going on the Internet, using smartphone or tablet, or playing video games, is associated with deleterious effects on the health of children” (p. 147). They do caution, that this correlation does not mean causation, and that it is unclear if health problems motivate greater media use or if media use leads to health problems.

After reviewing research on the effects of technology on older individuals as well as those with clinical conditions such as ADHD, depression and anxiety, and autism spectrum disorders; Gazzaley and Rosen are led to conclude “that the use of modern technology exacerbates the preexisting challenges these individual face in effectively interacting with their environment” (p. 157).

Our digital devices are determining the information landscape in which we live, and humans are information foragers. Marginal value theory explains much that we observe in Distracted Minds. Boredom is a difficult concept to define and study, but it is clear that boredom is a condition that leads individuals to forage for information online. Gazzaley and Rosen conclude, “We see the impact of boredom is not just to make us switch between information patches; we also seem to have lost the ability to simply do nothing and endure boredom” (p. 170). Humans also feel a compulsion to interact with information on their digital devices, and when devices are not available, we feel increased levels of anxiety. Perhaps the greatest threat to our cognition due to these devices is our lack of metacognition; we appear unable to recognize the negative effects of our devices and we are likely to continue using devices even when we are aware of the interference.

Adapting to Digital Distractions

While the book does lead to the rather distressing conclusion that our digital inventions are affecting our cognitive abilities, Gazzaley and Rosen do end the book with a review of some strategies that seem to reduce the negative impact of our Distracted Minds.

  • By increasing metacognition, thinking about what we are doing and taking steps to minimize the adverse effects of our digital, we can bring greater focus to our work and recover the efficiency and effectiveness of non-distracted cognition.
  • By decreasing accessibility, limiting our access to devices to specific times, we—in effect—increase the time needed to move to new sources of information, thus motivating us to complete tasks before being distracted.
  • By reducing boredom and anxiety, we can increase the probability that we complete tasks before distraction. Of the strategies recommended by Gazzaley and Rosen, this reduction seems to be the most difficult to achieve, but they suggest how both technical and non-technical interventions can reduce these factors.


Until I was an undergraduate student in science education, I had little interest in computers. When I discovered they were tools to help me understand and manage information, I became convinced of their role in my life (and my students’ lives). After 10 years teaching science and math, I started teaching computer courses for middle school students; in the decades since, I have been an educational technologist who advocates for greater use of digital devices and information in our schools.

In recent years, I have been reading the literature on our inability to multitask which has caused me to think educators need to take a more active role in modeling and recommending appropriate use of digital devices. Coincident with reading this book, I was working with students in a device-rich classroom (the students were given laptops under the school’s one-to-one initiative and probably 75% of the student also had a smartphone). The negative effects of these devices of attention and distraction was noticeable, and the better quality of the work done by students who were rarely using their devices for distracting purposes was noticeable.

While I recognize that my observations of the students were informal and in all probability influenced by my reading of this book, my observations seem to support the conclusion that ends the book, “We have been susceptible to distractions and interruptions for our entire lives, but technology’s impact on the Distracted Mind has caused us to overindulge” (p. 238).

Despite the rhetoric of integrating technology into our courses and our assumption that students are engaged with their digital devices, educators must follow the lead of this book and be more sophisticated in how we understand digital devices in classrooms. Changing our behavior to minimize the negative effects on our cognition and supporting our students as they do the same is a new lesson we must teach.

IT Users in Schools

Educators import technology expertise from other industries—the individuals who manage your school network and repair malfunctioning computers probably learned their craft in a field other than education. What they learned about keeping devices functioning and providing you with robust and reliable service can be transferred from business or industry into schools.

There is an important difference, however, between IT management in business and industry and IT management in K-12 schools. The nature of the users.

In business and industry, IT managers know much about their users (for instance they have known literacy skills and they are likely to have very specific and unchanging needs). In education, IT users can very unpredictable, and in many cases emerging literacy skills; further, students and teachers use IT for very diverse and changing tasks.

Consider passwords. These are essential for keeping networks and systems secure, and IT managers are likely to require complex passwords to ensure security. Those passwords may prevent young users of school computers from logging on and using the machines.

In my recently published Efficacious Technology Management: A Guide for School Leaders (which is available under a Creative Commons license), I include this chart to summarize the differences between IT users in business and industry and IT users in schools: