Technology Access and Initiative Success

Several people – over Thanksgiving break, and again this morning – have posed questions to me about whether a focus on getting more technology in the classroom is well-justified.  After all, tying technology infusion in the classroom directly to student achievement, for instance, is very difficult (although the same is true of virtually any initiative, the effects of which are difficult or impossible to fully entangle from other factors impacting students, teachers, and the learning environment.  

e5144-20161030While I’ve written in other articles about the basic justification for some of these things, I thought I’d post – for those of you with insomnia, perhaps, and nothing to do for an hour or so – a lengthy portion of something that I wrote a few months ago that details some of the more specific needs for technology access in schools, along with some of the research related to the success of educational technology implementations.  Warning: what follows is long and potentially boring, and is not well-formatted for a blog post.  Skimming is encouraged.  


Technology was once considered a luxury in the classroom, useful for rewards and supplementation at the fringes of the curriculum (Peggy A. Ertmer, Addison, Lane, Ross, & Woods, 1999).  This secondary emphasis could be seen in the typical manifestation of educational technology in schools, which frequently included a handful of Apple II computers, and – in larger or wealthier schools – a small computer lab for business applications (Becker, 1991).  As the A Nation at Risk report (Gardner, 1983) had spurred the nation’s interest in investing in educational reform, particularly in terms of improving competitiveness in math, science, and social studies (Maranto, 2015), the dotcom explosion of the 1990s served as a wakeup call to school and economic leaders that the United States had fallen behind in terms of technology education (Blackley & Howell, 2015).  In 1996, President Bill Clinton unveiled a technology modernization program aimed at putting a “computer in every classroom,” which ushered in an era where computers were seen as invaluable tools to support the learning process through universal connections to online resources and availability of digital tools (Coley, Cradler, & Engel, 1997). 

President Clinton’s classroom connectivity initiative coincided with a dramatic increase in the percentage of homes in the United States that had a computer, and perhaps more importantly, were connected to the internet (Morris & Ogan, 1996).  Prior to 1994, internet was only widely available in institutions, such as universities, hospitals, and research facilities (Hargittai, 1999).  With the launch of consumer internet services such as America Online, Prodigy, and CompuServe, home internet access became a reality, and the amount of content available online began to increase at an exponential rate (Coffman & Odlyzko, 2002).  By 2003, over 54% of U.S. households had a device that was capable of connecting to the internet, up from 18% in 1997 (File, 2013).  In 2015, 84% of Americans reported using the internet, including 51% of high school students who carry smartphones capable of accessing internet resources on a daily basis (Cavanagh, 2013; Perrin & Duggan, 2015). 

As the ubiquity of internet access increased, so did the amount that individuals and organizations relied upon internet resources.  Print, telephone, and software-based encyclopedias, application forms, government policies, and financial tools were rapidly replaced with online equivalents.  The necessity of technology and internet access in modern society now extends to social and economic aspects of our daily lives.  In 2015, 65% of American adults were active on some form of social media – such as Facebook, Twitter, or Instagram – and teenagers in the United States spent over nine hours per day viewing or interacting with digital media (Perrin, 2015; Sharif, Henry, & Nelson, 2015).  Applications for college or jobs will generally be completed online, and the new jobs being created for which recent graduates will apply are disproportionately in STEM-related – science, technology, engineering, and math (Hanson & Slaughter, 2015).  Basic computer skills are often required to complete employment-related functions even in positions not related to technology, such as accessing email or an online records system to retrieve a paystub or submit benefits information. 

In higher education, one-third of college students took an online course in 2013, a percentage that has been increasing since 2005 (Lederman, 2013).  Retention of students enrolled in online courses lags behind retention of students taking in-person courses, a factor that has been partially attributed to difficulties students face in navigating the technological requirements for online coursework (Estes, 2015).  Many universities require that all enrolled students own a computer, and the majority of college courses include an online component via a learning management system (LMS) such as Blackboard or Moodle (Fathema, Shannon, & Ross, 2015).  Despite these requirements, few colleges provide information literacy or introductory training programs (Badke, 2016). 

Despite the prevalence of and need for technology, access to and awareness of technology is not evenly distributed among members of different social groups in the United States.  The device availability and internet access rates among adults with incomes below $30,000 per year is substantially lower – 74% vs 95% in 2015 – than among adults with household incomes above $50,000 per year (Perrin & Duggan, 2015).  Young people from impoverished households are also more likely to drop out of school (Ceballos & Sheely-Moore, 2015), be convicted of a crime (Males, 2015), and to be unemployed as adults (Ullucci & Howard, 2015).  This digital divide – whereby poorer members of society are less likely to be able to access online and other technological resources that can contribute to development of academic, social, and economic skills and credentials – contributes to maintenance and expansion of achievement and employment gaps, and disproportionately impacts ethnic minorities (Ladson-Billings, 2013). 

Technology Access in Schools

Given the level at which technology is integrated into and required for basic social functions, access to technology in primary and secondary education is no longer equivalent to provision of a tool to support learning in general.  Rather, schools are in a position to provide students with the access, experience, and skills needed to use technology efficiently and safely.  This is generally addressed through school technology initiatives, which may originate at the federal level – such as the previously-mentioned “computer in every classroom” initiative in 1996 – or at state, district, or school building levels (Coley et al., 1997).

Technology initiatives can take many forms, from the deployment of a single software application – such as a LMS or an online productivity tool such as Google Drive – to a one-to-one initiative, wherein every student is provided with a device, such as a computer or tablet, that can be used both at school and at home.  As such, the term “technology initiative” refers to both small-scale initiatives that are generally narrowly-focused and inexpensive, to large-scale initiatives that have the potential to consume vast amounts of resources and alter the instructional and learning paradigms within a school (Donovan, Hartley, & Strudler, 2007). 

One-to-one initiatives represent large-scale technology initiatives, and have become increasingly prevalent as a mechanism by which schools can provide for standardized student access to technology both within and outside of the classroom, regardless of a student’s economic background or previous technology experience (Harper & Milman, 2016).  These initiatives are generally designed to improve outcomes in the areas of academic performance, equity, digital literacy, digital citizenship, and student engagement (Penuel, 2006).  Beyond one-to-one, other large-scale educational technology deployment models exist – classroom-assigned sets of computers, specialty labs, and bring your own device (BYOD) initiatives, for instance – some of which can be implemented in concert with a one-to-one approach, and most of which share some or all intended outcomes with one-to-one implementations (Song, 2014).  For the purposes of this study, the focus on technology initiatives will be confined to those initiatives that can be broadly classified as one-to-one deployment models, where all students in – at minimum – an entire grade level are issued devices by the school or district, which can be used by the student both within and outside of school. 

Evaluating Program Success

The relative success of a one-to-one initiative can be conceptualized and operationalized in a variety of ways, depending upon the program and/or research goals.  As with a number of areas of educational research, change in student performance – on standardized tests, particular assessments, or in terms of mastery of specific skills – forms the basis for implementation effectiveness evaluations in many cases (Zheng, Warschauer, Lin, & Chang, 2016).  This method offers advantages in terms of establishment of a direct correlation between the technology initiative and short-term student outcomes, although the difficulty or impossibility of conducting controlled experimentation within an active educational environment makes it difficult to identify causal relationships between a particular technology initiative and student performance, independent of the impacts of other educational or environmental factors (Wood, Lawrenz, Huffman, & Schultz, 2006). 

Another mechanism that has frequently been used has been to analyze usage rates of the technology being implemented, where high – or increased – usage is seen as evidence of program success.  Quantifying usage can be accomplished by tracking the frequency and duration of software use by students, or by quantifying the amount of time that student-assigned devices are actively utilized within the classroom, for instance (Penuel, 2006).  There are strengths to this approach – high levels of use, especially over a long period of time, can be shown to correlate with factors such as student and teacher buy-in, training effectiveness, and technology-related skill development – in addition to the intuitive conclusion that high usage levels of these technologies – that are intended to improve student academic performance and build technology fluency – are preferable to low usage rates (Penuel, 2006).  A weakness, however, is the risk that a utilization-driven evaluation of program success will skew towards programs wherein use is mandated, or where use may be uncorrelated with intended educational or social outcomes, such as allowing computer games as a reward for good behavior (Cuban, Kirkpatrick, & Peck, 2001). 

A third approach to operationalization of technology initiative success takes the form of stakeholder satisfaction ratings, in terms of the effectiveness of the initiative as a whole, as well as particular components of the initiative (Donovan et al., 2007).  High levels of satisfaction have been shown to correlate with high levels of usage, improved student performance, and reinvestment in and longevity of the initiative (Donovan et al., 2007; Penuel, 2006).  As with student performance data, however, it can be difficult to establish causal relationships given challenges related to controlling for environmental and other factors (Cuban et al., 2001). 

A fourth approach to assessment of one-to-one implementation success is analysis of factors that comprise or correlate to student engagement.  A variety of studies have shown that dropout and absentee rates are reduced following the implementation of one-to-one initiatives, and active student engagement during class is increased (Fishman, Penuel, Hegedus, & Roschelle, 2011; Penuel, 2006).  Student engagement has consistently been shown to directly influence achievement measures, which provides a theoretical basis for association of demonstrated increases in engagement with corresponding increases in academic achievement (Fredricks, Blumenfeld, & Paris, 2004).  Again, a challenge in terms of establishing a direct relationship between technology initiatives and student engagement is related to the fact that schools generally implement multiple initiatives to increase student engagement simultaneously, making it difficult to isolate the impact of any single initiative. 

Factors Impacting Technology Initiative Success

Given the personnel and financial costs associated with educational technology initiatives, educational leaders, school board members, and community stakeholders often expect that the results of major technology initiatives, such as one-to-one device programs, will be immediately apparent.  To the extent that devices are made available, software is installed, and services are delivered, the program outputs – direct results of the program implementation – are often immediate and tangible.  That said, teachers and students do not develop instantaneous familiarity with the new technology at their disposal, and interaction with the technology and all that it offers is likely to be superficial at the onset.  Given that the broader success of technology initiatives cannot be meaningfully evaluated during – or even shortly after – program deployment, it is crucial that school leaders understand the factors that have been shown to contribute to program effectiveness, as defined through long-term outcomes such as improved academic performance, student engagement, or students entrance into STEM (science, technology, engineering, and mathematics) career paths. 

It is often the case that negative impacts are apparent during early stage implementations, due to the fact that time that might have otherwise been spent on academic work, lesson plan development, or training related to other educational initiatives is instead being spent on getting acquainted with the hardware, software, and management aspects of the new program and associated technologies (Mouza, 2008; Zucker & Hug, 2008).  Long-term, and even short-term outcomes of one-to-one implementations often do not become apparent until years after the device deployment, and even then are often realized only when an initiative has been implemented with fidelity.  A 2007 study concluded that a full educational technology initiative implementation takes five to eight years, a time period that would span multiple generations of hardware and software (Silvernail & Gritter, 2007). 

Regular Technology Integration

Technology usage levels in the classroom have been shown to relate directly to the effectiveness of teacher training programs supporting the technology implementation (Bebell & Kay, 2010; Lemke & Martin, 2004; Shapley, Sheehan, Maloney, & Caranikas-Walker, 2008; Zucker & Hug, 2008).  Further, regular integration of technology during classes is shown to be a necessary condition for obtaining significant benefits from an educational technology initiative, whether in terms of academic performance, or secondary benefits such as decreased absenteeism, increased collaboration between students, and improved editing skills (Keengwe, Schnellert, & Mills, 2012). 

Implementation Model

Another important factor to consider as it relates to technology integration is program’s implementation model.  Most one-to-one initiatives, for instance, are based upon a concentrated model, wherein students have access to a laptop at school and are also able to take the laptop home (Zheng et al., 2016).  Other implementations, however, range from students only having access to laptops at school to having access in only one classroom (albeit one-to-one access in that classroom).  Several studies have compared outcomes resulting from these differing approaches to one-to-one computing, and have concluded that the model where students have access to laptops at school and at home is the most effective, largely due to the fact that computer access – and along with it, the ability to use software, engage in digital collaboration with other students, and the ability to gain experience and familiarity with the technology – is not limited to a particular time or place (Chan et al., 2006; Muir-Herzig, 2004; Rockman, 2004). 

Teacher and Administrator Training

Across all studies, technology-related professional development for teachers recurs as a critical component of educational technology initiative success.  It is important that teachers have time to work with the technology both in terms of becoming familiar with basic operational characteristics and procedures, as well as to explore how the technology can effectively supplement the curriculum (Bebell & O’Dwyer, 2010; Martin et al., 2010; Muir-Herzig, 2004; Russell, Bebell, O’Dwyer, & O’Connor, 2003).  Further, teachers must be exposed to teaching practice modifications geared towards accommodation of student-centered learning strategies – such as decentralized classrooms, flipped instruction, and project-based learning – which have shown to be highly correlated with technology program effectiveness (Keengwe et al., 2012; Lemke & Martin, 2004; Lowther, Inan, Ross, & Strahl, 2012). 

Teachers who had not received adequate technology training generally used the technology less frequently and spent a great deal of time dealing with technology issues rather than curricular issues in instances where they did design a lesson that made use of the technology (Lowther et al., 2012).  Specifically, professional development opportunities must be focused on a connection between the technology and the curriculum (Fishman et al., 2011), whereby teachers spend more time working on lesson planning with the technology in mind than on technology assistance (Martin et al., 2010).  

Operational Technology Support and Planning

While it may seem intuitive that technology support must be readily available in order for teachers and students to feel confident integrating technology into their work, the widespread adoption of 1:1 laptop initiatives in school districts has resulted in many districts being unable to provide adequate maintenance and repair service (Holcomb, 2009).  Research has shown that even in schools where technology resources are prevalent, inadequate support response times or repair rates result in a dramatic reduction of technology use in classrooms, compared to expected values based upon other criteria (Topper & Lancaster, 2013).  Beyond the basics of technology support, it is critical that network and internet functionality be robust in terms of availability, and sufficient in terms of bandwidth (speed).  If internet service is inadequate or unreliable, teachers will avoid making use of technology – even given adequate training, hardware, and software – since the most valuable and accessible resources are often found online (Sundeen & Sundeen, 2013). 

Administrative Leadership

As with many educational initiatives, it is important that school administrators positively and proactively engage with teachers regarding technology initiatives in schools (Anderson & Dexter, 2005).  Building administrators are generally responsible for prioritization of professional development time and development of instructional goals, in addition to being responsible for teacher evaluation and other areas of oversight with relation to the school’s educational program (Neumerski, 2013).  With adequate administrative support, adequate technology-related professional development can be established as a priority, with clear expectations regarding the use of the technologies that contribute to regular and effective integration in the school’s curriculum (Bebell & Kay, 2010).  Further, school leaders who themselves make use of the technologies at hand for communication and collaboration with their faculty and take steps to understand the impact of educational technology in the classrooms have significant impacts on technology outcomes (Anderson & Dexter, 2005).

Given that building administrator engagement has been shown to be important to the success of a technology initiative, it is worth considering the factors that contribute to high levels of technology leadership engagement on the part of building principals and assistant principals.  A logical conclusion may be that technology fluency on the part of the educational leader is directly correlated with level of engagement in terms of technology initiatives.  This potential effect is easy to conceptualize, as an educational leader who struggles with technology is less likely to have personal experiences, expertise, and an understanding of the potential for technology implementations.  Research that establishes a connection between technical expertise and administrative engagement would support this conclusion. 

Beyond the concept that expertise breeds engagement, however, the influence of other factors can be conceptualized and analyzed.  Attendance at and participation in educational technology conferences, for instance – or more broadly, interaction with the educational technology community – could contribute to administrator engagement, regardless of the administrator’s level of technology expertise (Dolle, Gomez, Russell, & Bryk, 2013).  Seeing a product demonstration in the context of a second grade classroom, for instance, may spur a principal to encourage their teachers and the school’s technology integration staff to implement the product in his/her school, regardless of whether the principal possesses the expertise to personally use or implement the technology.  Research relating to social basis for leader decision-making, especially where factors considered include participation with professional communities, would help establish this as a relevant factor. 

Another potentially-critical condition for leader engagement is the presence of strong district-provided instructional and technical support for the initiative.  Regardless of technical expertise on the part of the building administrator, lack of strong implementation support could dissuade promotion of or engagement with a technology-focused project or implementation (Peggy A Ertmer, Ottenbreit-Leftwich, Sadik, Sendurur, & Sendurur, 2012).  This factor may be somewhat difficult to operationalize, as it will require a research basis for establishment of criteria for technology support and integration effectiveness, as well as a mechanism to tie that support effectiveness not to classroom technology implementations, but to administrative engagement itself. 

The fourth additional factor that is worthy of consideration is administrator involvement or influence in planning the technology implementation.  While an edict from the highest levels of the district may fall on deaf ears, an initiative that an administrator was either directly involved in crafting or to which they appointed representatives in the planning process may be more likely to receive attention of the educational leader (Harris, 2013).  Research focusing on collaborative decision-making and buy-in could be valuable in establishing this factor as worthy of consideration. 

A fifth factor to consider – particularly relevant for technology implementations, but also analogous, for instance, to changes in state assessment mandates – is related to perceived longevity of the initiative.  An implementation that is thoroughly planned in such a way as to guide future years’ implementations, and involves funding and other resource commitments, may be more likely to spur administrative engagement than an apparently-one-shot program that an educational leader may expect to be supplanted after a short time (Davis, 2003).  While this factor is likely influential in terms of administrative engagement – school administrators have limited available time, and are unlikely to choose to expend resources on something that they don’t expect to be around a short while later – one of the keys will be the development of a strategy to not only promote program stability, but also to promote the perception of program stability. 

This final point speaks to the question of in what ways, if any, can district, building, and technology leaders facilitate increased engagement with technology initiatives on the part of relevant leader.  This question is more pressing given the limited budgets and competing priorities available to school districts.  While it may be that all of the aforementioned factors are significant, addressing each factor to an optimum level is likely not possible vis-à-vis the engagement of the school leader.  Attendance at conferences and participation in professional communities requires time and money, as does professional development designed to improve educational leaders’ technical expertise.  Staffing and resources available to school technical and technology integration support are typically far below industry standards in the private sector (McLeod & Richardson, 2013), and – especially in large districts – committee work and other planning processes can grind to a halt if meaningful, direct influence is provided to too-large a group of people (Van De & Delbecq, 1971).  Finally, schools operate within a funding paradigm where budgets are generally set on a year-by-year basis, and long term commitments – even using multi-year levies and bond issues – are often undermined by changes in previously-unrelated funding streams (Howell & Miller, 1997). 

Given the investment in technology resources in schools and districts throughout the United States, it is crucial that districts be able to plan technology initiatives with an understanding of the factors that will contribute to program success.  Further, districts must have some guidelines upon which an analysis of the costs and benefits of initiative support mechanisms can be weighed.  Research that addresses the two questions posed above has the potential to provide this resource to districts in terms of spurring leader engagement, which has almost-universally been shown to be an important factor in overall technology program success. 


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