• Home
• About
• Contact
• Site Map
• Search CT4ME

Math Topics

• Common Core
• Initiatives
• Methodology
• Resources
• Projects
• Manipulatives
• Software

Learning Support

• Standardized Test Prep
• Technology Integration
• Assisting Readers

Professional

• Associations
• Journals
• News
• Professional Development
• Education Standards
• Education Research
• CT4ME Publications

Technology Integration:
Essential Questions (Page 1 of 3)

 

How is educational technology defined?

Historically, there have been numerous definitions and statements concerning the nature and function of educational technology, according to Saettler (2004).  Educational technology has been a term including both instructional technologies, which focus on the teacher and the pedagogies they might employ, and learning technologies, which focus on the learner.  Its meaning has been "intertwined with certain historical conceptions and practices or bound to specific philosophical and psychological theory as well as with particular scientific orientations" and clouded by "the tendency in some quarters to equate new information technology with a technology of instruction" (Saettler, 2004, p. 5).  In the 20th century, four paradigm shifts, each with different philosophical and theoretical orientations, affected theory and practice and definitions of educational technology.  Saettler characterized those as "(1) the physical science or media view; (2) the communications and systems concept; (3) the behavioral science-based view . . .; and (4) the cognitive science perspective" (p. 7).

Definitions, and resulting mindset of the educational technologist, have been influenced by the nature of technology of the time and what could be done with it.  In the early and mid-20th century, the focus was on using tools associated with instructional technologies from blackboards to overhead projectors, B. F. Skinner's learning machines, films and movies, and mainframe computers. However, the advent of computer terminals, personal computers, the Internet, and the growth of broadband communications in the late 20th century enabled mindset shifts toward learning technologies, as those advances enabled greater interactivity and increased possibilities for collaboration among learners.

Thus in the 21st century, we see definitions reflecting a new mindset leaning toward learning technologies and on how instructional technologies can best serve learning. For example, the Association for Educational Communications and Technology (AECT) defined educational technology as "the study and ethical practice of facilitating learning and improving performance by creating, using and managing appropriate technological processes and resources” (Richey, Silber, & Ely, 2008, p. 24).  AECT has also addressed this issue fully in its book Educational Technology: A Definition with Commentary, edited by Alan Januszewski and Michael Molenda (2008).

In its final report on the EdTech Genome Project the EdTech Evidence Exchange (2021) noted that "education technology (edtech) is broadly defined" and "includes: content-less tools, content-only tools, and content + platform tools; free tools and paid tools; and software tools and hardware tools" (p. 119).

Read more on educational technology in Wikipedia.

 

 

Back to top

 

How is technology affecting the learning process?

Technology is affecting the learning process in at least seven ways, each of which is elaborated upon in what follows:

• It affects the nature of learning;
• It is empowering students;
• It has probable effects on cognition;
• It has given rise of informal learning and new learning theory (e.g., connectivism);
• It has led to personalization as a trend in life-long learning;
• It has led to new and emerging technologies for teaching and learning;
• It has led to new and enhanced processes in math education.

Nature of Learning

Technology is changing the nature of learning.  As noted in the National Education Technology Plan 2010 (U.S. Department of Education, 2010), there are "three connected types of human learning—factual knowledge, procedural knowledge, and motivational engagement ...  supported by three different brain systems. ... Social sciences reveal that human expertise integrates all three types of learning. Technology has increased our ability to both study and enhance all three types of learning" (p. 15).

In general, contemporary digital learning environments with their multimedia components provide important learning opportunities: interactivity; adaptivity to a user's behavior, knowledge, and characteristics; feedback on performance, choices so that learners can regulate their own learning, nonlinear access, linked representations, open-ended learner input, and communications with other people (National Academies of Sciences, Engineering, and Medicine, 2018, pp. 165-166).  There is a caveat to web-based learning, however, which may be debatable.  In his Framework for Thinking About Tech Integration, Paul Emerich France (2020) cited John Hattie's research on Visible Learning noting "Web-based adaptive products make students passive receptacles of knowledge as opposed to active co-constructors of knowledge, which limits opportunities for engagement.

One does not have to look far to see the affect and influence of the rise of broadband Internet connectivity, the increase in social networking, and greater use of mobile devices on learning.  These have enabled those who possess technology to quickly capture knowledge and information, easily communicate, get feedback from, and collaborate with peers.  Technology becomes another vehicle for creativity, self-expression, and self-production and publication.  It allows for constant engagement.

However, in promoting active use of technology such as seen in the figure found in the National Education Technology Plan 2017 update (p. 21), the U.S. Department of Education (2017) noted that schools have a role to play not just in making technology available to close a digital divide, but to close a digital use divide by "ensuring all students understand how to use technology as a tool to engage in creative, productive, life-long learning rather than consuming passive content.  Simply consuming media or completing digitized worksheets falls short" (p. 21).

Raj Vali (2015) pointed out changes in how students learn brought about by mobile technologies:

1. "Tablets change how we perceive computing."  Consider apps with animation, interactivity, and the entertainment factor.
2. "Education is gamified."  Consider the impact on motivation when educators introduce elements of games into curriculum.
3. Learners expect "real-time feedback."
4. However, the rise of digital communication platforms (e.g., use of social media hubs) does come with a potential danger in that "communication becomes truncated."  Vali stated that "some students are losing the ability to articulate ideas in longer form. Additionally, they have fewer opportunities to engage in face-to-face communication.  For that reason, it's important for educators to make sure students have the opportunity to participate in collaborative activities and face-to-face meetings" (section 4).
5. "Hands-on learning" via mobile technologies.  "Technologies such as the augmented reality Google Glass, digital and interactive paper, and animated learning through apps are changing the way education is becoming personalized. Today, forward-thinking learning centers avoid video lectures in favor of two-way interactions in which tutors walk students through problem solving and demonstrate new concept using tablets" (section 5).

Unlike using a paper-based book with a finite number of pages, technology makes the user aware that acquisition of knowledge is potentially limitless.  Knowledge is constantly evolving with the end result that complete mastery of any topic is not truly possible.  Not all information is complete, there are multiple points of view and opinions on a topic that can easily be accessed.  Not all of those perspectives are from authoritative, peer-reviewed sources.  The ease of anyone publishing anything leads to a need for constant questioning of what one reads.  The result is that schools must take a greater role in helping learners to critically evaluate online content.

 

Back to top

 

Empowering Students

Technology is empowering students in four key ways, according to Lemke and Coughlin (2009): democratization of knowledge, participatory learning, authentic learning and multimodal learning.  Democratization is brought about because the "Internet has become a treasure trove for content related to the academic curriculum, providing learners with free access to thousands of valuable courses, information sources, and experts" (p. 54).  Consider evidence such as the following:

• Wikiversity is "devoted to learning resources, learning projects, and research for use in all levels, types, and styles of education from pre-school to university, including professional training and informal learning" (Main page welcome section).
• Khan Academy claims you can learn anything for free working at your pace at the site: math, science, computer programming, history, art, economics, and more.
• YouTube Education
• P2P Foundation is dedicated to peer-to-peer dynamics in society, which "can be found in many communities and movements self-organising around the co-creation of culture and knowledge. Well known general examples include the free/open source software movement; free culture; open hardware; and open access in education and science." (About the P2P Foundation section).
• MIT OpenCourseware is a web-based initiative that contains "virtually all MIT course content. OCW is open and available to the world" (About OCW section).

"The advent of low-cost global communications has led to mass collaboration in the social, economic, and political sectors" (Lemke & Coughlin, 2009, p. 56) and has found its way into classrooms.  Teachers and students can use tools such as blogs and wikis for participatory and authentic learning in the context of those global issues. Sophisticated media combining text and visuals is supporting multimodal learning, but at the same time is posing challenges for educators in terms of helping learners to interpret and understand multimedia messages (Lemke & Coughlin, 2009).

Caution: This multimodal learning is evident in what 21st century students have come to expect in their learning.  They want learning on demand and speed is the name of the game.  They are not afraid of technology. They multitask, think less linearly than those of us over 30, enjoy fantasy as an element of their lives, are less tolerant of passive activities, and use their tools to stay connected with each other.  That connectedness is the main goal of their multitasking, according to Sprenger (2009), rather than for being productive.  However, excessive connectedness can lead to stress, which overtime can potentially "lower the effectiveness of the immune system, weaken cognitive functioning, and, in some cases, lead to depression" (p. 36).  Their excessive communicating digitally, while being efficient, also has the potential to weaken the development of emotional intelligence in dealing with face-to-face situations (e.g., reading facial cues and body language).

If parents do not monitor the time their kids spend on digital devices, there is a real danger that their overexposure will lead to worrisome behavior changes and addiction.  Per Dr. Nicholas Kardaras (2016), researchers have called screens "electronic cocaine" and "digital heroine."  The problem can be serious (e.g., increased depression, anxiety, aggression, loss of touch with reality) and difficult to treat.  He stated:

"Many parents intuitively understand that ubiquitous glowing screens are having a negative effect on kids. We see the aggressive temper tantrums when the devices are taken away and the wandering attention spans when children are not perpetually stimulated by their hyper-arousing devices. Worse, we see children who become bored, apathetic, uninteresting and uninterested when not plugged in" (para. 10).

"We now know that those iPads, smartphones and Xboxes are a form of digital drug. Recent brain imaging research is showing that they affect the brain’s frontal cortex — which controls executive functioning, including impulse control — in exactly the same way that cocaine does" (para. 12).

These behavioral changes might also manifest themselves in school and in learning.

 

 

Back to top

 

Probable Effects on Cognition

The use of technology has also brought about a rise in multitasking.  The rapid way in which ideas become freely available, the desire to get that information quickly, and the instantaneous way of switching from one source to another potentially affects learning in yet other ways.  While Schmidt (2010) noted benefits of technology (e.g., online gaming improves strategic reasoning, navigational reasoning, and hand-eye coordination), he voiced a concern that people might be losing deep-reading skills, as they spend less time reading long-form literature passages.  This probably has an effect on cognition and reading, although no one really knows what that does.

In Gasser and Palfrey's (2009) view, multitasking is not going to go away.  It helps today's youth to cope with the vast amount of information coming their way.  It takes on a couple of forms: parallel processing or doing more than one thing at the same time and task-switching or quickly changing from doing one thing to doing another.  Rather than preventing our students from multitasking, a better approach would be to help students understand how multitasking challenges their learning.  After reviewing several studies on the affects of multitasking, Gasser and Palfrey concluded:

• Multitasking does not render learning impossible.  It does not even necessarily make it more difficult to accomplish tasks.  However, we can safely conclude that task-switching in particular increases the amount of time needed to finish a task.
• Multitasking is likely to change learning qualitatively by making the learner rely on different memory systems that vary in flexibility when it comes to the use of knowledge.
• The loss of attention and the time spent switching from task to task is likely to have an adverse effect on digital natives' ability to learn complex new facts and concepts.  (p. 18)

Multitasking and participatory learning can be seen in the online activities of youth, many of whom benefit from the informal settings and activities they have defined for themselves.  In what has been called "the most extensive U.S. study of youth media use" to date, Mizuko Ito, Heather Horst, Matteo Bittanti, Danah Boyd, Becky Herr-Stephenson, Patricia G. Lange, C.J. Pascoe, and Laura Robinson (2008) found that youth use online media to extend friendships and interests. They engage in peer-based, self-directed learning online (pp. 1-2). The scenario has implications for instructional designers and educators:

• Adults should facilitate young people's engagement with digital media. "Contrary to adult perceptions, while hanging out online, youth are picking up basic social and technical skills they need to fully participate in contemporary society. Erecting barriers to participation deprives teens of access to these forms of learning" (p. 2).
• Youth using new media often learn from their peers, not teachers or adults. Yet, in interest-driven participation, adults have an important role to play (e.g. in setting learning goals) (pp. 2-3).
• To stay relevant in the 21st century, education institutions need to keep pace with the rapid changes introduced by digital media. (Ito, Horst, Bittanti, et al., 2008)

Commenting on results of a Pew Internet & American Life Project report, psychology professor Larry Rosen (2013) pointed out the multitasking with technology that learners do also can negatively affect academic performance in school as learners are unable to focus for long periods of time on any one task.  They might be only able to stay on task for as little as 3-5 minutes before being distracted by such things as having multiple devices in their study environments, texting, and using Facebook (p. 62).

Jeffrey Kuznekoff and Scott Titsworth (2013) provided additional evidence on the negative affect on academic performance of learners using mobile devices during class lectures.  They found that "Students who were not using their mobile phones wrote down 62% more information in their notes, took more detailed notes, were able to recall more detailed information from the lecture, and scored a full letter grade and a half higher on a multiple choice test than those students who were actively using their mobile phones" (p. 233).  They suggested informing students of the results of their research, perhaps including a short summary of it within a course syllabus as a way to help learners make a more informed decision on potential impact on their learning of using mobile phones during class lectures.  Yet this might not be enough to convince learners that results might apply to them.

So how should educators facilitate young people's engagement with digital media?  The key is teaching learners how to focus using a process in instruction involving "technology breaks."  According to Rosen (2013):

A tech breaks starts with the teacher asking all students to check their texts, the web, Facebook, whatever, for a minute and then turn the device on silent and place it upside down on the desk in plain sight and to "focus" on the classroom work for 15 minutes.  The upside-down device prohibits external distractions from vibrations and flashing alerts and provide a signal to the brain that there is no need to be internally distracted, because an opportunity to "check in" will be coming soon. (p. 64)

At the end of the focus time, the tech break begins again, and the cycle continues.  Teachers might begin with a focus time of about 15 minutes, gradually increasing the focus time between tech breaks.  However, they might find the maximum focus time might reach about 30 minutes.  Rosen indicated that this technique has also proved successful at the dinner table at home or in restaurants, and during business meetings.

 

Back to top

 

Rise of Informal Learning and New Learning Theory

Technology has also contributed to a rise in informal learning, or at least has made it more evident.  While content and courses are still viewed as the starting point of learning, George Siemens (2005a) indicated that the Web and the Internet are changing that.  Proof of this is illustrated in Ito and colleagues' study on living and learning with new media (2008) and in Lemke and Coughlin's view that the Internet has been a change agent for democratization of knowledge (2009).

Per Siemens (2005a), the majority of education no longer occurs in formal settings.  People are learning "through communities of practice, personal networks, and through completion of work-related tasks" in an environment in which "[k]now-how and know-what is being supplemented with know-where (the understanding of where to find knowledge needed)" (Introduction section). Thus, he viewed making connections, not content, should be perceived as the beginning point of the learning process.

Siemens' "connectivism" theory calls for a rethinking of learning in the digital age, illustrating that technology has led to new learning theory.  To date theories of behaviorism, cognitivism, and constructivism have dominated instructional design and still have their place in the domains of learning (see Table 1).  However, those theories are challenged in the digital age because "[m]any of the processes previously handled by learning theories (especially in cognitive information processing) can now be off-loaded to, or supported by, technology" (Siemens, 2005a, Introduction).  In contrast to established theories of learning, the essence of connectivism is that learning is viewed as a connections/network-forming process (Siemens, 2005c).

Connectivism recognizes that learning resides in a collective of individuals' opinions and even in non-human appliances. Core skills include an ability to see connections between fields, ideas, and concepts and to locate sources of unknown knowledge when you need it at its point of application.  The intent of learning activities is currency (accurate, up-to-date knowledge).  Because knowledge is increasing exponentially, it can rapidly change what is perceived as a reality.  Thus, the decision making process (what to learn and its meaning) is a learning process itself (Siemens, 2005a).  The process is complicated by new communications tools that have sprung up, which give greater end-user control over what is published on the Web, resulting in some amateur contributions of questionable quality.

 

 

 

Back to top

 

Personalization as a Trend in Life-Long Learning

Ultimately, the value of the theory of connectivism is its link to the concept of life-long learning and personalization of it.  According to Siemens (2005c), "We are moving from formal, rigid learning into an environment of informal, connection-based, network-creating learning...Knowing is no longer a destination. Knowing is a process of walking in varying degrees of alignment with a dynamic environment" (Conclusion section). Gone are the days of "this is what it is."

Personalization is a hot topic among educators.  But what is personalization?  One definition proposed in The Glossary of Education Reform (2015) states:

"The term personalized learning, or personalization, refers to a diverse variety of educational programs, learning experiences, instructional approaches, and academic-support strategies that are intended to address the distinct learning needs, interests, aspirations, or cultural backgrounds of individual students."  It's generally viewed as an alternative to "one-size-fits all" instruction and has also been called "student-centered learning" (para 1).

Personalization is among trends driving the global economy, and this is no less true when working with technology, and the internet.  However, as Benjamin Riley (2017) noted, "We need to stop treating technology use and personalization as synonymous" (p. 72).  To-date there has been multiple interpretations of personalized learning, a lack of a common definition of it, and almost no evidence thusfar from rigorous research in support of it.  In his view, common principles to many definitions of personalized learning include students having greater control over the content they learn and the pace at which they learn, and some use of technology to customize learning (Riley, 2017).

Regardless of one's definition, Scott Johns and Mike Wolking (n.d.) noted the following Core Four of Personalized Learning developed at Education Elements:

1. Flexible content and tools: Instructional materials allow for differentiated path, pace, and performance tasks;
2. Targeted instruction: Instruction aligns to specific student needs and learning goals;
3. Student reflection and ownership: Ongoing student reflection promotes ownership of learning;
4. Data driven decisions: Frequent data collections informs instructional decisions and groupings. (p. 6)

For personalized learning to really take-off in classrooms, technology will need to be a component.  Per Thomas Greaves (in Demski, 2012), the most effective implementations include a "well-implemented 1-to-1 laptop initiative," "learning management systems ...because they provide the framework that supports several different personalization functions without adding a lot of extra work for the teacher," "access to online remedial coursework," and "open access to search tools" (p. 35).

However, consider the conclusion Paul France (Waters, 2018) reached after being actively involved with implementing personalized learning with technology for several years: “The vision was a curriculum that catered to every child so they’re learning at their level all the time,” he said. “But when every child is working on something different, you’re taking away the most human component in the learning process, which is social interaction—learning from one another and collaborating to solve problems. They’re developing a relationship with their tablet but not with each other” (para. 13).  Waters (2018) also noted challenges from a RAND report: "Helping students work at their own pace can make group projects and collaboration more difficult because students are at different places, while also making it harder to prepare kids for year-end standardized tests" (para. 7).

If schools opt for personalized learning, according to Siemens (2005b), instructional designers should consider learning ecologies and networks, as they are structures that enable continual and personalized learning.  Learning communities, information sources, and individuals can all be considered nodes or connection points in a network and it only takes two nodes to share resources.  Such networks need to occur within an ecology, which means that the approach to learning is open, adaptive, decentralized, tolerates experimentation/failure, reflects a need for simplicity, promotes trust and learning in safe environments, and includes many tools for dialogue and making connections.  A learning ecology includes the following (Siemens, 2005b, Learning Ecology section):

• A space for gurus and beginners to connect (master/apprentice)
• A space for self-expression (blog, journal)
• A space for debate and dialogue (listserv, discussion forum, open meetings)
• A space to search archived knowledge (portal, website)
• A space to learn in a structured manner (courses, tutorials)
• A space to communicate new information and knowledge indicative of changing elements within the field of practice (news, research)

"Each of the following types of learning can be personalized for and by students, in part by adjusting the instruction, complexity, and level of authenticity" per Cheryl Lemke (2014):

• Drill and Practice
• Blended Learning (a Combination of F2F plus Apps/Objects, Video, Intelligent Adaptive Learning, etc.)
• Productivity Tools (word processors, spreadsheets, presentation software, etc.)
• Organizational Tools Enabling Self-Directed Learning
• Online Research
• Communication Tools (including video, audio, and text, etc.)
• Virtual Learning
• Visual Thinking/Learning Tools
• Collaboration/Social Networking and Media
• Online and Embedded Assessment
• Construction Tools/Game Creation
• Problem Solving/ Data Analysis
• Virtual Worlds/Serious Games/Simulations (Lemke, 2014)

A true personalized learning environment (PLE) "draws on a variety of discrete tools, chosen by the learner, which can be connected or used in concert in a transparent way. ... a PLE is not simply a technology but an approach or process that is individualized by design, and thus different from person to person. It involves sociological and philosophical considerations and cannot be packaged, passed out, and handed around as a cell phone or tablet computer could. Widespread adoption of PLEs ... will almost certainly also require a shift in attitudes toward technology, teaching, and learning" (Johnson, Adams, & Haywood, 2011, p. 30). 

Widespread adoption requires more than attitude shifts, however.  There are multiple challenges in evolving from our traditional way of delivering education to a personalized system.  To have a chance at success, Gross and DeArmond (2018) stated:

"Successful innovation and scaling requires that innovators have (1) a clear understanding of what they hope to accomplish—what problem is being solved and some way of knowing when they get there; (2) the flexibility and opportunity to take risks; and (3) strategies to learn through iteration.  If the goal is to innovate and learn as an organization, then innovators also need (4) processes and procedures for gathering what is learned, codifying it, and transferring this information to others." (p. 14)

Before undertaking any implementation, Tomlinson (2017) suggested that educators reflect on why they want to implement personalized learning and have a vision for its purpose.  How will this approach match with curriculum? "It's unwise to select an instructional direction without clarity about how compatible that direction is with local understandings about the nature of curriculum" (p. 13).  Personalization might not work for all students in a school, or even in a classroom, or particular content area.  For example, consider how you would provide quality educational experiences for learners challenged by "language acquisition, low proficiency in reading, emotional insecurity, a lack of background experiences, or even a weak attention span" (p. 14).  Consider the affect of its implemenation on existing systems, such as schedules, grading practices, and teacher evaluations, particularly if teachers can opt in or out of the approach.  What supports will teachers need logistically in the classroom, from professional development, and from school leadership?  How will you involve parents in the change process?  What changes would be needed in the school environment--would they conflict with any district or state-level mandates or expectations? (Tomlinson, 2017).

Based on outcomes from a 2014 national summit on this topic hosted by the Friday Institute for Educational Innovation at North Carolina State University (Abbott, Basham, Nordmark, Schneiderman, Umpstead, Walter, & Wolf, 2014), key components in a redesigned personalized learning system would include mass customization; flexible, anytime, everywhere learning; a teacher role as "guide-on-the-side"; project-based, authentic learning; a student-driven learning path; and a mastery/competency-based progression/pace. We would need  collaborative learning environments, "ongoing, embedded, and dynamic assessments of knowledge/skills, learning styles, and interests," and rather than a fixed-limited report card, we'd need portable electronic portfolio records, and integration of informal learning (pp. 2-3). It would require greater use of data, changes in curriculum, funding, policies, an enhanced technology architecture to access and manage data, content and communications; new research and development for what works for which students in a PLE, and new professional learning experiences, such as with differentiated instruction and blended learning instructional models (p. 5).

Readers should not confuse "mass customization" with lack of standards.  In a PLE, "each learner works toward achieving the same set of college- and career-ready standards with the support that they need along the way" (Friend, Patrick, Schneider, & Vander Ark, 2017, p. 5).  Despite its challenges, classroom teachers and schools are implementing personalized learning, as Friend and his colleagues illustrated.  Although there are differences in approaches, commonalities exist such as "kids learning individually and together, a combination of small group and whole group activities, demonstrations and instruction from the teacher, meaningful projects, extracurricular activities and more" (p. 6).

Personalization and the Research on Learning

Mastery/competency-based progression/pace, a key component just noted in a personalized learning system, is under scrutiny in the research on learning.  Soloway and Norris (2015) pointed out A Fundamental Flaw in Competency Learning, which centers around the difference between performance and learning.  Algorithms used to determine if students have mastered content are based on performance (e.g., the number of questions answered correctly on a quiz/test), and there is no guarantee that learning has taken place.  "The implications of this distinction are critical for competency learning. The computer algorithms used in competency learning implementations are not assessing the long-term changes in understanding and skills that are the hallmark of learning. Rather, the computer algorithms are — by necessity — assessing performance" (p. 2 online).  For more on this topic, read:

Patrick, S., & Sturgis, C. (2015). Maximizing competency education and blended learning: Insights from experts. Vienna, VA: International Association for K–12 Online Learning. https://aurora-institute.org/resource/maximizing-competency-education-and-blended-learning-insights-from-experts/

Riley (2017) believes principles of personalized learning conflict with some basic principles of cognitive science and how people learn.  In terms of giving students greater control over the content they learn, "Students who pull content from the Internet as a central part of their learning may be able to make short-term use of the facts they encounter, but unless they've somehow stored these facts in long-term memory -- a process unlikely to happen by chance -- they won't have really learned them" (p. 71).  In relation to students being given control over the pace of their learning, most students need help of teachers to "make sure students are getting their mental excercise at the appropriate pace" (p. 71).  The bottom line:

"[S]chools that implement personalized learning often find they need to create "guardrails" or frameworks around the content students are supposed to learn and the pace at which they learn it.  In other words, schools start to converge on a model not all that different from longstandng education models with a scope and sequence" (Riley, 2017, p. 71).

Readers might be interested in the following on personalized learning:

HOT!: Education Elements: Personalized Learning Guide is a comprehensive guide for educators, administrators, and parents.

Fred Keller and his Personalized System of Instruction posted by Athabascau University in Canada elaborates on this method, which Keller first proposed in the 1960s.  It includes five features:

1. go-at-your-own-pace;
2. advancement to the next unit after demonstrating mastery of the current unit;
3. "use of lectures and demonstrations as vehicles of motivation, rather than sources of critical information";
4. "stress upon the written word in teacher-student communication" which "typically includes a textbook and a study guide".  The instructor can "comment on, supplement, or correct the textbook," and specify behavioral objectives for the unit.  "A "unit" covers about a week's worth of work from the textbook. The size of a unit is limited by the fact that a unit test should assess the student on every major unit objective instead of merely sampling what has been learned."
5. "the use of proctors, which permits repeated testing, immediate scoring, almost unavoidable tutoring, and a marked enhancement of the personal-social aspect of the educational process."  The suggested ratio of students to proctors is 10:1.

Penuel and Johnson's (2016) Review of Continued Progress: Promising Evidence on Personalized Learning is a critique of the 2015 RAND Corporation research on three school-wide initiatives involving 62 schools promoting personalized learning.  Overall, the reviewers concluded the research had many high quality elements; however, owing to its limitations, "Broad conclusions regarding the efficacy of technology-based personalized learning ... are not warranted by the research" (p. 1).

John Pane's (2018) Strategies for Implementing Personalized Learning While Evidence and Resources Are Underdeveloped is a report from the RAND Corporation.  Pane offers "strategic guidance for designers of personalized learning programs to consider while the evidence base is catching up. This guidance draws on theory, basic principles from learning science, and the limited research that does exist on personalized learning and its component parts" (p. 1).  A key reason for such guidance includes that "Presently, early implementers of personalized learning are working with imperfect evidence, underdeveloped curricular resources, and policies that might hinder their efforts" (p. 9).

 

 

 

Back to top

 

Emerging Technologies Impact Teaching and Learning

The K-12 Horizon Reports lend support to views expressed above.  Written as a joint effort of the New Media Consortium and the Consortium for School Networking (CoSN) with funding from Microsoft, the reports examined "emerging technologies for their potential impact on and use in teaching, learning, and creative expression within the environment of pre-college education" (Johnson, Levine, Smith, & Smythe, 2009, p. 3).  The following were predictions from the 2009 report for technology adoptions that will change the learning process in the near future:

• In one year or less: collaborative environments and online communication tools.  Johnson, Levine, Smith, and Smythe (2009) indicated, “both groups of technologies are now standard in the digital toolset of postsecondary students. In many grade schools, on the other hand, integrating these kinds of technologies into teaching and learning has proven difficult because of barriers such as policy constraints on using online tools, the fact that many students do not bring laptops to school (as opposed to many college students, who do), and policies that restrict Internet access in many schools” (p. 4).

• Within two to three years, mobiles and cloud computing.  This time estimate "is a reflection of the fact that younger students are, at present, less likely than college-age students to carry mobile devices, especially Internet-capable ones — although there is a growing trend that suggests this will not always be the case — and that access to cloud-based applications is more difficult for younger students for the same reasons that collaborative environments and online communication tools are often out of reach” (p. 4). Note that cloud computing refers to large groups of networked servers, which have "made processing power and storage capacity available in abundant quantities. Applications that are developed to run in the cloud and take advantage of the ability to scale up or down along with the number of users and storage demands are changing the way we think about programs and files. Collaborative work, research, social networking, media sharing, virtual computers: all are enabled by applications that live in the cloud” (p. 5).

• In four to five years, smart objects and the personal web. Smart object appliances aimed at consumers are appearing on the market, and the technology shows promise for linking physical objects with rich caches of online content, but common use in schools is still several years away. The technology was placed on the same horizon in the higher education edition of the 2009 Horizon Report. The personal web, on the other hand, is perceived as being slightly closer to mainstream adoption in higher education than in grade schools; the topic appears on the mid-term horizon for higher education” (p. 4).

From the 2010 K-12 Horizon Report, Johnson, Levine, Smith, and Haywood (2010) noted that cloud computing and collaborative environments remain as top emerging technologies for adoptions within 2010-2011, followed by interest in and rise of adoptions of game-based-learning and mobiles within two to three years from 2010.  On a further horizon, set for four to five years away from 2010, adoptions of augmented reality and flexible displays were predicted, which are elaborated on within this report. Of key interest is that technology integration is challenged by the fundamental structure of K-12 education.  Unfortunately, many activities related to learning and education that take place outside the school setting are often undervalued or not acknowledged.

Table 2 contains comparisons of emerging technologies from K-12 Horizon Reports dating back to 2009.  Notice that the 2011, 2013, and 2014 reports included the emergence of learning analytics.  In 2015, adaptive learning technologies appeared.  For more on learning analytics and adaptive learning, consult the following:

• Society for Learning Analytics Research (SoLAR) has numerous resources on learning analytics.  For example, in What is Learning Analytics? SoLAR stated: "As a research and teaching field, Learning Analytics sits at the convergence of Learning (e.g. educational research, learning and assessment sciences, educational technology), Analytics (e.g. statistics, visualization, computer/data sciences, artificial intelligence), and Human-Centered Design (e.g. usability, participatory design, sociotechnical systems thinking)" (About section).  Its publications include the Journal of Learning Analytics and the Handbook of Learning Analytics with downloadable chapters.

• U.S. Department of Education, Office of Educational Technology. (2012). Enhancing teaching and learning through educational data mining and learning analytics: An issue brief.  Washington, D.C.: Author. https://tech.ed.gov/wp-content/uploads/2014/03/edm-la-brief.pdf

• Pearson & EdSurge. (2016). Decoding adaptive. https://www.pearson.com/content/dam/one-dot-com/one-dot-com/global/Files/about-pearson/innovation/open-ideas/DecodingAdaptive.pdf.  This document provides a definition of adaptive learning and a framework for understanding it.  A list of 24 tools is also included and where each adapts.

 

 

Cyberlearning researchers are also investigating the future of learning with technology.  They are "oriented toward a technical and educational horizon approximately 10 years in the future" (Roschelle, Martin, Ahn, & Schank, 2017, p. 1).  In their Cyberlearning Community Report, Roschelle and colleagues summarized six emerging genres (Table 3) and provided resources and examples throughout.

 

 

For 2020/2021, the eLearning Industry (Bui, 2020) posted ten educational technology trends:

1. eLearning: The rising demand for eLearning and distance learning was brought about by the spread of COVID-19 and school closures.
2. Video-assisted learning: Videos enrich learning and can make it more comprehensible.  They also improve student outcomes and reduce teacher workload.
3. Blockchain technology: Benefits to education have to do with data storage and ability to encrypt the data and transmit it over multiple computers.  For example, the technology is used in Massive Open Online Courses (MOOCS) and ePortfolios to verify skills and knowledge.
4. Big data getting bigger: This is allowing instructional designers to personalize learning experiences.
5. Artificial intelligence: For example, AI allows grading to be automated.  It can be found in AI tutoring and providing feedback and progress-monitoring in AI programs.
6. Learning analytics
7. Gamification
8. Immersive learning with virtual reality (VR) and augmented reality (AR)
9. STEAM-based programs (Science, Technology, Engineering, Art, Math) enable learners to explore real-world problems through hands-on activities and creative design.
10. Social media in learning (Bui, 2020).

 

 

To further keep abreast of how technology is changing the learning process, visit MindShift, which explores "the future of learning in all its dimensions. [You'll learn] how learning is being affected by technology, discoveries about the brain, poverty, inequities, mindfulness, agency, social and emotional learning, assessments, game-based learning and music, among many other topics."  Mindshift also reports "on shifts in how educators teach as they apply innovative ideas to help students learn, while meeting the rigorous demands of their standards" (About Mindshift section).

 

Back to top

 

New and Enhanced Processes in Mathematics Education

Technology (e.g., computers of all kinds, Web 2.0 and the social internet) is changing the learning process within mathematics education in ways Lemke and Coughlin (2009) noted (i.e., democratization of knowledge, participatory learning, authentic learning and multimodal learning) and in consideration of Siemens (2005c) theory of connectivism.

In terms of authentic learning, computers enhance the process of mathematics education by eliminating the need for learners to perform all calculations by hand and enabling them to explore "richer" real-world problems that they will encounter in everyday life and in the workplace.  Indeed, in his 2010 TED talk, Teaching Kids Real Math with Computers, Conrad Wolfram of Wolfram Research said "the part of math we teach — calculation by hand — isn't just tedious, it's mostly irrelevant to real mathematics and the real world."  This latter is one of the reasons kids lose interest in math.  One might also speculate that another reason kids lose interest in math is due to the nature of many of the apps they download.  In the words of France (2020), "the dehumanizing nature of many of these programs reinforces within our students the idea that learning isn’t about personal growth and liberation; instead, it reminds them that their voice is limited and that what’s most important is getting questions right so they can move on to the next level."

Maria Droujkova (2009), developer of Natural Math, formulated a Math 2.0 framework “where mathematical education is viewed within a cultural context, defining learning as taking on roles in communities and networks. Changes in mathematics education, then, are culture shifts that include many events at individual, family, local community and group, and global network levels" (p. 2).  This framework considers mathematical authoring; community mathematics; humanistic mathematics; executable mathematics; and psychology of mathematics learning and education (p. 2). In describing these directions, she noted (p. 3):

• Tools and practices of user-generated content, as well as the internet participatory trends of co-production, crowdsourcing, and open educational resources can powerfully support mathematical authoring.

• For community mathematics, free, well-designed communication platforms such as nings, blogs, wikis, microblogging, forums, aggregators, and distributed content mash-ups can support online and local math clubs and math circles, topical discussion and study communities, and networks growing around a variety of particular math endeavors: competitions, educational philosophies, comic strips, books, or curricula.

• . . . Humanistic mathematics approach promotes activities that an audience can enjoy. On the web, this includes infusing mathematics into robust artistic and musical communities; creation and viral spread of appealing math-rich media; and developing newbie-friendly tools and communities supporting authoring of such media.”

• . . . Web 2.0 brings several crucial changes to this field of executable mathematics, including zero-cost distribution of virtual manipulatives; an invitation for everybody to create their own math-rich objects through programming or “construction set” mash-up environments; situating math objects in multi-user virtual worlds; and ease of sharing and continuing development in open educational resource communities.

• Psychology of mathematics education incorporates theories of teaching and learning, studies and practices of meta-cognition, developmental awareness, and support of emotional well-being such as math anxiety reduction. Web 2.0 requires a shift toward more social views on the psychology of mathematics education and its role, within this framework, of supporting the other four dimensions. (Droujkova, 2009, p. 3)

Math in a Cultural Context (MCC): Lessons Learned from Yup’ik Eskimo Elders from the University of Alaska Fairbanks exemplifies Droujkova's framework.  MCC is "a long-term and ongoing set of interrelated federally funded projects. Central to MCC is its long-term collaboration with Yup’ik elders, teachers, and Alaskan school districts to develop culturally based curricular materials, especially supplemental math curriculum for elementary school students." In addition to supplemental math modules for grades 2-6, MCC includes  "supporting materials such as DVD clips of teachers’ implementing exemplary lessons, written case studies, a Guide to Implementing MCC, literacy activities and stories that develop cultural, mathematical, and contextual connections for students. Most importantly, most MCC modules have been tested using either a quasi or experimental design with findings repeatedly showing that MCC students outperform comparable control group students who use their regular math curriculum." (MCC About Us section)

Another resource illustrating community mathematics in Droujkova's framework (2009) is the Math Circles Network, a project of the American Institute of Mathematics.  The Math Circles are "communities focused on the enjoyment of mathematical problem solving. ... Math Circles can take many forms, including after-school programs for students, professional learning communities for teachers and mathematicians, or groups of parents or families who want to become more involved with mathematics education" (About section).

A Caveat: Overall, Robert Slavin (2009) noted that technology has "typically been used to supplement classroom teaching" in elementary grades with CAI [computer-assisted instruction] being particularly helpful with children's computational skills (pp. 4-5).  Technology is being used in teaching mathematics (at least in middle and high schools) in three ways: as supplementary programs to "fill gaps in a learner's knowledge," as core programs "where the computer largely replaces the teacher," and within "computer-managed learning systems that use a computer to assess students and provide teachers with feedback for use in lessons" (p. 5). However, he concluded from his research that there is "limited evidence that ordinary CAI improves math learning."  Rather, "there is strong evidence that using effective teaching strategies can make a real difference.  Changing the way that children work together, and classroom management and motivation, can improve math outcomes for all students" (p. 5).

 

 

Back to top

 

What is technological literacy?

Various definitions have been proposed for technological literacy.

The International Technology Education Association (ITEEA, 2000) defined technological literacy as the "ability to use, manage, assess, and understand technology" (p. 9). Greg Pearson and A. Thomas Young (2002) stated that it “encompasses three interdependent dimensions--knowledge, ways of thinking and acting, and capabilities," with the goal "to provide people with the tools to participate intelligently and thoughtfully in the world around them" (p. 9).  "Although technical competency is not the same as technological literacy, the development of skills in technology can lead to a better understanding of the underlying technology and could be used as a basis for teaching about the nature, history, and role of technology in our lives" (p. 11).

The North Central Regional Educational Laboratory and the Metiri Group (2003) offered a definition of Literacy for the Digital Age. This definition includes basic literacy, scientific literacy, economic literacy, technological literacy, visual literacy, information literacy, multicultural literacy, and global awareness.  "Technological literacy is knowledge about what technology is, how it works, what purposes it can serve, and how it can be used efficiently and effectively to achieve specific goals" (p. 15).

Per the State Educational Technology Directors Association (2007), "Technology literacy is the ability to responsibly use appropriate technology to communicate, solve problems, and access, manage, integrate, evaluate, and create information to improve learning in all subject areas and to acquire lifelong knowledge and skills in the 21st century" (p. 1).

In its Framework for 21st Century Learning, the Partnership for 21st Century Skills (2009) defined ICT (information, communications, and technology) literacy as applying technology effectively.  Learners should be able to:

• Use technology as a tool to research, organize, evaluate and communicate information

• Use digital technologies (computers, PDAs, media players, GPS, etc.), communication/networking tools and social networks appropriately to access, manage, integrate, evaluate and create information to successfully function in a knowledge economy

• Apply a fundamental understanding of the ethical/legal issues surrounding the access and use of information technologies(section: P21 Framework Definitions Document, pp. 5-6).

From their critical review of the literature using 15 reports, books, and articles on 21st century knowledge frameworks, Kereluik, Mishra, Fahnoe, and Terry (2013) formulated the following definition of digital and information literacy:

It can be defined as the ability to effectively and thoughtfully evaluate, navigate, and construct information using a range of digital technologies and thus to function fluently in a digital world. An important part of this is the ability to effectively seek out, organize, and process information from a variety of media. This form of literacy also includes a component of responsible use of technology and media, an important moral and ethical consideration beyond understanding basic information and communication technology systems and media forms. (p. 130)

The emergence and integration of ICT into instruction and student lives has given new meaning to Bloom's Taxonomy of cognitive objectives.  In Bloom's Taxonomy Blooms Digitally, Andrew Churches (2021, 2008) discussed a new set of digital verbs for each of the levels in the taxonomy, reflecting new objectives in the road to literacy.

Thus, by integrating technology into K-12 schools, we are assisting with the development of technologically literate citizens.  However, schools must also be aware of a conclusion reached by Ito and colleagues (2008): Given the diversity of digital media, "it is problematic to develop a standardized set of benchmarks to measure levels of new media and technical literacy" for our youth (p. 2).

Kereluik, Mishra, Fahnoe, and Terry (2013) also proposed that digital and ICT literacy is just one of nine subcategories within three categories of knowledge necessary for the 21st century: foundational, humanistic, and meta.  Foundational knowledge includes digital and ICT literacy, core content knowledge, and cross-disciplinary knowledge.  Humanistic knowledge includes job and life skills, ethical and emotional awareness, and cultural competence.  Meta knowledge focuses on creativity and innovation, problem solving and critical thinking, and communication and collaboration.  Educators need to be aware of the effect of technology on the acquisition of each type of knowledge.  The authors recognized that there is some overlap in categories and subcatagories, and viewed foundational, humanistic, and meta knowledge being of equal importance.  Their analysis revealed a much needed scheme giving "us a "big picture" of what we mean when we say 21st century learning" (p. 133).

As a resource, consider EasyTech digital literacy curriculum from Learning.com, which is available by content area and grade band for learners in K-8 and high school.  It is designed to equip students with the foundational digital skills they need to succeed in online and blended learning environments, including computational thinking, coding, typing, computer fundamentals, online safety, internet use, multimedia, visual mapping, virtual robotics, word processing, spreadsheets, and presentations.

 

Back to top

 

What do we mean by technology integration?

There are multiple ways to think about technology integration.  According to Johnson, Adams Becker, Estrada, and Freeman (2015, pp. 34-45; 2014, pp. 32-33), there are at least seven categories of technologies, tools, and strategies to help categorize emerging technologies and to serve as lenses into technology integration and innovation:

• Consumer technologies find their way into schools because people use them at home, for recreation, or professionally.  Examples include 3D video, drones, electronic publishing, mobile apps, robotics, tablet computing, telepresence, and wearable technology.

• Digital strategies are ways of using digital devices and software in both formal and informal settings.  Among strategies are Bring Your Own Device, the flipped classroom, games and gamification, location intelligence, makerspaces, and preservation/conservation technologies.

• Enabling technologies "expand the reach of our tools, and make them more capable and useful, and often easier to use as well" (2014, p. 32).  There are multiple examples to illustrate.  Among those are cellular networks, electrovibration, flexible displays, geolocation, machine learning, mobile broadband, natural user interfaces, next-generation batteries, open hardware, robotics, speech-to-speech translation, statistical machine translation, virtual assistants, and wireless power.

• Internet technologies "include techniques and essential infrastructure that help to make the technologies underlying how we interact with the network more transparent, less obtrusive, and easier to use" (2014, p. 33).  Consider technologies such as cloud computing, the Internet of Things, real-time translation, semantic applications, single sign-on, and syndication tools.

• Learning technologies are tools and resources designed for education.  They "include technologies that are changing the landscape of learning, whether formal or informal, by making it more accessible and personalized" (2014, p. 33).  Adaptive learning technologies, badges/microcredit, learning analytics, MOOCs, mobile learning, online learning, open content, open licensing, and virtual and remote laboratories exemplify this category.

• Social media technologies are characterized by keywords such as collaborative environments, collective intelligence, crowdfunding, crowdsourcing, digital identity, social networks, and tacit intelligence.

• Visualization technologies range from "simple infographics to complex forms of visual data analysis. What they have in common is that they tap the brain’s inherent ability to rapidly process visual information, identify patterns, and sense order in complex situations" (2014, p. 33).  Examples include 3D printing/rapid prototyping, augmented reality, information visualization, visual data analysis, and volumetric and holographic displays.

Technology integration, as defined by the National Forum on Education Statistics (2005), Forum Unified Education Technology Suite, "is the incorporation of technology resources and technology-based practices into the daily routines, work, and management of schools" (Part 8). Resources are computers and specialized software, network-based communication systems, and other equipment and infrastructure. Practices include collaborative work and communication, Internet-based research, remote access to instrumentation, network-based transmission and retrieval of data, and other methods.

Software for integration includes a wide variety of applications (Software & Information Industry Association, 2006) that:

• meet instructional, curriculum/content, assessment, classroom management, and enterprise level administrative tasks;
• are used in the classroom, school office, and potentially accessed offsite such as from home (student or educator) or from a mobile device;
• are installed on a computer or other device, installed on a school local network or wide area network, or hosted by a third party and accessed online via a web browser;
• include a wide variety of digital content ranging from an electronic version of a printed material (e.g., e-book or pdf file) to multi-media, interactive and adaptive courseware. (p. 3)

Aditi Rao (2013) made a concise comparison of "using technology" versus "technology integration."

•  Using Technology: In her view of "using technology," technology use is random, arbitrary, and often an afterthought.  Technology is rare and sporadically used in the classroom, used for the sake of using technology, used mostly by the teacher to instruct learners on content.  It's used more to complete lower order thinking tasks, and more instructional time is spent learning how to use the technology itself.  Learners would use it primarily for working alone.  Technology is used to facilitate activities that are feasible or easier to complete without technology.  Technology is used to deliver information and is peripheral to the learning activity. 
• Technology Integration: Whereas, in her view of "technology integration," technology usage is planned and purposeful; technology is a routine part of the classroom environment and used to support curricular content and learning objectives.  Technology is used to engage students and is used mostly by them.  The focus on using technologies is to create and develop new thinking processes.  More instructional time is spent using technology to learn.  Technology is used to encourage higher order thinking skills, to facilitate collaboration in and out of the classroom, and to facilitate activities that would otherwise be difficult or impossible.  Technology is used to construct and build knowledge.  It is essential to the learning activity.

To measure the extent of technology integration within your setting, consider the following key questions (National Forum of Education Statistics, 2005, adapted from Part 8):

• Are teachers and students proficient in using technology in the teaching/learning environment?
• To what extent (percentage) has technology been integrated in the teaching/learning environment?
• Do teaching and learning standards and student assessment include technology proficiencies and measures?
• Do administrative standards include technology proficiencies and measures?
• Are administrators and support personnel proficient in using technology for school management?
• Is technology incorporated into administrative processes?
• Is technology proficiency integrated into evaluation of instructional and support staff?

 

 

Back to top | Part 1: Technology Integration: Essential Questions: Page 1  |  2  |  3

 

References

 

Back to top

See other Technology Integration pages:

Part 1: Technology Integration: Essential Questions: Page 1  |  2  |  3

Part 2: Technology Integration Resources  |  Part 3: Web Page Design  |  Part 4: Multimedia in Projects

 

 

 

 

Comments?  Are you finding resources at CT4ME of value?

Send us your favorite math resources and tips for success.

Contact Dr. Patricia Deubel: pdeubel@ct4me.net

To cite this page, use the following format:

Deubel, P. (year from last revised). Technology integration: Essential questions. Computing Technology for Math Excellence. Retrieved Month, Day, Year, from https://www.ct4me.net/technology_integr.htm

CT4ME Author: Dr. Patricia Deubel

CT4ME Privacy Policy

Copyright © 2001-2024 [CT4ME.net].  All rights reserved.