Every day I read or hear about a new tool, app, web-site, kit, toy, or device that is reported to have a significant impact on student learning. Actually, none do. The way they are used might.
So-called “21st century skills” (such as collaboration, communication, creativity, critical thinking) have been arbitrarily chosen… and they existed long before the new century. These skills, and many others, have always been important in education.
However, the ever growing potential to use powerful technologies to facilitate thinking and share learning is empowering, invaluable, irresistible. So, to me, learning in the “21st century” means that students are learning how to use technology to better think, create, analyze, learn, and share.
Of course there are many people far more eloquent than I:
Thanks for reading this post! It was part of a #peel21st blog hop that transpired on November 18, 2014. Please take a look at the other posts in this hop. Each author had to respond to the question “Learning in the 21st Century – What does it mean to you?” in about 100 words.
Originally posted on Peel21st Project 188:
Hi #peel21st! I am an elementary ITRT working with educators in Mississauga. I love to see students using technology to create, learn, work together, explore ideas, and share.
What did I learn today? I learned (again) that change is the only constant. You would think that this clichéd, paradoxical observation is one with which we all would be familiar. True, it is familiar, but I think it is also true that we still expect to ‘get comfortable’ or ‘get used’ to something that we do, that we use, that we think in our professional practice. Things are easier after we get comfortable with them.
What specifically led me to this line of thought? A group of teachers and I were working and making good progress in our co-planning session. We were exploring blogging as a vehicle for students to share ideas related to the various numeracy and literacy goals…
View original 265 more words
[Note: This post was one of nine from the September 2014 #peel21st blog hop! Read on to learn more about ScratchJr and don’t forget to check out the other blog hop posts linked at the bottom of the page.]
- App Name – ScratchJr
- Cost – Free
- Platform(s) – only iOS currently (Android version planned)
- Developed by - Massachusetts Institute of Technology and Tufts University
- Download - https://itunes.apple.com/us/app/scratchjr/id895485086?mt=8
- Website - http://www.scratchjr.org/
What is ScratchJr?
Despite the fact that MIT’s Scratch (http://scratch.mit.edu) is probably the most accessible programming environment for children, you might be looking for an even simpler version, perhaps for very young children. ScratchJr was created specifically for them.
Both environments allow users to move and connect coding blocks to control the actions of characters (called sprites) within a rectangular window (called a stage). Blocks are organized into different categories; for example, one group of blocks control movement, another controls sprite size, and still others control when, and how many times, an event occurs.
Is ScratchJr the iPad version of Scratch?
No, ScratchJr is not the iPad version of Scratch. They are actually quite different when you examine the programming potential of each. ScratchJr would be more aptly characterized as “ScratchLite” or “SimpleScratch.” I have seen Scratch used by all ages of children in school, from K to 12, and very successfully. Programs in Scratch can be incredibly simple or incredibly complex. ScratchJr is only capable of fairly simple programs, and primarily narrative animations. However, ScratchJr works on the iPad! That’s great news for many classroom teachers and students alike. Scratch does not work on the iPad; it’s a web 2.0 tool that runs in your browser using Flash player.
What can students learn with ScratchJr?
The most important educational value of any programming environment is that it allows for the student to make their abstract thought processes visible on the screen. Once the thoughts are made concrete, they can be easily manipulated and controlled by the student in a more tangible way. And, because they are displayed visually on a screen, the teacher can also see what and how a student is thinking. Scratch and ScartchJr are designed so that this visualization is made clearer because the code is made of coloured boxes that snap together, not typed in command words. The blocks are visual and can be moved around and placed with the mouse or finger.
What are some project ideas that ScratchJr can support?
- Organize procedural thinking into a concrete creation, such as a narrative
- Create a game in which the user has to touch a fast moving character in order to move to the next level
- Use the built in x-y coordinate grid to create/test position pattern rules and transformational geometry concepts
- Create a realistic or funny animation, such as a character bouncing a ball and throwing it into a basket
- Use the voice record tool to create a word wall that reads the word out loud when touched by the user
Each of the above ideas has several connections to the Ontario Language Arts or Mathematics curriculum. ScratchJr is an excellent iPad app because it is open ended, supports creativity, and has an intuitive user interface. Plus it is free.
Here is an example narrative created by a young child using the ScratchJr app
Because the app is brand new (July 2014) I have not personally seen it in use with students yet. Most of this post is based on my explorations of ScratchJr and my experience using Scratch with students. I am very interested to see how ScratchJr can be used effectively with students and I plan to post a follow up post in the spring.
If you have used ScratchJr with students, please share your experiences in the comments section below or leave a link to your blog or web site.
Make sure you check out the other eight posts from the September 2014 #peel21st blog hop:
In a recent blog post by @MatthewOldridge, he questions the ‘whys’ of learning to code. And rightly so, I think. If you are at all following educational trends, you are probably aware that people are seriously discussing the merits of coding/programming in terms of a new literacy. For example, you have probably seen all or part of this video:
On the day I posted this, the video has nearly twelve million views. Unfortunately, I think the video’s message veers off course at times—it often sounds more like a sales pitch than an impassioned plea for educational reform. But this is not the first time this topic has been discussed. Probably the most significant initial examination of the interplay between programming and learning was presented by Seymour Papert in his book Mindstorms: Computers, Children and Powerful Ideas. I think this book is a doorway, at least, it was for me. Before reading it, I thought one way about how technology can influence learning. After reading it, I began thinking in a new way. Even though it was published in 1980, I think its message is still powerful today. (Papert’s construct, the microworld, was also the topic of my thesis.)
Critique of the video
So, on one hand, the video’s message is absolutely correct. Learning to program can be rewarding and lead to a job, or, at least, a skill with which you can earn money… much like being a lifeguard can earn you money. It was a great summer job. And it can be a great career, too. But it’s not for everybody. I definitely support the notion that all children take swimming lessons and learn to swim. But, not all children who learn to swim will become lifeguards. I would definitely support the notion that all children explore coding (in the service of learning). But, not all children who learn to code will become professional programmers. Nor should they. This is where the notion in the video, and the resulting ‘coding bandwagon’ in education, are a little out of whack. Everyone does not need to learn to code to a high degree (i.e., programming). You can be technologically literate but not know how to write a computer program. I know many people who know how to use a variety of digital devices, and understand how they interact, they know how the web works, how email works, how to buy and print movie tickets online, how to take pictures or record a video on their device, how to tweet, how to leave a comment on a blog… You are probably one of the millions of people who know how to do all of these things and that makes you literate in today’s digital society. I rarely see ‘coding’ or ‘programming’ listed in frameworks of modern educational objectives or in so-called ‘21st century learning’ frameworks (e.g., here, here, & here).
My experience with coding
I grew up in the late 70s, during the dawn of personal computers. The early computers were text-based, digital marvels that did absolutely nothing until you programmed them to do something. I remember going into stores and playing around on them and trying out little programs to see how (or if) they would work. They were quite simple:
Rather inane but fun to play around with. Anyway, I learned how to code by talking and learning from people I met in the stores who were also interested in programming languages. This became a sort of social network, but F2F… After two years of formal computer programming courses in grade 11 and 12, I discovered that I had developed a ‘real’ skill. At the time, I decided to myself that it was the first real skill that my work in school provided me with (forgetting about reading, writing, algebra, and the hundreds of other skills I learned in school). Nevertheless, I took no small satisfaction in the knowledge that any process I could work out with a paper and pencil I could translate into a computer program that did exactly the same thing. One of the later benefits of this skill was that I was contracted one summer to write a carpet tufting simulation program so that samples of carpet tufting designs could be created on the computer screen as a preview before being made by the machine. The money I earned from writing that program paid all of my university costs for a year.
An example of codified thought
I think coding and programming tasks in schools certainly have value so long as they are a means to an end. Programming projects are especially useful because they seek to solve a problem or provide an application that automates or simplifies a task. Programming is the concrete explication of abstract ideas and processes. I think that most programmers are very familiar with this concept. Ideas and processes, that begin as a purely cognitive conception, become concrete and real when translated into a computer programming language. Once codified, they can be applied by anyone using the software.
Years ago, while writing a datebook program (similar in functionality to a calendar app that stores events), I needed a function early on to determine if a given year was a leap year or not. Working it out on a piece of paper, I could describe the process like this:
I knew exactly what to do mathematically and ‘procedurally’ to find out if a given year needed Feb 29 or not. The next step was to translate this process into code that the computer could understand. In programming parlance, I had to define a new function in my program in which I could submit any year I wanted to, and the function would reply with a 1 (yes) or a 0 (no) regarding the existence of Feb 29 that year. Here is the function I wrote:
(The ‘mod’ part in this code stands for modulo which means: apply a division operation on two integers and then only retain the remainder portion. If the modulo equals zero, it means the dividend divides evenly by the divisor.) The middle three lines beginning with the word ‘if’ are the codified versions (in Borland Turbo Basic) of the three English sentences describing my process. The other bits of the code tell my program that I am defining a new function and gives it a name (fnLeap%) so that I can use I wherever I want to in my program. In Java, this might look like this (although my Java is rusty; correct me if I am wrong):
What about a real classroom example?
Regarding Matthew’s question of the ‘why’ of coding – what follows is an example of students who use coding to learn and gain a deeper understanding of a concept. In the example below, I wanted to use the conceptual change model to challenge my grade 6 students’ understanding of polygons. My students had played with Scratch long enough that they had a good understanding of how to move Scratch the cat around on the stage using the Motion blocks. They also knew how to use the Pen blocks so that Scratch drew a line as he moved on the stage. My students had become adept at both describing, in mathematical terms, the attributes of polygons, and at constructing polygons using a variety of pencil and paper tools. However, I noticed anecdotally that a variety of minor misconceptions were apparent pertaining to angles, such as reflex angles, the relation between 360° and 0°, and relative angular measurements. My students were able to construct various polygons and angles specified in the Ontario math curriculum but, if challenged to transfer those skills and their understanding to a different domain, my guess was that some degree conceptual confusion would result. So I decided to create a programming task using Scratch which utilized the conceptual change model. Learning objectives were as follows (taken directly from the mathematics curriculum):
- classify and construct polygons and angles
- construct polygons using a variety of tools, given angle and side measurements
- measure and construct angles using a protractor, and classify them as acute, right, obtuse, straight angles, or reflex
First, using concept mapping software that the students already had experience using (SMART Ideas), students created a flowchart that outlined the steps for constructing an equilateral triangle using pencil, paper, ruler and protractor. I wanted the flowchart to act as a learning artifact that students could use in a later reflection. Next, I told my students that they would be using Scratch to draw their triangle on the stage. Before beginning the activity, they were asked to predict what, if any, changes would need to be made to their existing flowchart for drawing it on paper. Students made a duplicate flowchart and then made modifications as required from their predictions. Students were challenged to create a program that results in Scratch the cat moving in such a way as to draw an equilateral triangle of any size on the stage. At this point, I paid very careful attention to students’ activities because it would be at this time they would potentially face cognitive conflicts. For example, because Scratch the cat rotates relative to his current position (rather than relative to a line just drawn), the supplementary angle for 60° must be used (120°) in this case in order to tell Scratch how to draw an equilateral triangle. Students worked with partners but each had to write their own code. They discussed and helped each other, and I was also engaged in coaching and suggesting ideas as required. Here are two Scratch coding examples that result in an equilateral triangle:
Once the students successfully created the triangle, they examined their prediction flowcharts and directly compare it to the program they have just written that successfully moved Scratch the cat in the shape of an equilateral triangle. Students spent time discussing with their partners the differences between their predictions and the code that produced the triangle (the conceptual conflict) and together they had to work out exactly why they were different and what was going on in Scratch’s world as opposed to their pencil and paper world. In so doing, the depth of their conceptual understanding of constructing polygons grew. This whole process was repeated for other polygons such as squares, hexagons and octagons. I think that the greatest thing about computer programming in the service of learning is that both the student and the teacher can see thoughts on the screen. Not finished, perfectly formed, organized thoughts… but constantly changing, experimental, incremental thoughts that changed in the way they were arranged second by second… Programming provides a concrete way to discuss and share these thoughts. In the example above, creating the program in Scratch acted an ‘object to think with’ (albeit a virtual one) for each student trying to accomplish a simple task: instructing Scratch to move in such a way so that he would draw an equilateral triangle.
Final thoughts – coding vs. programming vs. software development
I think that a distinction has not been properly drawn between coding and programming, or between programming and software development, in the current discussions of ‘all students need to learn to code.’ I hinted at a distinction in my post above but I want to make it more explicit now. There are many frameworks that attempt to define levels of computer programming competence; I still like Pea and Kurland’s from 1984 (starting on page 152, the levels are fully explained; the parenthetical explanations are my summaries of their descriptions):
- Level I – Program User (adept at using someone else’s code for its intended purpose or modifying it for a new purpose)
- Level II – Code generator (adept at writing original, short code pieces that accomplish a simple task)
- Level III – Program generator (adept at writing interconnected code – a program – to accomplish a complex task; not necessarily user friendly)
- Level IV – Software developer (adept at writing commercially valuable and usable code that is easy to use for large numbers of end users)
Without going into too much detail, my students (see the example above) who could use the Scratch environment were operating at Level II – they could write small snippets of code; single purpose mini-programs that accomplished one task. Yes, my students could code. But I would not describe them as programmers. And not anything close to software developers. Yet, at Level II, my students were writing code in the service of learning. Code was not being written so that they could later become programmers or software developers. Code was being written so that they could see their own thought processes on the screen and be able to reach out and move them around and organize them in such a way that reflected their understanding of a concept. Some students might enjoy this challenge so much that they will be motivated to develop their abilities further towards Levels III and IV.
As much as the “discovery” mode of learning in schools has been bashed by various education critics, I believe that the most powerful, memorable, impactful and longest lasting experiences in our lives arise from those periods in which we are completely immersed in a self-driven deep exploration of something or an equally self-driven need to create something.
The best characterization I have found for this phenomenon is from psychologist Mihaly Csikszentmihalyi. He called it “flow” (see also flow in Wikipedia). I think that designing educational environments that lead to flow is at the heart of what “discovery” learning is all about. Incidentally, I know of very few educators who actually use the term “discovery learning” —it is an imprecise and ambiguous term. I don’t like it either for the same reasons. I prefer to think of it, as Seymour Papert described it, as a constructionist activity.
One of the reasons for writing this blog post is to share a theory I have about student disengagement that occurs not only in school systems but also among children and adults in general. Obviously, “engagement” and “flow” are highly synonymous but I want to emphasize the view that understanding the concept of flow, and designing environments that engender such experiences, might function quite well as an antidote to disengagement. That is, understanding the conditions that would lead to flow, and actively taking steps to establish those conditions, might be an effective strategy to combat disengagement.
I also think that chronic disengagement can lead to depression and a negative self-image. I believe that all people want to feel purposeful and driven but, for whatever reason, many school-aged children are distracted, or redirected, from naturally creative pursuits or from activities that genuinely support their quest to find answers to questions that matter to them. With so many things pulling their attention away from self-regulated, self-selected activities, I think their emotional and intellectual selves get short-changed. I am convinced that supporting children to engage in creative and exploratory activities can lead to flow and quality learning.
There is something about seeing a child rapt in an act of creation: painting, writing a song, building a sand-castle, making a video, weaving a Rainbow Loom bracelet, putting on a play, or making a cardboard arcade—creation brings a passionate focus to action, and this focus often leads to flow and deep learning. There is also something about seeing a child spellbound in an act of inquiry: taking apart a machine, trying to put it back together, exploring a new place, asking big questions, researching online, doing experiments, or thinking ‘what if’—inquiry also generates a remarkable focus that often leads to flow and deep learning.
So, my question is, what are we doing as educators and parents to encourage and support our children to explore their creative impulses or find answers to the daily flow of questions that radiate from their minds every day? My guess is that we are doing quite a bit to support this kind of learning but I think we can do even better. I know I can do better. Sometimes I need to do things, one of them being writing this blog post, to remind me to do better and to remember, as Ken Robinson puts it, not to educate (or parent) the creativity or inquisitiveness out of our children.
There are many benefits to taking time and energy to effectively integrate technology into learning tasks, which already will include knowledge/skills/values from the curriculum and various pedagogical strategies. There is a very useful model, called the TPACK framework, and it can help educators visualize the overlap of each these areas of knowledge that are used when designing learning tasks. In my view, the two core messages of TPACK are that:
- technology, content and pedagogy interact simultaneously
- choices educators make in these domains when designing learning tasks affect the quality of learning.
Sometimes, teachers in the schools I support want to discuss the rationale for the integration of technology. Discussing the current paradigm shift (e.g., here, here, & here) can sometimes be a little dry, so often it is useful to share a more direct list of some benefits of employing technology in the service of learning:
- Facilitate differentiated instruction (consistent criteria but choice of tools / product, supports creativity)
- Permit greater access to educational objectives and student outcomes (SAMR model, combining technologies e.g., Popplet + blog post)
- Support a constructivist approach to learning (active knowledge building, cooperative learning, inquiry model, critical stance)
- Connect your classroom to a global audience (digital citizenship, global communication, sharing learning / artifacts, authentic feedback)
- Facilitate co-creation of knowledge and skills (collaboration via wikis/LMS/CMS, digital citizenship norms)
- Aid in the visualization of knowledge, ideas and concepts (creation of images / diagrams, concept maps, media/video production, programming)
- Initiate and develop digital citizenship (critical digital/media literacy, positive modeling, use over time, discussion of issues, nine elements)
- Enhance student engagement in learning (differentiated instruction, social media tools, choice, active vs. passive learning, animation, ePortfolios)
- Professionally stimulating (educator PLNs, connections via Twitter, blogging)
Our board is making its way through the first year of a standing, open-invitation to all students and teachers to BYOD–bring your own device–to school and use it for teaching and learning (also known as BYOT–bring your own technology). Schools are very complex environments and it will take time for personal device use to become a normal part of the classroom and school environment. Nevertheless, I have noticed a pattern at schools where BYOD/BYOT is taking off more quickly. Here are some observations I have noted that, so far, seem to be common factors at schools where device use is regular, more integrated, and has a greater impact on learning:
- Plan for BYOD/BYOT
Schools plan for a successful BYOD implementation. In almost every school I support, a team of teachers met regularly to discuss, plan, design, and communicate the implementation process to the rest of the staff. Any given school has its own set of challenges to BYOD working smoothly and issues, such as classroom routines or storage during phys-ed class / breaks, need to be addressed. Also, many teachers want a consistent approach to how BYOD looks and works within each class and throughout the school. Further reading: How to launch a successful BYOD program
- Ongoing professional learning & training (e.g. co-teaching, workshops, Twitter, blogs)
I am seeing teachers using social media to focus and control their own professional learning. Nothing is more powerful for teacher PD than the right knowledge at the right time. Teachers learning from each other in schools is also powerful; I see that all the time in active BYOD schools. The benefit for students of ongoing teacher collegiality is direct and impacts on all of the factors listed here. Our board also provides workshops and devotes a special section of their intranet website to the sharing of 21st century teaching and learning resources, including links and screencasts of available tools that can support BYOD classrooms. (Further reading: Tim Clark on Twitter regularly shares BYOT/BYOD resources. Also: 5 Tips to Help Teachers Who Struggle with Technology
- Regular device use, co-learning
Teachers recognize that regular use of devices in the classroom will encourage devices to continue to be brought in and it demonstrates to other students that devices will be used as a natural part of the classroom environment. When devices do come in, really effective teachers are taking a co-learning stance with students: teachers are learning from students about the potential of different devices and students are learning from teachers about new ways to use the device to help them learn, share, create, connect, communicate, etc. Also: Best practices for BYOD
- Clear routines & guidelines
Schools and classrooms are busy places and there isn’t time for messing around with lax expectations around device use. Teachers are having success when they and students develop, early on, what ‘appropriate use’ of technology means and how they are all going to commit to that. Obviously, ‘appropriate use’ guidelines/policies are often already developed by the school boards… but telling students to follow a long list of rules doesn’t guarantee the kind of ownership and commitment needed for success. I have noticed that when expectations are co-created with students, and in their language, there seems to be a better understanding and appreciation of the need for clear routines and guidelines.
- Digital citizenship
This is a deeply integrated set of values and norms in successful BYOD classrooms and schools. Good character is just as important online as it is face-to-face. But digital citizenship is more than just good character… and digital citizenship is not just a unit covered in early September. Teachers and students alike are expected to model positive, respectful, safe and responsible use of technology all the time and discussions about ideas, issues and incidents are on-going. If students are to be productive and fully literate members of a digital society, then a strong foundation of digital citizenship needs to be built. Further reading: Nine elements of digital citizenship
- Welcoming/sharing climate, patience
Teachers and students in schools where BYOD is more successful recognize that patience is important; technology does not always work perfectly, or quickly, or efficiently. Additionally, I often see students in successful BYOD schools helping each other, making suggestions, and taking the initiative to anticipate what a fellow classmate might need. Sharing is the norm in BYOD classrooms; sharing of ideas, resources, knowledge and technology. This doesn’t mean that a student who brings in his/her device hands it over to another student who does not have one… but, rather, a student with a device will invite and include another student without device during a learning task in the classroom.
- “Device neutral” language
In classrooms where there is a variety of devices coming in, teachers ensure that their language, when describing a learning task, does not assume the use of a specific kind of technology or app. For example, instead of saying “create a Keynote that shows your understanding of….” they might instead say “create a presentation that shows your understanding of….” thus allowing students to select an app that will be appropriate for that task. Further reading: Device neutral assignments
- Understanding myths
Most classroom environments where BYOD is taking off are designed by teachers who do not buy into the “digital native-digital immigrant” mythology. Every generation has its own expression of the “generation gap” and the “digital native” is the one thrown around these days. Today’s students might very well be more comfortable with technology than adults but that does not automatically lead to broad competencies with technology or the ability to use technology effectively for learning. Teachers can model use and design tasks that can build these competencies in students. Also: Digital native/immigrant notion can be misleading
This list is by no means complete… and I would invite any readers to comment and share other factors that influence the success of BYOD in their locations.
Prensky’s ‘digital natives’ and ‘digital immigrants’ dichotomy is just one current incarnation of the old “generation gap” cliché. Yes, I do concede that there might be a gap in the general knowledge and skills of what is happening in youth culture and what is happening in the culture of the parents of today’s youth. I also have to admit that Prensky’s notion has engendered a great deal of useful discussion among educators and the general public about developing new ideas to support learning in 21st century classrooms.
However, I think it is important that educators realize that they need to be very careful about making assumptions regarding student competencies with technology based on Prensky’s natives/immigrants concept. Often, I hear educators saying something like “my students know so much; they can teach me how to use all this technology.” While that might be true for a selection of specific uses and tools, all teachers still have a significant role to play in broadening student use of technology in the service of learning, collaboration, communicating, creating, and supporting critical thinking.
What follows is a cut-and-paste from the literature review section of a research paper I wrote in 2012 while studying at UBC. In it, I reviewed a number of academic papers that set out to evaluate the concept of the digital native.
The purpose of this review is to ascertain if there is solid empirical evidence that supports Marc Prensky’s generation-based conception of the digital native (2001a, 2001b). This conception, and the many ramifications for students, parents and educators, is very important to understand and critically examine because it can influence the decisions and policies of educators, administrators and politicians.
Don Tapscott (1998) and Nicholas Negroponte (1995) both laid the groundwork for the digital native concept. Prensky presents similar arguments (2001a) by stating that today’s students are the first to grow up with ubiquitous digital devices and instant access to information via the Internet: “our students today are all native speakers of the digital language of computers, video games and the Internet” (Prensky, 2001a, p. 1). These devices, and the information, games and communication inter-activities they permit, have created a generation of youth who think and learn differently compared to the generation above them (whom Prensky, 2001a, labels digital immigrants). In a follow-up article one month later, Prensky (2001b) asserts that digital natives think in a fundamentally different way to digital immigrants and cites neuroplasticity brain research to support his claims.
Superficially, Prensky’s notions are readily accepted by many educators and resonate with the traditional generation gap cliché. This is nothing new. However, Prensky makes a very bold statement regarding the state of education built on his premise:
It’s very serious, because the single biggest problem facing education today is that our
Digital Immigrant instructors, who speak an outdated language (that of the pre-digital age),
are struggling to teach a population that speaks an entirely new language. (2001a, p. 3)
Educators and researchers have a serious responsibility to engage critically with Prensky’s proselytism and hyperbole. Probing questions need to challenge the very premise of his dichotomous digital native-digital immigrant definition.
Selection of Studies
There has been a solid, critical response among academic researchers to Prensky’s digital native notion. In this review, I will present a balanced mix of very recent studies that seek to find evidence to support the digital native definition. A systematic assessment of all studies evaluating the digital native concept is beyond the scope of this review. Of the six studies included, there are three review studies, one quantitative study, one qualitative study, and one socio-historical study. I will demonstrate that a common conclusion exists in the studies selected. That is, that the technology use and competence of today’s students cannot be captured by a simple, general description such as the digital native portrayal. The reality is far more complex and variable.
Review and Critique
In 2008, Bennett, Maton and Kervin conducted a thorough literature review of studies examining the assumptions of the digital native characterization. They first detailed the claims made of this generation’s general abilities and then carefully examined these qualities and the results of research testing these statements. In their review of studies of university level students, they found that the primary use of technology were in the areas of word processing, emailing and using the Internet for leisure activities. Only a minority of tertiary students used Web 2.0 applications to create and share content. They also had significantly lower levels of competence than would be expected of digital natives. In their review of children’s and adolescent’s use of technology, they found a wide discrepancies in the ways ICT was being used with the sources of variation related to a number of factors such as age group, SES background, and the influences of home versus school. Bennett et al also examined the claim that digital natives prefer a specific learning style—one that is high speed, multitasking, and game based. Their review revealed that there is no evidence that supports the theory that today’s students belong to a homogeneous generation characterized by an idiosyncratic learning style. When researchers identified and measured learning preferences, wide variability was found in the group. The results are clearly at odds with Prensky’s broad notion that current students all learn and operate at what he calls “twitch speed” (2001a, p. 4).
In a related, later study, Bennett and Maton (2010) more closely examined the specific competence-based claims made about digital native youth. In their review of ICT access studies, a wide variation of access levels were apparent and connected to variables such as age, home, school, location. The complexities of measuring provision versus access also complicated the understanding. In terms of technology-based activities, Bennett and Maton state that while a majority of students did use technology to communicate and access information on the Internet, a minority used Web 2.0 tools to create content online. Interview data from some studies reported that students were often unaware of tools such as wikis and blogs. Additionally, studies revealed that groups of young people developed narrow competencies, specializing in one or two areas, for example online gaming, social networking, or messaging. The general conclusion of this review was that there exists wide variation of activities and proficiencies in the various samples surveyed or interviewed. This contrasts with Prensky’s view that all young people today speak with a new digital language unique to them.
Neil Selwyn’s (2009) literature review of studies examining online and digital technology use by younger students also presents a far more complex and variable reality than Prensky’s. Aside from other predictive factors that affected levels of Internet and computer use (e.g., rural location, females, and youth from families with a low level of parental education), studies in Selwyn’s review all showed wide variations between 7, 11, and 15-year-old children and their use of technology. For example, adolescents primarily played games, sent messages, and retrieved information online whereas pre-adolescent use centered on word processing, picture making and playing simple games. Selwyn also noted that various researchers observed passive activities online rather than active Web 2.0 digital content creation and collaboration activities that Prensky (2010) describes as distinctively digitally native. Another issue that surfaced in Selwyn’s literature review was the disquieting notion that pre-adolescents had difficulty finding and critically evaluating information found on the Internet. Prensky (2001a) asserted that digital natives are sophisticated users of information technology but Selwyn research review indicate that actual use and competence does not support this assertion.
Helsper and Eynon (2010) analysed data collected from the 2007 Oxford Internet Survey (OxIS) to ascertain specifically what variables best define a digital native. The OxIS is conducted face-to-face with individuals aged 14 or older. In 2007, there were 2,350 respondent s. Helsper and Eynon excluded data from non-Internet users or ex-users thus reducing the sample to 1578. They closely examined factors such as age (i.e., generation), gender, education, experience and breadth of use of technology. Their analysis of the OxIS survey data revealed that while generation was a significant variable in determining digital nativism, it was not the strongest:
Indeed, in all cases, immersion in a digital environment (i.e. the breadth of activities that people carry out online) tends to be the most important variable in predicting if someone is a digital native in the way they interact with the technology. (Helsper and Eynon, 2010, p. 515)
In fact, if age were held as the main factor in determining who is, and who is not, a digital native, the OxIS survey indicated that online digital activities significantly decrease after age 55 which would redefine the birth age of the digital native to 1952, not 1980.
In 2011, an interesting qualitative study of authentic adolescent use of technology and the Web was conducted by Thornham and McFarlane. These researchers saw an opportunity with BBC Blast to actually observe UK’s digital natives in action. BBC Blast was established in 2002 as both a nationwide touring media-workshop and Web 2.0 site that sought to be the ultimate destination for British teens wanting to learn how to create media, share media, and discuss each other’s media productions. The BBC Blast web site provided statistical access data as well as actual media productions and online discussion threads created by the age 13-19 users. A survey was posted on the web site to which 189 users responded. They also conducted 400 group and individual interviews regarding use of the site. Results of their inquiry revealed that teens rarely interacted with each other online in a meaningful or productive way. For example, many online discussions were sharing sessions of likes and dislikes (e.g., computer games they liked to play). Web site access data showed that the users spent an average of only three minutes on the site. Almost no evidence of collaboration or interaction was seen in the discussions. Additionally, questionnaire data suggested that teens would only consider uploading their productions if there was an incentive, such as a competition or feedback from an expert. The prediction that digital native UK teens would be self-motivated to use an online space to work collaboratively was not supported when this online space was made available to them. Essentially, cases in which teens were actually operating as digitally natives were the exception not the rule.
David Buckingham (2006) provided historical, sociological and philosophical background to the practice of generational definitions and their origin. His inquiry was based on a single question: Is there a digital generation? In his chapter, he chronicles the development of various generation gap assertions over the last century and connects them to well-known (yet hyperbolic) familial, educational, and societal moral crises or imperatives. He also asserts that generational definitions grounded in technological determinism (such as those from Prensky, 2001a, and Tapscott, 1998) often ignore the complex interplay of other factors such as government, business, and marketing influences. He also presents a brief literature review of studies that examine actual computer and Internet use by children. Again, the studies he cites concur with those reviewed because they “suggest that most children’s everyday uses of the internet are characterised not by spectacular forms of innovation and creativity, but by relatively mundane forms of information retrieval” (Buckingham, 2006, p. 10).
In the case of Prensky’s digital natives classification, tests and examinations of the current generation of students have been completed over the previous decade by a large number of researchers and it has been found to be an inaccurate characterization of what Prensky called “today’s students – K-12 through college” (Prensky, 2001a, p. 1). This subset of the population does not speak a language all their own which is distinct from that of their teachers.
It turns out that there are several factors at work that affect the extent to which today’s students develop the knowledge and skills that determine their level of competence with digital technology and Internet use. Prensky is correct that the current generation of children are the first to grow up in an environment saturated with nearly ubiquitous Internet access, the Internet, Web 2.0, and a myriad of digital devices. However, this does not automatically create a generation of digital specialists who can multitask and who are naturally collaborative, creative, and interactive.
Today’s students tend to use these tools in a variety of ways, and at a wide level of competencies, for reasons that serve their own individual wants and needs. Thus, students tend become very adept in select areas such as online gaming, texting, or retrieving information. Recall that Helsper and Eynon (2010) stated that it was the breadth of online activities that was most associated with the characteristics of Prensky’s digital native user, not age. Actual studies have revealed that a breadth of use is lacking; students who are using technology, usually do so well but in very narrow uses and in ways that match their interests and inclinations.
Conclusion and Further Study
It would seem that a wide variety of skills, knowledge and learning styles exist in the population Prensky calls today’s students. It is crucial that educators and policy makers have a solid foundation upon which to make decisions about pedagogy and funding. The portrayal of today’s students as digital natives does a disservice to both students and teachers because educators and politicians who accept the definition will make assumptions about today’s students that are not accurate.
Building on Helsper and Eynon’s (2010) analysis of the OxIS, and reviews of studies by Selwyn (2009), it seems reasonable that the collection of data regarding the levels and types of Internet access, and the types and extent of Internet and computer use, that today’s student engage in is essential information for educators and policy makers.
Finally, since it is clear that the digital native concept is not supported by empirical research, a problem now exists in the form of an inaccurate depiction of students that has been adopted by educators. How deeply is the digital native characterization entrenched in the minds of current teachers, school administrators, and school board administrators?
Bennett, S., Maton, K. & Kervin, L. (2008). The ‘digital natives’ debate: a critical review of the evidence. British Journal of Educational Technology, 39(5), 775-786.
Bennett, S., & Maton, K. (2010). Beyond the ‘digital natives’ debate: Towards a more nuanced understanding of students’ technology experiences. Journal of Computer Assisted Learning, 26(5), 231-331. doi: 10.1111/j.1365-2729.2010.00360.x
Buckingham, D. (2006). Is there a digital generation? In D. Buckingham & R. Willett (Eds.), Digital generations: Children, young people and new media (pp. 1–13). Mahwah, NJ: Lawrence Erlbaum.
Englert, K., Fries, D., Martin-Glenn, M., & Michael, S. (2005). How are educators using data? A comparative analysis of superintendent, principal, and teachers’ perceptions of accountability systems. Aurora, CO: Mid-continent Research for Education and Learning.
Gay, L. R., Mills, G. E., & Airasian, P. (2009). Educational research: competencies for analysis and applications. Upper Saddle River, New Jersey: Pearson Education, Inc.
Helsper, E. & Eynon, R. (2009). Digital natives: where is the evidence? British Educational Research Journal, 36(3), 503-520. doi:10.1080/01411920902989227
Negroponte, N. (1995). Being Digital. New York, NY: Alfred A. Knopf.
Prensky, M. (2001a). Digital natives, digital immigrants part 1. On the Horizon, 9(5), 1-6. doi: 10.1108/10748120110424816
Prensky, M. (2001b). Digital natives, digital immigrants part 2: Do they really think differently? On the Horizon, 9(6), 1-6. doi: 10.1108/10748120110424843
Prensky, M. (2010). Teaching digital natives: Partnering for real learning. Thousand Oaks, CA: Corwin.
Selwyn, N. (2009). The digital native: Myth and reality. Aslib Proceedings: New Information Perspectives, 61(4), 364-379. doi:10.1108/00012530910973776
Tapscott, D. (1998). Growing up digital: The rise of the net generation. New York: McGraw-Hill.
Thornham, H. & McFarlane, A. (2011). Discourses of the digital native. Information, Communication & Society, 14(2), 258-279. doi: 10.1080/1369118X.2010.510199
Office 365 offers are large number of powerful creation, communication and collaboration tools for students and teachers. Many of these tools already exist independently and are already used by many teachers and students. However, Office 365 consolidates all of the essential tools in on online environment so that a classroom learning community can be created and used in the service of learning and teaching by students and teachers.
The Office 365 environment can be overwhelming to new users due to the consolidation of so many tools. It might seem simpler, for example, to just use a dedicated blogging site, or wiki site, or email service, or cloud storage service. But all of these tools, as well as web versions of Microsoft Word, Excel, PowerPoint, OneNote, and Outlook, are available in one place.
A colleague at my board, Neal Larsen, has produced a helpful pamphlet for our teachers who are starting to explore Office 365 this year. Click on the link or image preview below:
(Created by @NealLarsen)
Even with device neutral assignments or web-based creation or collaboration tools, students in #BYOD friendly schools might still be looking for app suggestions to match the particular learning task they are engaged in. There are some incredibly detailed resources available, such as Allan Carrington’s “padagogy” wheel. But, if you are looking for something a little less complicated (and one that includes other platforms such as Android), take a look at this comparison chart, created by my colleague @tina_zita. It contains various app/tool suggestions for students using iOS or Android devices, web-based tools, or Ontario Ministry of Education licensed applications (see OSAPAC). The learning task categories on the chart are:
- Create a digital story
- Organize ideas
- Create an animation
- Capture thinking
- Create a game
Only two of the mobile device apps in the chart below are not free, that is, iMovie and Explain Everything. A free iOS-based option for creating a digital story is Puppet Pals HD (note: the paid version, called “Director’s Pass” allows for your own images to be used rather than just the ones that come with the app). And a free iOS-based option for capturing thinking is Educreations Interactive Whiteboard. Remember, too, that there is a free VoiceThread iOS app.