Posts Tagged ‘Generation Z’

The idea of ‘digital natives’ emerged at the turn of the century, was popularized by Marc Prensky (2001), and rapidly caught the public imagination, especially the imagination of technology marketers. Its popularity has dwindled a little since then, but is still widely used. Alternative terms include ‘Generation Y’, ‘Millennials’ and the ‘Net Generation’, definitions of which vary slightly from writer to writer. Two examples of the continued currency of the term ‘digital native’ are a 2019 article on the Pearson Global Scale of English website entitled ‘Teaching digital natives to become more human’ and an article in The Pie News (a trade magazine for ‘professionals in international education’), extolling the virtues of online learning for digital natives in times of Covid-19.

Key to understanding ‘digital natives’, according to users of the term, is their fundamental differences from previous generations. They have grown up immersed in technology, have shorter attention spans, and are adept at multitasking. They ‘are no longer the people our educational system was designed to teach’ (Prensky, 2001), so educational systems must change in order to accommodate their needs.

The problem is that ‘digital natives’ are a myth. Prensky’s ideas were not based on any meaningful research: his observations and conclusions, seductive though they might be, were no more than opinions. Kirschner and De Bruyckere (2017) state the research consensus:

There is no such thing as a digital native who is information-skilled simply because (s)he has never known a world that was not digital. […] One of the alleged abilities of students in this generation, the ability to multitask, does not exist and that designing education that assumes the presence of this ability hinders rather than helps learning.

This is neither new (see Bennett et al., 2008) nor contentious. Almost ten years ago, Thomas (2011:3) reported that ‘some researchers have been asked to remove all trace of the term from academic papers submitted to conferences in order to be seriously considered for inclusion’. There are reasons, he added, to consider some uses of the term nothing more than technoevangelism (Thomas, 2011:4). Perhaps someone should tell Pearson and the Pie News? Then, again, perhaps, they wouldn’t care.

The attribution of particular characteristics to ‘digital natives’ / ‘Generation Y’ / ‘Millennials’ is an application of Generation Theory. This can be traced back to a 1928 paper by Karl Mannheim, called ‘Das Problem der Generationen’ which grew in popularity after being translated into English in the 1950s. According to Jauregui et al (2019), the theory was extensively debated in the 1960s and 1970s, but then disappeared from academic study. The theory was not supported by empirical research, was considered to be overly schematised and too culturally-bound, and led inexorably to essentialised and reductive stereotypes.

But Generation Theory gained a new lease of life in the 1990s, following the publication of ‘Generations’ by William Strauss and Neil Howe. The book was so successful that it spawned a slew of other titles leading up to ‘Millennials Rising’ (Howe & Strauss, 2000). This popularity has continued to the present, with fans including Steve Bannon (Kaiser, 2016) who made an ‘apocalyptical and polemical’ documentary film about the 2007 – 2008 financial crisis entitled ‘Generation Zero’. The work of Strauss and Howe has been dismissed as ‘more popular culture than social science’ (Jauregui et al., 2019: 63) and in much harsher terms in two fascinating articles in Jacobin (Hart, 2018) and Aeon (Onion, 2015). The sub-heading of the latter is ‘generational labels are lazy, useless and just plain wrong’. Although dismissed by scholars as pseudo-science, the popularity of such Generation Theory helps explain why Prensky’s paper about ‘digital natives’ fell on such fertile ground. The saying, often falsely attributed to Mark Twain, that we should ‘never let the truth get in the way of a good story’ comes to mind.

But by the end of the first decade of this century, ‘digital natives’ had become problematic in two ways: not only did the term not stand up to close analysis, but it also no longer referred to the generational cohort that pundits and marketers wanted to talk about.

Around January 2018, use of the term ‘Generation Z’ began to soar, and is currently at its highest point ever in the Google Trends graph. As with ‘digital natives’, the precise birth dates of Generation Z vary from writer to writer. After 2001, according to the Cambridge dictionary; slightly earlier according to other sources. The cut-off point is somewhere between the mid and late 2010s. Other terms for this cohort have been proposed, but ‘Generation Z’ is the most popular.

William Strauss died in 2007 and Neil Howe was in his late 60s when ‘Generation Z’ became a thing, so there was space for others to take up the baton. The most successful have probably been Corey Seemiller and Meghan Grace, who, since 2016, have been churning out a book a year devoted to ‘Generation Z’. In the first of these (Seemiller & Grace, 2016), they were clearly keen to avoid some of the criticisms that had been levelled at Strauss and Howe, and they carried out research. This consisted of 1143 responses to a self-reporting questionnaire by students at US institutions of higher education. The survey also collected information about Kolb’s learning styles and multiple intelligences. With refreshing candour, they admit that the sample is not entirely representative of higher education in the US. And, since it only looked at students in higher education, it told us nothing at all about those who weren’t.

In August 2018, Pearson joined the party, bringing out a report entitled ‘Beyond Millennials: The Next Generation of Learners’. Conducted by the Harris Poll, the survey looked at 2,587 US respondents, aged between 14 and 40. The results were weighted for age, gender, race/ethnicity, marital status, household income, and education, so were rather more representative than the Seemiller & Grace research.

In ELT and educational references to ‘Generation Z’, research, of even the very limited kind mentioned above, is rarely cited. When it is, Seemiller and Grace feature prominently (e.g. Mohr & Mohr, 2017). Alternatively, even less reliable sources are used. In an ELT webinar entitled ‘Engaging Generation Z’, for example, information about the characteristics of ‘Generation Z’ learners is taken from an infographic produced by an American office furniture company.

But putting aside quibbles about the reliability of the information, and the fact that it most commonly[1] refers to Americans (who are not, perhaps, the most representative group in global terms), what do the polls tell us?

Despite claims that Generation Z are significantly different from their Millennial predecessors, the general picture that emerges suggests that differences are more a question of degree than substance. These include:

  • A preference for visual / video information over text
  • A variety of bite-sized, entertaining educational experiences
  • Short attention spans and zero tolerance for delay

All of these were identified in 2008 (Williams et al., 2008) as characteristics of the ‘Google Generation’ (a label which usually seems to span Millennials and Generation Z). There is nothing fundamentally different from Prensky’s description of ‘digital natives’. The Pearson report claimed that ‘Generation Z expects experiences both inside and outside the classroom that are more rewarding, more engaging and less time consuming. Technology is no longer a transformative phenomena for this generation, but rather a normal, integral part of life’. However, there is no clear disjuncture or discontinuity between Generation Z and Millennials, any more than there was between ‘digital natives’ and previous generations (Selwyn, 2009: 375). What has really changed is that the technology has moved on (e.g. YouTube was founded in 2005 and the first iPhone was released in 2007).

TESOL TurkeyThe discourse surrounding ‘Generation Z’ is now steadily finding its way into the world of English language teaching. The 2nd TESOL Turkey International ELT Conference took place last November with ‘Teaching Generation Z: Passing on the baton from K12 to University’ as its theme. A further gloss explained that the theme was ‘in reference to the new digital generation of learners with outstanding multitasking skills; learners who can process and absorb information within mere seconds and yet possess the shortest attention span ever’.


A few more examples … Cambridge University Press ran a webinar ELT webinar entitled ‘Engaging Generation Z’ and Macmillan Education has a coursebook series called ‘Exercising English for Generation Z’. EBC, a TEFL training provider, ran a blog post in November last year, ‘Teaching English to generation Z students’. And EFL Magazine had an article, ‘Critical Thinking – The Key Competence For The Z Generation’, in February of this year.

The pedagogical advice that results from this interest in Generation Z seems to boil down to: ‘Accept the digital desires of the learners, use lots of video (i.e. use more technology in the classroom) and encourage multi-tasking’.

No one, I suspect, would suggest that teachers should not make use of topics and technologies that appeal to their learners. But recommendations to change approaches to language teaching, ‘based solely on the supposed demands and needs of a new generation of digital natives must be treated with caution’ (Bennett et al., 2008: 782). It is far from clear that generational differences (even if they really exist) are important enough ‘to be considered during the design of instruction or the use of different educational technologies – at this time, the weight of the evidence is negative’ (Reeves, 2008: 21).

Perhaps, it would be more useful to turn away from surveys of attitudes and towards more fact-based research. Studies in both the US and the UK have found that myopia and other problems with the eyes is rising fast among the Generation Z cohort, and that there is a link with increased screen time, especially with handheld devices. At the same time, Generation Zers are much more likely than their predecessors to be diagnosed with anxiety disorder and depression. While the connection between technology use and mental health is far from clear, it is possible that  ‘the rise of the smartphone and social media have at least something to do with [the rise in mental health issues]’ (Twenge, 2017).

Should we be using more technology in class because learners say they want or need it? If we follow that logic, perhaps we should also be encouraging the consumption of fast food, energy drinks and Ritalin before and after lessons?

[1] Studies have been carried out in other geographical settings, including Europe (e.g. Triple-a-Team AG, 2016) and China (Tang, 2019).


Bennett S., Maton K., & Kervin, L. (2008). The ‘digital natives’ debate: a critical review of the evidence. British Jmournal of Educational Technology, 39 (5):pp. 775-786.

Hart, A. (2018). Against Generational Politics. Jacobin, 28 February 2018.

Howe, N. & Strauss, W. (2000). Millennials Rising: The Next Great Generation. New York, NY: Vintage Books.

Jauregui, J., Watsjold, B., Welsh, L., Ilgen, J. S. & Robins, L. (2019). Generational “othering”: The myth of the Millennial learner. Medical Education,54: pp.60–65.

Kaiser, D. (2016). Donald Trump, Stephen Bannon and the Coming Crisis in American National Life. Time, 18 November 2016.

Kirschner, P.A. & De Bruyckere P. (2017). The myths of the digital native and the multitasker. Teaching and Teacher Education, 67: pp. 135-142.

Mohr, K. A. J. & Mohr, E. S. (2017). Understanding Generation Z Students to Promote a Contemporary Learning Environment. Journal on Empowering Teacher Excellence, 1 (1), Article 9 DOI:

Onion, R. (2015). Against generations. Aeon, 19 May, 2015.

Pearson (2018). Beyond Millennials: The Next Generation of Learners.

Prensky, M. (2001). Digital natives, digital immigrants. On the Horizon, 9: pp. 1- 6

Reeves, T.C. (2008). Do Generational Differences Matter in Instructional Design? Athens, GA: University of Georgia, Department of Educational Psychology and Instructional Technology

Seemiller, C. & and Grace, M. (2016). Generation Z Goes to College. San Francisco: Jossey-Bass

Selwyn, N. (2009). The digital native-myth and reality. Perspectives, 61: pp. 364-379

Strauss W. & Howe, N. (1991). Generations: The History of America’s Future, 1584 to 2069. New York, New York: HarperCollins.

Tang F. (2019). A critical review of research on the work-related attitudes of Generation Z in China. Social Psychology and Society, 10 (2): pp. 19—28. Available at:

Thomas, M. (2011). Technology, Education, and the Discourse of the Digital Native: Between Evangelists and Dissenters. In Thomas, M. (ed). (2011). Deconstructing Digital Natives: Young people, technology and the new literacies. London: Routledge. pp. 1- 13)

Triple-a-Team AG. (2016). Generation Z Metastudie über die kommende Generation. Biglen, Switzerland. Available at:

Twenge, J. M. (2017). iGen. New York: Atria Books

Williams, P., Rowlands, I. & Fieldhouse, M. (2008). The ‘Google Generation’ – myths and realities about young people’s digital information behaviour. In Nicholas, D. & Rowlands, I. (eds.) (2008). Digital Consumers. London: Facet Publishers.

Back in the middle of the last century, the first interactive machines for language teaching appeared. Previously, there had been phonograph discs and wire recorders (Ornstein, 1968: 401), but these had never really taken off. This time, things were different. Buoyed by a belief in the power of technology, along with the need (following the Soviet Union’s successful Sputnik programme) to demonstrate the pre-eminence of the United States’ technological expertise, the interactive teaching machines that were used in programmed instruction promised to revolutionize language learning (Valdman, 1968: 1). From coast to coast, ‘tremors of excitement ran through professional journals and conferences and department meetings’ (Kennedy, 1967: 871). The new technology was driven by hard science, supported and promoted by the one of the most well-known and respected psychologists and public intellectuals of the day (Skinner, 1961).

In classrooms, the machines acted as powerfully effective triggers in generating situational interest (Hidi & Renninger, 2006). Even more exciting than the mechanical teaching machines were the computers that were appearing on the scene. ‘Lick’ Licklider, a pioneer in interactive computing at the Advanced Research Projects Agency in Arlington, Virginia, developed an automated drill routine for learning German by hooking up a computer, two typewriters, an oscilloscope and a light pen (Noble, 1991: 124). Students loved it, and some would ‘go on and on, learning German words until they were forced by scheduling to cease their efforts’. Researchers called the seductive nature of the technology ‘stimulus trapping’, and Licklider hoped that ‘before [the student] gets out from under the control of the computer’s incentives, [they] will learn enough German words’ (Noble, 1991: 125).

With many of the developed economies of the world facing a critical shortage of teachers, ‘an urgent pedagogical emergency’ (Hof, 2018), the new approach was considered to be extremely efficient and could equalise opportunity in schools across the country. It was ‘here to stay: [it] appears destined to make progress that could well go beyond the fondest dreams of its originators […] an entire industry is just coming into being and significant sales and profits should not be too long in coming’ (Kozlowski, 1961: 47).

Unfortunately, however, researchers and entrepreneurs had massively underestimated the significance of novelty effects. The triggered situational interest of the machines did not lead to intrinsic individual motivation. Students quickly tired of, and eventually came to dislike, programmed instruction and the machines that delivered it (McDonald et al.: 2005: 89). What’s more, the machines were expensive and ‘research studies conducted on its effectiveness showed that the differences in achievement did not constantly or substantially favour programmed instruction over conventional instruction (Saettler, 2004: 303). Newer technologies, with better ‘stimulus trapping’, were appearing. Programmed instruction lost its backing and disappeared, leaving as traces only its interest in clearly defined learning objectives, the measurement of learning outcomes and a concern with the efficiency of learning approaches.

Hot on the heels of programmed instruction came the language laboratory. Futuristic in appearance, not entirely unlike the deck of the starship USS Enterprise which launched at around the same time, language labs captured the public imagination and promised to explore the final frontiers of language learning. As with the earlier teaching machines, students were initially enthusiastic. Even today, when language labs are introduced into contexts where they may be perceived as new technology, they can lead to high levels of initial motivation (e.g. Ramganesh & Janaki, 2017).

Given the huge investments into these labs, it’s unfortunate that initial interest waned fast. By 1969, many of these rooms had turned into ‘“electronic graveyards,” sitting empty and unused, or perhaps somewhat glorified study halls to which students grudgingly repair to don headphones, turn down the volume, and prepare the next period’s history or English lesson, unmolested by any member of the foreign language faculty’ (Turner, 1969: 1, quoted in Roby, 2003: 527). ‘Many second language students shudder[ed] at the thought of entering into the bowels of the “language laboratory” to practice and perfect the acoustical aerobics of proper pronunciation skills. Visions of sterile white-walled, windowless rooms, filled with endless bolted-down rows of claustrophobic metal carrels, and overseen by a humorless, lab director, evoke[d] fear in the hearts of even the most stout-hearted prospective second-language learners (Wiley, 1990: 44).

By the turn of this century, language labs had mostly gone, consigned to oblivion by the appearance of yet newer technology: the internet, laptops and smartphones. Education had been on the brink of being transformed through new learning technologies for decades (Laurillard, 2008: 1), but this time it really was different. It wasn’t just one technology that had appeared, but a whole slew of them: ‘artificial intelligence, learning analytics, predictive analytics, adaptive learning software, school management software, learning management systems (LMS), school clouds. No school was without these and other technologies branded as ‘superintelligent’ by the late 2020s’ (Macgilchrist et al., 2019). The hardware, especially phones, was ubiquitous and, therefore, free. Unlike teaching machines and language laboratories, students were used to using the technology and expected to use their devices in their studies.

A barrage of publicity, mostly paid for by the industry, surrounded the new technologies. These would ‘meet the demands of Generation Z’, the new generation of students, now cast as consumers, who ‘were accustomed to personalizing everything’.  AR, VR, interactive whiteboards, digital projectors and so on made it easier to ‘create engaging, interactive experiences’. The ‘New Age’ technologies made learning fun and easy,  ‘bringing enthusiasm among the students, improving student engagement, enriching the teaching process, and bringing liveliness in the classroom’. On top of that, they allowed huge amounts of data to be captured and sold, whilst tracking progress and attendance. In any case, resistance to digital technology, said more than one language teaching expert, was pointless (Styring, 2015).slide

At the same time, technology companies increasingly took on ‘central roles as advisors to national governments and local districts on educational futures’ and public educational institutions came to be ‘regarded by many as dispensable or even harmful’ (Macgilchrist et al., 2019).

But, as it turned out, the students of Generation Z were not as uniformly enthusiastic about the new technology as had been assumed, and resistance to digital, personalized delivery in education was not long in coming. In November 2018, high school students at Brooklyn’s Secondary School for Journalism staged a walkout in protest at their school’s use of Summit Learning, a web-based platform promoting personalized learning developed by Facebook. They complained that the platform resulted in coursework requiring students to spend much of their day in front of a computer screen, that made it easy to cheat by looking up answers online, and that some of their teachers didn’t have the proper training for the curriculum (Leskin, 2018). Besides, their school was in a deplorable state of disrepair, especially the toilets. There were similar protests in Kansas, where students staged sit-ins, supported by their parents, one of whom complained that ‘we’re allowing the computers to teach and the kids all looked like zombies’ before pulling his son out of the school (Bowles, 2019). In Pennsylvania and Connecticut, some schools stopped using Summit Learning altogether, following protests.

But the resistance did not last. Protesters were accused of being nostalgic conservatives and educationalists kept largely quiet, fearful of losing their funding from the Chan Zuckerberg Initiative (Facebook) and other philanthro-capitalists. The provision of training in grit, growth mindset, positive psychology and mindfulness (also promoted by the technology companies) was ramped up, and eventually the disaffected students became more quiescent. Before long, the data-intensive, personalized approach, relying on the tools, services and data storage of particular platforms had become ‘baked in’ to educational systems around the world (Moore, 2018: 211). There was no going back (except for small numbers of ultra-privileged students in a few private institutions).

By the middle of the century (2155), most students, of all ages, studied with interactive screens in the comfort of their homes. Algorithmically-driven content, with personalized, adaptive tests had become the norm, but the technology occasionally went wrong, leading to some frustration. One day, two young children discovered a book in their attic. Made of paper with yellow, crinkly pages, where ‘the words stood still instead of moving the way they were supposed to’. The book recounted the experience of schools in the distant past, where ‘all the kids from the neighbourhood came’, sitting in the same room with a human teacher, studying the same things ‘so they could help one another on the homework and talk about it’. Margie, the younger of the children at 11 years old, was engrossed in the book when she received a nudge from her personalized learning platform to return to her studies. But Margie was reluctant to go back to her fractions. She ‘was thinking about how the kids must have loved it in the old days. She was thinking about the fun they had’ (Asimov, 1951).


Asimov, I. 1951. The Fun They Had. Accessed September 20, 2019.

Bowles, N. 2019. ‘Silicon Valley Came to Kansas Schools. That Started a Rebellion’ The New York Times, April 21. Accessed September 20, 2019.

Hidi, S. & Renninger, K.A. 2006. ‘The Four-Phase Model of Interest Development’ Educational Psychologist, 41 (2), 111 – 127

Hof, B. 2018. ‘From Harvard via Moscow to West Berlin: educational technology, programmed instruction and the commercialisation of learning after 1957’ History of Education, 47 (4): 445-465

Kennedy, R.H. 1967. ‘Before using Programmed Instruction’ The English Journal, 56 (6), 871 – 873

Kozlowski, T. 1961. ‘Programmed Teaching’ Financial Analysts Journal, 17 (6): 47 – 54

Laurillard, D. 2008. Digital Technologies and their Role in Achieving our Ambitions for Education. London: Institute for Education.

Leskin, P. 2018. ‘Students in Brooklyn protest their school’s use of a Zuckerberg-backed online curriculum that Facebook engineers helped build’ Business Insider, 12.11.18 Accessed 20 September 2019.

McDonald, J. K., Yanchar, S. C. & Osguthorpe, R.T. 2005. ‘Learning from Programmed Instruction: Examining Implications for Modern Instructional Technology’ Educational Technology Research and Development, 53 (2): 84 – 98

Macgilchrist, F., Allert, H. & Bruch, A. 2019. ‚Students and society in the 2020s. Three future ‘histories’ of education and technology’. Learning, Media and Technology, )

Moore, M. 2018. Democracy Hacked. London: Oneworld

Noble, D. D. 1991. The Classroom Arsenal. London: The Falmer Press

Ornstein, J. 1968. ‘Programmed Instruction and Educational Technology in the Language Field: Boon or Failure?’ The Modern Language Journal, 52 (7), 401 – 410

Ramganesh, E. & Janaki, S. 2017. ‘Attitude of College Teachers towards the Utilization of Language Laboratories for Learning English’ Asian Journal of Social Science Studies; Vol. 2 (1): 103 – 109

Roby, W.B. 2003. ‘Technology in the service of foreign language teaching: The case of the language laboratory’ In D. Jonassen (ed.), Handbook of Research on Educational Communications and Technology, 2nd ed.: 523 – 541. Mahwah, NJ.: Lawrence Erlbaum Associates

Saettler, P. 2004. The Evolution of American Educational Technology. Greenwich, Conn.: Information Age Publishing

Skinner, B. F. 1961. ‘Teaching Machines’ Scientific American, 205(5), 90-107

Styring, J. 2015. Engaging Generation Z. Cambridge English webinar 2015

Valdman, A. 1968. ‘Programmed Instruction versus Guided Learning in Foreign Language Acquisition’ Die Unterrichtspraxis / Teaching German, 1 (2), 1 – 14.

Wiley, P. D. 1990. ‘Language labs for 1990: User-friendly, expandable and affordable’. Media & Methods, 27(1), 44–47)


Jenny Holzer, Protect me from what I want