Young adolescence and D-education: Disillusioned, disengaged, disenfranchised, disadvantaged.

The wisdom of Pooh

Not every student has a great time at school. School can be challenging and confronting in a myriad of ways. Pooh, Winnie the, captures the driving yet poignant sentiment for disengagement from school well: “I always get to where I’m going by walking away from where I have been.” (A.A. Milne, 1850). There is a point, in a young person’s development at around 14 or 15 years where they start to hunger for independence prompting some to disengage. They see themselves moving to independence somewhat faster or differently than the schooling system allows or recognizes. School can seem out of kilter with their desires, family identity, or sense of self. Disillusioned, some make the choice, like Pooh, to walk away from school rather than walking toward anything in particular. Evidence shows that this is a poor decision with long-term negative impact.


Sadly, those who lack the personal and social supports to stay the course at school or on a career track, those that can’t quite muddle through, jump on what I call the de-education path; disillusioned, disengaged, disenfranchised, disadvantaged, and perhaps even delinquent. This is the road to nowhere fueling long-term social, financial, mental and physical health disadvantage. This article tracks some of the trends for school disengagement in Australian publicly available data. This uncovers potent evidence for the urgent need to focus specifically on the retention of students aged 14-15 years. Such focused attention and perhaps intervention could be the necessary long-term positive force against social disadvantage for these youth and their community. This could effectively break the cycle of disadvantage.

Profile of 14-15 year old youth

At the age of 14-15 an adolescent is driving toward adulthood, breaking ties with childish things, becoming more independent of parents, and establishing an identity for themselves as an individual. Along with awakening sexuality, physical morphological change, unstable hormonal patterns, neurological reconstruction, and social re-orientation toward peers, this period of growth can feature firm rejection of school. Neuronal reconstruction is at a peak at this age, heightening the risk for disengagement from school or career track opportunities.

A time of significant neural change

Emerging MRI technologies have enabled imaging and tracking of neural change across the life course. Of interest has been the discovery of neuronal connectivity proliferation followed by streamlining and pruning of connections across the period from about 12 or 13 through to 19 years of age. Associated with these structural changes is the important implications for social emotional functioning, cognition, motivation and learning (Immordino-Yang, Darling-Hammond, & Krone, 2019). During this period the adolescent brain has been described as “under construction”. Particular behaviors manifest as a result of changes to specific areas of the brain (Blakemore, 2010). There is evidence that childlike behaviors are destabilized without commensurate alignment with adult behavior. Impulsivity, self-consciousness, risk-taking are just some of the demonstrated correlates during this period of significant brain structural change and development (e.g., Andrews-Hanna et al., 2011; Somerville et al., 2010).

Neural correlates with change in adolescent behaviour

Established research correlates neural change to adolescent impulsivity, risk-taking and poor planning behaviors. Key quote: “Adolescence is a developmental period that entails substantial changes in affect and incentive-seeking behavior relative to both childhood and adulthood, including a heightened propensity to engage in risky behaviors and experience persistent negative and labile mood states.” (Andrews-Hanna, et al., 2011).  Adjustments drive this time of change to the interactions between the amygdala, uncinated fasciculus, ventral striatum, and pre-frontal cortex at this age.

Amygdala: controls emotional responses and is under development during adolescents impacting on their ability to respond affectively and consistently to stimuli. This is correlated with the rapid escalation of an emotive response to situations during mid-adolescence. Further, during mid-adolescence the amygdala led the response to stimuli moves from the more childlike fear reaction to one that is governed by reference to imperfect connections with the pre-frontal cortex. This tends to result in suppression of fear and aversive reaction to stimuli and can underpin a propensity for impulsive risk-taking without regard for aversive consequences.

Uncinate fasciculus: There is evidence that uncinate fasciculus development facilitates the connections between the amygdala and the pre-frontal cortex and may have a moderation effect that begins at early adolescence. The research suggests the existence of sensitive periods for intervention to facilitate the development of the moderating influence of the connection.

Ventral striatum: is responsible for decision making and reward-related behavior. Instability of the ventral striatum during adolescence makes young people particularly vulnerable to environmental stress exposure. Of particular relevance is the activation of the ventral striatum to environmental rewards, such as monetary gain or reputation.

Pre-frontal cortex: This part of the brain is connected to the conception of self and is involved in the planning of behavior associated with this. During adolescence changes bring a greater focus on the self, resulting in heightened self-consciousness, and susceptibility to peer influence.

A time for impulsivity and risk-taking

Impulsivity and risk-taking are developmentally aligned and particularly relevant to mid-adolescents aged 14-15 years. Executive function, self-regulation and metacognition correlate with developmental cognitive changes and are challenged and destabilized at this age (Carroll et al, 2007, 2009).  This is a period of heightened risk for negative risk taking and delinquency, leading to adverse health, social and educational consequences (Carroll et al., 2007, 2009). Research indicates that family plays an essential role in the establishment of academically related self-regulation at the age of 15 (Effeney, Carroll, & Bahr, 2013a; 2013b). Where there is social, educational or economic disadvantage in the family circle, the capacity for deterring impulsive and negative risk taking behaviour is diminished, reinforcing the cycle of disadvantage.

A critical time for Engagement

Engagement at this age is crucial to defeat the risk for long term disadvantage. Engagement depends upon a sense of directed agency to commit to specific activities and community. A sense of school belonging and social connectedness enhances student engagement (Carroll et al, 2017). In contrast, a mismatch between an individual’s interests and contextual demands or a lack of necessary support and resources can undermine a sense of agency and thereby prompt disengagement. It would appear then, that research into developmental change for young people aged 14-15 years might predict a peak in evidence of disengagement from school for youth at this age.


The aim of this paper is to profile youth disengagement using publicly available data published by the Queensland Department of Education for Queensland schools.

Research Question

The fundamental research question for this analysis is:

What can be understood from a review of age-related school disengagement indices for adolescents?


The Queensland Department of Education publicly provides detail of disciplinary incident rates such as suspensions and expulsions, attendance rates, Socio-educational status, and NAPLAN (National Assessment Program for Literacy and Numeracy)achievement. This data is aligned to schools and school districts and is available on the Departmental website and/or the Federal Government website: MySchool. A review and consolidation of this data and mapping against age provides insight to the existence of any critical age associations for school disengagement. Please note, in Queensland a year 8-9 student is aged 14-15 years.

Findings for Case study: Queensland

Figure 1 depicts the disengagement profile by age as published by the Department of Education (Queensland) in their report of disciplinary incidents in 2018 by year level. There is a clear peak for suspensions and expulsions for students aged 14-15/year 8-9. Cancellation of enrollment is only relevant for post-compulsory schooling and so only shows an effect in senior school years.

Figure 1: Year level profile for disciplinary incidents attracting expulsion, suspension, cancellation by year level 2018

 Disengagement aligns with locations and regions, that have been determined as being of low socio-educational status. Socio-educational status as rated by the ICSEA (Index of Community Socio-Educational Advantage) reflects the income and highest educational attainment of parents. Table 1 shows that the most prevalent regions for disengagement are the North Coast and South East. The next, Table 2, shows that these regions have lower ICSEA scores. Where schools have greater adolescent disengagement, there is an alignment between low ICSEA, low academic achievement as suggested by NAPLAN scores and poor attendance.

Table 1: Disciplinary incident count by region

Total Incident CountSDA Description
RegionShort Suspension (1-10 days)Long Suspension (11-20 days)ExclusionCancellation
Central Queensland  7 749   192   131   143
Darling Downs South West  7 280   275   105   121
Far North Queensland  6 145   300   89   122
Metropolitan  15 606   631   455   192
North Coast  18 140   590   249   238
North Queensland  6 583   337   162   66
South East  18 124   861   580   196

Table 2: Comparison of worst-case vs best case schools for dimensions of NAPLAN, ICSEA, and attendance with disengagement.

regionincidentsNAPLAN cp Nat Average% bottom quartile ICSEAAttendance (% attending at least 90% of the time) Average =31.4%
WORST 10 schools with the most number of suspensions etc. (current)
Yeppoon State High SchoolCentral Qld981Well below46%50%
Ipswich State High SchoolMetropolitan975Below53%44%
Redbank Plains State High SchoolMetropolitan770Below60%60%
Bremer State High SchoolMetropolitan741Below47%54%
Bundamba State Secondary CollegeMetropolitan725Well below60%40%
Marsden State High SchoolSouth East707Below52%59%
Mabel Park State High SchoolSouth East691Well below67%55%
Urangan State High SchoolNorth Coast669Close to43%51%
Caboolture State High SchoolNorth Coast626Well below44%55%
Dakabin State High SchoolNorth Coast608Well below49%45%
averages   46%51%
BEST 10 schools with fewest suspensions (current)
Longreach State High SchoolCentral Qld54well above31%61%
Holland Park State High SchoolMetropolitan44close to16%64%
Capella State High SchoolCentral Qld42close to57%50%
Miles State High SchoolDarling Downs South West40above41%69%
Malanda State High SchoolFar North Qld28above34%60%
Clermont State High SchoolCentral Qld26well above43%61%
Queensland Academy for Creative IndustriesMetropolitan133%79%
Monto State High SchoolCentral Qld9above42%81%
Milpera State High SchoolMetropolitan458%83%
Queensland Academy for Science Mathematics and TechnologyMetropolitan4well above0%97%
averages 33%71%

Figure 2 further depicts the relationship between with low ICSEA and poor attendance. So we have seen that disengagement concentrates at the 14-15 year age group, and that it is more pronounced where there is socio educational education disadvantage which appears to be associated with poor attendance, and poor basic skills for these students.

Figure 2: Comparison between worst and best schools with respect to discipline incidents rates.

This finding is supported by the literature,for example Mills et al predict that disadvantage is more prevalent where adolescents are disengaging with school, that is where there are lower attendance rates and highest punitive discipline profiles and where ICSEA is low (Mills et al, 2018).

A cycle of disadvantage

We know that young people of the age between 14-15 are undergoing cognitive, emotional, physical and social changes that heighten their impusivity, risk taking, and their need to build an identity. At this time, their self regulation is challenged and this is better managed when family are on hand to help them and support them to stay the course. We also know that disengaging at this time is linked to long term disadvantage, the kind of disadvantage exhibited by the community and supports surrounding the disengaging youth, and so the likely disengagement of the parents when they were at the same age sets the scene for generational disadvantage. The Queensland data supports this, and the cycle is depicted at Figure 3.

Figure 3 The cycle of disadvantage

As shown, we start with the socio-educational status of the youth’s parents. As the challenges of adolescence impact on the youth’s behavior there is an increasing risk of disengagement from school. They become more impulsive, rebellious, and seekers of risk as they prioritize notoriety for their growing independent identity. At this point the social, cognitive, physical and hormonal changes are destabilizing their ability to self-regulate their academic pursuits, and are upsetting their perception of school as a key determinant of their future. In this context, their parents, lacking educational and financial capital may not be able to assist with academic endeavors, and while they may be supportive, may not be able to effectively advise their child or provide a model to sustain engagement with school. At this point the youth, having not been prevented from disengaging elects behaviors that distance them from school. The cycle of disadvantage is reinforced through the d-education steps.

The adolescent becomes disillusioned with school, they may not be succeeding academically, or they may see little direct connection between their personal goals for identity and social relationships and the opportunities provided by their school context. They become disengaged, and as such become increasingly separated from the positive side of schooling as they experience punitive responses to their disengaging behaviours. They are disenfranchised in the regular school setting and so the long-term alienation positions them as disadvantaged, much like their parents, and so the cycle of disadvantage is reiterated. They are de-educated.


De-education in this way is a staged anti-growth model with particular impact at the ages of 14-15 years. Reflection on the research question stated at the outset: What can be understood from a review of age-related school disengagement indices for adolescents? This review has identified that there is a critical age span at about 14-15 years where disengagement from school is prominent, and that this disengagement is exacerbated by poor socio-educational family and community contexts. Therefore, if we can prepare families for the expected adolescent changes and build their capacity to encourage and support youth through this period it may be possible to avert disengagement and interrupt the cycle of disadvantage.

 Pooh’s reflections

If we return to the wisdom of Pooh, he makes an important observation: “While pounding on the piano keys may produce noise, removing them doesn’t exactly further the creation of music.” (Tao of Pooh). That is, if we simply remove disruptive students, or simply allow them to disengage we might be making a calmer learning context for those that remain, but we would most definitely not be providing the type of service for growth in disadvantaged communities.

Relevant references

Andrews-Hanna, J. R., Seghete, K. L. M., Claus, E. D., Burgess, G. C., Ruzic, L., & Banich, M. T. (2011). Cognitive control in adolescence: neural underpinnings and relation to self-report behaviors. PloS one, 6(6).

Blakemore, S. (2010). The developing social brain: Implications for education. Neuron, 65, 744-747.

Blakemore, S. J., & Choudhury, S. (2006). Development of the adolescent brain: implications for executive function and social cognition. Journal of Child Psychology and Psychiatry, 47(3‐4), 296-312.

Bower, J., & Carroll, A. (2015). Benefits of getting hooked on sports or the arts:  Examining the connectedness of youth who participate in sport and creative arts activities. International Journal of Child and Adolescent Health, 8 (2), 169-178. DOI: 10.1016/j.ijer.2015.02.004

Bower, J., & Carroll, A. (2015). Facts about students at risk of delinquency. In Adrian Ashman (Ed.), Education for inclusion and diversity 5th ed. (pp. 365-366) Pearson: Melbourne, Victoria, Australia.

Bower, J., Carroll, A., & Ashman, A. (2012). Adolescent perspectives on schooling experiences: The interplay of risk and protective factors within their lives. International Journal of Educational Research, 53, 9-21. DOI: 10.1016/j.ijer.2011.12.003

Bower, J., van Kraayenoord, C., & Carroll, A. (2015).  Building social connectedness in schools: Australian teachers’ perspectives. International Journal of Educational Research, 70, 101-109. DOI:10.1016/j.ijer.2015.02.004

Braams, B. R., van Duijvenvoorde, A. C., Peper, J. S., & Crone, E. A. (2015). Longitudinal changes in adolescent risk-taking: a comprehensive study of neural responses to rewards, pubertal development, and risk-taking behavior. Journal of Neuroscience, 35(18), 7226-7238.

Carroll, A., Bower, J., & Muspratt, S. (2017). The conceptualization and construction of the Self in a Social Context – Social Connectedness Scale: A multidimensional scale for high school students. International Journal of Educational Research, 81, 97-107. DOI 10.1016/j.ijer.2016.12.001.

Carroll, A., Bower, J., Hemingway, F., & Ashman, A. (2007). Mindfields: A self-regulatory intervention for young people at risk who want to change their lives. In N. Bahr & D. Pendergast (Eds.), The millennial adolescent (pp. 59-64). Camberwell, Victoria: ACER Press.

Carroll, A., Houghton, S., Durkin, K., & Hattie, J. (2009). Adolescent Reputations and Risk: Developmental Trajectories to Delinquency. Springer. ISBN 978-0-387-79987-2.

Effeney, G., Carroll, A., & Bahr, N. (2013a). Self-Regulated Learning: Key strategies and their sources in a sample of adolescent males. Australian Journal of Educational & Developmental Psychology, 13.     

Effeney, G., Carroll, A., & Bahr, N. (2013b). Self-regulated learning and executive function: exploring the relationships in a sample of adolescent males. Educational psychology, 33(7), 773-796.

Giedd, J. N. (2004). Structural magnetic resonance imaging of the adolescent brain. Annals of the New York Academy of Sciences, 1021(1), 77-85.      

Giedd, J. N. (2004). Structural magnetic resonance imaging of the adolescent brain. Annals of the New York Academy of Sciences, 1021(1), 77-85.      

Gutiérrez-García, R. A., Benjet, C., Borges, G., Ríos, E. M., & Medina-Mora, M. E. (2017). NEET adolescents grown up: eight-year longitudinal follow-up of education, employment and mental health from adolescence to early adulthood in Mexico City. European child & adolescent psychiatry, 26(12), 1459-1469.

Henry, K. L., Knight, K. E., & Thornberry, T. P. (2012). School disengagement as a predictor of dropout, delinquency, and problem substance use during adolescence and early adulthood. Journal of youth and adolescence, 41(2), 156-166.

Immordino-Yang, M. H., Darling-Hammond, L., & Krone, C. R. (2019). Nurturing nature: How brain development is inherently social and emotional, and what this means for education. Educational Psychologist, 54(3), 185-204.

Immordino-Yang, M. H., Darling-Hammond, L., & Krone, C. R. (2019). Nurturing nature: How brain development is inherently social and emotional, and what this means for education. Educational Psychologist, 54(3), 185-204.

Mills, M., Howell, A., Kubler, M., Tomaszewski, T., Lynch, D., Phillips, L., Carroll, A., Dungan, J., Hellens, A., & Sheppard, K. (2018).  Making every day count: Effective strategies to improve student attendance in Queensland state schools. Final Report to Queensland Department of Education on student attendance strategies. Brisbane, Queensland: The University of Queensland.

Pfeifer, J. H., Masten, C. L., Moore III, W. E., Oswald, T. M., Mazziotta, J. C., Iacoboni, M., & Dapretto, M. (2011). Entering adolescence: resistance to peer influence, risky behavior, and neural changes in emotion reactivity. Neuron, 69(5), 1029-1036.

Schreuders, E., Braams, B. R., Blankenstein, N. E., Peper, J. S., Güroğlu, B., & Crone, E. A. (2018). Contributions of reward sensitivity to ventral striatum activity across adolescence and early adulthood. Child Development, 89(3), 797-810.

Sebastian, C., Burnett, S., & Blakemore, S. J. (2008). Development of the self-concept during adolescence. Trends in cognitive sciences, 12(11), 441-446.

Somerville, L. H., Jones, R. M., & Casey, B. J. (2010). A time of change: behavioral and neural correlates of adolescent sensitivity to appetitive and aversive environmental cues. Brain and cognition, 72(1), p. 124-133.

Swartz, J. R., Carrasco, M., Wiggins, J. L., Thomason, M. E., & Monk, C. S. (2014). Age-related changes in the structure and function of pre-frontal cortex–amygdala circuitry in children and adolescents: A multi-modal imaging approach. Neuroimage, 86, 212-220.

Tottenham, N., & Galván, A. (2016). Stress and the adolescent brain: Amygdala-prefrontal cortex circuitry and ventral striatum as developmental targets. Neuroscience & Biobehavioral Reviews, 70, 217-227.

Weinberger, D. R., Elvevåg, B., & Giedd, J. N. (2005). The adolescent brain. Washington, DC: National Campaign to Prevent Teen Pregnancy.     Weinberger, D. R., Elvevåg, B., & Giedd, J. N. (2005). The adolescent brain. Washington, DC: National Campaign to Prevent Teen Pregnancy.    

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