The rise of the zombie academy, the valuing of higher education in future earning potential terms solely and the attainment culture cultivated in the UK education system are creating a toxic environment for both students and staff.
Concerns around the wellbeing and mental health of the student population are well documented. In the 2017 report ‘Not By Degrees’ (pg34) the IPPR comments on the YouGov survey findings. Study was found to be the primary cause of stress among students, this is coupled with pressure to find a high-class degree as ‘Finding a job after university’ is the second highest cause of stress reported by students (“Not by degrees”, 2017).
In addition, student wellbeing can be seriously compromised if the university is unable to create a caring environment, develop a sense of belonging among students and provide adequate campus-based counselling support (O’keeffe, 2013).
In parallel, there is an increase in childhood Mental ill-health and decrease in child wellbeing. A study published in the journal Psychological Medicine reported a rise in the number of 4 to 24 yrs olds with a longstanding mental health condition from 0.8% in 1995 to 4.8% in 2014 (The Guardian, 2018).
Headline findings from the 2019 Good Childhood report are that contentment amongst 10-15 yr olds in the UK has dipped to an average of 7.89, on a scale of 1-10, the lowest since the report launched in 2009-10. In addition, almost 5% of those surveyed reported scores below 5/10 indicating that they may be unhappy with their lives (Weaver, 2019).
The report also records a siginificant dip to a mean of 7.37 of happiness with school in 2016-17, but there is not significant change to happiness with schoolwork (“The Good Childhood Report 2019”, 2019, pg 13). Findings from The Children’s Society’s Household Survey of 10-17 year olds found that 28% were Quite or Very concerned about obtaining good grades and the future. Slightly lower than the 29% concerned about finding a job, 33% Quite or Very concerned about having enough money. The concerns relating to employment and having enough money were significantly higher amongst 14-17 years olds than 10-13 year olds (“The Good Childhood Report 2019”, 2019, pg 26).
With regard to broader issues, 14 to 17 yr olds were more worried about the economy, Brexit, crime and information sharing online. These areas that had the highest level of Quite or Very worried survey participants across 10-17 yr olds were: Crime 41%, Environemnt 41%, Cyber 37% and Homelessness 32% (“The Good Childhood Report 2019”, 2019, pg 27).
These concerns are not surprising. The Living Standards Audit reports investigates both recent and longer-term trends in UK living standards. Key findings from the 2019 report include an estimated annual growth of -0.3%, weaker than the early 1990s recession) and with regard to disposable income the two-year period 2017-18 and 2018-19 look to have been the worst on record outside of recession.
The report also found that over half of pre-primary school children living with one parent are in poverty and parents living in couples (up to age 35) are more likely to be living in poverty than a single pensioner over the age of 80 (“The Living Standards Audit 2019 • Resolution Foundation”, n.d.).
These issues aren’t limited to the UK. The Unicef ‘Children of the Recession’ report explores the impact of the economic crises on child well-being in rich countries. Between 2008 and 2012 child poverty increased in 23 of the 41 countries listed. Israel had the lowest increase, 0.55%, with Iceland’s increase the highest, 20.40%. However, Greece has the highest child poverty rate, 40.5%, after an increase of 17.50%. In the UK the child poverty rate rose from 24% to 25.6% over the same period. (Innocenti, 2014, pg 10)The report notes that children feel anxious and stressed in response to parental unemployment or income loss (Innocenti, 2014, pg 2).
The 2015 PISA Students’ Well-Being survey found that students who are amongst the 25% most wealthy in their country/economy were more likely to report being “very satisfied” with their lives compared to the 25% least wealthy. It has consistently been found that disadvantaged students perform worse than advantaged students.
However, school related anxiety affects both high and low performing students. The most commonly cited sources of stress for school-age children and adolescents are pressure to achieve higher marks and concerns about receiving poor grades. With regard to Science, on average across OECD countries 63% of low achieving students and 46% of high achieving students reported feeling anxious for a test no matter how well prepared they are (“PISA 2015 Results (Volume III)”, 2017, pg10).
The report found that study and assessment load were unrelated to schoolwork-related anxiety. But, the perceived relationship with teachers was found to have positive or negative impacts on anxiety levels. However, students who are highly motivated to achieve were more likely to feel anxious about a test.
Students who received individual help when they were struggling science were less likely to report anxiety. However, if a student feels that a teacher underrates their abilities, on average across OECD countries 60% are more likely to get very tense when they study and 29% feel more anxious about a test. Furthermore, students in “happy” schools (schools where students’ life satisfaction is above the average in the country) reported much greater support from their teachers than students in “unhappy” schools. This is important as students who have a greater sense of belonging with their school are more likely to perform better academically and be more motivated.
In addition, pedagogy and the design of assessments were also found to be important. Teachers were encouraged to help students identify their strengths and weaknesses, and provide guidance on how to mitigate weaknesses. Regular low-stakes tests, gradually increasing in difficulty can help students demonstrate their skills and build a sense of control were also recommended.
So, relationships and culture within schools are very important for students’ sense of belonging and wellbeing. The generation of students that were the cohorts for these surveys are now undergraduate’s in our Higher Education Institutions.
The increase in the proportion of young adults attending Higher Education Institutions has led to an increasingly diverse student intake (‘Who’s studying in HE?: Personal characteristics | HESA’, n.d.), however this is not always represented in the curricula or in how the curricula are presented to students.
In recent years there has been growing dissatisfaction with what some students describe as ‘pale, male and stale’ curricula. This has resulted in some high profile student campaigns to decolonise the curriculum at a number of leading UK universities including UCL (‘Why is My Curriculum White?’, n.d.) and Cambridge University (https://www.theguardian.com/education/2017/oct/25/cambridge-academics-seek-to-decolonise-english-syllabus), becoming a point of discussion and debate across the sector.
Selecting learning resources and situating learning in a manner that reflects the differing voices, perspectives and experiences of those generating and consuming knowledge are a fundamental part of compassionate pedagogy.
Even if our curricula are representative, how do we ensure an equity of experience for our students? Ableism in academia is endemic and so the concern for equality and equitability is on the increase (Brown and Leigh, 2018). In 2016/17 12% of students were known to have a disability, many of whom may not have a visible disability (“Who’s studying in HE?: Personal characteristics | HESA”, n.d.). Therefore, learning design and design choices made when creating learning resources are also key components of an inclusive, compassionate learning environment. Examples of these choices may include automatically adding closed captions to all videos created by an instructor, avoiding the use of colour to infer meaning, ensuring resources are created in formats that are compatible with institutionally supported accessibility tools or selecting an open textbook as the main course text.
These can both be considered as examples of universal design in education (UDE), where UDE is defined as “the design of educational products and environments to be useable by all people, to the greatest extent possible, without the need for adaptation or specialised design” (Burgstahler, 2015). This requires the acknowledgement and consideration of the diverse characteristics of all eligible students, these may include ability, language, race, ethnicity, culture, gender, sexual orientation and age. Therefore, the application of universal design principles can be considered an act of compassion.
For a course at a HEI, the products and environment would include the curriculum, facilities and technology used in the course. At a macro level this may be choosing teaching strategies, and at the micro, facilitating small group discussions. For example, when using a learning method such as UCL’s ABC method, the products and environments will include considering the variety of learning types selected, the blend of online and offline activity and the assessment load, both formative and summative. The Learning Designer tool enables you to see how much time is spent on tasks and what percentage of directed time is spent on each learning type (“Learning Designer”, n.d.). Additionally, tools such as the
Exclusion Calculator created by the University of Cambridge enables the quantification of accessibility of resources and helps to prioritise improvements.
Learning analytics is an ongoing trend and has been identified as one of the ‘Important Developments in Technology for Higher Education’ for 2018/19 (Becker et al., n.d.). Learning analytics has been defined as ‘the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs’(Siemens and Gasevic, 2012).
Higher Education Institutions store and generate a plethora of data about students and their interactions with the institution’s IT services and systems. Some of this data can be leveraged by educators to inform their practice and tailor student support. For example, the Echo 360 Active Learning Platform system enables students viewing recordings to flag content that they find confusing. This data could then be used by the instructor to inform planning for forthcoming lectures or tutorials. Demographic data could be used to identify students who may need additional support as they may have a specific learning difficulty or be first in family to attend university. It is also possible to identify students who may be over-using resources in an institution’s Virtual Learning Environment, e.g. repeatedly completing the same formative quiz, that may indicate support is required.
This data can be collated for different purposes; automated actions (e.g. email triggers) or as data for humans (e.g. tutors or students themselves) to interpret. An example of automated actions is Newcastle University’s Postgraduate Research Student attendance monitoring process undertaken by the Research Student Support Team (RSST) and the Medical Sciences Graduate School (MSGS). Of the three emails that can be sent to a student, the Level 1 email is an informal automated reminder sent to a student if there has been no recorded and confirmed meetings within 6 weeks (“Attendance Monitoring”, n.d.).
However, this does not mean that actionable insights will necessarily be drawn or that action will take place. Motivation is required at institutional and practitioner level to make meaningful use of the data, returning us back to our notion of compassionate pedagogy and a motivation to criticize institutional and classroom practices for the benefit of students. An added complication are concerns around HEIs’ obligation to act on any data analyses, in particular providing adequate resources to ensure appropriate and effective interventions (Prinsloo and Slade, 2017).
A return to a more compassionate pedagogy and the notion that education can transform what it is possible to do and to be, could dramatically change the culture of HE for all.
Samantha Ahern, Digital Education Innovation and Development Officer (University College London)
Samantha will be presenting a poster at the SMaRteN Conference, on Tuesday 17th December 2019.
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Brown, N. and Leigh, J. (2018), “Ableism in academia: where are the disabled and ill academics?”, Disability & Society, Vol. 33 No. 6, pp. 985–989.
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