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Ideas and reflections from UCL's Digital Education team


Archive for the 'Students' Category

Learning Analytics as a tool for supporting student wellbeing – Identifying student mental ill-health

By Samantha Ahern, on 20 November 2017

Research has shown that students who are distressed and at risk from mental ill-health will often exhibit one or more of the following indicators concurrently: academic struggles and failures, excessive absences from classes and obligations, excessive substance use, loneliness and isolation, social and interpersonal difficulties with others on campus, changes in self-care and lack of self-care, extreme risky behaviours, inability to tolerate frustration and normal stressors in college, inability to regulate emotions, hopelessness and despair(Anderson, 2015).

Gemmill and Peterson(Gemmill and Peterson, 2006) have found that internet communication may have the same buffering effects of stressful life circumstances in the same way as non-internet communication by increasing measures of social support and perceived social support.

This corresponds to findings by Gordon et al. (Gordon et al., 2007) who investigated types of student internet usage (meeting people, information seeking, distraction, coping and email) and four indicators of well-being: depression, social anxiety, loneliness and family cohesion.

Their findings suggest that it is the type of internet usage, more so than the frequency of use that relates to depression, social anxiety and social cohesion. Using the internet for coping purposes was significantly associated with lower levels of family cohesion and higher levels of depression and social anxiety. Whereas, information seeking and email were positively associated with family cohesion.

Research into predicting depression with social media(“Predicting Depression via Social Media – 6351”, n.d.), in this instance Twitter, found that social media contains useful signals for characterising the onset of depression in individuals, as measured through decrease in social activity, raised negative affect, highly clustered ego networks, heightened relational and medicinal concerns, and greater expression of religious involvement. It is noted that in order to identify changes in some behaviours, it was important to know the normal behaviours of the user e.g. an indicator of depression is a tendency to be more active at night. To be able to identify if there has been a change in activity the authors defined the normalised difference in number of postings made between the night window (9pm and 6am) and day window to be the “insomniac index” on a given day.

In summary, these studies show that identifying behavioural changes are key to identifying student mental ill-health, this therefore implies that an understanding is needed of normative behaviours of students.


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Learning Analytics as a tool for supporting student wellbeing – The role of HE Institutions

By Samantha Ahern, on 20 November 2017

Byrd and Mckinney (Byrd and Mckinney, 2012) found that the combined effects of both individual and institutional level measures were associated with student mental health, accounting for 49% of the variance in mental health after controlling for background and demographic characteristics.  The IPPR state that their findings(“not-by-degrees-summary-sept-2017-1-.pdf”, n.d.) suggest that a majority of HEIs should take measures to ensure that the nature of course content and delivery does not result in academic rigour being sought at the expense of students’ mental health and wellbeing.

Social problem solving, coping, was identified as a more useful indicator of suicide potential than hopelessness, they therefore note that the concept of coping, especially in relation to students’ adjustment to university life, deserves further attention.

In addition, O’Keefe(O’keeffe, 2013) states that 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.

The Huffington Post blog post ‘What Happened to Pastoral Care?’(“What Happened to Pastoral Care? | HuffPost UK”, n.d.) states that the term ‘pastoral care’ has been missing from many of the discussions on mental health in higher education, and asks if the loss of the term ‘pastoral care’ reflects that we no longer tend to hold universities responsible for student welfare?

The Universities UK Student mental wellbeing in higher education Good practice guide(Universities, 2015) states that there has been a very significant growth in the specialist support and guidance services provided for students in higher education.  This includes supported provided within faculties and teaching departments including personal tutoring and other pastoral systems.

With respect to duty of care, institutions have a general duty of care at common law to deliver their services to the standard of the ordinarily competent institution; and, in carrying out their services and functions as institutions, to act reasonably to protect the health, safety and welfare of their students.

The QAA report What students think of their higher education (“What-Students-Think-of-Their-Higher-Education.pdf”, n.d.) identifies that positive and supportive relationships with a personal tutor was essential to successful learners. However, inconsistencies in students’ experiences continued to be problematic with student comments including:

The personal tutor organisation has been really poor. After four years at […] I am now

on my seventh personal tutor, who doesn’t know anything about me and I don’t feel

very supported in my final (and very stressful!) year. I’m not very happy at the idea of

this person writing a reference for me for a future job as they will only have the basic

information that is on my student record.’

 Suggested improvements included greater and easier access to personal tutors through scheduled tutorials and that tutors should be contactable via email.

 A response to the inconsistencies in the approach to student advising and tutoring has been the establishment of UKAT, the UK Advising and Tutoring group. UKAT believes that personal tutoring and academic advising have not been given the attention they deserve in UK institutions and aims to redress this situation, offering professional development and training in this vital area, providing a forum for the exchange of ideas and working to ensure that tutors and advisers receive the respect they deserve (“About Us”, n.d.).


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Learning Analytics as a tool for supporting student wellbeing – Student Mental Health and Mental Wellbeing

By Samantha Ahern, on 20 November 2017

Mental health and mental wellbeing has become a key issue both nationally, with the independent Mental Health Task Force launched in 2015(“NHS England » Mental Health Taskforce”, n.d.), and for Higher Education Institutions (HEIs) with the number of 1st year UK domiciled students with a known mental health condition increasing 220% between 2010-11 and 2015-16(“Disability – Higher Education Funding Council for England”, n.d.).

Table 1: First year UK domiciled HE students with known mental health condition(“Students and graduates | HESA”, n.d.)

Year Number of students (all levels)
2015-16 15395
2014-15 11915
2013-14 9610
2012-13 7960
2011-12 7315
2010-11 6055

Most full-time first year students in UK HEIs are aged less than 25yrs (2015/2016: (“Higher Education Statistics for the UK 2015/16 | HESA”, n.d.) Table 4a) and are in the age group 16-24yr olds.

However, this does not account for those students that develop a clinically-recognisable mental health issue whilst attending HE institutions or those that report facing difficulties or distress. A mental health poll discussed the All-Party Parliamentary Group on Students in December 2015 found that 78% of respondents believed they had experienced problems with their mental health in the last year(“Mental Health Poll November 15 – Summary – Mental-Health-Poll-November-15-Summary.pdf”, n.d.).

The HEFCE blog post ‘Accommodating mental health’(“Accommodating mental health | HEFCE blog”, n.d.) reported that in 2015, student support services saw a 150% increase in appointments. Also, that approximately 29% of students experience clinical levels of psychological distressed associated with increased associated with increased risk of anxiety, depression, substance abuse and personality disorder.

The 2014 Adult Psychiatric Morbidity Survey (APMS) ((mr) Web Master, 2016) found that 15.7% of adults surveyed were identified with symptoms of Common Mental Disorder (CMD), with an expectation that this would be between 14.7% and 16.7% (95% confidence interval) for the whole population.  Common Mental Disorders comprise different types of depression and anxiety.  Anxiety disorders include generalised anxiety disorder (GAD), panic disorder, phobias and obsessive compulsive disorder (OCD).

Additionally the APMS suggests that amongst 16-24 year olds, there has been a growing gap in rate of CMD symptoms between men and women. In 1993 the rates were 8.4% (men) and 19.2% (women), increasing to 9.1% (men) and 26.0% (women) in 2014.  In addition, anxiety disorders were found to be more common young women than any other age-sex group(“apms-2014-cmd.pdf”, n.d.).

With regard to ethnicity, CMD did not vary significantly by ethnic group in men, but did in women with CMDs more common in Black and Black British Women (29.3%), and less likely in non-British white women (15.6%) compared to White British women (20.9%).

This is particularly worrying as evidence suggests that those who have high levels of depression are less likely to seek help and that depressive symptoms in young people are linked with negative attitudes towards help-seeking for mental health difficulties(“How psychological resources mediate and perceived social support moderates the relationship between depressive symptoms and help-seeking intentions in college students – 03069885.2016.1190445”, n.d.).  The Institute for Public Policy Research(“not-by-degrees-summary-sept-2017-1-.pdf”, n.d.) found that just under half of students who report experiencing a mental health condition choose not to disclose it to their university.

The APMS also asks participants about suicidal thoughts, suicide attempts and self-harm(“apms-2014-suicide.pdf”, n.d.).  A fifth, 20.6%, of adults reported having suicidal thoughts, with the expectation that this would be between 19.5% and 21.7% for the wider population (95% confidence interval). This was more common in women than men. It was noted that although men were likely to commit suicide, women were more likely to report attempts to do so. Additionally, more women than men reported self-harm.

The difference in self-reporting rates for suicidal thoughts, suicide attempts and self-harm between men and women are extremely noticeable between 16 to 34 year olds in comparison to other age groups.


Figure 1: Chart showing % men (M) and women (W) self-reported suicidal thoughts, suicide attempts and self-harm(“APMS 2014: Chapter 12 – Suicidal Thought, Suicidal Attempts, and Self-Harm – Tables [.xls]”, n.d.)

The authors of the APMS report note that although they did not find any significant differences due to ethnic group they recognised that this may be due sample size limitations and might mask real differences.

Following a Freedom of Information request from Universities UK, data on student suicide in the England and Wales (among students aged 18 and over) for 2007 to 2011 was released. These data are shown in Table 1: Student suicides in England and Wales (ages 18+), 2007 to 2011.  A University of York report(“Student Mental Ill-health Task Group Report Mar 2016.pdf”, n.d.) noted that while the overall number of students increased across the period, the relative increase in suicides far outstripped the increase in student numbers.

Table 2: Student suicides in England and Wales (ages 18+), 2007 to 20111234

Year 2007 2008 2009 2010 2011
Male 57 74 76 90 78
Female 18 21 33 37 34

Source: Office of National Statistics

  1. Figures for deaths registered in each calendar year
  2. Data for England and Wales includes deaths of non-residents
  3. Data relate to those classified as full-time students at death registration
  4. Suicide defined using the International Classification of Diseases Tenth Revision (ICD10) codes X60-X84, Y10-Y34

Self-harming method and reasons for self-harming data were grouped slightly differently, the age categories were 16-34 years, 35-54 years and 55+ years.  Across all age groups, cutting themselves was the most prevalent form of self-harm. This was reported by 84.3% of 16-34 year olds.  This age group (16-34) were also more likely to self-harm in order to relieve unpleasant feelings (81.9%) (which included feelings of anger, tension, anxiety or depression), than reporting self-harm in order to draw attention to themselves (28.6%, for all ages this was 31%).

With regards to help-seeking behaviour, 16-34 year olds were more likely to seek support from friends and family (29.9%) or GP/family doctor (29.1%) after a recent suicide attempt than hospital/specialist medical or psychiatric service (20.8%) with 51.6% not seeking any help.  37.7% of people who self-harmed received medical or psychological help afterwards, but for 16-34 year olds this value drops to just 31.1%.

A University of York Student Mental Ill-health Task Group Report (March 2016)(“Student Mental Ill-health Task Group Report Mar 2016.pdf”, n.d.) notes that students’ experiences of higher education have changed over the previous 10 years, which may have an adverse impact on their mental health highlighting three specific factors.

These factors were:

  1. The rapid withdrawal of financial support for home students and an increasing reliance on loans, and in consequence, an increase in student debt.
  2. The current cohort of students faces a more difficult labour market than earlier generations of students. There is a higher risk of unemployment and insecure employment for those graduating with arts and humanities degree than those studying medicine and subject allied to medicine.
  3. The electronic environment created by electronic communication technologies can expose young people and students to pressures that were avoided by previous generations. This includes cyberbullying and victimisation.

The Institute of Public Policy Research (IPPR) report Flexibility for Who? Summary (“flexibility-for-who-summary-july-2017.pdf”, n.d.) states that  younger workers in part-time and temporary work are more likely to experience poorer mental health and wellbeing, with 22% of younger graduates who are overqualified for their jobs report being anxious or depressed, compared to 16 per cent of those in professional/managerial jobs.  Younger workers who work part-time are 43% more likely to experience mental health problems that those who work full-time.

It has been reported that the most common type of mental health problems at any university or college are depression, anxiety, co-occurring substance problems, eating disorders, suicidal ideation, and self-injury(Anderson, 2015) echoing some of the findings of the 2014 Adult Psychiatric Morbidity Survey.


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Learning Analytics as a tool for supporting student wellbeing – Introduction

By Samantha Ahern, on 20 November 2017

In September I presented at the Association for Learning Technology Conference. My talk was an argument that we should be doing more to support students, especially with the growing concerns around mental wellbeing, and my belief that learner analytics can and should be used to assist in this support.

This talk was recorded and can be viewed on YouTube: https://youtu.be/M9Fzdn943eE?t=48m9s

In addition to the talk, I would also like to share my preparatory work with you. This will be presented over a series of blog posts, of which this is the first.

Learning Analytics as a tool for supporting student wellbeing – Introduction

The last few years has seen a raise in awareness of mental health/wellbeing issues through campaigns such as Heads Together and of student mental health/wellbeing with a number of articles being published on this topic by The Guardian.

At the same time questions have been raised about the quality of support for students in our Higher Education Institutions, will many students complaining about the poor quality of personal tutoring and the lack of information their tutors have about them, the course they are studying and their progress.

Much of the data that would be useful in assisting the role of the personal tutor, is also useful in the analysis and improvement of teaching and learning. In the emerging field of learning analytics data is being leveraged predominantly with the aim of improving student retention and enhancing the student experience.  I therefore ask if we can apply learning (learner) analytics to better informing personal tutoring.

However, there is much debate around the ethical implications of learning analytics and the data protection and privacy rights of students. Due to the sensitive nature of mental health and the potential fatal consequences of mental ill-health this is further complicated.

Due to the scale of the mental wellbeing issue within our institutions and the duty of care to our students, should these outweigh other concerns?

These blog posts will discuss four key themes with regard to this question, these are: student mental health and mental wellbeing, the role and responsibilities of HE Institutions in supporting students’ mental wellbeing, how mental wellbeing issues can be identified and the role learning analytics could play in supporting student wellbeing.

Jisc digital capability discovery tool

By Moira Wright, on 2 November 2017

UCL will be participating in the beta pilot of the Jisc digital capability discovery tool for staff and students which will run from December 2017 to May 2018.

The Jisc digital capability discovery tool has been designed to support staff across higher and further education and skills. It helps individuals to identify and reflect on their digital capability – particularly in relation to their work roles – and to develop their confidence through tailored feedback, ‘next steps’, and links to resources. Questions and feedback are mapped to the Jisc Six elements digital capability framework to provide a holistic view of the skills required. The discovery tool can also help managers and team leaders understand what support would be most helpful for their staff.

The tool uses the Potenial.ly platform and has tailored questions with one set for students and one for staff. The questions have been designed to capture the digital capabilities required to be successful in an educational context.

Users of the tool will respond to a series of questions that allow them to reflect on the digital skills they have already acquired and identify possible new ones. Feedback will include a digital capability profile and a summarised list of suggested actions.

Jisc Digital Capability Profile 2image Jisc Digital Capability Profile image

We’ll be making more announcements in the next couple of weeks providing information on how students and staff at UCL can access the tool.

If you would like to get involved in the pilot at UCL please contact Moira Wright.


Additional links:
Jisc Building digital capability project site: https://www.jisc.ac.uk/rd/projects/building-digital-capability
Jisc Digital Capability Blog: https://digitalcapability.jiscinvolve.org/wp/






TechQual+ Survey at UCL

By Moira Wright, on 13 October 2017

In early 2016, ISD (Information Services Division) carried out the first Staff and Student IT Survey using TechQual+. Over 1,000 of you completed the survey, and over the past 16 months we have been working hard to improve our services in response to your comments.

Below are just a few examples of changes that have been made as a result of the feedback received from the TechQual+ survey run in 2016:

Wi-Fi                        Three speech bubbles

A substantial investment in replacing and upgrading our Wi-Fi technology infrastructure

Service Desk

We’ve invested in staffing, tools and training to speed up response times and improve quality.

We’ve partnered with an external organisation and altered shift patterns to provide additional out of hours’ support.


We’ve rolled out 170+ additional printers over the past 18 months, targeting the busiest areas. This takes the current total to 660 printers. In areas of high usage, we’ve introduced new high capacity printers.


We have invested in storage and now all staff and students can store 100GB for free.


We are continuing to invest in additional cluster PCs, and loan laptops where there isn’t space for desktops. We added a further 550 desktops and 60 laptops by September 2017.
We operate one of the largest laptop loan services across UK universities – 266 laptops across 12 locations – and this year a further 60 laptops were added.


We delivered 221 courses last academic year, that’s nearly 1000 hours of training with about 3000 people attending.  We are working hard to publicise the courses we offer.

Audio Visual

In 2016 ISD invested £2.5m into improving the technology in teaching facilities. Approximately 70 centrally bookable spaces had their facilities updated; this included bringing 43 spaces in 20 Bedford Way up to the standard spec including installation of Lecturecast in approx. 30 spaces.  Lecturecast was also installed at 22 Gordon Street and Canary Wharf (3 spaces each).  We also refreshed the Lecturecast hardware in 12 rooms.

Drawing of a tablet with 5 stars

Based on the findings of focus groups at participating institutions, the TechQual+ project has articulated a set of generalised IT service outcomes that are expected of IT organizations by faculty, students, and staff within higher education. The TechQual+ core survey contains 13 items designed to measure the performance of the following three core commitments: 1) Connectivity and Access, 2)Technology and Collaboration Services, and 3) Support and Training.

The TechQual+ survey will be run again at UCL in December 2017 and we’ll be asking for your help to advertise it to your students, encouraging them (and you!) to complete it. All respondents will be entered into a prize draw with a chance to win some great prizes!

We’ll be providing more information and communications about the survey closer to the opening date.