Student mental health is a growing concern for universities internationally (Evans et al., 2018; Hartrey et al., 2017; Sarmento, 2015). In campus-based universities in the USA, it is estimated that a third of students meet the criteria for a clinically significant mental health issue (Lipson et al., 2018), and research shows that mental health difficulties have a serious effect on students’ likelihood of attaining their study goals. For example, students experiencing mental health difficulties are statistically less likely to complete and/or pass a course or module (Mojtabai et al., 2015; Richardson, 2015), they appear to attain lower grades, (Daniel et al., 2009), they are more likely to drop out of university (P. Brown, 2016; Mojtabai et al., 2015; Richardson, 2015) and they are more likely to experience long term consequences in terms of future employment, earning potential and overall health (Annapally et al., 2019; Arim & Frenette, 2019; Eisenberg et al., 2007). Additionally, students are more likely to experience or develop mental health problems than non-students, which would appear to imply that studying and university culture may be playing a role in the problem (J. S. L. Brown, 2018; Ribeiro et al., 2018; Tinklin et al., 2005; Winzer et al., 2018).
Furthermore, it is likely that distance learners are particularly at risk. Evidence shows that distance learning students are at least as likely to experience mental health issues that impact on their learning (Barr, 2014; Harrer et al., 2019; Richardson, 2015), and studies suggest that distance learning students are not able to access the same level of support as campus-based students (Barr, 2014). This is an additional concern due to the number of disclosures of mental health issues in distance learning students; for example, in 2017, 7.8% of UK Open University students disclosed a mental health condition; a substantially higher figure than the UK sector average of 2.02% of students disclosing a mental health condition (Higher Education Statistics Agency, 2017).
It is increasingly recognised in the sector that a responsive or service-provision approach to mental health is no longer sufficient, and that a proactive, whole-university approach is needed in order to effectively support students to succeed (Hughes & Spanner, 2019). Of course, teaching and learning is an essential part of this. This paper explores the potential for learning design to play a role in creating learning that supports student mental wellbeing, and explores a tool and method that may support this.
Students have reported that study can have a negative effect on their mental wellbeing, and that mental ill health can have a conversely negative effect on their studies (Andrews & Wilding, 2004; Markoulakis & Kirsh, 2013; Ribeiro et al., 2018; Salzer, 2012). This situation is not new; back in 2005, Tinklin et al. found that higher education, with its ‘systems’ and ‘structural issues’, ‘had exacerbated and even created some of the students’ difficulties’ (Tinklin et al., 2005). Markoulakis and Kirsch built on this work, locating areas where students experienced mental health difficulties, and found areas included the ‘learning environment,’ ‘difficulties with their studies,’ ‘structural difficulties imposed by the university,’ and ‘academic outcomes’ (Markoulakis & Kirsh, 2013). More recently, a dataset analysis of 80,509 students attending college counselling centres in the USA, UK and Canada confirmed this, finding that ‘academic distress’, including ‘academic performance, pressure to succeed, and postgraduation plans’, was the most unique predictor of anxiety (Jones et al., 2018).
It is clear that barriers to mental wellbeing do not reside solely within individuals, that they are inherent in aspects of higher education (Lister et al., 2021). Indeed, Ribeiro et al. found in a systematic review that ‘psychological suffering is inherent in academic life’ (Ribeiro et al., 2018). And while a certain level of stress is expected as part of academia, there is a strong case that higher education should adapt or update some of the systems, structures and academic practices that cause undue mental health difficulties. However, this recognition is not yet commonplace in the literature (Lister et al., 2021). In recent years, studies around how to better support student wellbeing have largely focused on pathologising students; for example, enhancing student resilience (e.g. Galante et al., 2018; Whiteside et al., 2017), enabling mental health-related support mechanisms (e.g. Brown, 2018; Byrom, 2018) and promoting self-care (e.g. Ayala et al., 2017; White et al., 2019) rather than adapting university practices or systems to create learning environments that engender wellbeing. Of course, these interventions are not without use; practices such as peer support and mindfulness have been proven beneficial (Byrom, 2018; Galante et al., 2018). However, if the location of a student’s distress is within academic practice, i.e. within their curriculum, assessment or learning environment, it would appear logical that the solution should focus removing barriers in that area, i.e. via inclusive curriculum, assessment or learning design (Lister et al., 2021).
In distance learning higher education, there is already a strong case for inclusion to be considered, planned for and anticipated during the learning design process (Coleman & Berge, 2018; Pittman & Heiselt, 2014). Indeed, in many universities accessibility and disability considerations are already embedded in learning design processes (Burgstahler et al., 2004; Coughlan, Lister, Seale, et al., 2019; Pearson et al., 2019). Universities have a duty to provide accessible learning content to students with disabilities, and this generally takes place through a combination of anticipatory and individual accommodations (Felsinger & Byford, 2010).
Learning designers can play a key role in designing for inclusion, and adopting student-centred, collaborative approaches to this design generates courses that incorporate a wider range of student support materials (Toetenel & Rienties, 2016). Thorpe advocates the process of creating a visual representation of the stages of a learning activity to inform and clarify choices about teaching, learning outcomes, activities and use of technology and also to define the context in which this learning takes place (Thorpe, 2008). By focusing on increasing student engagement with activities, learning tools, materials and communities, universities can incorporate a range of interventions using appropriate technology and resources. And by involving students at key points of the design process, they can anticipate potential barriers to this engagement, especially for students with mental health difficulties.
An example is the DO-IT centre in the University of Washington, which has worked for over twenty years to embed accessibility in instructional design (Burgstahler, 2009; Burgstahler et al., 2004). Other examples include the Open University, UK, where learning design workshops take place while modules are in production. In these, learning designers collaborate with module teams using a series of tools to support effective, inclusive design (The Open University, 2020; Toetenel & Rienties, 2016). Nottingham Trent University follow a similar process, using module maps and student personas to support inclusive learning design (Nottingham Trent University, 2020).
Learning analytics can also be a useful tool in designing for inclusion. Stone notes how learning analytics ‘can be constructively harnessed to inform the development, personalization and appropriate targeting of interventions’ (Stone, 2016). In an extension of this use of learning analytics, Nguyen et al. compared visual representations of course activities with the online engagement of students and with student responses to end of course surveys. They demonstrated how learning design ‘provides educators with pedagogical context for interpreting and translating Learning Analytics findings to direct interventions’ (Nguyen et al., 2017, p. 1). This link to learning analytics demonstrates a developing use of technology to support distance learning as it enables educators to track student engagement, link it to specific activities and to target interventions and support when students are perceived to be disengaged. Thus, the distance educator is able to respond to student choices about their learning in a more immediate way, assuming of course that the student is choosing to study online. A meta-analysis of student behaviour over a whole course then informs educators’ decisions about adaptations to future activities, creating a virtuous circle of educator and learner choices. Thus the conclusion from Rienties et al. (2018, p. 6) in their study of language students at The Open University that learning design “has a fundamental influence on our students’ learning behaviour, their satisfaction of the module, and most importantly pass-rates”.
Learning design is not only important for student success and satisfaction; it can also have an important impact on student wellbeing. There is limited exploration of this in the literature, but one example is Weller et al.’s research of the complex factors affecting student retention. A key finding for them was that collaborative activities, which are effectively structured, can enable students to engage in “deep learning” via a supportive community of learners (Weller et al., 2018). Such activities tend to push students out of their comfort zone and are also associated with higher rates of success (Rienties & Toetenel, 2016). However, research shows that these collaborative activities are associated with higher levels of student anxiety (McPherson et al., 2019). Thorpe (2008, p. 59) also notes that students tend only to engage with collaborative activities which are linked to assessment, and stresses it is crucial to make the process “enjoyable as well as mandatory” to maximize effective engagement. What students want is not always what they might need and the challenge for learning designers is to find the right balance between academic success and mental wellbeing.
Persona are fictional but realistic characters that are intended to represent, to some extent, the audience being designed for, thus aiding user-centred design (Miaskiewicz & Kozar, 2011; Pruitt & Grudin, 2003). A typical persona contains basic information about the character (e.g. name, age, gender, geographical location, employment status etc.) and additional narrative that can inform design choices, such as their likes and dislikes, goals, experiences, abilities, preferences, needs, motivations and other things that may act as barriers or blockers for that character (Miaskiewicz & Kozar, 2011).
Although personas may contain a short narrative, they generally represent a snapshot of what and who the fictional person is at a particular moment in time, and do not generally provide deeper insight into their history or experiences. However, Grudin and Pruitt advocated for the power of personas when they are combined with more detailed information, including life stories and goals (Grudin & Pruitt, 2002). Here they overlap, to some extent with vignettes. Vignettes are short, fictional stories about a person or an experience; they can be presented in ‘written or pictorial form’, or a combination of these (Barter & Renold, 1999). Commonly used in social sciences research (Barter & Renold, 1999, 2000; R. Hughes & Huby, 2012), they can complement personas and add more detail, background and nuance. This is particularly relevant when considering complex issues such as student mental health in learning design, as a story depicting past barriers, triggers and experiences will be more meaningful than a snapshot.
Personas and vignettes can support distance learning practitioners to make student-centred learning design decisions. However, there is a need to ensure that personas and vignettes are evidence based, that they represent a diverse spectrum of real student needs and circumstances. This can be particularly challenging in a distance learning environment, where students are less visible. Stone advocates for the need to ‘know who the students are’ (Stone, 2016), identifying that assumptions made in lieu of knowledge can increase barriers to learning. Learning analytics offers the opportunity to analyse and understand the learning behaviour and engagement of students, and this can inform the development of evidence-based student personas and vignettes that discourage stereotyping of students. Additionally, informed, qualitative information about specific student needs and barriers they have experienced can complement learning analytics and demographic data. In this study we adopt a mixed-methods approach, combining qualitative data from interviews with learning analytics and demographic data to create vignettes for learning designers.
An important factor to consider is vignette design; how best to represent a student journey, and how to make it engaging for participants using it.
Institutions frequently represent student journeys as a process flow, depicting the university’s view of a typical student journey and key milestones. Examples are shown in Figures 1 and 2.
These can be practical and visually appealing, but do not adequately represent diversity in students, variation in student journeys or the contexts that affect them (Coughlan, Lister, & Freear, 2019). In contrast to this, vignettes used in research contexts are often text-based; an example is shown in Figure 3.
This style is clearly capable of representing greater depth and individuality of circumstances, and thus greater student diversity in a learning design context. However, it is less visually engaging, and more difficult to draw comparisons between vignettes, which can be useful for learning designers. A balance is needed between ensuring vignettes are aesthetically appealing and ensuring they represent diversity in student journeys.
To address this need, we used an online platform called Our Journey (available at https://ourjourney.ac.uk/) to represent student journeys and form the basis for the vignette design. Our Journey uses a mixture of text and pictorial elements, adopting a board game aesthetic with cards for different events in the journey, and using emojis and icons to accompany text descriptions (see Figure 4.) It was developed in an attempt to give students agency and choice in how they represent their study journeys, providing a flexible structure that is engaging for user and viewer. This work originated from a participatory research initiative with disabled students, and the tool was co-designed with students and student support stakeholders throughout the development process. It is currently openly available as a free online platform, supporting students to capture and reflect on their journeys, and share them with their institutions or support networks if they choose (Coughlan, Lister, & Freear, 2019). This study aimed to trial its use as a tool for representing fictional journeys, or vignettes, in a way that is accessible and engaging. More information about the platform can be found at https://ourjourney.ac.uk/.
This study takes place in the Open University (OU), a large distance learning institution in the UK. In March 2020, it had 15,941 students disclosing a mental health condition, 12.2% of its total cohort of 129,641 students. It also had a module completion gap of –16 percentage points between students with and without a disclosed mental health issue, and student mental health was considered a strategic priority in the institution.
In order to investigate barriers to mental wellbeing and inform vignette design, semi-structured narrative inquiry interviews were carried out with students and tutors. Students were recruited via email invitation sent to a sample of students disclosing mental health difficulties to the institution, while tutors volunteered in response to an internal advertisement seeking tutors with experience of supporting students with mental health difficulties. Overall, 16 students (10 female, 6 male) and 5 tutors (4 female, 1 male) were interviewed.
This study was approved by the OU’s Human Research Ethics Committee, and the study is recounted in greater detail in Lister et al. (2021).
Interviews were recorded and transcribed, and the transcripts were analysed in NVivo using thematic analysis (Braun & Clarke, 2006, 2019). A range of barriers and enablers to education were identified; these will be reported more fully in a subsequent publication, but Table 1 shows examples of recurrent barriers that were selected to be represented in the vignettes. These have been classified as barriers relating to student development of skills, the course they were studying or the broader learning environment.
|SKILLS-RELATED BARRIERS||COURSE-RELATED BARRIERS||ENVIRONMENT-RELATED BARRIERS|
|Low level of study skills, e.g. referencing, time management||Assessment stress, especially exams and presentations||Feelings of not belonging|
|Managing high expectations and disappointment||Working to deadlines||Environments where not safe/in control (i.e. hallways, classrooms)|
|Feeling out of depth||Anxiety around using forums||Feeling powerless|
|Lack of skills in managing mental health||Collaboration and groupwork||Comparing self to others|
|Difficulties concentrating||Cognitive load and frustration of not understanding||Stigma and fear of speaking out|
|Low self-esteem||Distressing/triggering curriculum content||Isolation|
These themes were combined with institutional demographic data (i.e. diversity in student age, ethnicity, disability disclosure, mental health conditions and faculty distribution) and with learning analytics data (i.e. typical challenge points or pinch points in modules.) This combination of data was used to create fictional student vignettes that illustrated the barriers identified without compromising the anonymity of the interview participants. A disguise approach was used, with stories woven together from different student sources, to ensure no vignette could be identified via jigsaw identification (Saunders et al., 2015). However, to maintain the authenticity of the vignettes, participants’ own words were used as far as possible to illustrate the themes and barriers identified (Barter & Renold, 1999, 2000; Hughes & Huby, 2012).
Ten vignettes were created in total using the Our Journey approach of cards, events and emojis. To maintain the authenticity of the vignettes, students’ own words were used as far as possible to illustrate the themes and barriers identified (Barter & Renold, 1999; R. Hughes & Huby, 2012), but were edited for clarity. For example, an interview participant said, ‘I couldn’t sit in class without getting like a panic attack, um, or like walking in hallways;’ in the vignette for Vanessa this was edited to read ‘I just got so anxious in classes, walking in the halls, etc.’
The cards were combined with short persona descriptions featuring a pseudonym and stock photo or AI-generated image. Five of these vignettes are shared in the following pages (Figures 5, 6, 7, 8 and 9) in the hope that they may be of use to institutional designers, either in their existing format or as a template to inform the creation of institution-specific vignettes. The other vignettes are available for download at https://wellbeinginthecurriculum.weebly.com/.
These vignettes were created for an internal audience, and there are references to acronyms that may not be meaningful in an international environment. These are explained below:
OU: Open University
TMA: Tutor-marked assignment (a standard mid-module assessment in the OU)
EMA: End of module assessment
GCSE: School leaver exams, usually taken at 16 years old
A-levels: Further education exams, usually taken at 18 years old
Focus group events were held with staff and students with the aim of analysing the vignettes and identifying considerations for module design, tuition and student support. Two in-person events were held, one in England and one in Scotland, and a further online event was held. 116 staff attended in total; a breakdown of their roles can be found in Table 2.
|EVENT||LECTURERS||TUTORS||LEARNING DESIGN||STUDENT SUPPORT||STUDENTS||LEADERSHIP||EQUALITY & DIVERSITY||OTHER||TOTAL|
In the events, participants were first given an overview of mental health in higher education in order to set the context. This was followed by a plenary discussion with opportunities for questions. Next, they were asked to work in small groups of 6–8 participants. They were given the vignettes and invited to choose three or four of them with the aim of identifying the barriers to mental wellbeing the students experienced. Finally, they were asked to identify considerations for learning design and other areas of practice that could have a positive impact on students’ wellbeing in distance learning.
During the focus groups, staff identified 278 barriers to mental wellbeing in distance learning. Furthermore, they identified 94 considerations for practice, support and learning design that may mitigate these. These will be reported in detail in a subsequent publication, but examples of considerations that relate to learning design are summarised in Table 3.
|Cognitive load of studying when in low mental health||Breaking up heavy reading with multimedia, graphics and frequent activities|
|Distressing or triggering content||Embedding activities to teach emotional resilience in studying distressing subjects|
|Isolation in between modules and study activity||Modules signposting to ‘bridging materials’, accompanied by community forums|
|Anxiety around using forums||Including in module material activities to build confidence using forums|
|Stress and time management at the end of modules||Signposting in module materials around which sections can be skipped or skimmed if short of time|
|Anxiety around groupwork||Activities and training in modules about how to collaborate|
|Low confidence in study skills||Explicitly teaching study skills such as time management, referencing, note-taking and essay writing|
|Exam stress||Embedding material and activities on managing exam stress in modules|
To illustrate how the vignettes were instrumental in drawing these conclusions, a comment from a participant is given in full below:
“I looked at John’s vignette and one of the barriers he raised was around being isolated and wanting to make friends and feel part of a community and the fact that he was scared at the end of the module as he didn’t have anything to study and focus on until the start of the next module. Bridging materials could be really useful here together with opportunities to engage with other students and OU staff via the forums on the subject/Study Home website. This may help with providing a sense of community and connection which is broader than the module for students who experience this barrier.”
These design considerations are currently being adopted as part of the standard learning design recommendations for new modules, and it is hoped this will shortly begin to have an impact on student experience, wellbeing and success.
Following the event, staff participants were asked to feed back on their experience of the event and using the vignettes. 20 participants did so; 10 completed a survey and 10 elected to send comments by email.
Survey results indicated that using the vignettes was a positive experience. In response to the question ‘How usable did you find the vignettes?’ all staff responded they had found them very or reasonably usable, with no staff selecting neutral or negative responses. When asked if they had been able to identify barriers and possible solutions from the vignettes, all staff responded positively, again with no staff selecting neutral or negative responses.
Open comment boxes and text-based email feedback were almost entirely positive. Positive comments included:
‘Worked really well, I’d like to see this across the faculties’
‘Excellent activity – need to get this online’
‘It was very interesting to look through these vignettes. I think it would be helpful for these to form part of staff induction, particularly those who have interactions with students.’
‘I found these vignettes so interesting to read.’
There were three constructive comments. One was a request for a larger font (this has since been addressed) and two related to the use of emojis in the design:
‘I like the format, apart from that I found the emoticons and symbols a distraction.’
‘Less emojis – format is quite busy’
These comments have been taken into account and will be considered for future iterations of the vignettes.
The interviews with students and tutors indicated a variety of areas in which studying had directly affected student mental health. These barriers are explored in more depth in a different publication (Lister et al., 2021), but the examples given in this paper do support the broader literature in this area. For example, the barrier presented by the ‘Cognitive load of studying when in low mental health’ aligns with Weller et al.’s findings about students withdrawing from study due to feeling ‘overwhelmed’ by curriculum content (Weller et al., 2018); studies have linked distressing curriculum content with mental health challenges for students (Bentley, 2017; Slavin et al., 2014); ‘anxiety around groupwork’ is a theme in the literature (McPherson et al., 2019), and there are many studies aiming to understand or alleviate stress around exams or assessment (Jones et al., 2020). This supports research contentions that triggers for mental health difficulties can reside within higher education environments, systems and curricula as well as within the individual (Lister et al., 2021; Markoulakis & Kirsh, 2013; Tinklin et al., 2005).
The results of the focus group events imply that vignettes are a useful tool in identifying barriers in mental wellbeing and learning design considerations that can lead to more inclusive practice. By analysing the vignettes in a collaborative environment, participants were able to identify a series of barriers to mental wellbeing in learning, and the discussion around these led to a range of learning design considerations that could mitigate these barriers. The solutions and ideas resulting from the workshop are explored in greater depth in a subsequent paper, and most are specific to the OU teaching model and distance learning context (i.e. modules signposting to ‘bridging materials’, accompanied by community forums.) However, some examples given in this paper do appear to support or build on interventions identified in broader literature in this area. For example, the explicit teaching of study skills to build confidence and support mental wellbeing has been explored with Law students by Hewitt and Stubbs (Hewitt & Stubbs, 2017), and teaching students skills for collaborative activities that support wellbeing and compassion has been explored extensively by Gilbert (Gilbert, 2017; Gilbert et al., 2018).
The broad range of learning design considerations identified through use of student vignettes supports the contention that use of personas and narratives can lead to user-centered (or student-centered) design (Miaskiewicz & Kozar, 2011; Pruitt & Grudin, 2003). Participant feedback following the event implies that the vignettes were engaging and enjoyable for participants to use, although larger-scale evaluation is needed in order to definitively draw this conclusion. Furthermore, additional work is needed in order to explore how to optimise the efficacy of the vignettes. For example, with regard to authenticity of student voice, these vignettes were paraphrased by the researcher; this means the student voice was mediated to an extent, although efforts were made to use participants’ own words as far as possible. Seale discusses the way that mediating marginalised voices can be problematic in higher education (Seale, 2006), but there are tensions between authenticity of voice, participant anonymity and the design aesthetic of printed word as opposed to spoken word that require additional exploration.
In this study, student vignettes have clearly been an effective way for student voice to influence learning design. However, more work is clearly needed in this area. This paper aims to open the door for other institutions to expand on this method and identify ways to improve or scale it up, in order to identify the barriers to mental wellbeing students experience in distance learning and to explore proactive, whole-university approaches to reduce or mitigate these through inclusive learning design (Hughes & Spanner, 2019). For example, learning analytics data used in collaboration with student reflective journeys could provide insight at greater scale; or collaboration between students and learning designers to form a community of practice (Lave & Wenger, 1991) could provide more nuanced, participatory design considerations to be piloted and scaled up. This study has begun to lay the groundwork for new methods towards more inclusive practice, but more work is needed, and technology may afford exciting opportunities to build upon it.
In recognising that barriers to mental wellbeing can reside within university environments and study practices, this paper aimed to explore the potential for learning design to play a role in creating learning that supports student mental wellbeing, and to trial a method by which students’ experiences of mental health difficulties in study can play a role in the learning design process. The vignettes used in this study were effective in illustrating barriers and enablers to mental wellbeing in study, and in supporting practitioners to identify learning design considerations. Additionally, this paper shares examples of student vignettes created with the hope they may support learning designers, and introduces an online platform that institutions can use to create vignettes with their own students.
There were several limitations to this study. The qualitative nature of the study meant it was conducted at small scale, with only 21 participant interviews contributing to the creation of the vignettes. Furthermore, it takes place within one distance learning institution, and more research is needed to identify its relevance to other institutions. However, student mental health is a global issue, and one in which student voice and lived experience is sorely needed. Therefore, the successful use of vignettes to communicate student mental health difficulties, engage practitioners and inform learning design considerations is a step towards more inclusive distance learning environments.
The authors have no competing interests to declare.
Andrews, B., & Wilding, J. M. (2004). The relation of depression and anxiety to life-stress and achievement in students. British Journal of Psychology (London, England: 1953), 95(Pt 4), 509–521. DOI: https://doi.org/10.1348/0007126042369802
Annapally, S. R., Jagannathan, A., Kishore, T., Thirthalli, J., Daliboina, M., & Channaveerachari, N. K. (2019). Barriers to academic reintegration in students with severe mental disorders: Thematic analysis. Asian Journal of Psychiatry, 45, 107–112. DOI: https://doi.org/10.1016/j.ajp.2019.09.010
Arim, R., & Frenette, M. (2019). Are Mental Health and Neurodevelopmental Conditions Barriers to Postsecondary Access? Analytical Studies Branch Research Paper Series. Statistics Canada. https://eric.ed.gov/?id=ED594930
Ayala, E. E., Omorodion, A. M., Nmecha, D., Winseman, J. S., & Mason, H. R. C. (2017). What Do Medical Students Do for Self-Care? A Student-Centered Approach to Well-Being. Teaching and Learning in Medicine, 29(3), 237–246. DOI: https://doi.org/10.1080/10401334.2016.1271334
Barr, B. (2014). Identifying and Addressing the Mental Health Needs of Online Students in Higher Education. Online Journal of Distance Learning Administration, 17(2). http://www.westga.edu/~distance/ojdla/summer172/barr172.html
Barter, C., & Renold, E. (1999). Social Research Update 25: The Use of Vignettes in Qualitative Research. Sociology at Surrey, University of Surrey. http://sru.soc.surrey.ac.uk/SRU25.html
Barter, C., & Renold, E. (2000). ‘I wanna tell you a story’: Exploring the application of vignettes in qualitative research with children and young people. International Journal of Social Research Methodology, 3(4), 307–323. DOI: https://doi.org/10.1080/13645570050178594
Bentley, M. (2017). Trigger warnings and the student experience. Politics, 37(4), 470–485. DOI: https://doi.org/10.1177/0263395716684526
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. DOI: https://doi.org/10.1191/1478088706qp063oa
Braun, V., & Clarke, V. (2019). Reflecting on reflexive thematic analysis. Qualitative Research in Sport, Exercise and Health, 11(4), 589–597. DOI: https://doi.org/10.1080/2159676X.2019.1628806
Brown, J. S. L. (2018). Student mental health: Some answers and more questions. Journal of Mental Health, 27(3), 193–196. DOI: https://doi.org/10.1080/09638237.2018.1470319
Brown, P. (2016). The invisible problem? Improving students’ mental health (p. 66). Higher Education Policy Institute.
Burgstahler, S. (2009). Universal Design of Instruction (UDI): Definition, Principles, Guidelines, and Examples. In DO-IT. DO-IT. https://eric.ed.gov/?id=ED506547
Burgstahler, S., Corrigan, B., & McCarter, J. (2004). Making distance learning courses accessible to students and instructors with disabilities: A case study. The Internet and Higher Education, 7(3), 233–246. DOI: https://doi.org/10.1016/j.iheduc.2004.06.004
Byrom, N. (2018). An evaluation of a peer support intervention for student mental health. Journal of Mental Health, 27(3), 240–246. DOI: https://doi.org/10.1080/09638237.2018.1437605
Coleman, M., & Berge, Z. (2018). A Review of Accessibility in Online Higher Education. Online Journal of Distance Learning Administration, 21(1). http://www.westga.edu/~distance/ojdla/spring211/coleman_berge211.html
Coughlan, T., Lister, K., & Freear, N. (2019). Our Journey: Designing and utilising a tool to support students to represent their study journeys. 13th annual International Technology, Education and Development Conference, Valencia, Spain. DOI: https://doi.org/10.21125/inted.2019.0826
Coughlan, T., Lister, K., Seale, J., Scanlon, E., & Weller, M. (2019). Accessible Inclusive Learning: Foundations. Ubiquity Press. DOI: https://doi.org/10.5334/bcg.d
Daniel, E., Ezra, G., & B, H. J. (2009). Mental Health and Academic Success in College. The B.E. Journal of Economic Analysis & Policy, 9(1), 1–37. DOI: https://doi.org/10.2202/1935-1682.2191
Eisenberg, D., Gollust, S. E., Golberstein, E., & Hefner, J. L. (2007). Prevalence and correlates of depression, anxiety, and suicidality among university students. American Journal of Orthopsychiatry, 77(4), 534–542. DOI: https://doi.org/10.1037/0002-9418.104.22.1684
Evans, T. M., Bira, L., Gastelum, J. B., Weiss, L. T., & Vanderford, N. L. (2018). Evidence for a mental health crisis in graduate education. Nature Biotechnology, 36, 282–284. DOI: https://doi.org/10.1038/nbt.4089
Felsinger, A., & Byford, K. (2010). Managing reasonable adjustments in higher education. Equality Challenge Unit.
Galante, J., Dufour, G., Vainre, M., Wagner, A. P., Stochl, J., Benton, A., Lathia, N., Howarth, E., & Jones, P. B. (2018). A mindfulness-based intervention to increase resilience to stress in university students (the Mindful Student Study): A pragmatic randomised controlled trial. The Lancet Public Health, 3(2), e72–e81. DOI: https://doi.org/10.1016/S2468-2667(17)30231-1
Gilbert, T. (2017). When Looking Is Allowed: What Compassionate Group Work Looks Like in a UK University. In P. Gibbs (Ed.), The Pedagogy of Compassion at the Heart of Higher Education (pp. 189–202). Springer International Publishing. DOI: https://doi.org/10.1007/978-3-319-57783-8_13
Gilbert, T., Doolan NTF, M., Beka, S., Spencer, N., Crotta, M., & Davari, S. (2018). Compassion on university degree programmes at a UK university: The neuroscience of effective group work. Journal of Research in Innovative Teaching & Learning, 11(1), 4–21. DOI: https://doi.org/10.1108/JRIT-09-2017-0020
Gourlay, A., Mshana, G., Birdthistle, I., Bulugu, G., Zaba, B., & Urassa, M. (2014). Using vignettes in qualitative research to explore barriers and facilitating factors to the uptake of prevention of mother-to-child transmission services in rural Tanzania: A critical analysis. BMC Medical Research Methodology, 14(1), 21. DOI: https://doi.org/10.1186/1471-2288-14-21
Grudin, J., & Pruitt, J. (2002). Personas, Participatory Design and Product Development: An Infrastructure for Engagement. Proceedings of Participation and Design Conference (PDC2002), Sweden, 2, 144–161.
Harrer, M., Apolinário-Hagen, J., Fritsche, L., Drüge, M., Krings, L., Beck, K., Salewski, C., Zarski, A.-C., Lehr, D., Baumeister, H., & Ebert, D. D. (2019). Internet- and App-Based Stress Intervention for Distance-Learning Students With Depressive Symptoms: Protocol of a Randomized Controlled Trial. Frontiers in Psychiatry, 10. DOI: https://doi.org/10.3389/fpsyt.2019.00361
Hartrey, L., Denieffe, S., & Wells, J. S. G. (2017). A systematic review of barriers and supports to the participation of students with mental health difficulties in higher education. Mental Health & Prevention, 6, 26–43. DOI: https://doi.org/10.1016/j.mhp.2017.03.002
Hewitt, A., & Stubbs, M. (2017). Supporting Law Students’ Skills Development Online—A Strategy to Improve Skills and Reduce Student Stress? Research in Learning Technology, 25, 24. DOI: https://doi.org/10.25304/rlt.v25.1786
Higher Education Statistics Agency. (2017). Table 15—UK domiciled student enrolments by disability and sex 2016/17 | HESA. Higher Education Statistics Agency. https://www.hesa.ac.uk/data-and-analysis/students/table-15
Hughes, G., & Spanner, L. (2019). The University Mental Health Charter. Leeds: Student Minds. Student Minds.
Hughes, R., & Huby, M. (2012). The construction and interpretation of vignettes in social research. Social Work and Social Sciences Review, 11(1), 36–51. DOI: https://doi.org/10.1921/1746622.214.171.124
Jones, E., Priestley, M., Brewster, L., Wilbraham, S. J., Hughes, G., & Spanner, L. (2020). Student wellbeing and assessment in higher education: The balancing act. Assessment & Evaluation in Higher Education, 1–13. DOI: https://doi.org/10.1080/02602938.2020.1782344
Jones, P. J., Park, S. Y., & Lefevor, G. T. (2018). Contemporary College Student Anxiety: The Role of Academic Distress, Financial Stress, and Support. Journal of College Counseling, 21(3), 252–264. DOI: https://doi.org/10.1002/jocc.12107
Lave, J., & Wenger, E. (1991). Situated Learning: Legitimate Peripheral Participation. Cambridge University Press. DOI: https://doi.org/10.1017/CBO9780511815355
Lipson, S. K., Lattie, E. G., & Eisenberg, D. (2018). Increased Rates of Mental Health Service Utilization by U.S. College Students: 10-Year Population-Level Trends (2007–2017). Psychiatric Services, 70(1), 60–63. DOI: https://doi.org/10.1176/appi.ps.201800332
Lister, K., Seale, J., & Douce, C. (2021). Mental health in distance learning: A taxonomy of barriers and enablers to student mental wellbeing. Open Learning: The Journal of Open, Distance and e-Learning, 36(2), Article 2. DOI: https://doi.org/10.1080/02680513.2021.1899907
Markoulakis, R., & Kirsh, B. (2013). Difficulties for University Students with Mental Health Problems: A Critical Interpretive Synthesis. The Review of Higher Education, 37(1), 77–100. DOI: https://doi.org/10.1353/rhe.2013.0073
McPherson, E., Collins, T., & Gallen, A.-M. (2019). Enabling inclusive group work. Proceedings of the 12th Annual International Conference of Education, Research and Innovation (ICERI 2019), (In Press). DOI: https://doi.org/10.21125/iceri.2019.0675
Miaskiewicz, T., & Kozar, K. A. (2011). Personas and user-centered design: How can personas benefit product design processes? Design Studies, 32(5), 417–430. DOI: https://doi.org/10.1016/j.destud.2011.03.003
Mojtabai, R., Stuart, E. A., Hwang, I., Eaton, W. W., Sampson, N., & Kessler, R. C. (2015). Long-term effects of mental disorders on educational attainment in the National Comorbidity Survey ten-year follow-up. Social Psychiatry and Psychiatric Epidemiology, 50(10), 1577–1591. DOI: https://doi.org/10.1007/s00127-015-1083-5
Nguyen, Q., Rienties, B., & Toetenel, L. (2017). Mixing and Matching Learning Design and Learning Analytics. In A. Zaphiris, Panayiotis and Ioannou (Ed.), Learning and Collaboration Technologies: Technology in Education—4th International Conference, LCT 2017 Held as Part of HCI International 2017 (pp. 302–316). Springer. DOI: https://doi.org/10.1007/978-3-319-58515-4_24
Nottingham Trent University. (2020). Creating student personas and a module map. https://www.ntu.ac.uk/about-us/academic-development-and-quality/flexible-learning/creating-student-personas-and-a-module-map
Pearson, V., Lister, K., & Coughlan, T. (2019). Accessibility Coordinators: A Model for Embedded, Sustainable change towards Inclusive Higher education. Proceedings of the 12th Annual International Conference of Education, Research and Innovation (ICERI), 3127–3136. DOI: https://doi.org/10.21125/iceri.2019.0798
Pittman, C. N., & Heiselt, A. K. (2014). Increasing Accessibility: Using Universal Design Principles to Address Disability Impairments in the Online Learning Environment. Online Journal of Distance Learning Administration, 17(3), 11.
Pruitt, J., & Grudin, J. (2003). Personas: Practice and theory. Proceedings of the 2003 Conference on Designing for User Experiences, 1–15. DOI: https://doi.org/10.1145/997078.997089
Ribeiro, Í. J. S., Pereira, R., Freire, I. V., de Oliveira, B. G., Casotti, C. A., & Boery, E. N. (2018). Stress and Quality of Life Among University Students: A Systematic Literature Review. Health Professions Education, 4(2), 70–77. DOI: https://doi.org/10.1016/j.hpe.2017.03.002
Richardson, J. T. E. (2015). Academic Attainment in Students with Mental Health Difficulties in Distance Education. International Journal of Mental Health, 44, 231–240. DOI: https://doi.org/10.1080/00207411.2015.1035084
Rienties, B., Lewis, T., McFarlane, R., Nguyen, Q., & Toetenel, L. (2018). Analytics in online and offline language learning environments: The role of learning design to understand student online engagement. Computer Assisted Language Learning, 31(3), 273–293. DOI: https://doi.org/10.1080/09588221.2017.1401548
Rienties, B., & Toetenel, L. (2016). The impact of learning design on student behaviour, satisfaction and performance: A cross-institutional comparison across 151 modules. Computers in Human Behavior, 60, 333–341. DOI: https://doi.org/10.1016/j.chb.2016.02.074
Salzer, M. S. (2012). A comparative study of campus experiences of college students with mental illnesses versus a general college sample. Journal of American College Health: J of ACH, 60(1), 1–7. DOI: https://doi.org/10.1080/07448481.2011.552537
Sarmento, M. (2015). A “Mental Health Profile” of Higher Education Students. Procedia – Social and Behavioral Sciences, 191, 12–20. DOI: https://doi.org/10.1016/j.sbspro.2015.04.606
Saunders, B., Kitzinger, J., & Kitzinger, C. (2015). Participant Anonymity in the Internet Age: From Theory to Practice. Qualitative Research in Psychology, 12(2), 125–137. DOI: https://doi.org/10.1080/14780887.2014.948697
Seale, J. (2006). E-learning and disability in higher education: Accessibility research and practice. London: Routledge. DOI: https://doi.org/10.4324/9780203969595
Slavin, S. J., Schindler, D. L., & Chibnall, J. T. (2014). Medical Student Mental Health 3.0: Improving Student Wellness Through Curricular Changes. Academic Medicine, 89(4), 573–577. DOI: https://doi.org/10.1097/ACM.0000000000000166
Stone, C. (2016). Opportunity through online learning: Improving student access, participation and success in higher education [NCSEHE 2016 EQUITY FELLOWSHIP FINAL REPORT]. University of Newcatsle. https://www.ncsehe.edu.au/publications/opportunity-online-learning-improving-student-access-participation-success-higher-education/
The Open University. (2020). Open University Learning Design Initiative. Open University Learning Design Initiative. http://www.opehttp://www.open.ac.uk/blogs/archiveOULDI/index.phpn.ac.uk/blogs/OULDI/
Thorpe, M. (2008). Effective online interaction: Mapping course design to bridge from research to practice. Australasian Journal of Educational Technology, 24(1), 57–72. DOI: https://doi.org/10.14742/ajet.1230
Tinklin, T., Riddell, S., & Wilson, A. (2005). Support for students with mental health difficulties in higher education: The students’ perspective. British Journal of Guidance & Counselling, 33(4), 495–512. DOI: https://doi.org/10.1080/03069880500327496
Toetenel, L., & Rienties, B. (2016). Learning Design – creative design to visualise learning activities. Open Learning: The Journal of Open, Distance and e-Learning, 31(3), 233–244. DOI: https://doi.org/10.1080/02680513.2016.1213626
Weller, M., van Ameijde, J., & Cross, S. (2018). Learning Design for Student Retention. Journal of Perspectives in Applied Academic Practice, 6(2), Article 2. DOI: https://doi.org/10.14297/jpaap.v6i2.318
White, M. A., Whittaker, S. D., Gores, A. M., & Allswede, D. (2019). Evaluation of a Self-Care Intervention to Improve Student Mental Health Administered through a Distance-Learning Course. American Journal of Health Education, 50(4), 213–224. DOI: https://doi.org/10.1080/19325037.2019.1616012
Whiteside, M., Bould, E., Tsey, K., Venville, A., Cadet-James, Y., & Morris, M. E. (2017). Promoting Twenty-first-century Student Competencies: A Wellbeing Approach. Australian Social Work, 70(3), 324–336. DOI: https://doi.org/10.1080/0312407X.2016.1263351
Winzer, R., Lindberg, L., Guldbrandsson, K., & Sidorchuk, A. (2018). Effects of mental health interventions for students in higher education are sustainable over time: A systematic review and meta-analysis of randomized controlled trials. PeerJ, 6, e4598. DOI: https://doi.org/10.7717/peerj.4598