Digital Education team blog
  • We support Staff and Students using technology to enhance education at UCL.

    Here you'll find updates on institutional developments, projects we're involved in, updates on educational technology, events, case studies and personal experiences (or views!).

    Subscribe to our elearning newsletters.

  • Subscribe to this blog

  • Meta

  • Tags

  • Creative Commons Licence

  • A A A

    Archive for the 'Samantha’s Scribbles' Category

    Ethics education in taught courses – not just a STEM issue?

    By Samantha Ahern, on 18 December 2018

    On the 12th December I visited Central St Martins for the UAL Teaching Platform event Ethics in Arts, Design and Media Education. Much of the discourse at present is focused on ethics education in STEM discplines such as Computer Science and Data Science, or more predominantly the lack of meaningful education.  Much of this has been driven by growing concerns around the algorithms deployed in social media applications and seemingly rapid growth of AI based applications. The House of Lords AI report explicitly talks about the need for ethics education in compulsory education if society and not just the UK economy is to benefit.

    I was intrigued by a potentially alternative viewpoint.

    The role of the arts is to push the boundaries, but are there limits to artisitic expression?

    Are rebellion and social responsibility mutually exclusive?

    UAL seem to think not.

    The focus of the day was ethics in the context of what students make and do, in postgraduate and undergraduate taught course contexts. UAL aim to entwine ethics into the creative process, developing ethics as lived practice.

    One approach to this has been the development of the Bigger Picture unit which requires groups of students to undertake both collaborative practice and participatory design projects. Some of these projects required students to work with vulnerable members of society e.g. the homeless. How do we ensure that the participants equally benefit and not exploited? Throughout the unit students were encouraged to work collaboratively with these participants respectfully, honestly and with integrity. To enable this, explicit sections on ethical considerations were added to the unit handbook and project brief.

    Additionally, UAL has been working on the development of an Educational Ethics Code and establishing an educational ethics committee.

    The code has 3 main themes, these are:

    • Respect for persons
      • Respecting the autonomy of others
    • Justice
      • Does everybody benefit?
      • Are there privilege and power differences?
      • What social good will the project do?
    • Beneficence
      • The art of doing good and no harm

    There was a general acknowledgement amongst the attendees that many of the ethical decisions we make are situation specific and timebound,with key consideration to be given to who is part of the conversation and who has got the power? Privilege and power are important considerations, especially when it comes to consent models, regardless of discpline.

    It was also acknowledged that there is a fineline between support (e.g. timely guidance) and imposition (e.g. lengthy formal ethical review processes).

    Attending this event made me wonder: is this just one part of a much wider debate around compassion and social responsibility? To my mind it is.

    Event related readings:

     

     

     

    Call for Participants

    By Samantha Ahern, on 19 November 2018

    Participants required for the following study:

    What synergies or conflicts exist between current Higher Education Institution Learning Analytics and student wellbeing polices?

    As part of an ongoing response to increasing concerns around student wellbeing and mental health UUK, in their September 2017 #StepChange report, recommended the alignment of learning analytics with student wellbeing. However, is it currently possible for these to be aligned?

    The aim of this study is to identify the key characteristics of existing policies relating to student wellbeing and learning analytics across the UK Higher Education sector, and the synergies or conflicts that exist between them. This will help to establish whether, at present, learning analytics and student wellbeing initiatives are sufficiently aligned, and if amendments are required to aid alignment.

    The study is looking to recruit HEIs who would be willing to share their institutional policies related to student support and wellbeing, and where applicable learning analytics.

    For details of the study please view the study’s Information Sheet.

    If you would like your institution to participate in the study please complete and return the Registration Form by Monday 21st January 2019.

    Participating institutions will be requested to share their policies by Monday 21st January 2019.

    Please return competed registration forms either via email (s.ahern@ucl.ac.uk) or by post to the address below:

    Ms S. Ahern

    ISD –  Digital Education

    UCL, Gower Street, London WC1E 6BT

    This project is registered under, reference No Z6364106/2018/11/55 social research in line with UCL’s Data Protection Policy.

    Download (DOCX, 36KB)

    Download (DOCX, 36KB)

    TPCK, data and learning design

    By Samantha Ahern, on 13 February 2018

    Samantha is an experienced educator, technologist and creator.

    This is my standard biog text. Technology is both what I have studied and what I have taught others. The use of technology in learning activities was authentic and integrated into the learning design. Technology, pedagogy and curricula are therefore intrinsically intertwinned.

    For meaningful use of technology in teaching and learning these three elements should form a braid.

    The 2007 paper What is Technical Pedagogical Content Knowledge? is a good discussion of this interplay and is pretty much how I view the relationship between technology and pedagogy.

    When talking about learning and the use of technology in learning I often used the phrase and advocate for ‘pedagogic intent’.

    Its a great phrase, but what does it mean?

    Lecture capture is very popular with students, and increasing numbers of lectures are recorded.  However, there can be a quite passive use of the technology.

    However, it can be used create engagement in the classroom.  The technology becomes part of the pedagogy of the classroom experience.  Our UCL colleague Parama Chaudhury presented a great webinar for the Echo 360 EMEA community on ‘Engaging students with active learning: lessons from University College London’.

    This technology can also be used post session to identify content that is that is either difficult, identified by a flag, or of particular interest to students, that could inform future session planning.

    Additionally, many taught modules have corresponding Moodle courses.  Although the e-Learning baseline introduces a degree of consistency, these vary immensely in their purpose and content types.

    A move towards blended learning designs provides data points that could support post-course review or, perhaps most interestingly, to flag ‘critical-path’ activities (quizzes, forum posts, downloads etc) for intervention in real time. In this case ‘blending’ in online activities becomes an essential part of the student experience.

    This identification of course elements of pedagogic interest of existing learning designs and how resulting questions could be answered by the identification of corresponding data points and analysis can be embedded into the learning design process.

    The upcoming JISC Data informed blended learning design workshop aims to help participants ensure that their blended learning designs are purposeful. It will seek to make explicit the pedagogic intent in a learning design and explore how data can enable us to understand whether or not learner behaviour is corresponding to those expectations.

    Thus returning us to the intertwinned relationship between technology, pedagogy and curricula.

     

    The purpose of education?

    By Samantha Ahern, on 25 January 2018

    “Were all instructors to realize that the quality of mental process, not the production of correct answers, is the measure of educative growth something hardly less than a revolution in teaching would be worked.”
    John Dewey, Democracy and Education

    Over the last few weeks I have attended a number of events, but they have all the same common thread.

    They have left me asking two questions; firstly, what is the purpose of education and secondly, what do we mean by learning?

    This has reminded me of comments made by Peter Goodyear in his keynote at the 2017 ALT Conference regarding learning spaces, ‘attributes and qualities of spaces do not determine the learning and outcomes and objectives’ and ‘it’s what students actually do that effects what they learn .. can not be designed’.

    In the #IOEDebates event What if… we really wanted evidence-informed practice in the classroom? Gert Biesta (Professor of Education and Director of Research, Brunel University London) noted that ‘Teaching is: Open, semiotic and recursive’ and this makes teaching a messy business. We can remove the messiness but would this reduce teachers to technocrats and create an education environment of uniform conformity, evidence must not become another thing to tell you what to do.

    Professor Biesta went on to ask ‘What do we want education to work for:’

    • Qualification?
    • Socialisation?
    • Subjectification?
     This had parallels to discussions at the debate What is a university education and where is it going? where Lord Willetts discussed the wider benefits of Higher Education:
    http://blogs.staffs.ac.uk/mikehamlyn/files/2015/06/willetts1.jpg
    How do these benefits relate to the learning or the learning gain that takes place within our universities?
    Many of the presentations at the HEFCE open event Using data to increase learning gains and teaching excellence hosted by the OU primarily focused on non-subject knowledge gains and employability.
    HEFCE define learning gain as ‘an attempt to measure the improvement in knowledge, skills, work-readiness and personal development made by students during their time spent in higher education.’ (http://www.hefce.ac.uk/lt/lg/). They go on to state that measuring learning gain will ‘contribute to a broader international understanding about the value of higher education, and help governments shape their policies and investments accordingly.’.
    So what is primary purpose of learning within our institutions? Can this learning be effectively measured?
    I don’t know. All I do know is that I now have more questions than answers about the nature of learning and the purpose of a university education.

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

    By Samantha Ahern, on 20 November 2017

    Learning analytics is 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’(“Guest Editorial – Learning and Knowledge Analytics. Educational Technology & Society, 15 (3), 1–2. Siemens, G., & Gašević, D. (2012)”, n.d.).

    Applications of learning analytics include Early Alert and Student Success, Course Recommendation, Adaptive Learning and Curriculum Design(Sclater, 2017).

    Can and should this learning analytics be extended to identify normative behaviours of students and recognise changes to those behaviours, aiding pastoral support?

    Although much of the data for informing pastoral support is the same as that for Early Alert and Student Success the aims and implications are different. The data needs may also be more demanding. For example, there will be additional considerations around data sharing and protection as mental ill-health is classified as a protected characteristic.

    For inclusion of engagement data from virtual learning environments, this would involve understanding the seasonality of student interactions with online course content, cohort interactions, how a student’s interactions are differing from both their cohort and their own normative behaviour with respect to the seasonality.

    Prinsloo and Slade (Prinsloo and Slade, 2017) note that ‘Not  only  do various  stakeholders  in  the  institution  work  in  silos,  responding independently  of  each  other and resulting  in  overlap and inconsistencies, institutional  sense-making  of  students  at  risk is  also  fragmented’, which may hinder student well-being support.

    Evidence on the effectiveness of learning analytics based interventions in unclear. A systematic review and quality assessment of studies on learning analytics in higher education by the University of Exeter(Sonderlund and Smith, 2017) was only able to include 20 of 560 papers identified due to the methods employed in the studies, only 4 studies evaluated the effectiveness of interventions based on learning analytics. The key recommendation from the review is that more research into the implementation and evaluation of scientifically-driven learning analytics to build a solid evidence base.

    The combination of the lack of evidence of the effectiveness of learning analytics based interventions and the potential negative consequences for both our students and institutions, therefore causes us to question whether learning analytics should be used to support student mental well-being.

    Conclusion

    Student mental wellbeing and in particular student mental ill-health is of major concern, with 48% of UK HEIs having appropriate policies in place(Universities, 2015), and continually needs to be addressed.

    An “unhelpful divide” of distinguishing intellectual needs from emotional needs, then students mental health may suffer if the emotional needs are ignored(“What Happened to Pastoral Care? | HuffPost UK”, n.d.). Therefore, pastoral care in addition to academic support is crucial student mental wellbeing.

    The Higher Education Academy UK Professional Standards Framework (“UK Professional Standards Framework (UKPSF) | Higher Education Academy”, n.d.) dimension A4, Developing effective learning environments and approaches to student guidance,  indicates that student support is an area of activity in which those teaching and supporting learning in higher education should be involved. Additionally, the Universities UK #stepchange(“#stepchange”, n.d.) guidance states that HEIs should seek to promote a diverse, inclusive and compassionate culture as part of their preventive actions.

    Unfortunately, there are a number of inadequacies with the current provision of pastoral care in UK Higher Education Institutions.  I propose that learning analytics can be used to help to address some of these inadequacies by providing timely and meaningful data to personal tutors about their tutees., this is in alignment with the Univerisites UK guidance(“#stepchange”, n.d.) to align learning analytics with student wellbeing. However, this will require action on behalf of tutors, and there are legal questions still to be answered around negligence and failing to act on or engage with information provided via learning analytics.

    Despite the potential ethical and legal issues around using learning analytics to support pastoral care and student mental wellbeing, I believe that this application area that should be explored.

    References:

    Download (PDF, 42KB)

    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.

    References:

    Download (PDF, 42KB)