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Sat, 25 Jan 2025 17:16:33 +0000

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Tue, 21 Jan 2025 21:09:45 +0000

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Tue, 21 Jan 2025 20:09:38 +0000

Data collection methods and tools THEORETICAL POSITIONING Thinking about the question “what is the research process and how am I influencing it?” (Jamieson, et al. 2023), I was considering that I am the entirety of the research process: both participant and researcher. So unavoidable bias and influence will occur, but I will try and minimise these things by not deciding when the study will take place, and doing it retrospectively rather than pro-actively. I am also aware that I am unlikely to find anything of any great CO2e impact, about my daily activities in the university, as using devices is as Berners-Lee (2020) suggests a pretty low carbon activity — so my data usage will be, quite minor in terms of its impact. Significantly less than getting a return flight from London to Hong Kong (which I am doing to see my partners family in Feb 2025, this leaves me with bittersweet feelings in terms of its GHG impact). Being cognisant doesn’t allude to or offer me any real thing other than simply being aware of my constant micro impacts. As I’m collecting data on myself, critique of auto- data collection is necessary. Alvesson (2003) suggests autoethnography is much too inward looking, and Delamont (2009) harshly rejects autoethnography for various reasons suggesting laziness and introspection, and states it might even represent a worldview of those in power, such as researchers rather than their subjects (Poerwandari, 2021). Some however, see small merits, such as Eriksson (2010) who after indicating that autoethnography is in essence, narcissistic — a position which I must say I agree with — goes on to suggest that a method of self-examination could present a better understanding for the interest of others (Poerwandari, 2021). This position is furthered by Hamdan (2012) who suggests that auto(ethnographic) researchers might possess insider knowledge which mean they experience the phenomenon from a position of understanding and therefore might be able to better analyse their findings from this position of prior knowledge (Poerwandari, 2021). In the defence of my rationale for choosing (auto)self-analysis is predominantly because gathering intimate data about emails sent and received, files uploaded, stored, downloaded, is as current data protection and privacy practices suggest, information that is protected. With a wider scope, sample, and longer timeframe, this data could of course be collected through ethical means and frameworks, but was out of scope for this Action Research Project. It may turn out that the methods I undertook could become some sort of teaching or dissemination skeleton framework [AN ACTION?] in order to broaden the data sample and be able to draw comparisons and comparative analysis. It would also ethically be easier for people to gather data on themselves following my protocol of collection. . METHODS AND TOOLS For my data collection I used a retrospective auto-quantitative direct-measurement method, using a strucrured (almost systematic) approach to the collection and analysis of the data (Sage, 2024). Almost statistical. As I can’t seem to locate the correct specific academic terminology on the exact approach I took, we can call the research design in a tokenistic way, ‘innovative’ (Hara, 2015).  I unpack my use of the above terminology below:Retrospective, as I collected data after the event had happened, rather than try and actively record everything I was doing as I was doing it (to attempt to reduce participant bias through conscious awareness of each of my actions) (Sage, 2024)Auto-quantitative, meaning the gathering of quant data on myself (Sage, 2024)Direct-measurement, by being able to quantitatively look at data on myself (emails sent, received, files uploaded, downloaded, stored etc) using direct collection methods, such as quantitative counting of the information in the sample (volume of emails received) in understandable metrics allows the study to be easily repeatable or teachable (INTRAC, 2017) Structured (almost systematic) I used repeatable, quasi-statistical methods of recording the data by using a spreadsheet and a tool for documentation, and used the same approach repeatedly (Sage, 2024). I admit, that although its rigorous, its probably not actually ‘systematic’ in the eyes of actual research. My data collection method, laid out in detail below, was in short: for each of the 10 days of data collection, record in a spreadsheet each email received or sent; mark down if there were others in the email chain, or students if they were in the Moodle ‘quick-mail’. I then did an overall data audit to see what, if any files were uploaded or downloaded to OneDrive, and total volume of stored data In a way, this data collection sits in the sort of quantified-self / auto-analysis, which has over recent years become popular outside of research circles. This practice is encouraged by the increased availability of devices, tools, and desires to self-analyse and know more about oneself (James Wilson, 2012; Wolfram, 2012) However, some argue of negative consequences that occur from quantified-self-analysis, offering us intriguing new framings and nomenclature, such as ‘data-festishism’(Sharon and Zandbergen, 2017) where people are enamoured by the data gathering purely in an autotelic way, or negative overwhelming feelings occur through the auto-gathering of data on themselves, being called an ‘infodemic’ (WHO, 2022). . SAMPLE PERIOD AND RATIONALE To try and reduce participant bias and measurement bias, I did not specify the 10 days of data collection ahead of time — I decided a range of 4 weeks, working backwards from the end of term (Friday 13 December 2024). Meaning the potential range period of the data collection was between 15 Nov 2024 — 13 Dec 2024. The exact start date for the 10 day sample window was decided by a ‘truly’ random number generator (Haahr, 2024), see Figure 1 below. I chose 10 days, because its 1/3 of an average month (The mean month-length of the Gregorian calendar is 30.436875 days) FIGURE 1: Random.org for ‘truly’ random number generation (Haahr, 2024) . DATA COLLECTION METHODOLOGY FIGURE 2: Stage 1 of data collection method STAGE 1 1 — Filter the email box for date range, in this example: 6 Dec 2024 2 — Go sequentially through this list of emails, and if the email chain is obvious, mark down recipients in spreadsheet (see STAGE 5). However, if its from Moodle, as per this example, further deduction is needed to work out roughly who this email was sent to. I then clicked the Moodle link [No 2] to follow to Moodle to find out who it was sent to. . FIGURE 3: Stage 2 of data collection method STAGE 2 1 — We can now see this is FDD (Fashion Design and Development), but we don’t know which year this Moodle email was sent to. 2 — So, I find the Assessment Brief of the particular unit, and follow highlighted link to see which year the email was sent to. . FIGURE 4: Stage 3 of data collection method STAGE 3 1 — I confirm the course 2 — I now know its Stage 2-Level 5, which means its BA Y2 . FIGURE 5: Stage 4 of data collection method STAGE 4 1 — I go on to UAL ActiveDashboards > Enrolments Summary Charts (UAL, 2025) 2 — Select LCF 3 — School of Design and Technology 4 — BA Fashion Design and Development 5 — locate year 2 6+7 — locate the Home and Overseas student numbers for 24/25 academic years 8 — make a sum of home (50) and overseas (39) = 89 students in y2 BA FDD at LCF . FIGURE 6: Stage 5 of data collection method STAGE 5 1 — sequentially add data to the cumulative spreadsheet, inputting minimal data, and anonymising it where necessary 2 — +89 (as per total from STAGE 4) to column E: Students/others in chain; +1 to column F: ‘+1 for me’ to be able to add the total for this column to know how many emails I personally received; +1 to column H: ‘Moodle’, to mark which emails were from Moodle, and which ones were not. . References Alvesson, M. (2003) Methodology for close up studies – Struggling with closeness and closure. Higher Education, 46, 167–193. Berners-Lee, M. (2020). How bad are bananas?: The carbon footprint of everything. London: Profile. D’Ignazio, C. and Klein, L.F. (2020) Data Feminism. London, England: MIT Press. Delamont, S. (2009) The only honest thing: Autoethnography, reflexivity and small crises in fieldwork. Ethnography and Education, 4, 51–63. Eriksson, T. (2010) Being native: Distance, closeness and doing auto/self-ethnography. Art Monitor, 8, 91–100. Haahr, M. (2024) Random.org – calendar date generator, Random.org. Available at: https://www.random.org/calendar-dates/ (Accessed: December 19, 2024). Hamdan, A. (2012) Autoethnography as a genre of qualitative research: A journey inside out. International Journal of Qualitative Methods, 11, 585–606. INTRAC (2017). Direct Measurement. [online] M&E Training & Consultancy. Available at: https://www.intrac.org/wpcms/wp-content/uploads/2017/01/Direct-measurement.pdf James Wilson, H. (2012) “You, by the numbers,” Harvard business review, 1 September. Available at: https://hbr.org/2012/09/you-by-the-numbers (Accessed: January 17, 2025). Jamieson, M.K., Govaart, G.H. and Pownall, M. (2023). Reflexivity in Quantitative research: a Rationale and beginner’s Guide. Social and Personality Psychology Compass, 17(4), pp.1–15. doi:https://doi.org/10.1111/spc3.12735. Kara, H. (2015) Creative research methods in the social sciences: A practical guide. Bristol, England: Policy Press. Poerwandari, E.K. (2021). Minimizing Bias and Maximizing the Potential Strengths of Autoethnography as a Narrative Research. Japanese Psychological Research, 63(4). doi:https://doi.org/10.1111/jpr.12320. Sage (2024) Research Methods Map, Sagepub.com. Available at: https://methods.sagepub.com/methods-map/ (Accessed: December 21, 2024). Sharon, T. and Zandbergen, D. (2017) “From data fetishism to quantifying selves: Self-tracking practices and the other values of data,” New media & society, 19(11), pp. 1695–1709. Available at: https://doi.org/10.1177/1461444816636090. UAL (2025) UAL ActiveDashboards, Arts.ac.uk. Available at: https://dashboards.arts.ac.uk (Accessed: January 7, 2025). WHO (2022) Infodemics and misinformation negatively affect people’s health behaviours, new WHO review finds, Who.int. Available at: https://www.who.int/europe/news-room/01-09-2022-infodemics-and-misinformation-negatively-affect-people-s-health-behaviours–new-who-review-finds (Accessed: January 19, 2025). Wolfram, S. (2012) “The Personal Analytics of My Life,” Stephen Wolfram Writings. Available at: writings.stephenwolfram.com/2012/03/the-personal-analytics-of-my-life (Accessed: January 17, 2025) […] “Data collection methods and tools”

g00s wrote a new post on the site GO—S. PgCert Blog.

Mon, 20 Jan 2025 19:40:48 +0000

Literature Review & Rationale:   The Environmental and Social Impact of Digital Technologies and Data Centres The environmental and social impact of digital technologies, data centres, and digital devices is becoming an ever increasingly intersectional problem, with pledges for impact reduction and resilience being made at all scales: global aims (UN, 2024); national aims (UKGOV, 2024); and sectoral aims (UniversitiesUK, 2023). At an institutional level University of The Arts, London has committed to the significant reduction of its carbon emissions (measured in CO2 equivalent/CO2e, which is a simplified metric where any greenhouse gas (N2O, methane, hydrofluorocarbons, etc) are converted into equivalent CO2 so they can be easily compared) by 2040 (UAL, 2023a; UAL, 2023b). The university has committed to 92% reduction (ibid.) in scope 1+2 carbon emissions (scope 1+2 are emissions in direct control of the institution, such as heating and energy usage). With scope 3 (indirect, supply chain, etc) reductions coming a decade later in 2050 (ibid.). This ambitious target is in a way essential as universities integrate more digital systems, but it also highlights the environmental challenges tied to our expanding digital footprint.These problems are vast — at an almost innumerable scale — and reduction pledges are made all the way through the human-wrought late-capitalist hierarchy (global, national, sectoral, institutional), but my feeling is that although large swathing actions are both justifiable and magnanimous, small measurable changes can happen at the individual personal level. These small actions of change have the capacity to leave us with the feeling of agency, and agency suggests hope (Zaki, 2024), rather than unsurmountable doom.This literature review explores the wider global and situational conditions for this Action Research Project, and some of the contextual challenges, focusing on data centres, the hidden carbon costs of digital technologies, and the intersectional impacts of digital infrastructure. I conclude by acknowledging all of these intersecting, complex, hyper-object-like (Morton, 2016) problems, and state that the rationale for this project is to look at my individual contribution through my work at UAL and intend to do something about it. FIGURE 1: (Malmodin et al., 2024) Illustration of the journey of data being sent through the internet, from laptop to the cloud servers running in a data centre Data centres (see Figure 1) are the hidden backbone of the modern digital landscape, storing everything from academic research to cloud storage of photos of cats. Yet, they come with a significant environmental cost. Recent studies estimate that global data centre energy consumption reached 196 terawatt hours (TWh) in 2020 (Mytton & Ashtine, 2022; Masanet et al., 2020). In addition, the networking systems that support these centres consumed 272 TWh in 2020, a 10% increase from 2015 (Malmodin et al., 2023). As demand for data transmission grows — up 600% from 2015 to 2022 (IEA, 2023) — power demand grows too, but interestingly there is not a direct relationship between gigabytes of data transferred and amount of energy consumed (Malmodin et al., 2024). This complex relationship needs further research and is out of scope for this project, and its on the cutting edge of network-based research. This already mentioned study by Jens Malmodin (2024) suggests there is not a linear causality between volume of data transferred and energy consumed, but it does suggest the storage of data uses energy, and that the cloud servers storing data have a permanent coefficient of energy usage.Institutions like ours, UAL have turned to cloud computing to reduce their direct (scope 1+2) energy use. Cloud services are more energy-efficient due to their centralised nature, where large providers like our provider, Microsoft manage highly optimised data centres. However, as The National Archive (2023) notes, the carbon savings reported by these providers often rely on rough estimates, and there is little transparency about the actual emissions associated with these services. The embodied carbon of cloud infrastructure—considering everything from device manufacturing to waste disposal—remains significant, even if direct emissions are reduced (The National Archive, 2023). Beyond the energy consumed by data centres and the transference of information, we must also consider the growing potential issue of ‘dark data’. Jackson and Hodgkinson (2024) describe this as the large volume of unused but stored data, which can be overlooked when calculating digital carbon footprints. This includes everything from old documents in cloud storage systems like OneDrive and Google Drive to archived media that are rarely, if ever, accessed. As Dourish (2017) argues, invisible digital storage has disconnected us from the immense physicality of information storage, fostering a kind of digital hoarding. In turn, this has escalated the demand for more and more storage capacity, with significant environmental consequences as described earlier. Furthermore, Siddik, Shehabi, and Marston (2021) highlight, U.S. data centres alone consumed 513 billion litres of water in 2018. Such figures bring attention to the hidden resource consumption of the digital world, which extends far beyond electricity use.Anecdotally, UAL in 2022 doubled the limit of academic staff OneDrive storage from 500gb to 1000gb (1tb) — what impact could this have caused when doubling the 2740 (HESA, 2024) academic staff’s data limit? For context thats 1,370,000gb more of storage, or 1,370terrabytes or 1.37petabytes. This extra storage is unlikely to be actually used by all staff of course, but the availability is real. The environmental impact of digital technologies is not felt equally to all people and environments. As Davis and Todd (2017), Davis (2023), and Nayar (2021) argue, the extractivist practices underpinning the manufacturing and production of digital devices disproportionately affect the global majority. The extraction of rare earth minerals needed for producing digital hardware often takes place in regions home to indigenous populations. This risks perpetuating colonialist environmental injustices, as the destruction of ecosystems and communities accompanies the growing demand for digital infrastructure (Davis, 2023).Whyte (2016) discusses how this extractivist model echoes colonial practices, where the resources of marginalised communities are exploited for global technological advancement. This colonial dynamic is increasingly evident in the digital world, where the benefits of technological progress are often unevenly distributed. As Swift (2022) argues, mainstream environmental movements often fail to address these intersectional issues, leading to a form of climate activism that overlooks the voices and struggles of the most affected people and areas (MAPA), who are disproportionately affected by the impact of climate change (Greene-Dewasmes, 2023). Therefore impact that digital technologies (or anything for that matter) has, both impacts more, and goes overlooked in global majority populations. Higher education institutions, such as UAL, can play a role in shaping the impact of digital technologies, ib both the dissemination of ideas and empirical actions. Barnett (2021) argues universities could become inclusive ecologies presenting the notion of the Ecological University, and questioning: How might higher education contribute to better futures for all in 2050? and How should higher education evolve to meet the challenges of this future? (ibid.). Higher education can of course contribute to a ‘better future’ by embracing human and nonhuman ecological sustainability and as part of that shaping and forging of responsible digital practices, but the unhelpful question remains — how? UAL, is of course attempting to do this, but as often is the way with anything intentionally radical but is actually institutionalised — it doesn’t go far enough.Many institutions are focusing on ‘greening’ their IT systems, The National Archives (2023) internal study suggests that this alone is not enough. Instead, universities (and indeed all of us) must reduce hardware waste, use and improve the efficiency of the devices they use, how we do this, none of us are sure. Mike Berners-Lee (2020) suggests most of the CO2e impact is embodied within the manufacturing and the extracted raw materials of the device itself, not its use. This ‘embodied carbon’ of the digital devices themselves, and the environmental costs associated with their production, life-cycle, and disposal, can be overlooked in analysis. While much research has focused on the energy consumption of data centres and networks there are still significant gaps. One key limitation is the lack of transparency about the empirical carbon emissions of cloud service providers. Companies like AWS (Amazon Web Services) and Microsoft Azure often provide only rough estimates of carbon savings, or none at all (Etsy, 2016). More reliable data on the carbon footprint of cloud services and the lifecycle of digital hardware is needed to form a clearer picture of their environmental impact.Additionally, while much of the focus has been on energy use, the intersectional social and environmental consequences for the global majority remain under-explored. Digital technologies, particularly data centres, appear to have a significant environmental and social impact that cannot be ignored. Universities like UAL are showcasing themselves as taking important steps toward reduction of impact, but as always more needs to be done to address the broader issues. As mentioned, the growing demand for digital infrastructure places a heavy strain on global resources, and the colonial dynamics of the manufacture of digital hardware exacerbate existing inequalities. These issues go way beyond what is capable for a university, or indeed even a continent to solve, or reduce enough to preserve ongoing human existence. So in this project, we do not try. But I do want to know what is my rough, very rough, estimated impact through my university-based work using digital technologies. I teach predominantly digital software and physical hardware, using computers and devices, so I am unavoidably contributing to the specified impact of digital tools and their perpetual desire. This project is in order to try and work out how I can personally reduce my impact and disseminate the above knowledge and encourage others to do so too. . References Barnett, R. (2021) Towards the Ecological University: A Concept Note. [Online] Available at: https://ronaldbarnett.co.uk/Futures%20Project%20-%20concept%20note.pdf [Accessed 19 January 2025]. Davis, H. (2023) “Waiting in Petro-time,” Environmental Humanities, 15(3), pp. 52–64. Available at: https://doi.org/10.1215/22011919-10745979. Davis, H. and Todd, Z. (2017) On the Importance of a Date, or Decolonizing the Anthropocene, Environmental Humanities, 16(4), pp. 761-780. Dourish, P. (2017) ‘The Materialities of Information: Digital Hoarding and the Changing Spatialities of Data’. Technology and Culture, 58(4), pp. 3-5. Etsy (2016) ‘Cloud Jewels: Estimating kWh in the Cloud’. [Online] Available at: https://www.etsy.com/codeascraft/cloud-jewels-estimating-kwh-in-the-cloud/ [Accessed 05 January 2025]. Greene-Dewasmes, G. (2023) Climate week messages from Most Affected People and Areas, World Economic Forum. Available at: https://www.weforum.org/stories/2023/10/mapa-voices-key-climate-week-messages-from-most-affected-people-and-areas/ (Accessed: January 20, 2025). HEPI (2024) Decarbonising higher education – the investment challenge, HEPI. Available at: https://www.hepi.ac.uk/2024/06/21/decarbonising-higher-education-the-investment-challenge/ (Accessed: January 20, 2025). Jackson, T. and Hodgkinson, I. (2024) ‘Decoding the Digital Carbon Footprint: Exposing the Global Data Challenge’, Chronicle.com. Available at: https://sponsored.chronicle.com/decoding-the-digital-carbon-footprint-exposing-the-global-data-challenge/index.html [Accessed 1 December 2024]. IEA (2023) ‘Global Data Centre Energy Consumption 2023’. International Energy Agency. [Online] Available at: https://www.iea.org/reports/global-data-centre-energy-consumption-2023 [Accessed 19 January 2025]. Masanet, E., Shehabi, A., & Koomey, J. (2020) ‘The Energy and Climate Impacts of Data Centres’. Nature Communications, 11(1), pp. 1-12. Mytton, M. & Ashtine, A. (2022) ‘The Evolution and Energy Footprint of Data Centres’. Journal of Sustainable Technology, 15(2), pp. 124-137. The National Archives (2023) ‘Digital Services and carbon emissions in the heritage sector: some preliminary findings – Archives sector’. Available at: https://www.nationalarchives.gov.uk/archives-sector/digital-services-and-carbon-emissions-in-the-heritage-sector-some-preliminary-findings/ (Accessed: 16 December 2024). Nayar, J. (2021) Not So ‘Green’ Technology: The Complicated Legacy of Rare Earth Mining, Harvard International Review. Available at: https://hir.harvard.edu/not-so-green-technology-the-complicated-legacy-of-rare-earth-mining/ (Accessed: January 15, 2025). Siddik, A., Shehabi, A., & Marston, S. (2021) ‘Water Consumption and Energy Use of Data Centres: The U.S. Context’. Journal of Environmental Impact Assessment, 37(3), pp. 245-260. Swift, J. (2022) ‘Climate activism without intersectionality isn’t enough: Why we need intersectional environmentalism’, Black Women Radicals. Available at: https://www.blackwomenradicals.com/blog-feed/leahthomas [Accessed 19 January 2025]. UAL (2023a) Carbon Management Plan – realising a net-zero carbon institution by 2040. Available at: https://www.arts.ac.uk/__data/assets/pdf_file/0021/213852/UAL-CMP-v1272.pdf. UAL (2023b) Environmental policy and management, UAL. Available at: https://www.arts.ac.uk/about-ual/climate-action-plan/change-the-way-we-operate/environmental-policy-and-management (Accessed: January 13, 2025). Whyte, K.P. (2016) ‘Is it Colonial Déjà Vu? Indigenous Peoples and Climate Injustice’. In: Humanities for the Environment, pp. 102-119. Routledge. Zaki, J. (2024) Hope for cynics: The surprising science of human goodness. Little, Brown Book […] “Literature Review & Rationale:  ”

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Mon, 20 Jan 2025 15:22:31 +0000

ARP Research QuestionWhat is the estimated environmental impact* of my everyday use of the UAL digital tools and services, as an academic staff member of UAL (LCF/LCC)? . *in terms of GHG emissions / kilograms of CO2e

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Mon, 20 Jan 2025 11:36:46 +0000

Ethics FormsETHICS FORM […] “Ethics Forms”

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Fri, 20 Dec 2024 19:27:23 +0000

Positionality StatementBoth in research and outside, […] “”

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Mon, 21 Oct 2024 14:38:44 +0000

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Mon, 21 Oct 2024 14:36:31 +0000

ARP Reference ListAcosta, A. […] “ARP Reference List”

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Mon, 15 Jul 2024 16:58:12 +0000

interesting yes, trying to find the comfort within the discomfort. I feel the university could potentially aim to evolve a set of iterative, cyclical approaches to diversity training and actual institutional changes, as Sara Ahmed (2012) suggests with priming rather than a kind of tick box for anti-racism work

In reply to - g00s wrote a new post on the site GO—S. PgCert Blog. Blog 03: RaceThe Channel 4 […] “Blog 03: Race”

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Mon, 15 Jul 2024 16:53:06 +0000

thanks for your comments, its interesting you pick up on this! This position is also reflected in your writing about ways of reiterating and signposting and wayfaring students to some of the resources available, such as the multi-faith spaces, and the Choudrey (2016) intersectional resources. In terms of teaching materials and curricula I think it…Read more

In reply to - g00s wrote a new post on the site GO—S. PgCert Blog. Blog Post 02: FaithKwame Anthony Appiah (2014) […] “”

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Blog 03: RaceThe Channel 4 […] “Blog 03: Race”

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Intervention Report My teaching […] “Intervention Report”

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Blog Post 02: FaithKwame Anthony Appiah (2014) […] “”

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Intervention Proposal Outline My […] “Intervention Proposal Outline”

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Blog Post 01: Disability DIS-abl […] “Blog Post 01: Disability”

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Blog Post 05: Looking aheadLooki […] “Blog Post 05: Looking ahead”

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Case Study 03Assessing learning […] “Case Study 03”

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Wed, 20 Mar 2024 12:30:00 +0000

Blog Post 04: Reflection on conversations As I’m reflecting on the first unit of the PgCert, I realise that the conversations that I’ve had have throughout these few weeks have been the most revelatory thing. At times they’ve felt utterly profound. I will name a couple of instances. One came in the discussion that served as my observation with my tutor. Linda observed and recognised something inside of me that had been niggling me for at least 2 years, it sat so very deeply inside of me I had struggled to grasp it. When teaching the discussed workshop I’d used a transmissive form of teaching, but even though I’d always struggled with doing it, I couldn’t not do it. Until the conversation with Linda alongside a feeling that had been growing throughout the unit — I realised that in only this one lesson I was doing exactly opposite to what we were discussing. Learning doesn’t happen by students being told things. A feeling of insecurity led me to feel I needed to overly explain, but it actually does nothing for learning. Shuell (1986) is appropriately quoted in John Biggs 2007 book saying “what the student does is actually more important in determining what is learned than what teacher does” (p. 52) Observing my peer Mahalia teach was equally enlightening. But it was the conversation afterwards that struck me — the way we were unpacking what had happened in her session lead me to form new understandings about how I might communicate with students in similar settings. She navigated a challenging student without realising quite what she’d done until we discussed it. Her question to the student “what would you do if you had to leave the piece in an exhibition tomorrow?” I felt was so keenly perceptual, that it felt illuminating. In response, the student thought about it for a second and realised themselves how much needed to be done, without being directly criticised. Amazing. These conversations, and many others have led me to form a reflective opinion that the summative assessment in the PgCert (as is often the case, and widely academically discussed) an admin formality to create markable boundaries. The learning I’ve absorbed has occurred within me through reflection, discussion, and observation, not writing quippy blog posts reflecting that I’ve done so. Example Module, Mark Russell, 2010 Looking at the short text from Mark Russell in 2010, I perceive that this unit structure is a typical example of a high-stake summative assessment, due in a couple of days, and the microteach as a formative assessment 30–40% through the unit. I bring this up as although I was encouraged to distribute the work across the term — and perhaps my learning would be different — doing the majority in a compressed time has meant that I both recall things from across the unit (which Dylan Wiliam (2020) suggests is great for learning, to activate prior knowledge from memory) and I am drawing connections between aspects of the unit and submission I perhaps otherwise would have missed. Summative isn’t all bad then. References AITSL (2020) Three principles and five strategies – Dylan Wiliam. May 5. Available at: https://www.youtube.com/watch?v=I7ERyN82Q5U (Accessed: March 18, 2024). Biggs, Biggs, J. B. and Tang, C. S.-K. (2007) Teaching for Quality Learning at university: What the student does. Buckingham, England: Open University Press. Russell, M. (2010) ‘Assessment Patterns: a review of the possible consequences’, ESCAPE project, University of Hertfordshire. Available at: https://blogs.kcl.ac.uk/aflkings/files/2019/08/ESCA […] “Blog Post 04: Reflection on conversations”

g00s wrote a new post on the site GO—S. PgCert Blog.

Mon, 18 Mar 2024 18:37:24 +0000

Case Study 01 Knowing and […] “Case Study 01”

g00s wrote a new post on the site GO—S. PgCert Blog.

Sun, 17 Mar 2024 16:51:19 +0000

Case Study 02Planning and […] “Case Study 02”

g00s wrote a new post on the site GO—S. PgCert Blog.

Sun, 25 Feb 2024 23:50:00 +0000

Blog Post 03 — Peripheral variation in written assessment feedbackAfter reading Allan Davies’ (2012) paper, I am reflecting on assessment and assessment criteria. I must admit that (except for the first couple of times I marked student work) I’ve always quite enjoyed what the ambiguity of assessment criteria affords — how the written assessment of submitted work varies slightly between tutors as perceptual opinions and varying awareness of details within the work are layered into the feedback. This variation, of course, does not present within the actual distinct grade, as these are mutually agreed and benchmarked. Through personal and undocumented observation, the writing is often encouragingly varied between marker — slight but specific tutorial emphasis on certain assessment criteria or descriptors are reoccurring. This array of discrete observations between tutors all written in a lecturer’s characteristic style highlights to me how important the discerning eye is to the art and design academic institution. As Davies (2012) says “students only need to understand whether they have addressed / met the outcome or not” and therefore I’m not convinced that the subtle idiosyncratic differences between tutorial feedback are consistently perceived by students themselves. These subtleties, however, are enjoyable for me to read as a tutor if you sneakily read another tutor’s feedback on the UAL Assessment Feedback tool. What indeed this tutor focused on to write about compared to what I would have said about this student’s submission, is perhaps a minor but common example of what Davies (2012) suggests — a focus on meaningfulness, rather than measurability. What is meaningful depends on who is looking — right? Not in the grandiose administrative sense of hitting or not hitting an assessment criterion, no, in the sense of what small but specific thing I am going to write about in the 150 word (for parity) feedback form. This small discretionary act is for me where I get to really say, within reason, what I like. Knowing that if I genuinely feel or perceive something and if needed, I could justify it, then it’s within the parameters of academic acceptance and it cannot change. To me, there is something in that. Could this feeling I get be a possible freedom within what Davies (2012) calls the bureaucracy of outcomes in art and design, and the resulting overwhelming of both teachers and students? I had a recent opportunity to defend nuance within written feedback. I marked 32 y2 BA students, the unit lead co-benchmarked 7 students, it was interesting that the unit lead had not marked at UAL before — but had at another university in the engineering department. During benchmarking variation in writing styles came up: they asked me to be more like them in content. I said it probably wasn’t possible because different elements of the submission would excite me compared to what presented to them, but I would be happy to include any specific things if required. Satisfied with my response, they allowed me to continue making my challenging decisions over which students evidenced “development of intuition, inventiveness, imagination, visualisation, risk-taking, etc.” (Davies, 2012) References Danvers, J. (2007) “Assessment in the arts: qualitative and quantitative approaches,” Networks, University of Brighton, (1), pp. 14–19. Davies, A. (2012) ‘Learning outcomes and assessment criteria in art and design. What’s the recurring problem?’, Networks, Issue 18. Available at: http://arts.brighton.ac.uk/projects/networks/issu […] “Blog Post 03 — Peripheral variation in written assessment feedback”

g00s wrote a new post on the site GO—S. PgCert Blog.

Mon, 05 Feb 2024 18:20:37 +0000

Microteach Reflection In my […] “Microteach Reflection”

g00s wrote a new post on the site GO—S. PgCert Blog.

Mon, 15 Jan 2024 15:17:00 +0000

Blog Post 02 — Workshops 01 + 02NB — this post I wrote i […] “”

g00s wrote a new post on the site GO—S. PgCert Blog.

Fri, 12 Jan 2024 18:14:00 +0000

Blog Post 01 — Reflections on the first reading In this post I will summarise […] “”

g00s wrote a new post on the site GO—S. PgCert Blog.

Wed, 13 Dec 2023 11:33:41 +0000

I am an artist and designer, I teach at LCF and LCC, my title is Lecturer in Creative Communication. I teach mostly communication and graphic design, moving image, experiential media, and at LCC I teach on the […]