For UK universities, league table rankings are prominent ways to measure an institution’s prestige. League tables include the Complete University Guide, the Guardian and the Times/Sunday Times rankings. League tables are published by subject area and at the overall level, and can take into account a broad range of metrics in creating their indices of university quality. League table rankings are taken seriously by institutions for many reasons, not least of which being the effect on student recruitment. A prominent position in a league table is thought to be a factor in students’ application preferences. As such, a higher ranking could be a predictor of greater competitiveness for places, and thus of the ability to recruit the highest-performing students.
However, league tables are often responsive to metrics which can vary significantly in the short term, such as student satisfaction and expenditure on academic services or facilities per student. University reputation may be a more long-term value – influenced, to be sure, in the short-term by factors such as league table rankings and scandals, but with a more permanent component. As such, evaluating university league table rankings against different measures of the name recognition and reputation of an institution can provide insights into the potential relevance and power of league table rankings in influencing students’ application choices. Here, I use a novel way of measuring the name recognition of UK universities, and analyse this in comparison to league table rankings.
This data comes from the trivia website Sporcle.com, for which I designed a quiz which allows users to attempt to name as many UK universities listed in the 2021 Complete University Guide as possible in twenty minutes. Users type the names of universities into the answer bar, which once accepted then appear in the website’s interface. The quiz was structured to display universities in the order of their 2021 Complete University Guide ranking, making ranking salient for users as part of the design. But there was no prompt, incentive or requirement to enter universities in ranking order. At the time of writing, the game has been attempted 3,862 times, across three distinct versions based on the 2015, 2019 and 2021 league table rankings. The most recent version (2021) has been attempted the fewest times, however the results are very similar to previous iterations. In the analysis below, I use figures from the 2021 version, but findings were generally consistent.
In the most recent iteration of the game, 130 distinct universities could be entered by users. The most recognised universities were, unsurprisingly, Oxford (99.1%) and Cambridge (98.9%). These are also the top two highest ranked universities in the Complete University Guide. Other highly recognisable universities were generally those in major UK cities: Manchester (95.1%, ranked 17th=), Edinburgh (94.3%, ranked 15th), Leeds (93.8%, ranked 16th), Birmingham (93.6%, ranked 13th) and Glasgow (93.1%, ranked 19th).
Of the 20 most recognised universities, the lowest ranked in the league table was Liverpool (93.1%, ranked 33rd). All of the other top 20 recognised universities ranked in the top 30 of the league table. This suggests that there is a strong association between elite status in the league table and public awareness and recognition of universities.
The most well-recognised universities which ranked in the bottom half of the league table (65th or below) are Plymouth (83.2% – 27th most recognised, ranked 71st) and Brighton (80.5% – 31st most recognised, ranked 112).
The least recognised institutions are generally also those at the lower end of the league tables. The 130th ranked university in the league table is also the least recognised institution – Ravensbourne University London (17.2%). The other least recognised institutions are Newman (21.4%, ranked 120), Royal Agricultural University (22.8%, ranked 114) and Bishop Grosseteste (27.6%, ranked 106).
However, in contrast to the upper echelons of the recognition ordering, several universities amongst the least recognised in the set are from the upper half of the league table. Appearing 124th to 126th in the recognition stakes in the game are St. George’s (30.7%, ranked 59), University for the Creative Arts (29.6%, ranked 44) and Harper Adams (28.1%, ranked 42). This phenomenon was not broadly replicated in the data, but there were several other highly-ranked institutions which had relatively low levels of recognition, e.g., Heriot-Watt (51.1% – 96th most recognised, ranked 29) and SOAS (53.8% – 88th most recognised, ranked 37). There are very few highly ranked universities with high levels of recognition, however, other than the aforementioned Plymouth and Brighton. This suggests that although highly recognised universities are always rated as high quality per the league table, a strong league table performance is insufficient to ensure public awareness and recognition. The cases of Heriot-Watt, Harper Adams and the University for the Creative Arts are particularly demonstrative of this phenomenon.
I analysed the relationship between league table ranking (1-130) and percentage recognition in the game (0-100%), testing for the expected association between the values. The relationship was statistically significant at p < 0.01, with an R2 value of 0.4936. See Fig. 1, below, for a scatterplot of the values depicting the correlation between ranking and recognition. This suggests that there is a fairly solid association between the users’ awareness of an institution and its ranking in the league table: the higher ranked the institution, the more likely users were to identify it. Of course, there is insufficient information here to draw causal inferences regarding an effect of league table ranking on institutional recognition – there are plausible causal relationships in the opposite direction (reputation and recognition may have an effect on league table ranking through a number of variables considered by league table creators, such as entry standards and graduate prospects), and it is highly likely that the correlation is at least in part due to common causes such as the underlying quality of the institution.
Several other factors have a noticeable effect on the recognition of institutions by users, but do not seem to be related to league table performance. As previously stated, institutions which are located in major UK cities seemed to be more frequently identified by users. This is likely to be due to a number of overlapping effects. First, users are likely to remember institutions which are close to their homes, located in places they have visited, or larger institutions which therefore have a more prominent profile. In each case, a large city-based university is likely to have an advantage in recognisability. In particular, larger institutions are more likely to be sited in or associated with larger cities, and to be more recognisable to the public. We observe that of the top 20 largest UK cities by population (excluding London), amongst those which have a university which bears their name, the recognition rankings were very high:
|City/University||Recognition (% – Ranking)||League Table Ranking|
|Birmingham||93.6% – 6th||13th|
|Leeds||93.8% – 5th||16th|
|Glasgow||93.1% – 7th||19th|
|Sheffield||87.8% – 19th||28th|
|Bradford||67.2% – 52nd||69th|
|Manchester||95.1% – 3rd||17th|
|Edinburgh||94.3% – 4th||15th|
|Liverpool||93.1% – 9th||33rd|
|Bristol||90.3% – 12th||14th|
|Cardiff||93.1% – 8th||30th|
|Leicester||83.9% – 26th||38th|
|Coventry*||75.9% – 39th||54th|
|Nottingham||88.9% – 16th||20th|
|Newcastle||90.9% – 10th||23rd|
|Sunderland||65% – 57th||108th|
|Brighton||80.5% – 31st||112th|
|Hull||77.4% – 33rd||64th|
|Plymouth||83.2% – 27th||71st|
*Coventry is most prominently home to Warwick University. However, Coventry University is used here to depict the relationship between city name recognition and university recognition.
As we see in Fig. 2, in every case, universities which bear the name of a major city outperformed their league table ranking in terms of recognition by the users. This may further be explained in part by the comparative ease of remembering the names of such institutions – users did not have to remember anything beyond the name of the city in which the institution is located to identify it. By contrast, high-ranking institutions in the league table which have names which do not solely relate to their location showed a tendency to underperform their league table ranking in terms of recognition.
|University||Location||Recognition (% – Ranking)||League Table Ranking|
|London School of Economics (LSE)||London||84.3% – 25th||3rd|
|Imperial College London (Imperial/ICL)||London||82.3% – 28th||5th|
|University College London (UCL)||London||88.5% – 17th||10th|
|King’s College London (King’s/KCL)||London||88% – 18th||20th=|
|Royal Holloway (RHUL)||London||57.8% – 75th||24th|
|East Anglia (UEA)||Norwich||77.2% – 34th||25th|
|Queen’s Belfast (Queen’s)||Belfast||73.4% – 46th||27th|
|Heriot-Watt||Edinburgh||51.1% – 96th||29th|
|Surrey||Guildford||72.1% – 47th||34th|
|Queen Mary (QMUL)||London||63% – 61st||35th=|
|Strathclyde||Glasgow||55.7% – 79th||35th=|
|School of Oriental and African Studies (SOAS)||London||53.8% – 88th||37th|
|Sussex||Brighton||76.1% – 37th||40th|
In Fig. 3, we see that most institutions whose names did not consist of the name of the city in which they are located ranked considerably lower in the recognition data than in the league table. Notably, Brighton University (80.5%) was more recognised than Sussex University (76.1%) despite both being located in Brighton, and despite Sussex outperforming Brighton in the league table by 72 places (112th vs. 40th).
Specialist universities which teach particular fields of study also tended to underperform their league table ranking in terms of recognition – social science university LSE, science university Imperial College, agricultural university Harper Adams, arts universities such as the University of the Creative Arts and University of the Arts London, and medical college St. George’s, all were considerably less likely to be identified by users in comparison to their league table ranking.
There are numerous shortcomings to this approach, which limit the ability to make inferences from this data. Users self-selected to play the game, which renders it likely that those who attempted the quiz have considerably greater than average interest in and knowledge of British universities. This has a specific, if limited, effect on inferences from the data – we should avoid inferring that the percentages of recognition for a given university are reflective of broader levels of recognisability in the country. However, it is reasonably likely that the relative levels of recognition amongst a knowledgeable community will be similar to the relative levels of recognition amongst a broader population, albeit at considerably higher absolute levels across the board. In other words, while a score of 90% should not be taken as evidence that, in a wider sample of the population, 90% of individuals would be able to name the institution as a UK university, it can be taken as some evidence that the university would be more recognisable than a lower-scoring institution.
Furthermore, there is no guarantee that the game was played by distinct individuals each time: a single individual could repeatedly attempt the game – for instance, seeking to improve their score. Repeated attempts by a single individual might skew the data towards that individual’s recognition profile. This effect could not be identified or controlled for in the context of this data-gathering approach.
Finally, there may be some effects of overlap between university names in the observed results. This overlap effect is likely to advantage older institutions. The game was designed to accept different variants upon the names of institutions. For instance, for universities widely known by initials such as “London School of Economics”, the game would accept the initials (i.e. “LSE”). In some cases, multiple institutions based within the same city each include the city name – for instance, “Nottingham” and “Nottingham Trent”. In cases of complete overlap such as these, it was not possible to reasonably create a gameplay environment in which users could enter the full name “Nottingham Trent” without the interface first registering “Nottingham” as a correct answer. So, a user attempting to signal recognition of Nottingham Trent University would count first as having recognised Nottingham University. Universities with such suffixes (e.g., Birmingham City, Southampton Solent, Bath Spa, Liverpool Hope, Liverpool John Moore’s, Sheffield Hallam, etc.) are generally lower ranked in the league tables and tend to be more recently founded institutions. This could therefore reinforce an apparent connection between league table ranking and recognition. To attempt to correct for this effect, any unique university suffixes in these situations (e.g., ‘Hope’, ‘John Moore’s’, ‘Napier’, ‘Solent’, ‘Hallam’, ‘Trent’) were accepted in isolation – i.e., entering “Trent” alone was accepted as recognising Nottingham Trent University. As such, it was possible to register recognition of a university such as Nottingham Trent University without also registering recognition of Nottingham University.
In some cases, university names had more complex overlap – for instance “Birmingham City” and “City, University of London”. In this case, “City” was coded to refer to “City, University of London”, and “Birmingham City” would need to be entered in full. In most such cases, the full name of the university was required, such as where multiple universities shared the suffix “Metropolitan” (“Met” was also accepted). But in the case of “City” University, as the university in question is primarily known by that name alone, it was assigned that designation. This has the consequence that some users may have entered “City” intending “Birmingham City” and contributed towards the figures for recognition of City University of London.
Public trivia websites such as Sporcle.com can offer a novel source of data on public awareness and recognition of information, applicable to a range of phenomena, including awareness of the range of universities in the UK. By designing quizzes on such platforms and making these available to the public, researchers can gain access to interesting data streams which can inform discussions of public perceptions and knowledge.
The data on the awareness of Sporcle users of different UK universities is suggestive that while universities which are well-recognised by the public overwhelmingly are those which score highly in league tables such as the Complete University Guide, a good performance in such a league table is not itself sufficient for correspondingly high levels of recognition. There are institutions which remain relatively unknown to the public despite good rankings in the league tables. A range of other factors could be identified which contribute to name recognition and awareness, including institution size, location, and correspondence between the institution’s name and widely-recognised, populous city names. These factors are likely to influence both recognition and thus reputation, independently of league table performance. There is a statistically significant association between league table position and public awareness in this dataset, though more research would be needed to identify and reach conclusions about the nature of this relationship.
Most recent edit: 01/11/2022.