First year undergraduates make use of recordings to overcome the barriers to higher education: evidence from a survey

Jill R.D. MacKay*

Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Roslin, United Kingdom

Received: 4 June 2020; Revised: 19 August 2020; Accepted: 20 August 2020; Published: 16 October 2020


In this study, 295 (13.8% response rate) first year students from a large, Scottish, Russell-Group university were surveyed on their attitudes to and use of lecture recordings in 2018. Kruskal–Wallis tests were used to compare the ranked responses between students in different categories relevant to monitoring equality and diversity, such as carer status (5% of respondents), learning adjustments (9% of respondents) and non-native English speakers (27% of respondents). Students most commonly watched a full lecture by themselves when studying with 60% watching a full lecture at least once a week. Non-native English speakers were more likely to watch specific parts of a lecture more frequently (H2 = 8.52, p = 0.014). Students with learning adjustments more often reported being unable to find a resource (H3 = 8.356, p = 0.039). There was no effect of students’ language, carer status or learning adjustment status on their self-reported likelihood to attend a lecture, likelihood to change note-taking behaviour or concentrate on a lecture if it was being recorded. Non-native English speakers were still more likely to worry about keeping up with a lecture, even when it was being recorded (H2 = 10.492, p = 0.005). In conclusion, lecture recording has different impacts on students from different backgrounds, and inclusive lecture recording education policies need to consider this impact.

Keywords: lecture recording; technology-enhanced learning; blended learning; inclusive learning

*Corresponding author. Email: jill.mackay@ed.ac.uk

Research in Learning Technology 2020. © 2020 J.R.D. MacKay. Research in Learning Technology is the journal of the Association for Learning Technology (ALT), a UK-based professional and scholarly society and membership organisation. ALT is registered charity number 1063519. http://www.alt.ac.uk/. This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), allowing third parties to copy and redistribute the material in any medium or format and to remix, transform, and build upon the material for any purpose, even commercially, provided the original work is properly cited and states its license.

Citation: Research in Learning Technology 2020, 28: 2476 - http://dx.doi.org/10.25304/rlt.v28.2476


Lecture recording, the practice of capturing all or parts of a teaching activity, is not a novel technology and has been utilised in some form since the late sixties (Zawacki-Richter and Naidu 2016). Advances in technology, particularly the ability to automatically store and retrieve large amounts of video data, have prompted a boom in the technology’s provision in institutions across the higher education (HE) sector (Newton et al. 2014). This has also led to sector-wide discussion regarding whether lecture recording may devalue the classroom experience (Anderson and McGreal 2012; Conole et al. 2008).

The implementation of lecture recordings has the potential to transform the learning space, and staff and students approach the concept differently (MacKay 2019b). Danneels (2004) defines a ‘disruptive technology’ as one which eventually supplants a traditional technology, but lecture recording is often described as a supplementary resource by higher education institutions (HEIs; MacKay and Bovill 2020). Therefore, there is considerable interest in how students might use lecture recordings. There has been a work attempting to characterise the patterns of student use, for example Phillips et al. (2010) proposed five behavioural patterns based on the review of how often and when approximately the 500 students watched recordings. ‘Conscientious’ students showed regular revision over time, ‘Crammer’ students watched a large volume of recordings close to exam periods, ‘Good-Intentioned’ students began watching large volumes of recordings and then decreased, ‘Repentant’ students watched more recordings after class tests and ‘Bingers’ watched recordings in large batches. More recently, Ebbert and Dutke (2020) performed cluster analyses on 1079 students in a German university and identified five behaviour patterns. Approximately 27% of students were ‘frequent repeats’ who watched recordings in their entirety multiple times; another 27% watched whole lectures repeatedly, but only selecting certain lectures; 10% of students watched parts of a recording repeatedly; 15% of students watched selected parts of a recording rarely, potentially to review only topics they were unsure of; and 16% of students showed increased absenteeism in class, watching the recordings instead, usually completely.

As we explore how students may be using lecture recordings, we can aim to provide support for what strategies are more successful. There is presently a limited evidence-based guidance regarding supporting students to use lecture recordings (Nordmann and McGeorge 2018). However, both staff and students are receptive to exploring how lecture recording can be used to support inclusivity and diversity (MacKay 2019b), particularly when recordings are viewed as a supplementary resource. Inclusive education, which often encompasses other terminologies such as inclusivity, diversity, equity, equality and widening participation, is a priority in many countries. For example, Scotland aims to have 20% of HE entrants from the 20% of most deprived backgrounds within the country by 2030 (Scottish Funding Council 2018). HESA defines ‘widening participant’ in education as the participation of groups that are under-represented in HE, relative to the population as a whole (HESA, no date). This is often characterised as low-income areas but can include Black Asian and Minority Ethnic groups, students with a range of gender and sexual identities and students with disabilities. Widening participation strategies have been considered the outcome of the neoliberalisation of HE, resulting from a desire for a more educated workforce (Kettley 2007), and this can lead to inclusivity in education being discussed performatively or with ‘innocent fraud’, as the education sector aims to sell a palatable product to society (Slee 2006). This presents the sector with a challenge: how can we meaningfully engage with inclusive education initiatives without contributing to the underlying fraud? Berlach and Chambers (2011a) suggest that inclusivity work start with clear definitions regarding what is meant by terms, and there are many examples where a lack of clarity regarding what is meant by inclusivity hampers progress towards an inclusion goal (Berlach and Chambers 2011b; Minnaert 2014).

There are multiple definitions of inclusive education, but the definitions generally agree that inclusive education is an approach to diverse education environments that ‘supports teachers to respond to individual differences between learners, but avoids the marginalisation that can occur when some students are treated differently’ (Florian 2014). In this paper, I will use the European Universities Association definitions of diversity, inclusivity and equality (Claeys-Kulik and Jørgensen 2018) as this is relevant sector level guidance for defining the terms, and so may allow for more generalisability of this papers’ findings to other institutions which follow the same guidance. As per their definition, diversity refers to the demographic and social composition of a group, encompassing factors such as sex, gender, age, sexual orientation, ethnicity and cultural associations, religions, health conditions and socio-economic background. With this definition, widening participation agendas prompt HEIs to strive for diverse student populations. Inclusivity refers to the actions taken to ensure a diverse population is feel valued. Inclusive educational policies require the HEI to be aware of the differences and privileges within their student body. Equality can then be thought of as the end goal for widening participation agendas, as it acknowledges that the student body has different starting points, and that specific barriers are faced by some students, which need to be overcome for those students to meaningfully engage. The underlying philosophy of this paper is that widening participation is a positive outcome for HEIs, but that I am conscious of the ‘innocent fraud’ of performatively working on inclusion. Inclusivity can be challenging to assess and measure (Dimitrellou, Hurry, and Male 2020), and often this can mean that individuals from under-represented groups are asked to do more labour to represent themselves or explain their needs. Recognising and acting upon inequities is a key component of critical allyship (Nixon 2019), and so this work aims to explore and characterise how the Claeys-Kulik and Jørgensen definitions of equality, diversity and inclusion can be observed in data about student use of lecture recording.

At an institutional level, digital teaching resources can support widening participation policies in four main areas as per Lane (2012). The availability, affordability, accessibility, and acceptability of the resource to the student. There is a prevalence of literature debating whether recordings are a supplement or a complement to traditional education, but very little exploring the mechanisms through which recordings might complement lectures. For example, one study found that women, older students and students who lived away from campus were more likely to make use of recorded resources (O’Brien and Verma 2018). This may well not be surprising, given that transport inequality is a significant barrier to widening participation in HE (Kenyon 2011) and the unequal care burden on women (Balka, Green, and Henwood 2010; Chopra 2015). Another study found no observed difference in achievement across students who made use of lecture recordings, but did find that those students who were non-native English speakers or had learning adjustments made far higher use of the learning recordings (Leadbeater et al. 2013). While Ebbert and Dutke (2020) and Phillips et al. (2010) did not find consistent evidence of social differences between their groups, there is still work to be done exploring how social factors influence student use of recordings. In this study, I explore factors relating to under-represented groups in academia, including carers, those with learning adjustments and non-native English speakers, and their influence on student recording use in a purposeful sampling of first year undergraduates at the University of Edinburgh, and I use this evidence to provide suggestions for inclusive and equitable study guidance.

Materials and methods

Ethics approval

This study was approved by the School of Education Ethics Sub-Committee at the University of Edinburgh, reference number 1218, and also by the Central Student Surveys Ethics Committee (reference 10042018).


This project was part of a larger evaluation of implementing a lecture recording system at the institution, see MacKay (2019b) for full details. In this study, I report quantitative analyses of the student survey, which was thematically analysed and reported upon in the previous study. The overarching study occurred over a non-consecutive 14-day period of industrial action on the behalf of academics.

Participants and recruitment

To avoid contributing to survey fatigue within the institution (Porter, Whitcomb, and Weitzer 2004), I decided to target a specific cohort of students to capture a range of experiences. To do this, I first explored other sources of data, including the previous year’s course evaluation questionnaires (CEQ) across the institution. Through the examination of the CEQ-free text responses, eight schools were selected as a sample of a range of user experiences, for example schools where students had praised lecture recording, schools where students had expressed frustration with lecture recording and schools with neutral lecture recording responses. Schools were also selected to capture experiences across the three colleges: the Science & Engineering College, the Medicine & Veterinary Medicine College and the Arts, Humanities and Social Sciences College.

First year students were sampled to avoid conflating the results of the present lecture recording system with other systems that schools may have used. The institution’s Central Surveys Team distributed a Jisc Online Surveys link to eligible students via student’s email. The survey opened on 2 May 2018 and a reminder was circulated on 14 May. The survey closed on 1 June (duration: 29 days). It was sent to 2125 first year students across the eight schools. A total of 295 students responded (13.8% response rate) and all respondents answered all questions. There was no need to exclude any responses.

Survey items

To capture student experience during this evaluation, the original intent was to use a series of focus groups to explore student feeling and utilisations of recordings. As industrial action was likely to occur prior to the examination period, and collecting data on students would not be appropriate near the examination diet, I devised a survey to explore student attitudes and beliefs about lecture recording. A series of questions was developed in consultation with working groups across the institution, who consisted of academic staff, professional services staff, student interns and student representatives. The questionnaire design process followed Artino et al.’s (2014) seven-step process as much as possible within the time constraints of the impending industrial action, with the working group feedback and student interns serving as interview feedback, and piloting.

As we were interested in how lecture recording may impact under-represented groups in HE, respondents were asked to if they identified as having a learning adjustment schedule, had English as a first language or considered themselves as a carer. Students were also asked to give their gender identity and age. All demographic questions were optional and featured a ‘prefer not to say’ response. Respondents were asked questions about the frequency of accessing lectures and recordings as a 5-point scale (at least once a day, at least once a week, at least once a month, less than once a month, never). Students were also asked about their behaviour in recorded lectures in comparison to non-recorded lectures with a 5-point Likert-like scale with responses ranging from ‘Much Less Likely’ to ‘Much More Likely’. There was also a free text response. The full survey is available as an appendix.

Data analysis

Data were exported from Jisc Online Surveys and processed with R (Version 3.5.2, ‘Eggshell Igloo’, R Core Team 2019). Likert-like questions were analysed using the ‘likert’ package (Bryer and Speerschneider 2016) to explore differences in item responses by groups. Kruskal–Wallis tests were used to compare ranked data between groups of respondents, and these are interpreted through the use of post hoc testing (one- and two-tailed multiple comparison tests to establish which group is different, and Jonckheere-Terpstra tests to establish whether a pattern exists across multiple groups). Due to the relatively small dataset in comparison to the number of tests run, these results have been interpreted conservatively. Participants with missing demographic data were removed from that particular test.

A total of 159 (53.9%) respondents elected to leave a comment regarding lecture recording in the survey. As thematic analyses had already been performed on this dataset, a natural language processing approach was taken to provide comparable results across datasets as per MacKay (2019a). This analysis was undertaken using the ‘tidytext’ package (Silge and Robinson 2016). Two measures of interest were explored: the term frequency and term frequency-inverse document frequency (TF-IDF). The term frequency is a count of how often a word appears within a body of text and is a relatively blunt measure of the term’s importance (Rosen and Russell 1957). The term can then be analysed through the use of a sentiment analysis, to explore what negative and positive words are being used within a body of text. The TF-IDF is a measure of how unique a term is within a body of text in comparison to another body of text. Using the tidytext approach, student comments can be assigned a different group (e.g. carer comments vs. non-carer comments) and the TF-IDFs between groups can be compared. If one group has particularly high TF-IDFs, that is an indication they may be using that word more frequently than the comparison group, and it may be a topic of interest for that group.


Responses were received across all sampled schools, from 12 students in School F (Science and Engineering) to 51 students each in Schools B (Medicine and Veterinary Medicine) and H (Science and Engineering). Sixty-nine percent of respondents identified as a woman, the majority (87%) did not state they had any learning adjustments, 73% were native English speakers and 93% had no caring responsibilities (Table 1).

Table 1. Demographics of respondents including school and Course Evaluation Questionnaire responses.
School College CEQ satisfaction with lecture recording resources n %
School A Science and Engineering Negative 48 16
School B Medicine and Veterinary Medicine Negative 51 17
School C Arts, Humanities and Social Sciences Negative 37 13
School D Science and Engineering Mixed 30 10
School E Medicine and Veterinary Medicine Mixed 31 11
School F Science and Engineering Positive 12 4
School G Arts, Humanities and Social Sciences Positive 35 12
School H Science and Engineering Positive 51 17
As a man 83 28
As a woman 204 69
In another way 1 0
Prefer not to say 6 2
No response 1 0
Learning adjustments
Learning adjustments 26 9
No learning adjustments 257 87
Not sure 11 4
Prefer not to say 1 0
Native language
Native English speaker 215 73
Non-native English speaker 79 27
Prefer not to say 1 0
Caring responsibilities
Carer 15 5
Not a carer 273 93
Not sure 7 2

Student use of recorded lectures

Students considered that their most common use of recorded lectures was to watch the full lecture by themselves with 60% responding that they watched full lectures at least once a week or more frequently (Table 2). Forty-nine percent watched the specific parts of a recorded lecture that often, and only 3% watched a recorded lecture with their classmates that frequently.

Table 2. N (%) of respondents who have engaged with recorded lectures.
Lecture habits Frequency n %
Wanted to go back and watch but been unable 1. At least once a day 18 6
2. At least once a week 59 20
3. At least once a month 86 29
4. Less than once a month 102 35
5. Never 30 10
Watched a full recorded lecture 1. At least once a day 39 13
2. At least once a week 139 47
3. At least once a month 74 25
4. Less than once a month 27 9
5. Never 14 5
Watched a recorded lecture with classmates 1. At least once a day 1 0
2. At least once a week 9 3
3. At least once a month 31 11
4. Less than once a month 44 15
5. Never 210 71
Watched specific parts of a lecture 1. At least once a day 33 11
2. At least once a week 113 38
3. At least once a month 79 27
4. Less than once a month 39 13
5. Never 31 11

There was no difference in students’ reported frequency of watching lectures, or being able to obtain lectures by their carer status, whether they were a native English speaker, whether they had learning adjustments, or gender. However, non-native English speakers were slightly more likely to watch specific parts of a lecture more frequently (H2 = 8.52, p = 0.014; Figure 1).

Fig 1
Figure 1. Student self-reports of lecture watching behaviour by native language (n = 294).

Students generally were able to find recorded materials when they wanted them, with 45% of students reporting that they experienced trouble in finding recorded materials less than once a month. However, 26% of students reported being unable to watch a recorded lecture weekly or more frequently. Students with learning adjustments were more likely to report being unable to watch a lecture back again at least once a week (H3 = 8.356, p = 0.039; Figure 2), and this was significantly different from students with no learning adjustments in two-tailed post hoc testing. While this is a small effect observed, it is worth highlighting for future research in this area.

Fig 2
Figure 2. Student self-reports of ability to find recordings when needed by learning adjustment (n = 292).

Student behaviour

Students were asked how likely they were to perform certain behaviours if they were in a recorded lecture. Only 24% of students reported that they might be less likely to attend a lecture if they felt it was being recorded (Figure 3), and this was not affected by the school, whether or not the student had a learning adjustment, whether they were a native English speaker, their carer status or gender. Sixty-nine percent of students thought there would be no difference in their concentration levels when lectures were recorded, and there was no difference across student status and school. Similarly, 67% of students felt there would be no difference in their likelihood to take notes during a recorded lecture; however, there was a significant trend for students who identified as male to consider themselves less likely to take notes during recorded lectures. As these data included a small number of students who did not identify as male or female, a comparison was made strictly between students who identified as male (n = 83) and students who identified as female (n = 204), and this difference was no longer significant (Figure 4). Eighty-one percent of students reported that there would be no difference in their likelihood to answer questions in a recorded lecture (Figure 3), with 10% even reporting they would be more likely to answer questions in a recorded lecture. Slightly fewer (77%) students reported there would be no difference in their likelihood to ask questions in a recorded lecture. There was some evidence that female students would be less likely to answer questions in recorded lectures, but this was again insignificant when compared strictly against male students (Figure 4). Although this difference did not remain significant, it is worth noting that, in total, 24 students (8.1% of total) reported they would be less likely to answer questions in a recorded lecture, and of these 24, 79% identified as a woman. There was a suggestion that students with learning adjustments may also be less likely to ask a question in a recorded lecture; however, this difference was small (H3 = 10.47, p = 0.015; Figure 5) and did not remain significant during post hoc testing.

Fig 3
Figure 3. Student self-reports of behaviour in recorded lectures.

Fig 4
Figure 4. Student self-reports of question-asking and note-taking behaviour during recorded lectures by gender.

Fig 5
Figure 5. Student self-reports of note-taking behaviour by learning adjustment.

How do recorded lectures affect student worry?

Seventy-four percent of students responded that they would be less likely to worry about keeping up with a lecture when it was recorded, while 87% of students felt there would be no difference in their concerns regarding their own privacy, and 73% felt there would be no difference regarding their worries about giving the wrong answer in class (Figure 6).

Fig 6
Figure 6. Student self-reports of worry in recorded lectures.

Worries about keeping up, giving the wrong answer and privacy concerns were not affected by school or student status; however, non-native English speakers were significantly more likely than native English speakers to worry about keeping up with lectures even when the lectures were recorded (H2 = 10.492, p = 0.005; Figure 7), which remained significant in a post hoc two-tailed test.

Fig 7
Figure 7. Student self-reports of worrying about keeping up with materials in lectures by native language.

How do students study with recorded lectures?

Students were asked how useful lectures were for exam revision and given a series of ranked options (not good, okay, good and best) and an ‘other’ category, which had the option to provide more information. The majority of students (62%) considered lectures as a good resource for exam revision (Figure 8), alongside reading other text and practicals. Perhaps of concern, 28% of respondents considered lectures were the best resource for exam revision as they ‘gave all the information’. Only one student elected to provide ‘other’ information, and they considered lecture recordings extremely beneficial. There were no significant differences in a Chi2 test in how students responded to this question if they were non-native English speakers, carers or had learning adjustments.

Fig 8
Figure 8. Student rating of lectures’ usefulness as a study aid.

Free text exploration

Across the 159 students who elected to leave a comment regarding lecture recording, a simplistic sentiment analysis suggests that negative feeling expressed in these comments is predominantly around ‘worry’ and being ‘unsure’, which is likely to be about how lecture recordings alleviate these feelings, given students did not report worrying more in lecture recordings above. Positive contributions to the sentiment come mainly from lectures being discussed as ‘valuable’ or as a ‘support’ (Figure 9).

Fig 9
Figure 9. Words used in free text comments and their contribution to sentiments.

Perhaps unsurprisingly, people with learning adjustments are more likely to use the word ‘disability’, although there were no notable differences across gender, native language or carer status.


Supporting and promoting equality, diversity and inclusion in HE is a powerful motivator for adopting lecture recording (MacKay 2019b). This may not be surprising as student ‘stories’ are an effective method of promoting support for students with dyslexia in workplace placements (Tee and Cowen 2012). However, it is often challenging in education to identify what social norms, epistemological assumptions and barriers may exist for students in education systems (Aikman and Dyer 2012), especially as most senior academics in decision-making roles are more likely to come from privileged backgrounds (Aldercotte et al. 2017). In this work, I wanted to characterise how lecture recording may differentially affect students with different widening participation characteristics. The relatively small number of participants in relation to the number of statistical tests run requires caution in the interpretation of these results. Additionally, the institution of study is not necessarily representative of the student body in other institutions, but these findings can be used to provide education policy makers with an insight into how lecture recording policies may affect widening participation strategies.

Key findings and implications

Students who were non-native English speakers were more likely to rewatch specific parts of a recorded lecture compared with native English speakers, and even when lectures were recorded, they were still more likely to worry about keeping up with materials. Both Ebbert and Dutke (2020) and Phillips et al. (2010) identified study patterns which showed repeated rewatching of specific lecture parts, and both considered this as a positive pattern. However, without knowing why a student is revisiting material frequently, we should be more cautious in this characterisation. If the student is revisiting a section to cope with a challenging accent or technical terminology (as seen in Chinnery, Hughes, and MacKay 2018), then we may be reassured. On the other hand, this time investment for non-native English speakers may be a source of added pressure which, prior to the introduction of lecture recording, was not present. Implementation of lecture recording should be sensitive of the reasons why these patterns of behaviour manifest and ensure that students are guided as to how to make use of new resources.

A concerning finding was that students with learning adjustments reported being less able to find materials, and possibly less likely to ask questions during lecture recordings. In this study, learning adjustments were self-reported and undefined, so we do not know what adjustments students had. We know, however, that students with dyslexia can struggle to make complete notes (Olofsson, Ahl, and Taube 2012), and so they may be more likely to seek out additional note-making resources in their revision. When a lecture is not recorded for pedagogical reasons, they may ‘feel’ the absence of the recording more than students without learning adjustments. Alternatively, these students may feel they cannot make use of the recordings or materials through the expressive and instrumental order of the school (Donnelly 2018).

Finally, while we observed no statistically significant differences in patterns of use from carers and between genders, there are some interesting observations in these data. There were some individuals in this survey, who were less comfortable asking questions in recorded lectures, although they did not leave any free text data to explore the reasons why. It is vitally important that lecturers and educators are aware of these issues and build respectful discourse into their learning communities. It is important that we continue to use qualitative research to explore the ‘deeper’ experiences of students as they utilise these resources.

Inclusive learning with lecture recording

To advise on how lecture recording can be used to support an inclusive learning environment, we must consider both what we consider an inclusive learning environment to be and how the usage of recordings may impact on that. Returning to Florian’s (2014) definition of an inclusive learning environment, if lecture recording is to support these aims, it should assist teachers in responding to learners’ individual differences, and avoid marginalising students by treating some differently to others. An inclusive learning environment, as per Claeys-Kulik and Jørgensen’s (2018) definition of inclusivity, is one which recognises the different barriers and experiences of the individuals in the room. There can be no ‘one size fits all’ application of inclusive lecture recording because the impact of provision (and the impact of a lack of provision) is felt differently. Students with invisible disabilities, such as Asperger’s syndrome, dyslexia or attention deficit hyperactivity disorders, can be perceived as disruptive in classrooms, and educators need to be supported to understand their challenges (Maxam and Henderson 2013). Lecture recording is often spoken of as ‘mainstreaming accessibility’ (Chinnery, Hughes, and MacKay 2018; Ellis 2011), in that if it is provided as ‘default’, it stops students from having to ‘out’ themselves to lecturers by requesting additional help or pauses from lecturers (MacKay In Press). Where it is provided as a default option, it should be promoted as a supplementary resource for students, and students require explicit guidance regarding how to make use of them (Nordmann and McGeorge 2018). Further, inclusive learning environments must go beyond alterations to assessment, which often simply ‘move’ stress points within a curriculum for affected students (Hewett et al. 2017). Institutions should move to provide more flexible ways to access materials, and we need a greater understanding of how, when and why individuals and groups access educational resources. As part of this, we need to also reflect how students will be expected to access education and development opportunities in future. Online video media, such as Massive Open Online Courses (MOOCs), is now an accepted method of providing continuing professional development (Murray 2019), and universities should be preparing their students with how to learn in this environment to prepare their graduates for the world. As universities strive to create authentic learning environments, we should seek to provide opportunities to learn in the context people will learn in after their graduation (Herrington and Herrington 2006).

Fundamentally, for lecture recording to be part of an inclusive learning environment, students must be supported to make the best use of the resource. We cannot expect students to study with, or use lecture recordings in a way that we do not ourselves explicitly model and teach. If the importance of lectures is that practitioners can model practice (MacKay 2019b), then lecture recordings should also model this good practice through highlighting the ethical implications of recordings, affording students privacy for asking questions where appropriate and appropriate conduct during recordings. Pye et al. (2015) examined how diverse student groups engaged with blended learning and highlighted that blended learning designs need to be framed for students in a way that makes staff expectation of students clear. Students cannot ‘intuit’ how they are supposed to learn without clear frameworks about what their discipline expects of them (Boud and Molloy 2013; Lea and Street 2006). This is even more important for students from widening participation backgrounds, who may struggle to adapt to hidden curricula. An introduction of learning recording therefore needs to clearly detail how students are expected to make use of the resource.


There are important differences in how students from different groups perceive the use of lecture recordings, particularly around their access to recordings, and how they report using recordings in their studies. When implementing lecture recording programmes, allowing students to revisit recordings when they wish, making recordings a ‘default state’ and particularly supporting flexibility in learning environments can support inclusive learning policies. Institutions should be aware that limitations on how students can utilise recordings may have a negative impact on inclusive learning goals.

Conflicts of interest

The author states no conflict of interest. This work was funded through the University of Edinburgh Lecture Recording Implementation Project.

Open data and ethics

This study followed BERA’s ethical guidelines (Bera 2011). In line with open science practices, this paper is preprinted at the Open Science Framework (https://osf.io/3g7fd/) with associated data and analysis files (https://osf.io/upz7r/).


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