Lecture Capture: Friend or Foe?
Publication: Journal of Veterinary Medical Education
Volume 49, Number 1
Abstract
Lecture capture (LC)—a recording of the live lecture provided as a supplementary resource—is accepted as a standard provision in UK higher education. Previous research has shown it to be very popular with students, although there have been conflicting findings in terms of its impact on attendance and attainment, and suggestions that student engagement with this resource varies depending on their own preferences and approaches. The aim of the present study was to determine the impact of LC on students in a wider sense, encompassing pedagogic and pastoral aspects of student development. This mixed-methods study analyzed focus group and questionnaire data from first- and second-year veterinary students at one UK university. Results demonstrated the student belief that LC is important for learning and well-being but highlighted the facilitation of passive and surface learning that this resource offers. More worryingly, this study identified a group of students for whom this resource may be particularly unhelpful. This group, relied excessively upon LC for learning, felt overwhelmed by their workload despite working fewer hours, and subsequently achieved poorer exam results. A key theme in this negative relationship appeared to be low self-efficacy. The findings enable educators to consider how resources are provided and to encourage implementing mechanisms to help students make better choices, and take control of their learning.
Introduction
Lecture capture and the present study
Lecture capture (LC) is a recording of a live lecture presented as an additional resource after the class alongside other “standard” resources such as slides and notes. Access to LC used in this way is optional, unlimited, and at the student’s behest.
LC has become a near-standard supplementary resource across higher education—it is the “new norm”. Despite its increasing provision in the higher education sector, and popularity among the student body, LC is by no means an educational panacea. It is clear that some students consider LC enhances their learning,1 supports their mental well-being,2 and provision of this resource has been shown to improve student satisfaction.3–5 On balance it seems that the benefits of LC probably outweigh the drawbacks, when used well, but research is beginning to suggest that LC as “good” or “bad” is not a binary issue6; LC has been shown to facilitate strategic learning7 and there are differences in its impact on students’ academic development depending on their learning approach8,9 and type of access.10 The impact on student well-being is likely to be equally complex and dependent on the individual. There is a need to consider the impact of LC holistically and in the context of the individual student, from both a pedagogic and pastoral perspective, to better inform their usage.
This study presents an initial investigation of the impact of LC on the well-being and learning of year 1 and 2 undergraduate veterinary students at one UK veterinary school. This cohort consists of 78% students who started their veterinary studies aged 18–19 years following completion of secondary school education, 15% graduate students and 7% older students (> 21 y) who have non-traditional qualifications and have taken foundation courses for university entry. Veterinary students, while by no means a homogenous group, present some features which make them a useful focus for this research.
The UK veterinary undergraduate student body
Graduates, and particularly those entering clinical professions, require deep learning approaches11 and strong lifelong learning skills.12 An intrinsic factor underpinning the success of a learner is their ability to manage13 and audit their own learning.14 They need to be able to think critically and reflect on their progress.15 Key to achieving this is the possession of some level of self-efficacy; the belief that they possess the ability to determine and enact the tasks required to achieve their goals.16
Undergraduate veterinary students in the UK tend to be highly motivated, high-achieving and driven, and the majority progress through their studies with few academic issues. Veterinary students have, however, been characterized as often highly strategic in their learning approach,17 tending to focus on activities they think likely to yield the most reward rather than developing intellectual curiosity and learning skills.
Veterinary students and professionals are also widely recognized as experiencing increased levels of mental ill-health and risk of suicide compared to the general population.18 Veterinary students often have perfectionistic tendencies19 and experience excessive levels of stress and anxiety20–22 during their studies and throughout their careers,23,24 exceeding that of other comparable professions (such as medical students) in some studies.20,25
There are several factors contributing to the development of mental distress in any individual, and to the increased levels seen among veterinary students.18,20,26 Stress has been shown to be more prevalent in those who achieve lower academic grades,26 and both workload20 and expectation (personal and that of others)19,27 have been shown to be key factors linked to stress, anxiety, and depression.
The veterinary curriculum: workload and resources
The veterinary curriculum, in common with other professional degrees, demands a high degree of commitment and presents a consistent and high workload, both in terms of contact hours and personal study requirements. This demand is essentially equal for all students in a cohort, yet it is recognized that a proportion of students consider this workload to be overwhelming,28 while others manage it well. It is the perception of workload which is key, and a workload perceived as heavy has been shown to have a negative impact upon academic achievement29,30 and well-being.20,31
At the University of Liverpool School of Veterinary Science (LSVS), much attention is given to making learning as accessible and inclusive as possible. To this end, it is now routine for each lecture to be supported by online provision of lecture slides, lecture notes, links to relevant websites or ebooks, revision quizzes and a recording of the live lecture, all presenting the same content in different formats. Considering that year 1–3 students can expect around 13 hours of lectures in a 26-hour timetabled week, this amounts to a significant bank of resources. Informal feedback at LSVS suggests that provision of so many resources, even replicating the same material, causes some students to feel anxious and disengaged, and to rely heavily on recorded sessions for learning.
Conceptual framework and current study
While students who already possess positive qualities and approaches are likely to make good choices and progress well both academically and personally, the authors were concerned that students who are not self-efficacious, who struggle to self-regulate and exhibit surface learning approaches may be adversely affected by (or at least not be assisted by) provision of LC due to the ease of access and apparently low cognitive demand they offer.
The considerations above yielded a conceptual framework which links workload and LC with well-being, learning skills and academic achievement (Figure 1).
This can be encapsulated by the question “Is lecture capture a friend, or a foe?”, and the hypothesis that struggling students may rely on LC more and benefit from it less.
Aim and Research questions
This report aims to determine the variable impact of providing lecture capture on student well-being and learning in a high-stakes, high workload environment.
How does the impact of LC provision vary between students, in terms of:
1.
Well-being, based on student experience of stress, workload, anxiety, and depression?
2.
Learning skill development, based on evidence of deep, flexible learning approaches, and self-efficacy?
3.
Academic achievement based on examination results?
Methods
This two-stage project employed qualitative techniques, to explore individual experiences and gauge strength of feeling and beliefs regarding use of LC, and semi-quantitative techniques, to identify trends and relationships between attitudes to LC usage and academic achievement, perceptions of learning and stated well-being. Data gathering utilized focus groups and questionnaires. Ethical approval was gained from LSVS Research Ethics Committee, prior to commencing data collection.
Students in years 1 and 2 of the 5-year BVSc were invited to join the study; these cohorts were selected as they had the most exposure to LC. Data gathering ran from February to May 2016, ensuring year 1 participants had experienced at least one semester and year 2 participants has experienced three semesters of study.
Focus groups were run as stage 1 of the project. Volunteers were sought, and 17 year 1 and 11 year 2 students were assigned by the authors to one of six focus groups each containing 4–6 students. Each focus group contained students who self- declared as low/zero, medium and high users of LC and were further subdivided into four year 1 groups and two year 2 groups. The focus groups each lasted 60–75 minutes and were chaired by an experienced, independent facilitator who structured the discussions to ensure equal participation of all individuals.
Focus group questions and prompts were developed from the conceptual framework, formal course feedback and informal interviews with individual students. The facilitator received an in depth briefing prior to the focus groups. Table 1 shows the major questions used to frame discussion in the focus groups.
| Question |
|---|
| Do you consider yourself a non/low/moderate/high user of lecture capture? |
| What is your opinion of live-recorded lectures as a learning resource? |
| What learning skills do you think you will need as you progress up the school and into practice? |
| How do you think recorded lectures impact on your learning? |
| How would you describe levels of stress and anxiety among veterinary students? |
| Has lecture capture affected in any way how you learn socially/work with your peers? |
| How would you describe your workload on the course? |
| Why do you think members of staff provide recorded lectures? |
The focus groups were recorded and independently transcribed. Simple inductive thematic analysis was performed independently by the three authors who then identified themes which were used to develop questions for the questionnaire. This initial analysis was superseded by the framework analysis described below, hence is not presented here. There were no clear differences in the focus group themes derived from the first- and second-year cohort and so these data are pooled.
The final stage of the project was a questionnaire consisting of 34 Likert-type questions, which was distributed for voluntary completion to years 1 and 2 in May 2016; prior to the summative examinations. Students were requested, on a voluntary basis, to give their student identification (ID) number at the start of the questionnaire, to enable correlation with academic achievement and background. The questionnaire and corresponding student academic data were pseudonymized using a numbering system to protect identity during data analysis.
Data analysis
Qualitative analysis of the focus group data was performed in NVivo qualitative data analysis software (QSR International Pty Ltd. Version 10, 2012). A framework analysis approach was used, enabling comparison of the views and experiences of participants in different self-stated usage groups (Table 2). Data were independently coded by the three authors to reduce bias and, through iterative discussion, organized into minor, major and overarching themes (Figure 2). Focus group analysis was validity-checked by triangulation with the facilitator reports written contemporaneously with the running of each group.
Figure 2: Thematic development
LC = lecture capture
| Usage | Learning approach | Engagement | Well-being |
|---|---|---|---|
| High | Heavy reliance on provided resources. Significant passive, inefficient and strategic learning approaches. Some individuals so reliant upon LC that cannot believe they could succeed without them. Subgroup demonstrating forward thinking and efficient approaches to learning. | Strategic learning to the extent that some participants acknowledge filtering the classes they choose to attend. Concentration is an issue, potentially exacerbated by the knowledge that sessions are being recorded. | Consider workload very heavy. Acknowledge LC is tiring to engage with. Possibly increased isolation with the use of LC. Perceive positive well-being impact from LC, in supporting varied lifestyles and learning difficulties. Minor theme that LC provides a safety net. Pressure from self and external sources. |
| Mod | Appreciate need for collaborative learning and self-testing. Evidence of using LC actively and to solve problems. More integrated approach to learning but still some evidence of inefficient and strategic learning. Reliance on provided resources and desire for spoonfeeding, even while acknowledging this is not beneficial. | Acknowledge reduced attendance by peers due to LC but discussed anxiety over reliability of provision. Appreciation of benefits of attendance, and discussed that LC may increase this by encouraging disengaged students to stay at home. Fairly strong feeling that LC may support disengagement by providing sense of security. | Safety net imagery used frequently. Strong feeling of pressure from peers regarding workload. Avoid LC when under time constraints, although a subgroup do find LC efficient. Sense that students understand that missing lectures/being distracted decreases well-being as postpones work. |
| Low | Clearly articulate need for active/deep learning, and use LC to achieve this. Only using LC for specific reasons, and describe active learning during taught sessions. Some evidence of passive approaches to learning and reliance on provided resources, albeit less focused on LC. Discuss ways to make learning active, even using LC. Appreciate need for varied learning approaches, and value of reflection in learning. | Perceived positive impact on engagement in students attending lectures, because students who do not engage in that environment can stay away. Feel that provision of back-up resources, for this group, enables increased in-class engagement. Noted negative impact of social media on engagement and concentration during class time. | Support for varied learning approaches. Heavy use of safety net image. Definite feeling that attendance is best to manage stress. Feel that LC as a main resource in addition to attendance would increase stress due to time. Feel provision of comprehensive resources is necessary for well-being. Targeted use of LC, as exhibited by this group, is seen as reducing stress by saving time. |
| None | Feel very strongly about active learning, and consider LC to be entirely passive. Articulate more confidence in their ability to learn. | Consider LC may facilitate in-class disruption by providing a back-up. | Feel that LC too time consuming, and seem to be protecting themselves from becoming reliant on this easy-access resource. |
LC = lecture capture
Exam scores were not normally distributed (as ascertained by Shapiro-Wilk tests) and so, in order to examine whether summative exam results differed in relation to questionnaire responses, Kruskal Wallis tests were performed on multiple groups. Mann–Whitney tests were performed to test differences between two independent groups of data. Exam score data are presented as median and associated interquartile range.
To explore associations between learning behaviors and student well-being from the questionnaire responses, we determined Spearman’s correlation coefficients from the Likert-type questions.
Statistical significance was taken at p < .05 throughout. Statistical analyses were conducted using SPSS software version 22.0 (IBM Corp., Armonk, N.Y., USA).
Results
Focus group data
Initial coding yielded 13 major and 3 overarching themes. Several of the major themes were further coded for whether they pertained specifically to LC, or not, generating minor sub-themes (Figure 2).
Each participant was assigned an attribute based on their self-identification as a high, moderate, low or non-user of LC, enabling comparison of data from these groups of students during the framework analysis. Table 2 shows a summary of the results of this analysis and interpretation.
Questionnaire data
Two hundred and twenty-two questionnaires were returned; 112 from year 1 and 110 from year 2; a response rate of 68% of eligible registered students. Of these, 88% (195 respondents) chose to give their student ID, which enabled us to link their summative exam result with their Likert responses.
Most respondents used LC for 1–3 hours per week with reported usage as follows: 25.7% didn’t use it at all, 64.9% used for 1–3 hours per week, 6.8% used it for 4–6 hours per week and 2.7% students used LC for over 7 hours per week.
Of the respondents who used lecture capture, 79.2% stated that they used it to fill specific knowledge gaps and 16.5% to listen to the whole lecture again.
Comparing summative exam data to student questionnaire responses
Relationships identified between questionnaire responses and summative exam data were consistent in both cohorts, so these data have been combined. Students who self-identified as good learners had significantly higher summative exam results than those who identified themselves as average or poor learners, and those who acknowledged spending the least amount of time in private study achieved lower marks in summative assessments (Table 3).
| Learning perceptions and characteristics | No. (%) | Exam performance (%) | p value (Mann-Whitney) | |
|---|---|---|---|---|
| Median | Interquartile range | |||
| Student perception of their ability as a learner | ||||
| Good | 39 (20) | 74.0a | 11.0 | < .001 compared to c |
| Average | 140 (73) | 64.0b | 13.1 | < .001 compared to a |
| Poor | 12 (6) | 54.0c | 7.6 | < .001 compared to b |
| No. of hours that students engage in private study | ||||
| 0–10 | 83 (43) | 62.6a | 16.3 | |
| 11–16 | 63 (33) | 68.5b | 11.8 | .004 compared to a |
| >16 | 46 (24) | 66.9b | 14.1 | .003 compared to a |
| All the information I need to know is in the recorded lecture | ||||
| Strongly agree | 24 (13) | 60.5a | 10.8 | |
| Agree | 84 (44) | 66.7b | 14.1 | .005 compared to a |
| Disagree/strongly disagree | 84 (44) | 66.63b | 15.7 | .007 compared to a |
| If recorded lectures did not exist, I would not change my other learning methods | ||||
| Strongly agree/agree | 125 (65) | 67.8a | 13.9 | |
| Strongly disagree/disagree | 66 (35) | 62.8b | 13.3 | .019 |
Multiple groups were first analyzed using Kruskal Wallis test and, if statistically significant, pairs of data were analyzed using Mann–Whitney tests. Data with different superscriptsa,b,c within each question are statistically different.
Students achieving lower results were more likely to limit their learning to LC and acknowledge that other methods would be needed if recorded lectures did not exist (Table 3). This limiting of learning extends further than relying on the LC, for some students: 25% of respondents acknowledged that they ignore a learning outcome if it is not covered in the recorded lecture.
Academic achievement also linked to student well-being in many areas (Table 4).
| Perceptions of well-being | No. (%) | Exam performance (%) | p value (Mann-Whitney) | |
|---|---|---|---|---|
| Mean | Interquartile range | |||
| I have experienced increased feelings of anxiety or depression since beginning veterinary school | ||||
| Agree/Strongly agree | 99 (53) | 63.8a | 13.6 | |
| Disagree/Strongly disagree | 89 (47) | 68.2b | 15.3 | .01 |
| I have an excessive workload | ||||
| Agree/Strongly agree | 75 (39) | 63.2a | 14.1 | .001 |
| Disagree/Strongly disagree | 117 (61) | 69.2b | 13.6 | |
| Competition from my peers pressurizes me to work long hours | ||||
| Agree/Strongly agree | 119 (63) | 63.6a | 12.8 | .005 |
| Disagree/Strongly disagree | 71 (37) | 70.2b | 12.9 | |
| There is pressure from staff to work long hours | ||||
| Agree/Strongly agree | 148 (77) | 59.6a | 13.0 | < .001 |
| Disagree/Strongly disagree | 44 (23) | 67.6b | 13.5 | |
Data were analyzed using Mann–Whitney tests. Data with different superscripts a,b,c within each question are statistically different.
The majority of participants agreed that an excessive workload is a cause of stress (Figure 3), but perceptions of their current workload varied; lower-achieving students were much more likely than high achieving students to perceive their workload as excessive (Table 4), despite, in fact, undertaking fewer hours of study (Table 3).
Reinforcing the apparent link between well-being and academic achievement, lower-achieving students were more likely to acknowledge experiencing anxiety or depression than higher-achieving students. This lower-achieving group were also more likely to perceive external pressure; from peers and staff (Table 4).
Associations between LC, learning behaviors and student well-being
Students in both first and second year perceived a reduction in stress with their increasing usage of LC and acknowledged that LC was likely to reduce their attendance in live lectures (Table 5a).
| 5a | Year of study | Increasing lecture capture self-study hours | All the information I need to know is in the recorded lecture | If I think a lecture will be recorded I am less likely to attend | If I don’t understand something, the first resource I use is the recorded lecture | If recorded lectures did not exist, I would not change my other learning techniques |
|---|---|---|---|---|---|---|
| I have experienced increased feelings of anxiety or depression since beginning university | 1st year | 0.039 | 0.137* | |||
| 2nd year | 0.269* | |||||
| I feel less stressed when I know lectures are being recorded | 1st year | 0.397* | 0.074 | 0.256* | 0.389* | –0.075 |
| 2nd year | 0.374* | 0.280* | 0235* | 0.458* | –0.321* | |
| Recorded lectures reduce my workload | 1st year | 0.188* | 0.190* | 0.153 | –.0.277* | |
| 2nd year | 0.486* | 0.321* | 0.327* | –0.404* | ||
| All the information I need to know is in the recorded lecture | 1st year | 0.08 | ||||
| 2nd year | 0.267* |
| 5b | Year of study | I have an excessive workload | Recorded lectures reduce my workload | I have experienced increased feelings of anxiety or depression since beginning university |
|---|---|---|---|---|
| I have experienced increased feelings of anxiety or depression since beginning university | 1st year | 0.183 | 0.052 | |
| 2nd year | 0.326* | 0.2* | ||
| If a learning outcome isn’t covered in the recorded lecture I ignore it | 1st year | 0.238* | 0.141* | 0.146* |
| 2nd year | 0.107 | |||
| Having lots of resources for each class increases the pressure I feel to work long hours | 1st year | 0.259* | 0.224* | 0.198* |
| 2nd year | -0.059 | 0.006 | ||
| There is pressure from staff to work long hours | 1st year | 0.194 | 0.234* | 0.016 |
| 2nd year | 0.401* | 0.136 | 0.301* | |
| Competition from my peers pressurizes me to work long hours | 1st year | 0.096 | 0.284* | |
| 2nd year | 0.368* | 0.375* |
Significant correlations (p < .05) are marked with an asterisk (Spearman’s rho). Insignificant data are included for comparison where year 1 and year 2 year cohorts are different. Data from both cohorts are combined where responses are similar.
There were clear differences between the responses of first- and second-year students. Second-year students who felt that LC reduced their workload were more likely to limit their learning to LC, and to state that they had suffered from anxiety and low mood (Tables 5a & 5b). Furthermore, second-year students who had feelings of anxiety and low mood were also more likely to state that they had an excessive workload and used LC for an increasing number of hours (Table 5a & b).
Most students did not consider that LC reduces their workload (Figure 3), but those who believed that LC did reduce workload were limiting their learning (Table 5b) and reducing attendance to classes (Table 5a). There was also a clear positive correlation between those students who used LC for increasing hours per week and a feeling that it reduced their workload, particularly second-year students (Table 5a). First year students who perceived an excessive workload were also more likely to limit their learning to material covered in lectures. There were clear links with perceived workload and external pressure, with students in both cohorts likely to link their workload with the provision of plentiful resources, and second-year students more likely to experience pressure from peers and staff (Table 5b)
These data, linking Likert-type question responses to summative assessment results, highlight a potentially vulnerable group of students, most clearly identified within the second-year cohort, and alongside the focus group findings, suggest the role LC may play in facilitating negative behaviors in these students.
Discussion
In the present study it is clear that students consider LC an essential resource, although the ways they use the recordings differ widely. In common with findings from other studies, most students in this study used LC to revisit difficult concepts, viewing specific sections of the lecture to fill gaps in knowledge, or to “attend” missed lectures.1,3,32
The focus groups agreed that most students use LC on their own, whether in their own study time or in place of attending classes. There is therefore no contact between the student and the lecturer or peers, during viewing, meaning there is no imperative for students to engage in interactive elements, and no “risk” to the student of potentially being asked to contribute to the discussion. The focus group discussions within the present study further highlighted that LC particularly lends itself to passive viewing.
“It’s nice, easy, it’s like Netflix isn’t it, you can do it from your bed” (Low user).
This seems to offer a low-stress option, but creates potential for students to avoid cognitive engagement with the learning opportunity. It also precludes the student from questioning the lecturer, and prevents the lecturer from identifying and addressing confusion regarding the concepts being learned. Reduced student interaction has been noted as a negative aspect of LC in other studies.2 These issues are particularly pertinent when LC is used in place of attendance, which is a more common behavior among weaker students.8
There are many aspects of LC that can be viewed as very positive, particularly for learners who have a developed, insightful and proactive approach.33,34 For these students, it appears that LC provides a valuable safety-net, and can be used actively and socially:
“A group of my friends organise group revisions and we find that really beneficial because we’ll get up the PowerPoint with the learning objectives and we’ll go through it as a group … and go okay, we misunderstood that as a group and then we’ll go and ... re-listen to a particular part of the lecture” (Moderate user)
Students who are academically stronger tend to use LC as an adjunct to other learning resources and attendance,35 and are even able to use it to improve their in-class learning by allowing them to fully engage and interact rather than worry about writing everything down.
“I’ll take a moment just to think about something that the lecturer said and I won’t like stress out about missing the next thing she said.” (Low user)
In contrast, some students in this study relied very heavily on LC as their main resource for learning. While a subgroup of these students still demonstrated good learning behaviors and insight, there appears to be a link between a heavy reliance on LC and several undesirable student outcomes in these areas:
•
learning approach;
•
attendance/engagement in class;
•
workload and well-being; and
•
academic achievement.
In identifying these links, it is important to be clear that no causative relationship between LC and poor performance or well-being can be claimed based on the findings in the present study. However, students in this struggling group do articulate an excessive reliance on LC and, whether cause or effect, this is unlikely to be wholly helpful. This echoes the findings in other studies, which showed that use and impact of LC differs between students of differing academic ability.33,34 It is particularly concerning that these negative relationships were most marked in second-year students in the present study. As this study did not track cohorts across years, it could simply be a difference between the two cohorts, but it behoves us to consider that, for these students, their learning approach and habits may be failing to develop during their studies and, potentially, even worsening over time.
Learning approach
In the present study, stronger students exhibited a high degree of self-efficacy and self-belief; students who believed they were good learners were in fact more likely to achieve well.
A key negative theme that emerged from the data presented above, however, was dependence. Students across the LC usage spectrum demonstrated a concerning tendency to rely entirely on the delivered curriculum and the gospel word of the lecturer. This was most evident in the focus groups, when students were asked what they would do differently if they did not have LC:
“Without [LC], more people would be emailing lecturers.” (Moderate user)“If I didn’t have [LC] I wouldn’t have any notes or anything; I wouldn’t have anything to revise from.” (High user)“If they haven’t recorded it, I just record it myself, like I would record them anyway.” (High user)
This apparent lack of self-regulation was often discussed alongside evidence of very passive learning approaches, particularly among the high usage group, to the extent that students even stated that they expect to be spoon fed:
“I feel with the amount of stuff we need to cover ... we need to be spoon fed.” (High user)
When used passively, LC may lull weaker students into a false sense of security by giving them a sense of familiarity with the material without challenging them to evaluate their learning. The potential contribution of LC to this “lecture-centric” dependent approach was also suggested by Leadbeater et al., in their 2013 study.36
In the present study, not only were some students highly dependent, they were limiting their learning; most students (57%) believed that all the information they need is in the LC, and 25% of students actually ignored a learning outcome if it was not covered in the LC. This suggests that these students are not auditing their learning; limiting it to that which is directly presented to them, rather than ensuring they can meet the requirements of the curriculum.
There was evidence in every usage group of active and mature learning approaches, but it was clear that the prevalence of these increased as claimed LC usage decreased. It was not simply that these students were using fewer LC recordings, but that students in the lower usage groups were more likely to describe deep, active learning approaches and reflective practice; all factors which contribute to good academic achievement.37,38
“I learn better by answering questions and seeing where I have gone wrong so sitting and watching a whole lecture again wouldn’t help.” (Moderate user)“[LC is] exactly the same as the normal lecture so if you didn’t understand it there you’re obviously going to need help somewhere else aren’t you.” (Low user)
In the highest usage group, conversely, students were quick to claim that learning would be impossible without LC; a feeling which reflects the findings of others, that students think LC increases their performance1,39:
“I’d fail my degree if I didn’t have [LC].” (High user)
Previous studies are undecided as to the impact of LC on learning approach. Some authors have suggested that LC generally benefits learning by enabling students to make better notes and more deeply digest the subject matter, due to the option to pause the recording.4,40,41 Others have highlighted that replacing attendance with LC is associated with surface learning strategies.8 In the cohort studied here, in common with other cohorts on densely timetabled courses, it could be argued that the negative aspects may be more prominent due to the limited time available outside timetabled sessions, meaning that high usage of LC requires lower attendance.
Attendance/engagement
All focus groups agreed that LC has impacted upon attendance in general, although there are no quantitative data to confirm this. The high user group acknowledged reduced attendance in recorded sessions, and also demonstrated evidence of selectively attending classes and filtering out certain subjects.
The stated reason for choosing to miss these classes was the perception that they are less important, but there is a suggestion that a lack of self-efficacy may be an equally salient factor. Some students were clearly reluctant to learn core material that had not been recorded, even when the original learning opportunity was an interactive and discursive session rather than a lecture format.
[Regarding an interactive discussion session] “they might want to repeat it in exams and stuff, but surely if we haven’t got it [recorded] to start with, how are we ever going to answer it in an exam if we needed to?” (Moderate user)
There is good evidence that attendance is linked to academic achievement,35,42 and it also appears that LC viewing fails to compensate for the negative impact of low attendance on attainment.43 As noted above, students with surface learning approaches tend to replace, rather than augment, attendance with LC8; a picture that is supported by the present study.
Low LC users were more likely to perceive the value of attending the learning activity:
“Actually going to the lecture structures my day, it structures my week and then forces me to concentrate and be motivated in the lecture” (Low user)
While moderate and high users were more likely to view the learning activity simply as an information gathering exercise while the learning takes place later.
“You don’t actually absorb the information because you’re just getting it down so that you’ve got the notes” (Moderate user)
These students demonstrated a desire for all sessions to be recorded, whether lecture, practical, tutorial or interactive discussion. This reinforces the theme that some students are adopting a passive approach to learning with little self-regulation.
The authors expected that provision of LC may enable students to engage more actively in class, by reducing the pressure to take notes, and that for some students a recorded lecture may prove more engaging than the classroom or written resources. Certainly, these aspects were discussed in the focus groups, particularly in the low user group, but this fails to reflect the full picture. There was a clearly split opinion on the effect LC has on student engagement in class, drawn from unprompted discussions around the impact LC has on disengaged students. On the one hand, students felt that provision of LC meant that students who do not learn well in the classroom environment would stay at home, thereby reducing disruption and allowing engaged students to learn better:
“If people who don’t want to be there can do learning in different ways that’s going to benefit people that do want to be there” (Low user)
This is an interesting counterpoint to the findings of Hall and Ivaldi, who found students in their study actually resented non-attending students, considering it unfair that these students attained the same grades and degrees as those who attended the learning activities.7
On the other hand, in the present study, there was a contrasting opinion that providing LC takes the pressure off, so those students who do attend the lecture stop concentrating and disrupt the class by chatting with classmates or browsing online:
“But I’ve found, like everybody else, if its lecture captured I won’t pay attention.” (High user)“[The lecture] was really, really complicated and she was there watching this cake video and I was just watching it with her because I couldn’t take my eyes off it.” (Moderate user)
Distractions during learning activities, such as those described by the students in this study, have been shown to negatively affect learning gains, even in high interest lectures44,45 and more work is needed to specifically investigate the impact of LC on the frequency of distraction. The balance of opinion in the focus groups tended toward considering that LC increased the likelihood of distraction, although some students felt distraction was simply to be expected, and that the draw of social media and other online activities may be a generational feature which they were already working hard to manage:
“ I think we as a generation, that it’s so important with social media that people don’t lose these personal skills and lose respect for people.” (Moderate user)“I used to take my laptop to the lecture at one point and I’ve given up with laptops because I can easily divert straight onto Internet Explorer, Facebook, Twitter.” (High user)
Workload and well-being
This study presented a complex interplay between perceptions of workload, student well-being, and use of LC. Higher-achieving students were less likely to consider their workload excessive, despite in fact undertaking more hours of self-study, reinforcing that perceived workload is only weakly related to time spent studying.29 The students who did consider their workload to be excessive were more likely to limit their learning, experience negative mental health and achieve poorer academic results. This is in common with findings from some other studies, which demonstrated that excessive perceived workload can be associated with poor learning approach, short cuts and surface learning,29,30 and can contribute to stress which can, in turn, lead to anxiety and other mental health issues.46,47 The effect of excessive workload differed between the two cohorts under scrutiny in the present study: first-years were more likely to limit their learning, while second-years were more likely to experience anxiety or depression. Naivety may play a part in the first of these findings—the first-year students had only completed one semester of study and no summative assessments—and perhaps chronicity of the high perceived workload, and the requirement to build on the previous year’s knowledge, may go some way to explain the negative effects on the year 2 students’ well-being, as suggested by Siqueira Drake et al., in their 2012 study.48
The role played by LC in students’ perception of workload is contradictory and highlights the heterogeneous nature of the student population. The vast majority of students in this study agreed that LC does not reduce workload, which agreed with the focus group data that students of all usage levels considered that LC is time-consuming to use. Those in lower usage groups considered that use of LC as a major resource would have a negative effect on their well-being as a result. A significant minority of students in this study did, however, consider that LC reduces their workload. These students were also more likely to limit their learning and heavily rely on LC over attendance and other learning methods. It is perhaps unsurprising that these students consider their workload lower when they choose not to attend and limit their learning, but this is a false impression since, as stated above, LC is a poor replacement for attendance.8,43 The perception that LC reduces workload also correlated with feelings of depression and anxiety among the second-year students in this study. Poor mental health is known to have a negative impact on learning approach,19 which may shed some light on this potentially contradictory relationship; students experiencing negative mental health may be more likely to make learning choices which seem easy but which in fact perpetuate, rather than improve, their struggles.
The way in which students use LC is likely to have an impact on workload. A group of students in this study mainly re-watched the entire lecture having also previously attended the lecture/teaching session. Given that the focus groups largely agreed that LC is inefficient as a major resource, it seems likely that this approach may negatively affect these students’ perceived workload.
“It could potentially be very useful to me but because of its length, I can’t.” (Low user)“It’s just like postponing the stress because then that evening not only do you have to go through all the lectures … you actually have to listen to something.” (Moderate user)
In planning this study, the authors were concerned that provision of plentiful resources may, in itself, present a source of pressure for some students, and indeed this theory was borne out among those students who perceived an excessive workload. This serves to further highlight the heterogeneity of the student cohort, since it is known that, generally, students prefer a variety of resources49 for learning, and in the present study the low users in the focus groups felt that provision of comprehensive resources actually improves well-being. The role LC plays in this perceived pressure is not clear; the students who viewed rich resources as a source of pressure did not seem to consider LC as contributing to this, and in fact the first-year students in this group were likely to view LC as reducing their workload. The perception of external pressure among second-year students with excessive workload extended beyond resource pressure, with these students also experiencing a sense of pressure from staff and from their peers. This is in common with several other negative outcomes for year 2 students identified in this study, which highlights a need for longitudinal research to establish whether there is indeed a worsening in well-being and learning approach for a subgroup of students.
Students in the focus groups were consistent in their view that access to LC reduces their anxiety and stress, in its capacity as a safety net. There was a variation in views regarding the impact of routine LC use on mental health. High users clearly viewed LC as beneficial despite acknowledging that it is time consuming and may contribute to isolation. Moderate and low users felt that good attendance was the better way to manage stress. This provides an interesting counterpoint to those students who felt that LC reduces workload. It is pertinent to note here that the heaviest year 2 LC users in this study were more likely to suffer from anxiety and depression and yet consider that LC reduced their workload. A causative relationship cannot be asserted, but it is an observation which is worthy of further research.
Given LC is a time-consuming resource to use, a heavy reliance on this resource cannot be beneficial to struggling students. Students experiencing anxiety and low mood were more likely to be perceiving external pressure, heavy workload, exhibiting naive, passive learning approaches and achieving poorer academic results. This presents somewhat of a chicken and egg situation—anxiety and low mood reduce concentration and lead to procrastination.19 These students’ desire to reach for a non-challenging resource is therefore not surprising, but their engagement with the LC may suffer as they may be more prone to distraction, and their feeling of excessive workload is likely to be worsened.
Academic achievement
The factors described above were all linked to lower-achieving students. Higher-achieving students tended to exhibit good learning approaches, attend and engage well, consider their workload reasonable, and have better mental health. The way in which students use LC had no demonstrable relationship with their academic achievement, so perhaps it is the extent to which they rely on this resource, rather than how they use it, which is more important. This is in contrast to findings in other studies, which showed that higher-achieving students tended to mainly use targeted sections of recordings, whereas weaker students tended to re-watch the whole thing.33
Considering the above as a whole, the group of struggling students appear to be in a vicious circle with each factor impacting upon the others. There is a concerning suggestion that this phenomenon may be worsening over time, with year 2 students exhibiting poorer learning approaches and more indications of negative well-being. The role LC plays in this appears to be largely positive in the eyes of the students, but is more likely to be negative when the evidence is weighed. A time-consuming resource, easy to use passively, creating a feeling of ease and facilitating procrastination, permissive of disengagement or non-attendance, is unhelpful to students with poor learning approaches and low self-efficacy or those struggling to manage their mental well-being.
Limitations of this study
Participants
This study focused on students at a single site, and in the early years of the veterinary curriculum. This confers some strengths to the study in terms of consistency and response rate, but also limits the available sample size.
As with any self-selecting study, the representativeness of the sample cannot be guaranteed; students may have brought their own agenda to influence their answers. It is also important to note that the first-year cohort had only studied at university for a single semester and so their responses may have been more influenced by their previous academic experience.
Data and results
It must be acknowledged that the statistically significant correlations discussed above are small. This is to be expected in such multifactorial issues as learning, academic achievement and well-being, hence the authors consider them meaningful in this context.
As with most research of this type, much of the data are derived from the assertions of the participants. This is particularly pertinent in terms of students’ claimed usage of LC; participants in the focus groups were asked to classify themselves as high, moderate or low users, without guidance as to what was meant by these categories—it is possible that two students using LC in exactly the same way could have self-classified differently. Future research would give descriptors for these categories, to enable students to select a category that better reflects their usage.
The lecture capture software that was used for this study did not enable analysis of LC use, hence the researchers could only rely on the claims of the participants. Future research will utilize software which has enhanced learning analytics capability.
Conclusions
This study examined the impact of LC use on first- and second- year undergraduate vet students at one UK veterinary school. This allowed examination of a population of relatively naive students with nascent learning approaches. Findings agreed with other authors, in that students viewed LC as an essential resource, whether or not they actually use it. They view it as supportive for their learning and their well-being, and value it as a key resource.
Used well, LC offers students a supplementary resource to cater for additional learning needs, illness, and to offer another chance to hear that crucial explanation. Used poorly, LC is time-consuming, passive, and may too easily displace other, more challenging learning activities.
This study highlighted a group of students who appear to be in a vicious circle, where their academic development, achievement and well-being intertwine in a negative dynamic. These students tend to view LC as a lifeline; an absolutely crucial resource without which they could not progress. This study suggests that these students’ reliance on this resource is certainly unlikely to be helpful, and may be damaging, and it behoves educators to consider this group particularly when devising teaching plans.
Consideration must be given to actively helping students develop the skills needed to make good choices. Suggested actions arising from this study were:
•
Ensure attendance is valuable—ensure that attendance offers something that the LC does not;
◦
Increase use of interactive and student-centered activities, to replace didactic lectures.
•
Include learning skill development as a core part of the curriculum;
◦
A developmental and personalized approach to self-efficacy should be fostered, providing students with the opportunity and support to take ownership of their learning.
To shed further light on the relationships suggested by this study, further research should employ usage analytics from the streaming software to quantify the link between LC usage and the factors discussed here. In addition, research into the impact of LC on in-class distraction would be valuable, and investigation of the relationships between mindset, perceived workload and engagement with resources would clarify the broader picture underpinning the poorer outcomes experienced by the struggling minority. It would be interesting, furthermore, to compare contrasting student cohorts to see if the findings of this study are consistent among students with different motivations and abilities, and to track cohorts across years to identify changes in learning behaviors and well-being as students progress through their course.
References
1 Gosper M, Green D, McNeill M, Phillips R, Preston G, Woo K. The impact of web-based lecture technologies on current and future practices in learning and teaching. Aust Learn Teach Counc [Internet]. 2008 [cited 2018 Mar 23];1–7. Available from: http://researchrepository.murdoch.edu.au/id/eprint/12120/1/ce6-22_final2.pdf
2 Dommett EJ, Gardner B, van Tilburg W. Staff and student views of lecture capture: a qualitative study. Int J Educ Technol High Educ [Internet]. 2019 Dec 28 [cited 2019 Sep 3];16(1):23. https://doi.org/10.1186/s41239-019-0153-2
3 Traphagan T, Kucsera J V., Kishi K. Impact of class lecture webcasting on attendance and learning. Educ Technol Res Dev [Internet]. 2010 Feb 3 [cited 2018 Mar 22];58(1):19–37. https://doi.org/10.1007/s11423-009-9128-7
4 Newton G, Tucker T, Dawson J, Currie E. Use of lecture capture in higher education - Lessons from the trenches. TechTrends. 2014;58(2):32–45. https://doi.org/10.1007/s11528-014-0735-8
5 Al Nashash H, Gunn C. Lecture capture in engineering classes: Bridging gaps and enhancing learning. Educ Technol Soc. 2013;16(1):69–78.
6 Nordmann E, Mcgeorge P. Lecture capture in higher education: time to learn from the learners. Psyarxiv Prepr [Internet]. 2018;(May). Available from: https://psyarxiv.com/ux29v. https://doi.org/10.31234/osf.io/ux29v
7 Hall G, Ivaldi A. A qualitative approach to understanding the role of lecture capture in student learning experiences. Technol Pedagog Educ [Internet]. 2017 Aug 8 [cited 2018 May 18];26(4):383–94. https://doi.org/10.1080/1475939X.2016.1263805
8 Vajoczki S, Watt S, Marquis N, Liao R, Vine M. Students Approach to Learning and Their Use of Lecture Capture. J Educ Multimed Hypermedia. 2011;20(2):195–214. https://www.learntechlib.org/primary/p/36105/
9 Wiese C, Newton G. Use of lecture capture in undergraduate biological science education. Can J Scholarsh Teach Learn [Internet]. 2013;4(2):1–24. https://doi.org/10.5206/cjsotl-rcacea.2013.2.4. Available from: http://ir.lib.uwo.ca/cjsotl_rcacea/vol4/iss2/4
10 Bos N, Groeneveld C, van Bruggen J, Brand-Gruwel S. The use of recorded lectures in education and the impact on lecture attendance and exam performance. Br J Educ Technol. 2016 Sep 1;47(5):906–17. https://doi.org/10.1111/bjet.12300
11 Khosa DK, Volet SE, Bolton JR. An Instructional Intervention to Encourage Effective Deep Collaborative Learning in Undergraduate Veterinary Students. J Vet Med Educ [Internet]. 2010 Dec 1 [cited 2019 Sep 3];37(4):369–76. https://doi.org/10.3138/jvme.37.4.369. Medline:21135404
12 Towle A, Cottrell D. Self directed learning. Arch Dis Child. 1996;74(4):357–9. https://doi.org/10.1136/adc.74.4.357. Medline:8669942
13 Mega C, Ronconi L, De Beni R. What makes a good student? How emotions, self-regulated learning, and motivation contribute to academic achievement. J Educ Psychol. 2014;106(1):121–31. https://doi.org/10.1037/a0033546
14 Pintrich PR. A conceptual framework for assessing motivation and self-regulated learning in college students. Educ Psychol Rev. 2004;16(4):385–407. https://doi.org/10.1007/s10648-004-0006-x
15 Kyndt E, Dochy F, Struyven K, Cascallar E. The perception of workload and task complexity and its influence on students’ approaches to learning: A study in higher education. Eur J Psychol Educ [Internet]. 2011 [cited 2017 Jun 16];26(3):393–415. https://doi.org/10.1007/s10212-010-0053-2. Available from: https://lirias.kuleuven.be/bitstream/123456789/284275/2/Kyndt,+Dochy,+Struyven,+Cascallar,+Accepted+(2011).pdf
16 Bandura A, Freeman WH, Lightsey R. Self-efficacy: The exercise of control. J Cogn Psychother. 1999;13(2):158–66. https://doi.org/10.1891/0889-8391.13.2.158
17 Sykes A, Denny P, Nicolson L. PeerWise-The Marmite of Veterinary Student Learning. In: Proceedings of the 10th European Conference on e-Learning Brighton Business School, University of Brighton, UK [Internet]. 2011 [cited 2017 Sep 12]. p. 820–30. Available from: http://eprints.gla.ac.uk/90693/1/90693.pdf
18 Platt B, Hawton K, Simkin S, Mellanby RJ. Systematic review of the prevalence of suicide in veterinary surgeons. Occup Med (Chic Ill). 2010;60(6):436–46. https://doi.org/10.1093/occmed/kqq044. Medline:20591857
19 Zenner D, Burns GA, Ruby KL, Debowes RM, Stoll SK. Veterinary students as elite performers: Preliminary insights. J Vet Med Educ [Internet]. 2005 [cited 2017 Sep 12];32(2):242–8. Available from: https://s3.amazonaws.com/academia.edu.documents/42342695/Veterinary_students_as_elite_performers_20160207-14055-129wq59.pdf?AWSAccessKeyId=AKIAIWOWYYGZ2Y53UL3A&Expires=1505237084&Signature=g9oCWcPX5KK2WL8UXf%2BByBBXhg8%3D&response-content-disposition=inli
20 Reisbig AMJ, Danielson JA, Wu T-F, Hafen M, Krienert A, Girard D, et al. A study of depression and anxiety, general health, and academic performance in three cohorts of veterinary medical students across the first three semesters of veterinary school. J Vet Med Educ [Internet]. 2012 [cited 2017 Apr 24];39(4):341–58. https://doi.org/10.3138/jvme.0712-065R. Medline:23187027
21 Sutton RC. Veterinary students and their reported academic and personal experiences during the first year of veterinary school. J Vet Med Educ. 2007;34(5):645–51. https://doi.org/10.3138/jvme.34.5.645. Medline:18326777
22 Pickles KJ, Rhind SM, Miller R, Jackson S, Allister R, Philp J, et al. Potential barriers to veterinary student access to counselling and other support systems: Perceptions of staff and students at a UK veterinary school. Vol. 170, Veterinary Record. 2012. p. 124.
23 Bartram DJ, Baldwin DS. Veterinary surgeons and suicide: a structured review of possible influences on increased risk. Vet Rec [Internet]. 2010 Mar 27 [cited 2018 May 17];166(13):388–97. https://doi.org/10.1136/vr.b4794. Medline:20348468
24 Weston JF, Gardner D, Yeung P. Stressors and protective factors among veterinary students in New Zealand. J Vet Med Educ. 2017;44(1):22–8. https://doi.org/10.3138/jvme.0116-014R1. Medline:28206841
25 Saravanan C, Wilks R. Medical students’ experience of and reaction to stress: The role of depression and anxiety. Sci World J. 2014;2014. https://doi.org/10.1155/2014/737382. Medline:24688425
26 Nahar VK, Davis RE, Dunn C, Layman B, Johnson EC, Dascanio JJ, et al. The prevalence and demographic correlates of stress, anxiety, and depression among veterinary students in the southeastern United States. Res Vet Sci. 2019;125:370–3. https://doi.org/10.1016/j.rvsc.2019.07.007. Medline:31377419
27 Gelberg S, Gelberg H. Stress management interventions for veterinary students. J Vet Med Educ. 2005;32(2):173–81. https://doi.org/10.3138/jvme.32.2.173. Medline:16078169
28 Collins H, Foote D. Managing stress in veterinary students. J Vet Med Educ [Internet]. 2005 Jun [cited 2017 Apr 24];32(2):170–2. https://doi.org/10.3138/jvme.32.2.170. Medline:16078168
29 Kember D. Interpreting student workload and the factors which shape students’ perceptions of their workload. Stud High Educ [Internet]. 2004 Apr [cited 2018 Mar 23];29(2):165–84. https://doi.org/10.1080/0307507042000190778
30 Struyven K, Dochy F, Janssens S, Gielen S. On the dynamics of students’ approaches to learning: The effects of the teaching/learning environment. Learn Instr. 2006;16(4):279–94. https://doi.org/10.1016/j.learninstruc.2006.07.001
31 Gardner DH, Parkinson TJ. Optimism, self-esteem, and social support as mediators of the relationships among workload, stress, and well-being in veterinary students. J Vet Med Educ [Internet]. 2011 [cited 2017 Apr 24];38(1):60–6. https://doi.org/10.3138/jvme.38.1.60. Medline:21805936
32 Soong SKA, Chan LK, Cheers C, Hu C. Impact of video recorded lectures among students. In: ASCILITE 2006 - The Australasian Society for Computers in Learning in Tertiary Education. 2006. p. 789–94.
33 Owston R, Lupshenyuk D, Wideman H. Lecture capture in large undergraduate classes: Student perceptions and academic performance. Internet High Educ [Internet]. 2011;14(4):262–8. https://doi.org/10.1016/j.iheduc.2011.05.006
34 McCunn P, Newton G. Student perception of topic difficulty: Lecture capture in higher education. Australas J Educ Technol. 2015;31(3):252–62. https://doi.org/10.14742/ajet.1681
35 Von Konsky B, Ivins J, Gribble SJ. AJET 25(4) von Konsky, Ivins and Gribble (2009) Lecture attendance and web based lecture technologies: A comparison of student perceptions and usage patterns. Australas J Educ Technol [Internet]. 2009;25(4):581–95. https://doi.org/10.14742/ajet.1130. Available from: http://ascilite.org.au/ajet/ajet25/vonkonsky.html
36 Leadbeater W, Shuttleworth T, Couperthwaite J, Nightingale KP. Evaluating the use and impact of lecture recording in undergraduates: Evidence for distinct approaches by different groups of students. Comput Educ [Internet]. 2013;61(1):185–92. https://doi.org/10.1016/j.compedu.2012.09.011
37 Lizzio A, Wilson K. Action Learning in Higher Education: An investigation of its potential to develop professional capability. Stud High Educ [Internet]. 2004 [cited 2017 Sep 4];29(4):469–88. https://doi.org/10.1080/0307507042000236371. Available from: http://reforma.fen.uchile.cl/Papers/Action Learning in Higher Education & Professional capability - Lizzio, Wilson.pdf
38 Zeegers * P. Student learning in higher education: A path analysis of academic achievement in science. High Educ Res Dev [Internet]. 2004 Feb [cited 2018 Apr 24];23(1):35–56. https://doi.org/10.1080/0729436032000168487
39 Kushnir LP, Kushnir LP, Berry K, Wyman J, Salajan F. Proceedings of ED-MEDIA 2011--World Conference on Educational Multimedia, Hypermedia & Telecommunications [Internet]. Vol. 2011, EdMedia: World Conference on Educational Media and Technology. AACE; 2011 [cited 2018 Apr 26]. 3168–3178 p. Available from: https://www.learntechlib.org/p/38309/
40 Gosper M, McNeill M, Phillips R, Preston G, Woo K, Green D. Web-based lecture technologies and learning and teaching: A study of change in four Australian universities. ALT-J [Internet]. 2010 Nov 13;18(3):251–63. https://doi.org/10.1080/09687769.2010.529111. Available from: https://journal.alt.ac.uk/index.php/rlt/article/view/891
41 Elliott C, Neal D. Evaluating the use of lecture capture using a revealed preference approach. Act Learn High Educ [Internet]. 2016 Jul 1 [cited 2016 Oct 20];17(2):153–67. https://doi.org/10.1177/1469787416637463
42 Hove MC, Corcoran KJ. FACULTY FORUM If you post it, will they come? Lecture availability in introductory psychology. Teach Psychol [Internet]. 2008 [cited 2018 Mar 22]; 35:91–5. https://doi.org/10.1080/00986280802004560. Available from: https://www.researchgate.net/profile/M_Hove/publication/247504756_If_You_Post_It_Will_They_Come_Lecture_Availability_in_Introductory_Psychology/links/0a85e53acbf81262ca000000/If-You-Post-It-Will-They-Come-Lecture-Availability-in-Introductory-Psychology.pdf
43 Edwards MR, Clinton ME. A study exploring the impact of lecture capture availability and lecture capture usage on student attendance and attainment. High Educ. 2019;77(3):403–21. https://doi.org/10.1007/s10734-018-0275-9
44 Gupta N, Irwin JD. In-class distractions: The role of Facebook and the primary learning task. Comput Human Behav. 2016;55:1165–78. https://doi.org/10.1016/j.chb.2014.10.022
45 Zureick AH, Burk-Rafel J, Purkiss JA, Hortsch M. The interrupted learner: How distractions during live and video lectures influence learning outcomes. Anat Sci Educ. 2018;11(4):366–76. https://doi.org/10.1002/ase.1754. Medline:29178200
46 Sanders AE, Lushington K. Effect of perceived stress on student performance in dental school. Journal of dental education. 2002 Jan;66(1):75-81.
47 Kausar R. Perceived Stress, Academic Workloads and Use of Coping Strategies by University Students. J Behav Sci. 2010;20(1):31.
48 Siqueira Drake AA, Hafen M, Rush BR, Reisbig AMJ. Predictors of anxiety and depression in veterinary medicine students: A four-year cohort examination. J Vet Med Educ [Internet]. 2012 [cited 2017 Apr 24];39(4):322–30. https://doi.org/10.3138/jvme.0112-006R. Medline:23187025
49 Sankey MD, Birch D, Gardiner MW. The impact of multiple representations of content using multimedia on learning outcomes across learning styles and modal preferences. Int J Educ Dev Using Inf Commun Technol. 2011;7(3):18–35.
Information & Authors
Information
Published In
Journal of Veterinary Medical Education
Volume 49 • Number 1 • February 2022
Pages: 126 - 137
PubMed: 33956584
Copyright
2022 AAVMC.
History
Published online: 6 May 2021
Published in print: February 2022
Key Words:
Authors
Metrics & Citations
Metrics
Related Content
Citations
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.
Download article citation data for:
Journal of Veterinary Medical Education 2022 49:1, 126-137
Journal of Veterinary Medical Education 2022 49:1, 126-137