Tel. 61-3-9905-3730; Fax: 61-3-9905-3726.
Engagement of students with lectures in biochemistry and pharmacology
Article first published online: 29 AUG 2012
Copyright © 2012 Wiley Periodicals, Inc.
Biochemistry and Molecular Biology Education
Volume 40, Issue 5, pages 300–309, September/October 2012
How to Cite
Davis, E. A., Hodgson, Y. and Macaulay, J. O. (2012), Engagement of students with lectures in biochemistry and pharmacology. Biochem. Mol. Biol. Educ., 40: 300–309. doi: 10.1002/bmb.20627
- Issue published online: 14 SEP 2012
- Article first published online: 29 AUG 2012
- Manuscript Received: 9 MAY 2012
- Manuscript Revised: 9 MAY 2012
- Lecture attendance;
- student engagement;
- academic performance;
- online resources;
- online lecture recordings
Academic staff at universities have become concerned about the decrease in student attendance at lectures and the implication of this on student achievement and learning. Few studies have measured actual lecture attendance in a coherent or comprehensive way. The aim of this study was to measure actual lecture attendance of students over two year levels enrolled in two separate science disciplines, biochemistry and pharmacology. The study further sought to determine the factors that influence lecture attendance. Attendance at lectures in four units of study was monitored over a 12-week semester. Attendance at lectures decreased over the semester and was lower at early morning lectures (8 A.M.; 9 A.M.). A questionnaire surveying students about their preparation for lectures, their compensation for missed lectures and the factors influencing their nonattendance was administered at the end of the semester. Students reported that the major factors influencing their attendance at lectures related to timetable issues and the quality of lecturing. If students missed lectures, the majority read the lecture notes and listened to the online recordings. The availability of online recordings of lectures was not a major influence on attendance at lectures. In three of the four units studied there was no correlation between self-reported lecture attendance and exam performance. The results of the study indicate that universities should dedicate more resources to timetabling and to supporting staff to improve the quality of their lectures.
Student success and achievement is a major issue in higher education. One factor that impacts on student success is student engagement, which has been defined in a number of ways, usually based on student behaviors. Definitions include the willingness or level (time and energy) of student participation and involvement in normal student academic, community and social activities within their institution. Measures of academic engagement include: preparation for and attendance at classes, studying, and interacting with academic staff and peers [1–4]. Studies of student engagement have examined links between engagement, persistence, and grades [5, 6]. Large scale studies, which gather data from a range of higher education institutions, are performed annually in both the USA [The National Survey of Student Engagement (NSSE)] and Australia [Australian Survey of Student Engagement (AUSSE)]. However, as noticeable variation between disciplines, countries and universities has been reported [7, 8], it is difficult to make generalizations; hence, there is a need to study specific aspects of engagement and individual cohorts of students.
To improve student engagement and learning there has been a move away from the traditional didactic lecture format to more interactive engaging lectures requiring active student participation, and the introduction of modalities, which aim to empower students to be active learners [9–12]. An example is the introduction of virtual learning environments (VLEs), which are designed to support learning provide more flexible learning environments and cater to varied learning styles . Although there have been major changes in the student learning environment, in many institutions lectures still remain a major component of most university students' learning experience, particularly where classes are large and resources (both academic staff and physical) are limited. However, many academics report that attendance at lectures is declining and much discussion revolves around the reasons for the decline and the perceived effect on student learning .
Studies that have examined the relationship between attendance at lectures and academic performance have produced conflicting results. While some have suggested a positive relationship between lecture attendance and academic performance [14–22], others have found no such correlation between attendance and performance [23, 24]. Importantly, Millis et al.  reported that a cohort of students performed satisfactorily regardless of their level of attendance. Correlations between lecture attendance and academic achievement must be interpreted with care as there are many factors that may influence academic achievement including student innate ability, effort, and motivation.
Student motivation is consistently discussed in the literature as a major factor in determining attendance at lectures with the assumption that more motivated students are less likely to miss lectures and also more likely to make use of other resources including online lecture notes and audio recordings [22, 25]. A large Australian study  noted that the most common reasons for choosing to attend lectures include motivational aspects (older students) and meeting friends (younger students) while reasons for nonattendance include the inability to attend and the view that they are able to learn as well using web based lecture technologies. The students liked lectures, found them motivating and valued the contact with staff and peers . This study also reported that web based learning technologies and lecture attendance are not necessarily mutually exclusive. In support of this, Grabe and Christopherson  reported that those who attended class more frequently made greater use of online lecture resources.
Many academics at Monash University, Australia have reported (personal observations and communications) a decline in student attendance at lectures and expressed concerns regarding the impact of this on student learning and engagement. While many factors have been proposed as contributing to low attendance rates at lectures, one recurring argument is that the increased flexibility of the learning environment, including online resources such as lecture notes, audio-recordings, quizzes with extensive feedback, references and textbooks, is one of the major factors. This is consistent with views expressed in other studies [20, 26].
Given the many factors reported to influence student attendance at lectures and the variable effect of attendance on academic performance, the objective of this study was to gain a better understanding of Monash University students' engagement with the lecture component of their biochemistry or pharmacology studies. In addition, we aimed to determine how these students compensated for missed lectures and the effect of attendance on exam performance.
The students in this study were enrolled in second- or third-year Biochemistry (BCH) or Pharmacology (PHA) units (subjects) in semester two of 2009. These units could be undertaken as part of either the undergraduate Bachelor of Science (BSc) or Bachelor of Biomedical Science (BBiomedSc) programs at Monash University, Australia. Each of the units ran over a 12-week semester and was equivalent to 0.125 of the full time student load for that year.
The primary modes of learning in these units were face–face lectures (2–3 hours/week), and compulsory laboratory classes or tutorials (3 hours/week). While the lectures were not compulsory, attendance was strongly recommended as they provided the underlying concepts explored further in the weekly practical/tutorial classes. The lectures were recorded by Monash University lectures online (MULO) and were provided either as audio-only recordings (pharmacology units) or full audio-visual recordings via EchoSystem (biochemistry units). EchoSystem captures the visual content, as displayed to students in the lecture from the teaching presentation computer, and synchronizes this with the recorded audio of the lecture—it does not include video of the presenter. Media content was made available on the internet at the conclusion of the lecture via Rich Media streaming or direct download, vodcast or podcast. Lecture notes (powerpoint or PDF) were available to students before the lectures.
Attendance at lectures in each unit was monitored by a manual head count of students in the lecture theatre ∼30-45 min into each 50-min lecture. This count was done either by the lecturer (during an appropriate break in the delivery) or by other staff members who also informally observed student in-class behavior.
During the last week of semester, students were invited to complete a paper-based survey during a timetabled class. This survey was not compulsory and could be anonymous, although students were given the option of providing their student ID number so that responses could be related to academic performance. The survey collected information related to the demographics of the student cohort, student engagement with lectures and factors that influenced lecture attendance using closed-ended questions (demographics) or a 5 point Likert scale. In addition, questions specific to each unit were used to determine patterns of lecture attendance. Students were invited to provide general comments about lecture attendance and the role and value of lectures in a free response section. Ethics approval for this survey was granted from the Monash University Human Research Ethics Committee.
Survey responses were entered into excel spreadsheets, which were collated and formatted for statistical analysis using SPSS (PASW software). Tests employed were one way ANOVA and the nonparametric Kruskal–Wallis test.
Where the 5 point Likert scale (5 = strongly agree, 1 = strongly disagree) was used to gauge how closely students agreed with each survey statement, data is presented as % agree that includes % agree and % strongly agree.
The demographic data for the students completing the surveys are presented in Table I. The response rates varied between 76% and 88% for the four units (Table I). Of the students responding, the majority were <22-years-old (80–95%) and female (59–72%), which reflected the enrollment profile for each unit. The average time spent on campus each week was between 22 and 26 hours and the average number of hours spent traveling to and from university was between 5 and 6 hours (Table I). While there were no significant differences between second- and third-year students, nor between disciplines (p > 0.05; one-way ANOVA), it must be emphasized that the average times varied within each unit. Some students reported that they spent long hours (>30) at university and some reported that they travelled for more than 10 hours each week.
|Number completing survey||101||61||113||42|
|Age (in years)|
|Gender of respondents|
|Median tertiary entry score (ENTER)||86||90||89||87|
|Average number of hours spent:|
|On campus each week (range)||26 (2–48)||24 (3–45)||23 (5–50)||22 (1–40)|
|Traveling to university each week (range)||5 (<1–20)||6 (<1–16)||6 (<1–30)||5 (<1–15)|
|Students in paid employment||45%||38%||37%||34%|
|Students studying full-time||98%||98%||99%||95%|
Although the students surveyed were enrolled in several different degree programs with different entry requirements, there was no difference in the median tertiary entrance score (ENTER; http://www.vcaa.vic.edu.au/vce/) between the groups (Table I).
The majority of students in each unit were enrolled as full time students (Table I), although over one-third of students in each unit indicated that they had paid employment (Table I). Of these, the majority were working between 5 and 15 hours each week (Table II). Across the units, there were no significant differences in the percentage of students working (Table I), or in the hours spent working (Table II) (p > 0.05 Kruskal–Wallis One-Way ANOVA). Interestingly, less than a third of students agreed that their paid job interfered with their attendance at university, but higher numbers (37–45%) agreed that their job interfered with their private study (Table II).
|Biochemistry (%)||Pharmacology (%)|
|Hours spent in outside employment:|
|Students who agree or strongly agree that their paid job interferes with their:|
|Attendance at university||13||18||26||10|
Although analysis of planned destination of the students once finishing their degree revealed no significant differences between the groups (Fig. 1; p > 0.05 Kruskal–Wallis ANOVA) there were some trends in the data. In both pharmacology and biochemistry, a 4th year involving a discipline-specific research project was more likely to be considered by third- than second-year students. In addition, a greater number of pharmacology students were considering postgraduate programs.
Overall, analysis of the demographic data demonstrated the homogeneity of the student cohorts across the four units examined.
Lecture attendance for each of the four units is presented in Fig. 2. From this data it could be seen that the lowest attendance was at the 8 A.M. lectures (Fig. 2), whereas there was a trend for attendance to be highest at lectures scheduled between 10 A.M. and 1 P.M. Regardless of time of day, attendance decreased such that by the end of the semester, with the exception of third-year pharmacology, less than 50% of the enrolled students were attending (Fig. 2).
Interestingly, attendance at lectures in the third-year pharmacology unit (Fig. 2 d) did not decrease to the same extent as that seen with the other units (including second-year pharmacology) with attendance in the final week being the highest of the semester. It should be noted that there was an in-class assessment task held in the Friday lecture in week 12 and students had been notified that this assessment was based on information presented in the previous (Monday) lecture.
Weekly fluctuations were evident in lecture attendance in all units. Informal discussions with students indicated that factors such as heavy traffic and social activities (e.g. the Science Student's Ball), as well as deadlines for assessments influenced attendance, particularly at morning lectures.
Self-Reporting of Lecture Attendance
Students were asked to indicate how many lectures a week they normally attended for the specific biochemistry or pharmacology units. From this, three subsets were defined—students who normally attended all lectures; those who missed 1–2 lectures each week and those who normally did not attend any lectures for that unit (see Table III).
|Biochemistry (%)||Pharmacology (%)|
|% Students who:|
|Attend all lectures||29||29||37||55|
|Miss 1 or 2 lectures/week||62||69||52||38|
|Attend no lectures||9||2||11||7|
|% Students who indicated that they routinely miss lectures at the same timeslot|
In the units which had three lectures a week (both biochemistry units and second-year pharmacology), <40% of students normally attended all lectures and a large proportion of the class regularly missed 1–2 lectures each week. Students reported a higher attendance at all lectures in third-year pharmacology, which only had 2 lectures/wk. However, a similar percentage of students attended no lectures in this unit.
Factors Influencing Lecture Attendance
From informal discussions with students and staff a list of factors that may influence attendance at lectures was developed and students were asked to indicate using the 5-point Likert scale (strongly agree = 5, to strongly disagree =1), which of these influenced their attendance. These factors were broadly divided into sub categories of timetabling issues; outside commitments and quality of lecturing (Figs. 3 a– 3 c).
In all units, timetable clashes with practical classes or other lectures were identified as major reasons for non-attendance at lectures. This was particularly evident in the second-year pharmacology (68%) and the third-year biochemistry (73%) units (Fig. 3 a). The units with the highest percentage of students agreeing that their lecture attendance was influenced by the lectures being too early in the day were the biochemistry units. Other major influences on lecture attendance were lack of sleep (Fig. 3 b), poor quality of lecturing, and student motivation (Fig. 3 c).
Do Students Value Lectures?
Only a small percentage (∼10%) of the students surveyed agreed that the availability of online audio-recordings or comprehensive lecture notes discouraged them from attending lectures (Q10 and Q11, Table IV). Similarly, a minority of students agreed that lecture recordings or online lecture notes were a substitute for lecture attendance (Q15 and Q12, Table IV).
|Biochemistry (%)||Pharmacology (%)|
|Q10. The availability of online audio-recordings discourages me from attending lectures||9||11||10||12|
|Q11. The availability of comprehensive lecture notes on Blackboard discourages me from attending lectures||9||5||4||7|
|Q12. I believe that online lecture notes are a substitute for lectures||18||25||18||21|
|Q14. I believe that online lecture notes complement lectures||89||85||81||71|
|Q15. I believe that the availability of online audio recordings of lectures replaces the need to attend lectures||6||8||14||10|
|Q16. I believe that I learn more if I attend lectures||78||67||73||81|
|Q17. I believe that my exam results would be better if I attended more lectures||66||56||51||57|
|Q18. I believe that university teaching should move away from lectures||8||5||14||2|
Despite the low attendance, the majority of students did not believe that university teaching should move away from lectures (Q18, Table IV). Most not only believed that they learn more if they attend lectures (Q16, Table IV) but also that their exam marks would be better if they attended more lectures (Q17, Table IV).
Preparation for and Behavior at Lectures
While the majority of students in all units accessed the lecture notes prior to the lecture (if available) and took them to the lecture (Q3, Table V), few read the notes or references before attending the lecture (Q1 and Q2, Table V). There was no difference between the disciplines in the numbers of students who read through the lecture notes before attending the lectures (Q1, Table V).
|Biochemistry (% agree)||Pharmacology (% agree)|
|Before the lecture:|
|Q1. I usually read through lecture notes (if they are available) before attending the lectures||13||19||13||12|
|Q2. I usually read the references given before the lectures||3||3||4||2|
|At the lecture:|
|Q3. I usually take lecture notes (if available) to the lectures I attend||75||75||77||76|
|Q4. I usually write notes at lectures||74||86||85||79|
|After the lecture:|
|Q5. I usually read my lecture notes after the lecture||60||64||48||46|
|Q6. I usually read the references given after the lecture||25||31||14||13|
|Q13. I use online recordings to clarify points from lectures I attended||55||60||55||57|
Within each unit, the majority of students indicated that they usually write notes at lectures (Q4, Table V). While the degree of note taking was not explored in any great detail in this study, informal observations of students within these lectures suggested that the main form of note taking was annotation of the instructor-provided lecture notes. Furthermore, these informal observations of student behavior revealed that a small percentage of students who were physically present were engaged in other activities (including watching online videos; completing assessment tasks for that or other units).
Although students were taking notes to class and writing notes in class, fewer followed up the lecture material after the lecture either by reading over their notes or reading the references given (Q5 and Q6, Table V). This seemed particularly apparent in the pharmacology units where only 48% of the second-years and 46% of the third-years indicated that they read their lecture notes after the lecture. However, over 50% of students in each unit made use of the online lecture recordings to clarify points from lectures after the lecture (Q13, Table V).
What do Students Do if They Do not Attend Lectures?
If students did not attend lectures, they were most likely to read the lecture notes (Q8, Table VI), and over 50% listened to the online lecture recordings (Q7, Table VI). Third year students were more likely to read the lecture notes than second-year students (Q8 Table VI), with 95% of the pharmacology third-year students reading lecture notes to make up for missed lectures.
|Biochemistry (%)||Pharmacology (%)|
|If I do not attend lectures I:|
|Q7. Listen to the online audio-recordings||54||73||65||60|
|Q8. Read the lecture notes||78||85||79||95|
|Q9. Read the references given||25||32||19||17|
Importantly, few of the students who missed lectures read the references that had been provided (Q9, Table VI). Pharmacology students were least likely to read the references given with only 19% of the second-years and 17% of the third-years reading these. The percentage of students who read the references was similar whether they attended (Q6, Table V) or missed the lecture (Q9, Table VI).
Correlation Between Self-Reported Lecture Attendance and Exam Performance
Within each unit a number of students volunteered their ID number, which allowed us to link their responses to their academic performance within the unit (Table VII). For this comparison, students in each unit were separated into the three attendance subsets (Attended all lectures; missed 1–2 lectures each week; and attended no lectures) and the mean exam marks (± standard deviation) for each subset were calculated. These data are presented in Fig. 4.
|Number students completing survey||101||61||113||42|
|Number students providing ID number||57 (56%)||41 (67%)||65 (58%)||16 (38%)|
For both biochemistry units and the second-year pharmacology unit, students who attended all lectures achieved a higher exam mark than students who regularly missed one or more lectures each week. This correlation was statistically significant for the second-year pharmacology unit (p < 0.05; Kendall's tau nonparametric test). The third-year pharmacology unit did not follow this trend and there was little difference in the mean exam mark between the three attendance groups.
The results of this project have provided a deeper understanding of the patterns of attendance of science and biomedical science students at biochemistry and pharmacology lectures at Monash University and the factors that influence this. It is worthwhile noting that in the units studied, 100% lecture attendance was never seen, even in the first lecture in which unit guides were given and assessment tasks were introduced. It needs to be highlighted that second-year is the students' first exposure to biochemistry and pharmacology and while some second-year students may have completed one semester of biochemistry, this is the first semester of pharmacology that can be taken. Students undertaking the third-year units are likely to have selected the discipline as their major sequence of study. It would be expected, therefore that they have an inherent interest in the discipline. Indeed, a number of the third-year students in both pharmacology and biochemistry had indicated that they were considering doing a fourth-year research project in that discipline. However, comparing the second- and third-year biochemistry units (Figs. 2 a and 2 c), attendance was no greater in the third-year unit despite the fact that the third-year lecture material is based on cutting edge research not yet incorporated into the recommended texts. The pattern of attendance at the third-year pharmacology lectures differed from that of the other units. A number of factors could contribute to this difference including the lower enrollment and the inclusion of in-class assessment tasks in weeks 11 and 12. Interestingly, this unit also had fewer lectures per week and a lower proportion of students reported timetable clashes as an influence on lecture attendance for this unit.
Previous studies looking at attendance at lectures carried out at different institutions and for various degree programs, have reported varying levels of attendance [6, 14, 18, 17]. However, it is important to differentiate self-reporting of attendance from actual counts of students present, particularly in light of reports that self-reporting of course-related behaviors do not accurately represent actual behaviors [27, 28]. In our study, counts of students revealed that attendance frequently fell below 50% of the enrolled cohort, which concurs with the majority of students indicating that they regularly miss at least one lecture a week. It is interesting to note that in some studies  low attendance was at 75%, while in others , as in this study, attendance fell to much lower levels.
At Monash University, day classes are scheduled to run between 8:00 A.M. to 6:00 P.M. The lectures for the units studied as part of this project were spread across the week, but tended to occur in the morning sessions. The fall in attendance over the semester is consistent with other studies of lecture attendance [14, 24]. Interestingly, Newman-Ford et al.,  and Kelly  found attendances at early morning lectures were not significantly different from attendance later in the day. In contrast, our data shows much lower attendance at early morning (8:00 A.M.) lectures and this was supported by the student survey in which “lectures too early in the day” was the third most important factor influencing lecture attendance. Fewer students indicated that they attended all lectures in the biochemistry units, which had 8:00 A.M. lectures. Comments such as “I live too far to come to lectures” and “Lectures should start later. Those who live far have to get up at 6am!” reinforce the importance of timing on lecture attendance.
Informal observations of student behavior during lectures revealed that while some students were attentive and taking notes, a number of students were engaged in nonlecture related activities including reading unrelated web sites, watching videos, and working on other assessment tasks. These students exhibited little engagement with the lecture content during the period of observation, reminding us that attendance does not necessarily guarantee engagement. As von Konsky et al. (24, p. 593) noted “physical presence during a lecture does not mean that a student is paying attention.” Thus, lecture attendance per se may not be the issue. The concern is that some of the content covered in the lectures underpins the learning activities of the weekly laboratory classes and tutorials. Without this context, students may not achieve the expected learning outcomes particularly those relating to the integration and application of knowledge.
At Monash University, lectures are not a compulsory activity and individual timetables may have clashes between lectures in one unit and classes in other units. Indeed, timetable clashes were the major factors influencing lecture attendance in all units. Other timetabling issues affecting attendance were lectures being too early in the day and either large gaps between classes or too few timetabled hours on a day. The later point is particularly relevant for students who spend many hours traveling to and from university. It was noted that the range of travel times for students was large, with some spending up to 30 hr a week traveling to and from classes. Comments such as “Due to travel time its not worth travelling 2 hrs to attend a 50 min lecture” and “I like learning from lectures. I would attend more if I didn't live so far away” support this. This is likely to be a particular issue with early lectures requiring travel in peak hour. Travel time may be a point of difference between universities in Australian cities and some international studies where students are more likely to live on or close to campus and this makes it difficult to generalize across populations, emphasizing the need for research of specific student cohorts. In this study, a minority of students indicated that outside commitments (work, family commitments) influenced attendance although the survey results suggested that work commitments were more likely to affect personal study than attendance at classes. Kelly  and Kottasz  also found that work commitments have a minor affect on lecture attendance.
Availability of Online Materials
While some academics have expressed the view that the fall in lecture attendance correlates with the increased availability of online learning materials and the recording of lectures , several studies both within Australia [26, 27], and the USA  have concluded that this is not the case, which correlates with the feedback from students in this study. Only ∼10% of the respondents agreed that the availability of online audio-recordings or comprehensive lecture notes discouraged them from attending lectures. Our data is in line with that of Copley , who found that 12% of the UK students surveyed reported that the availability of online lectures contributed to their nonattendance at lectures. Indeed the majority of students in our study did not agree that lecture recordings or online lecture notes were a substitute for lecture attendance, but rather complimented lectures, which supports the findings of Gysbers et al.  that online resources do not fully substitute for the face-to-face lecture. The use of online recordings was similar between the biochemistry and pharmacology units despite the former using the Echo system, which provided audio and visual recordings of the lectures and therefore a more comprehensive resource than the audio only recordings used for the pharmacology units.
It should be noted that even though students did not agree that the availability of online recordings influenced their attendance at lectures, it is possible that they were more likely to miss a lecture for other reasons knowing that a recording would be available. The recordings may, therefore, be a safety net for missed lectures. In this way our findings are consistent with Gysbers et al.  and Scutter et al.  who found that students do not generally substitute lectures with recordings but use the recordings for review or to revisit difficult concepts. In addition, Larkin  and Gysbers et al.  reported that students “expressed a preference for not using recorded lectures to replace face-to-face teaching” [27, p. 243], which correlates with our students who expressed a strong view that university teaching should not move away from face-to-face teaching.
Counting students at each lecture only gave an indication of the numbers of students present and did not allow us to identify whether the same students were consistently absent. From the self-reporting of lecture attendance, it was evident that the majority of students were missing at least one lecture each week, particularly in the units with early (8:00 A.M.) lectures. Given the feedback from students that timetable clashes and early lecture times were factors influencing their nonattendance at lectures, it was not surprising that these students routinely miss lectures in the same timeslot. However, quite a high percentage of students missed lectures at different times, which reinforces that there are a variety of reasons for nonattendance. Of concern is that there was a proportion of each class (<11%) that did not attend any lectures, which leads us to question how they are learning and the timing of this learning.
The survey aimed to gain a better understanding of how students used lectures as part of their learning. To do this we asked questions relating to how students prepared for lectures they attended; their note-taking behavior and also how they reviewed the material covered. The results suggested that there is little preparation for lectures with few reading either the lecture notes or references prior to the lecture. While the timing of the availability of the notes would be expected to influence whether students read over them, it is interesting to note that lecture notes for the two biochemistry units were usually available a week before the lecture, whereas the notes for the pharmacology units were often not available until the day before. Despite this difference in timing, there was no difference between the disciplines in the numbers of students who read through the lecture notes before attending the lectures. The low use of the references given may relate to the importance put on these by the lecturer as most provided these as suggestions for additional clarification or extension rather than required readings.
Generally, the results from this survey point to students' having adopted a passive approach to learning from lectures—they used the notes provided. However, the lecturing style must also be taken into account and, for at least some of the lectures in each unit; it is likely that there was little opportunity for students to be actively involved in the learning process in class. It would be interesting to explore further the impact of lecturing style on student engagement, in particular note-taking and participation in class discussions.
If they missed a lecture, some students made an attempt to cover the material they had missed by reading the notes provided and/or listening to the lecture recordings. It is important to emphasize that this survey did not collect any data as to when they did this, so it is possible that this was some time after the actual lecture was given and may not have been in time to help them with understanding of the weekly practical class/tutorial activities. Of concern is that some students may do little to make up for missed lectures while others may rely solely on the lecture notes thus gaining a very superficial coverage of the material.
To determine whether lecture attendance affected academic performance we correlated self-reported lecture attendance with exam mark, which was considered the most appropriate indicator of knowledge and concepts covered within the lecture series. Our ideal study would have allowed us to record attendance of individual students to allow comparison with academic performance of all students. However, this was not possible given the Monash University policy of noncompulsory attendance at lectures and ethical requirements when using students as research subjects. While only a proportion of the full class provided student ID numbers to allow this correlation, we believe the data does provide a snapshot of the relationship between self-reported lecture attendance and exam performance. While there were trends for increased lecture attendance to be associated with increased exam performance in three of the four units, this was only significant for the second-year pharmacology unit. While for the third-year pharmacology unit, there was no trend for decreased exam performance with missing lectures, it should be pointed out that this unit had the lowest number of students in each attendance group, which makes it difficult to generalize from this data.
Previous studies, which have addressed the question of whether there is a correlation between lecture attendance and academic performance have produced varying results, with both positive [14, 15, 17–19, 21, 34] and neutral [23, 24] correlations being reported. Interestingly, Van Walbeek  reported that the differential in test scores between poor lecture attendees and regular lecture attendees increases as the term progresses. However, it has been argued that student motivation rather than attendance may be a more important factor . Other studies have examined factors such as school grades [35, 36] sex and ethnicity [35, 37] as predictors of academic performance, along with other possible confounding factors such as ability, prior knowledge , the recognition of exam clues given in lectures,  and engagement with specific learning experiences . Von Konsky et al.  reported that if students perceive that something is of value to their learning then they are more likely to use it. In our study, the unit that included in-lecture assessment and lectures that were associated with a specific assessment task, motivated students to attend.
While we have presented data from four units across one semester of study, lecture counts and student survey data has been collected for a number of years and similar trends were evident across all years. This highlights that lecture attendance is an issue of ongoing concern that needs a coordinated response involving curriculum design and University policy.
Student attendance and interactions with academic staff have been reported to be an important aspect and measure of engagement [3, 4, 7]. While VLE and newer online communication systems may be able to overcome a lack of face-to-face interaction , for many students face-to-face learning in the classroom is the only regular opportunity they have for interacting with other students and academic staff. Thus, using the classroom to create communities of learning, which engage students must be a high priority. If we believe that lectures provide a medium to engage and enthuse students in the subject  we need to consider not only the style of the lecture but also timetabling issues, which impact on attendance. The results of this study suggest that there is a need for universities to support staff to improve the quality of lecturing and that careful consideration must be given to the timetabling issues of early morning lectures and class clashes.
- 22011) Are nursing students engaged in learning? A secondary analysis of data from the national survey of student engagement. Nurs. Educ. Perspect. 32, 89–95., (
- 32008) Why integration and engagement are essential to effective educational practice in the twenty-first century. Peer Rev. 10, 27–28.(
- 62007) Engineering student attendance at lectures: Effect on examination performance, International Conference on Engineering Education–ICEE 2007 Available online at http://icee2007.dei.uc.pt/proceedings/papers/107.pdf (accessed 09/02/12).(
- 72003) What we're learning about student engagement from NSSE. Change 35, 24–32.(
- 92011) Students' experiences of active engagement through cooperative learning activities. Active Learn. High. Educ. 12, 23–33.(
- 122005) Learning in lectures: Do interactive windows help? Active Learn. High. Educ. 6, 17–31.(
- 161995) The effects of attendance on student learning in principles of economics. Am. Econ. Rev. 85, 343–346., (
- 172003) Nonmajors' performance in biology. J. Coll. Sci. Teach. 33, 18–21., (
- 192007) The relationship between lecture attendance and academic performance in an undergraduate psychology class. S. Afr. J. Psychol. 37, 656–660., , (
- 242009) Lecture attendance and web based lecture technologies: A comparison of student perceptions and usage patterns. Australas. J. Educ. Tec. 25, 581–595., , (
- 262008) The impact of web-based lecture technologies on current and future practices in learning and teaching, http://www.altc.edu.au/project-impact-webbased-lecture-macquarie-2006 (Accessed 12/01/12)., , , , , (
- 272004) Helping students succeed in introductory science courses. J. Coll. Sci. Teach. 33, 14–17.(
- 292010) “But they won't come to lectures …” The impact of audio recorded lectures on student experience and attendance. Australas. J. Educ. Technol. 26, 238–249.(
- 302005) Reasons for student non-attendance at lectures and tutorials: An analysis. Investig. Univ. Teach. Learn. 2, 5–16.(
- 322011) Why do students still bother coming to lectures, when everything is available online? Int. J. Innov. Sci. Math. Educ. 19, 20–36., , , (
- 332010) How do students use podcasts to support learning? Educ. Technol. 26, 180–191., , , (
- 362006) Academic attributes of college freshmen that lead to success in actuarial studies in a business college. J. Educ. Bus. 81, 256–260., (
- 382007) Reflections on the lecture: Outmoded medium or instrument of inspiration? J. Further High. Educ. 31, 397–406.(