Researching the student experience
Mary Thorpe
Institute of Educational Technology The Open University
Walton Hall
Milton Keynes, MK7 6AA M.S.Thorpe@open.ac.uk
ABSTRACT. Distance learning and elearning claim to overcome the barriers of time and place. However, empirical studies show a relationship between student perceptions and management of study time, and the quality of their learning. Students who drop out often relate this to lack of time for study. Students who pass courses also fall behind the study schedule and find workload on some courses much more than expected. Pedagogically desirable uses of learning technologies such as collaborative conferencing and synchronous virtual meetings can bring added time pressures rather than benefits for learning. Research is needed to explore how students use time for study and to compare their study workload practices with the expectations of educators and designers.
RÉSUMÉ. L’enseignement à distance et le e-learning prétendent surmonter les obstacles du temps et de l’espace. Toutefois, des études empiriques montrent un lien entre les perceptions et la gestion de son temps d’étude par l’étudiant et la qualité de son apprentissage. Les étudiants qui abandonnent leurs études évoquent souvent le manque de temps. Les étudiants qui réussissent prennent aussi du retard par rapport au programme prévu, et trouvent que les travaux d’étude sont souvent beaucoup plus importants qu’ils ne le prévoyaient.
L’utilisation, pédagogiquement souhaitable, de technologies éducatives pour des conférences collaboratives et des réunions virtuelles synchrones par exemple, ajoute parfois aux difficultés d’organisation plus qu’elle ne facilite l’apprentissage. Il est donc nécessaire de conduire une recherche plus approfondie pour comprendre comment les étudiants gèrent leur temps d’étude et pour comparer la façon dont ils effectuent leurs travaux d’étude avec ce que les pédagogues et les concepteurs de ces travaux en attendent.
KEYWORDS: study workload, learning quality, course design, elearning, pedagogy, distance learning.
MOTS-CLÉS : charge de travail pour l’étudiant, qualité de l’apprentissage, conception des cours, pédagogie, apprentissage à distance.
Introduction
Our conceptions of time and learning are inter-related historically. For example, achieving a degree used to require attendance at a campus for a set number of weeks a year for several years. However, many learners are no longer studying full-time or physically attending a campus, but they are required to demonstrate certain learning outcomes in order to pass their course, and these reflect expectations about what ought to be achieved within a certain time frame. Achievement of these learning outcomes may also be phased over time, and require participation in group events and interactions that are scheduled and paced. Participation in such courses therefore, however flexibly presented, will still require some coordination between the learner’s personal time and the time schedule of the course.
However, the application of information and communication technologies to campus-based as well as distance learning has tended to strengthen the rhetoric about overcoming barriers to learning. Goodyear comments that The dominant techno-romanticist discourse of e-learning asserts that time and space are no longer barriers and that time is “strangely under-examined in the literature of e- learning” (Goodyear, 2006, p. 83-84). This may reflect the difficulty of researching time. Our perceptions about how long something takes to study can be skewed by whether we find the task interesting, or the context supportive. The same task can take more or less time, depending on how we feel at the time, and what other events are happening in our lives. The same time conditions do not provoke the same response in others, and there are many different ways in which each of us interprets the time we have available, and the “fit” between this perception and our goals and responsibilities.
Although we claim to have reduced the time barriers against learning, we may in reality have displaced them, and in so doing, moved time management issues back to learners. Open and online learning may be taken up at the study times preferred by the learner, but also leave length of study time to the discretion of learners too.
Lacking the immediate guidance of a tutor, learners may study tasks for longer than was intended – or indeed spend less time than was intended and postpone study until just before the deadline for assessment. Neither approach may be appropriate or helpful for the quality of learning.
This article opens up a number of issues about how learners perceive time and use time in the context of study. First there is the issue of how student approaches to learning are influenced by perceptions of study tasks, including their workload requirements. Second there is the issue of how learners manage study time, and the impact of this on their completion of courses. Third there is the issue of match or mis-match between the quantity and pacing of study time by educators, and the pacing and quantity of study time used by learners. Fourth, learners have different expectations about how much time for study is required and may struggle to complete courses that exceed their expectations. eLearning can also present new challenges, related on one hand to desynchronisation of study activities, and on the other, to the
intensification of structure and pacing. Finally, there is the issue of “what is to be done” and suggestions are made for research in support of effective pedagogy for elearning.
Study time and the quality of student learning
The relational approach to student learning in higher education has established an association between students’ perceptions of the quality of the study environment, and their approach to how to study. The key features of this perspective are that students approaches to learning are seen to be relational rather than mainly characteristics of the student, and that variation in approaches to learning is related to variation in the quality of the outcomes of learning. (Trigwell, 2006, p. 108) Students may be pressured by excessive workload for example, and may adopt a focus on completing work rather than trying to understand. This has been termed a “surface” approach, whereas a “deep” approach, in which the student focuses on finding meaning in what is studied, is preferred (Marton et al., 1984).
Trigwell also reports a phenomenographic study of teaching that demonstrated how teachers’ approaches were associated with deep or surface approaches to learning by their students (Trigwell, 2006, p. 113). Teachers who focused on what their students were doing and understanding, and gave a lot of time for discussion during teaching sessions were more likely to have students who took a deep approach to study.
Excessive workload however can militate against such an approach by reducing time for discussion and pushing students towards a surface approach, characterised by anxiety and memorisation rather than understanding.
When students evaluate the quality of their courses, workload is one of the key issues from their perspective. Ramsden has developed a survey instrument, The Course Experience Questionnaire designed to provide data on the teaching effectiveness of programmes of study (Ramsden, 1991). He reports the work of Marsh (1987) who includes workload as one of the key dimensions in effective teaching, based on a large survey of the literature. Ramsden’s Course Experience Questionnaire was developed, informed by this literature and by small-scale pilots in Australia. It uses a number of scales including “appropriate workload”, assessed by items such as the following, with which students are invited to agree or disagree: The sheer volume of work to be got through in this course means you can’t comprehend it all thoroughly (p. 134). This questionnaire has been used in national surveys of student evaluations of course quality in higher education institutions in Australia, the results confirming the validity of each of the scales used in the survey (Ramsden, 1991, p. 144).
The Course Experience Questionnaire has also been used several times at the Open University with some amendments to accommodate the teaching system, and the results have confirmed the validity of the instrument for identifying differences of teaching quality between courses and between programmes of study (Lawless and Richardson, 2004, p. 370). Students make effective use of the “appropriate
workload” scale as well as the scales for good materials, clear goals and standards, generic skills, student choice and good tutoring, to assess the quality of their courses.
Course-specific studies have also found a link between approach to study and the amount of time that students spend studying. Activities in study texts for example, provide opportunities for students to test out their understanding, to make connections between old and new knowledge, and generally to study actively and in-depth. Lockwood undertook interviews of a range of students registered on Open University courses, and discovered that while most could see the value of activities, ability to do them properly was impeded by a perceived lack of study time (Lockwood, 1992). Some learners did engage with the activities as set, and in interview reported that they took as long as necessary for understanding. Others reported that time pressures led them to degrade activities – not thinking them through, or only reading the solution, and sometimes ignoring them completely (Lockwood, 1992, p. 112-117);
Lawless also studied a sample of six courses, three in mathematics and two in computing, all of which used activities extensively and included about twenty per unit. Qualitative research established that students tackled these activities in different ways, captured by these scenarios describing the distinctive approaches (Lawless, 2000, p. 100):
1. Make a serious effort and succeed.
2. Make a serious effort but give up as unable to complete.
3. Briefly attempt then read the solution.
4. Read the solution only.
5. Ignore the activity.
A survey of a random sample of students (1321) on these courses with a response rate of 64%, found that two-thirds said that they never ignored activities, and roughly half (53.4%) said that they usually made a serious effort and succeeded.
Around two-thirds however sometimes adopted scenarios 3 and 4, indicating some variation in study approach across the course. The average study time reported for both scenarios1 and 2 was around one hour per activity. This was roughly twice the average time that students spent who adopted the scenarios of a brief attempt or reading the solution only (scenarios 3 and 4 above), which was about half an hour.
Students were also asked about their reasons for studying the course, and responses split between “mainly to learn the subject” (47.8%) and “mainly to pass the course” (47.3%). Students studying mainly to learn the subject were more likely to spend longer on activities and to make a serious effort to solve and succeed (Lawless, 2000, p. 106). Students’ orientation to study thus appears to support their willingness to study for longer, and to take advantage of course features that develop understanding. However it was also found that students on one course spent longer on activities than on any other course. This course used fewer activities, they were computer-based and were strongly related to the core content of the course, which
was about computing. We have evidence therefore that study time is influenced by both learners’ study purpose and by the teaching approach and how it is perceived by learners.
These different studies point towards the importance of study workload in the perceptions of students, but also show that there is no simple causal relationship between workload and student response. Student context as well as the teaching context play important roles.
The learner perspective on course study and workload management
We can explore these issues further, in the context of learner perspectives generated during study of undergraduate courses at the Open University UK. The concept of workload refers to study as a programme of learning that is intended to be completed and assessed within a defined period of time, determined by an educational authority. In the OU context, the typical study period is 32/34 weeks, with most courses intended for either 8 or 16 hours study on average every week.
Data on student perceptions of the workload on their courses is generated by means of regular large scale questionnaires. The next section deals with issues revealed by the annual survey of students who drop out from their courses.
Study workload in the perception of students who drop out from their courses There are indicators that students perceive finding time to study as a factor that influences whether or not they persist or decide to drop out. Students who drop out from their courses are asked to complete a questionnaire at the point when they notify the university. In 2005 the response rate was 20%, with 5916 student respondents. Students were asked what factors in their view caused them to drop out. The response selected most frequently was I fell behind with my course work.
Table 1 shows that not being able to keep up with study goals is selected by the biggest percentage of students, and pressure from work and home obligations directly affects at least a third of all our students who drop out.
Table 1. Reasons for withdrawal stated by student who drop out of their course*
Reasons for withdrawal %
I fell behind with my course work 43
General personal/family or employment responsibilities 37 Increase in personal/family or employment responsibilities 29
* Ashby, 2004, p. 71.
Questions can be raised about whether or not time is a causal factor, or whether it masks other factors that are less palatable. Students who feel that they are not succeeding, may choose to lay the blame on factors outside themselves and their own abilities. But time is implicitly bound up with learning success, in that different learners might be able to learn the same thing, but some would take very much longer than others. Learning often has to be measured within time constraints, meaning that we cannot ignore the length of time it takes learners to achieve mastery.
Study workload in the perception of students who complete their courses Evidence we have about the experience of students who do not drop out and who pass their course, suggests that study workload is also an issue for successful students. The Open University surveys every year a random sample of about 40,000 students selected from approximately one third (120) of all its courses. Students are asked to rate all aspects of the quality of their course, including workload issues.
Only those who have completed both the continuous assessment and the examination for their course are included, so that their responses do reflect experience across the whole course. In 2005 the response rate was 49% with 14,367 students responding out of 26, 348 who completed the assessment.
When asked whether they fell behind the study calendar for their course, 57%
of those surveyed in 2005 said that they had done so, and previous years produced a similar figure. This is also an average and we know that some courses present more workload pressures than others, with students more likely to fall behind as a result.
Time is of course not a straightforward issue. We may think of it as a zero sum game. When we spend an hour in one task, we can never recoup that time and allocate it to another task. Nor can we expand the number of hours in a day – chronologically measured time is finite, in this context. However, students differ in their perceptions of how much time they have available for study, and this will impact on how pressured each hour of available time will be. Time may be measured objectively, but students experience it subjectively, coloured by the pressures and activities going on in the rest of their lives (Dieumegarde et al., 2006).
Student expectations about study hours versus actual study time
The evidence from the Open University is that from one third up to two thirds of our students say that they have to study for longer each week than the University’s estimated study hours for their course.
Most courses at undergraduate level are designed as either one quarter or one half of a full time year’s study. Thirty point courses are designed for 5 to 8 hours study per week on average, and sixty point courses for 13 to 16 hours study per week. These average study time figures are included in student information and referred to in course guides. However, table 2 shows that some students come with
quite different expectations. The majority of students studying thirty point courses (5-8 hours a week) expect study time to be higher than officially stated and only 27%
say that their actual study hours were within the expected band of 5 to 8 hours per week. Two thirds studied for longer – 33% for more than 13 hours a week.
Table 2. Expected study hours and actual study hours for 30 and 60 point courses, 2005 (Courses Survey data, for students completing the course)
Average study hours per
week
Courses designed for 5-8 hours study per week (30 points)
Courses designed for 13-16 hours study per week
(60 points) Study hours
Expected by the student
Actual study hours
Study hours Expected by the student
Actual study hours
0-4 4% 7% 1% 1%
5-8 42% 27% 9% 10%
9-12 33% 33% 33% 26%
13-16 16% 19% 44% 28%
17-20 3% 10% 10% 22%
More than 20 1% 4% 3% 13%
These data tend to confirm the impression that many Open University staff and students have, which is that courses aiming to create the equivalent of a quarter of the study load of a full time year at university, are more difficult to get right in terms of study time, than courses designed to be the equivalent of half-time study.
Turning to sixty point courses intended to require 13 to 16 hours study a week on average, table 2 shows that 43% of our students actually expected their course to require fewer hours per week and a minority – 37% – claimed that their actual study hours were less than the recommended hours per week. At the other end of the scale, 35% of students were studying more than the recommended study hours, with 13%
claiming that they study for more than 20 hours per week. Students studying for less than the recommended study hours include those who would like to give more time to study but cannot. They are not necessarily happy with studying for less than the recommended time, and often express regret that they do not have the time to study all the materials and activities offered and recommended by the course team. One of the most common findings is that students prioritise what to study on the basis of what is assessed.
These findings indicate some of the complexity of the study workload issue. It is not a simple case of over-loaded courses. Some students may be so time-pressured that any course would generate unwelcome study workload. On the other hand,
some students manage to pass courses studying for less time than is recommended.
Variation of this kind is to be expected in a university which has an open access policy and which recruits adults, some of whom already possess a degree, while others lack virtually any qualifications.
However, in the gap between study hours expected and study hours actually expended, lies the possibility of time proving manageable or unmanageable for our students. In the Courses Survey we ask students whether the amount of time spent studying this course was as you expected?, and we monitor the proportion responding that it was a lot more than expected as one of the key performance indicators for our courses. The average figure across all courses surveyed in 2005 is shown in table 3, with the figure for 2004 in brackets for comparison.
Table 3. Expectations of the amount of time spent studying*
Was the amount of time you spent studying this course as you expected?
Course level 1:
2005%
(2004)
Course level 2:
2005%
(2004)
Course level 3:
2005%
(2004)
averageOU
A lot more than expected 22% (24%) 23%(26%) 25%(30%) 23% (27%) A little more than expected 25% (28%) 26% (28%) 26% (27%) 25% (27%) About as expected 37% (34%) 39% (35%) 40% (35%) 39% (36%)
A little less 11% (10%) 9% (8%) 7% (5%) 9% (8%)
A lot less 5% (4%) 3% (3%) 2% (2%) 3% (3%)
* (data for 2005 and 2004, response rate 24%). Source: Courses Survey data from students who completed the assessment requirements for their course).
Table 3 shows some improvement on 2004, but still only 39% of our students feel that the workload was about as expected. Our aim is to construct courses that a majority of our students find as expected, in terms of the study workload they require. However, table 3 shows that for just over one fifth of our students, workload was a lot more than expected. This suggests therefore that these students will feel under time pressure – even though they manage the situation sufficiently well as to pass their course.
Study time in the context of e-learning
Synchronisation versus individualisation of study activity
Distance education is predicated on the idea that information and communication technology can overcome barriers of space and time. With regard to time, the
emphasis has been on building-in individualisation through not imposing strict pacing and through drawing on the use of asynchronous technologies (Garrison and Baynton, 1987). However, the benefits of collaborating online lead educators towards teaching strategies that require learners to interact at specific times, if not exactly synchronously. Dieumegard, Clouaire and Leblanc (2006) report a recent study of learners registered on a course at l’Institut National Polytechnique de Grenoble in 2004 which illustrates some of the contradictions between individualisation in terms of when students study and how study is paced, and effective support for learning.
The course researched offered a mix of independent study and tools to enable contact between students and with the tutor. The course was open only to appropriately qualified people with two year’s experience in engineering. The course, spread over a six month period, was structured into six periods of five to seven weeks each, with two modules being studied in parallel each week. Weekly study required learners to send homework to a lecturer for marking. The course, its exercises and corrections, and homework were available on the platform Lotus LearningSpace. Lecturers were available either by email or synchronously by audio and white board, telephone or visits. Four learners were studied in depth and interviewed about specific study weeks, during which they retained all notes and evidence of their study activity.
The researchers note that time for study was arranged differently by each learner, with two squeezing study into the working day and the others using evenings and weekends. All were studying different modules in different ways and in spite of the aims of the course, study activity was de-synchronised (Dieumegard et al., 2006).
Learners also estimated being either ahead or behind with regard more to deadlines they set for themselves, and perceptions of what others were doing, than with regard to the deadlines prescribed by the course.
When learners came across problems or needed help to understand, they typically tried to sort out the difficulty themselves, using either course materials or other sources. When they did contact each other, mainly using the telephone, they were often not able to resolve problems because each was at a different study stage with the modules. By contrast, when learners contacted a lecturer, they immediately solved troubling issues, but in twelve out of 13 instances, email was used as the mode of contact. Consequently only a proportion of contacts led to a resolution in the time frame required by the learner. Some were still waiting for a reply. NetMeeting was available for synchronous contact, but not used. The authors conclude that the key factor in determining interactions between learners and lecturers is the way in which both groups organise their own work tasks and study times, rather than the technologies available (Dieumegard et al., p. 219). The key point is not that this contact should take place using synchronous methods but that learners should be able to synchronise their need for support as it arises, with access to support at those particular times. It may be more reliable to consult written sources than to risk contacting a member of staff without success.
The desynchronisation made possible by e-learning – the individualisation of study to fit with each learner’s lifestyle and preferences – ensures that study and work
can be combined, but undermines the possibility of either lecturers or co-learners helping each other to any great effect. The solutions suggested include setting activities that require learners to work together, introducing regular negotiation between learners and staff and using the tracking facilities of a virtual learning environment to enable learners to see where each of them is up to in studying course material (Dieumegarde et al., 2006, p. 221). The authors note that even these require careful judgement to avoid re-introducing time rigidities into the study process.
Structuring study time in e-learning
Research at the Open University has also focused on the impact of integrating Internet, email and conferencing into its teaching. The university is moving rapidly towards all courses being delivered within a virtual learning environment, while retaining varying amounts of printed material. A sample of thirty-six courses was selected based on their use of software, Internet resources and conferencing. A random sample of 4512 students from these courses was surveyed in 2004, with a response rate of 47%. (Thorpe and Godwin, 2006). Open-ended comments from students were analysed and these revealed that time factors particularly concerned students in relation to conferencing. Conferencing may be perceived as a time consuming extra, for example, where time spent is less useful than on other forms of study, as these comments make clear:
Time required to partake in voluntary conferencing meant I did not consider it a priority.
Too many conferences and they tend to take up a great deal of time if you participate fully.
Easy to spend study time conferring with fellow students rather than with the course materials.
Previous research has identified that where new technologies are not made an essential aspect of study, students feel able to ignore them or prioritise other aspects of their course (Kirkwood and Price, 2005, p. 269-270). Conferencing and online tutorials can also add to study workload if they are not well moderated or well structured. More time is required to read large numbers of messages when conferences are not tightly threaded or a tutor does not weave together the themes effectively or summarise and guide the discussion (Hilt and Turoff, 1985; Kear, 2001).
However, these problems of study time were not necessarily avoided even on courses which used conferencing effectively by creating helpful activities for online interaction and building participation into the assessment for the course.
This required students to log on and study several times a week, and sometimes daily. Deadlines for completing activities increased and sometimes ran in parallel.
Students thus found themselves much less able to adjust the study workload to suit themselves on a week by week basis. For some students this created added workload pressures:
It’s more demanding and time pressuring. For an OU student sometimes it’s hard to cope with the deadlines.
Gives little leeway if you get behind with your work and a compulsory conference is due.
Conferences are time specific so we have less choice about when/where to study – making it less flexible than other courses.
This creates a very different study experience from a course with little or no online study. Here students are free to study how and when they wish, so long as they meet the deadlines for the assignments. Conferencing which is tied in to important learning tasks at key stages of a course, in effect adds to these deadlines.
While many students demonstrate that they can adjust to this and can enjoy the benefits that interaction brings, some are finding the change to their routines for study more difficult to accommodate.
These impacts do not reflect intrinsic features of the technologies concerned, so much as the pedagogical practices set up for their use. Furthermore, our research identified many aspects of elearning that students did find effective and supportive of their learning. Being able to read and interact with other students broadened awareness, clarified understanding and helped develop opinions and judgements;
students were also better supported – they were able to synchronise their need for help with access to helpful responses from other students and their tutor (Thorpe and Godwin, 2006, p. 211). However, only email prompted any comments relating to time efficiency. Email was generally seen as time efficient as a medium particularly for contacting the tutor. First it passes control to the recipient, unlike the telephone, and students very often report that they dislike ringing a tutor with the risk of interrupting other activities. Second the act of putting into writing a question can be helpful to the student in clarifying exactly what the problem is. Third, on the tutor’s side, the answer can be given more reflection, yet composing and writing an email may still take less time than a phone call.
Changes in the lifestyles of university students
Thus far we have been considering evidence about students’ response to the time demands of their courses. However, there is also evidence that the lifestyles of students themselves are changing and these changes are impacting on the time available for study. Universities UK recently commissioned research by the OU Centre for Higher Education and Research Information (CHERI), into term-time working by university students. Just over half the students sampled from seven universities differing in type, subject spread, vocational/non-vocational and location, had undertaken paid work during term time. The average number of hours worked was 14.2 in 2000/01 and 12.7 in 2001/2 – which was the final year of study for these students (Cheri, 2005). Students working during term time were more likely to be women, minority ethnic students, from lower social classes, living with
their parents or a partner and/or children, and those with entry qualifications other than A level.
The longer the number of hours worked, the more likely students were to report having missed lectures, seminars and classes and to have produced poor quality assignments. Not all students were equally affected by the negative impact of term time working however. The report notes, the student group most likely to produce poor quality assignments because of their term-time work were students aged 25 and over. Two-thirds of older students said term-time work meant they frequently or occasionally produced poor quality assignments, compared to only 48% of those under 25 (Cheri, 2005, p. 97). The researchers were also able to verify the final results of some students in the sample, and these substantiated students’ views on the negative impact of long hours worked during term time. …the greater the number of hours students worked during term-time, the lower their academic attainment (as measured by either average end of year marks or final degree results). This negative association is irrespective of the type of university students attended.
For a student working 16 hours a week, the odds of getting a good degree…to not getting a good degree are about 60% of the odds for a similar non-working student.
(op. cit., p. 11).
There is good reason to believe therefore that more attention to helping students manage the time that they do have available for study, is an important strategy for the future and for the development of e-learning.
Some implications for pedagogy and research
The evidence reviewed suggests that issues of study workload, pacing of study tasks and coordination of study activities by students and teachers remain important issues, with impacts on the quality and effectiveness of learning. E-learning can both ease time constraints and also introduce new restrictions. However research can contribute to understanding these time-learning issues, by developing a mix of individual case studies alongside larger-scale surveys of student samples and populations.
More evidence about how individual students use study time, and how they perceive their study tasks is required. Email interactions, focus groups and interviews can all be used to collect this data. A small number of such cases can build a picture of the range of approaches in use, if not their typicality. This can help raise the awareness of teaching staff to the diverse ways in which students approach study time, including how and when they study. The aim is not to attempt to provide courses that dovetail exactly with this range of student study time approaches, but to adopt strategies that support rather than conflict with the strategies students themselves can manage. This may mean for example providing information about estimated study times and grouping study tasks into blocks of time that are clearly indicated. Students may choose not to study according to these blocks of time, but
the clarity of the time structure will make it easier for students to adapt it to suit their preferred study periods.
Evaluation of how populations or random samples of students experience study time is also needed. Regular surveys where students are asked to compare the time they expected to study with actual hours studied provide an indication of time pressure experienced. The value of such findings is that they provide not an exact measure of study time but evidence about whether a majority is experiencing time pressure on a scale that requires action. Findings across different courses can be compared to check out worst cases and provide a basis for further evaluation to identify areas of overload and strategies for improvement. Teaching staff themselves will also have relevant information about how effectively different parts of their courses have been studied, as a result of marking students’ work. These impressions should be used to help interpret the results of surveys of student workload. Studies of this kind are particularly valuable in the light of new uses of ICT tools and resources where there is little experience of how effectively learners use them and what impact they have on study time. This requires more evaluation of the learner’s experience in using online courses and making effective use of particular tools such as conferencing, searching the Internet, formative assessment software, weblogs, wikis and so on.
We have a wealth of options for how to teach but a dearth of good evidence of their impact on learners.
We need also to reflect on the actions that teaching staff can take, when designing courses that use ICT, for distance study or campus-based. New work to address the issue is being undertaken at the Open University, where courses are typically produced by course teams. A spreadsheet tool has been developed enabling the course team to produce a cumulative report on the study workload of all the materials as they are produced. This identifies whether the weekly study time is likely to be exceeded and action can be taken to reduce the draft materials, before they are used by students. Week by week charts of study activities are also used to plan courses, and to show how different media fit together over the study period. Course teams use them to build in features that support students who fall behind the schedule – an experience that affects the majority at some point in their studies. Strategies both to avoid overload and to help students “catch up” include not setting new study in the week before assignment deadlines, building in reading or review weeks, and study- free weeks where national holidays make it extremely difficult for students to study as normal. This does not of itself reduce the overall study load, but distributes it in a manner that students find easier to handle.
Looking to the future, we can see in the growing use of mobile devices the possibility for learners to make good use of every spare minute in the day using a hand held device (Sharples, 2003; Sharples et al., 2005). We take them with us as we walk round galleries, do the shopping or commute on the train, keeping learning going alongside apparently “non-educational” activities. However, this does not mean that we have rendered time irrelevant, but that we are using it differently.
It suggests that we can combine activities in new ways, can better support multi-
tasking and even that we might squeeze more into every hour of our day. But how will this impact on learning? Will there be a fragmentation of time for learning and will that impact on the quality of the work that learners produce? These are key questions for pedagogy, and pedagogically-oriented research needs to retain a focus on the time dimension of learning, as experienced by learners themselves. This presents both new challenges for us as well as exciting new opportunities.
References
Ashby A., “Monitoring student retention in the Open University: definition, measurement, interpretation and action”, Open Learning, 2004, 19 (1), p. 65-78.
Centre for Higher Education Research and Information and London South Bank University, Survey of higher education students’ attitudes to debt and term-time working and their impact on attainment: A report to Universities UK and HEFCE, Universities UK, 2005.
Garrison D.R, Baynton M., “Beyond independence in distance education: The concept of control”, The American Journal of Distance Education, 1987, 1 (3), p. 3-15.
Goodyear P., “Technology and the articulation of vocational and academic interests: reflections on time, space and e-learning”, Studies in Continuing Education, 2006, 28 (2), p. 83-98.
Hilt S.R. and Turoff M., “Structuring computer-mediated communication systems to avoid information overload”, Communications of the ACM July 1985, 1985, 28 (7), p. 680-689.
Kear K., “Following the thread in computer conferences”, Computer and Education, 2001, 37, p. 81-99.
Kirkwood A. and Price L., “Learners and learning in the twenty-first century: what do we know about students’ attitudes towards and experiences of information and communication technologies that will help us design courses?”, Studies in Higher Education, 2005, 20(3), p. 257-274.
Lawless C., “Using Learning Activities in Mathematics: workload and study time”, Studies in Higher Education, 2000, 25 (1), p. 97-111.
Lawless C. and Richardson J.T.E., “Monitoring the experiences of graduates in distance education”, Studies in Higher Education, 2004, 29 (3), p 353-374.
Lockwood F., Activities in Self-Instructional Texts, London, Kogan Page Ltd, 1992.
Marton F. and Saljo R., “Approaches to Learning”, Hounsell D. and Entwistle N. (eds), The Experience of Learning, Edinburgh, Scottish Academic Press, 1984, p. 36-55.
Ramsden P., “A performance indicator of teaching quality in higher education: the course experience questionnaire”, Studies in Higher Education, 1991, 16 (2), p. 129-150.
Sharples M., “Disruptive Devices: Mobile Technology for Conversational learning”, International Journal of Continuing Engineering Education and Lifelong Learning, 2003, 12 (5/6), p. 504-520.
Sharples M., Taylor J. and Vavoula G., “Towards a theory of mobile learning”, 2005, accessed 12/06/06, http://www.eee.bham.ac.uk/sharplem/write.htm
Thorpe M. and Godwin S., “Interaction and e-learning: the student experience”, Studies in Continuing Education, 28(3), Special Issue on Advances in Adult e-learning, 2006, p. 203-221.
Trigwell K., “An analysis of the relations between learning and teaching approaches”, Sutherland P. and Crowther J. (eds) Lifelong learning: concepts and contexts. Oxford, Routledge, 2006, p. 108-116.
