Vocational education refers to the training of speci c skills or trades. It is often done part time or in personal time over a lengthy period (months to years). As such, it requires persistence, self motivation and self regulatory skills including goal setting, planning and time management. A growing body of evidence suggests that these self-regulating skills are a key determinant in learning performance and can be improved with support. We report in this paper our experience with a leading vocational education provider in Australia who is transitioning from classroom-based training to a pilot e-learning system. We present the key lessons learned and the prototype interface we designed to improve user self-regulation in planning and time management.
Vocational education, which refers to the training of speci c skills or trades,
differs from academic education as the focus lies in skills and knowledge for speci c
industries or job roles and often requires proof of practical competency to
complete. However, similarly to academic learning, self-regulated learning [
It is important to understand the key challenges for e-learning systems aimed at vocational education and how their personalisation and sca olding features can support self-regulation. We performed a study with an Australian leading vocational education provider who transitioning from a classroom focused training model to an online and self-managed training model using a pilot e-learning system. We analysed student usage patterns over a 6 month period to understand how this e-learning system is used and interviewed trainers and trainees to get qualitative feedback on how students managed their learning in the system.
In this paper, we present the key lessons learned from our study and a prototype with user interface designed to demonstrate the key features for future e-learning systems to personalise and support for self-regulation of learning. 2
Vocational education and training represents a critical sector of education where
skills for a particular industry, trade and career are created. Over 11 percent of
the Australian population between 15 and 64 undertake vocational education
and training and the age spread is wide [
We worked with a leading vocational education provider in Australia who has operated a nationally accredited certi cation program for their employees for over 10 years. Recently, they started transitioning from a classroom training model to a pilot e-learning training program requiring self directed learning and assessments. A key motivating factor is motivate and encourage students to regulate their own learning and to reduce the contacts needed with trainers.
The pilot e-learning system is used for accessing online learning materials, perform assessments and uploading evidence for practical experience and competence. In the pilot program, participants rst read or view online learning material, gain practical experience and reinforce their learning and then physically attend a classroom learning workshop. They then complete online assessments via the e-learning system. While the online learning material is not mandatory, they contain the knowledge needed to pass the online assessments. The workshop o ers an opportunity for trainers to reinforce the online learning material, provide discussion and simulated practical experience to prepare learners for their formal online assessment.
We performed a 6 month study to analyse student usage patterns based on data from the e-learning system for over 600 trainees. We also interviewed 3 participants and 3 trainers to gain an qualitative view of the challenges with self-regulation and performance. 3.1
Planning and time management is a signi cant challenge for many students. A commonly cited problem by students, including the trainees in our study, is the lack of time. However, interviews with trainers indicate that this is not the case because trainees are allocated time or are getting paid for their time spent on learning. Rather, the key issues cited by trainers are attention focusing, planning, and time management rather than time constraints. In many cases, work priorities con ict with the planned learning times and students do not adjust their planning or they forget.
While the majority of trainees complete their learning on their own, trainers needed to organise separate workshops speci cally for certain groups of trainees to concentrate and complete their online learning away from their workplace which can be busy and not conducive for learning. Trainers found that the trainees' lack of self-regulation skills in time management, planning, prioritisation, and remembering to perform tasks were key challenges. The di culty level of the learning material was rarely an issue in this program. 3.2
According to the social cognitive theory, the social and work environment are
a key determinant of behaviour [
Feedback from both trainer and trainee suggests that those who managed their social and learning environment well had little trouble completing the course. For instance, one successful trainee, who managed his environment by performing his study during his day o , had a study partner in the program. He also ensured that he completed the planned task on schedule through either performing them on time or adjusting his plan. This trainee was able to complete the learning tasks well ahead of schedule.
Our hypothesis is that trainees who are struggling in the vocational program can be supported through sca olding or computer aided support to improve their planning and time management. We built a prototype system, augmenting the existing e-learning platform, with user interface elements designed to promote self regulation. The prototype system lets trainees set time schedules for their learning objectives, monitor their performance and adjust them when necessary. It is also available via mobile application and sends them reminders of upcoming tasks. The prototype system also allows trainers to monitor the performance of their trainees and identify those who need personalised attention. 4.1
To address the feedback above, we made planning and time management a core
skill for the prototype system to support and sca old. There have been very few
user interfaces designed to sca old time management and planning. A previous
approaches used Zimmerman's cyclic model of self-regulated learning as the basis
to detect and model the learner states [
As part of the interface, the user is allowed to monitor his/her progress in the
program. They are also reminded about their upcoming planned tasks, what they
have completed and what they still have pending, see gure 3. This allows them
to monitor their progress, re ect on their planning and scheduling. In addition,
users can monitor their progress compared to their peers for each of the learning
objectives in their program, see gure 4. Studies have shown that behaviour can
be modi ed through comparing one's own performance against peers [
We found a key challenge for vocational education students is time and environment management. We designed a prototype system to support students in becoming better planners and time managers. We believe such goal setting and time management interface designs can also be integrated into other e-learning systems where the learning pro le is similar to vocational education (e.g., self redirected professional learning, part time academic studies). Peer and trainer engagement and support appears to be important to trainees and trainers and future systems should investigate how sca olding can be applied. This can potentially reduce withdrawals, increase engagement and motivation for the trainees. 6
This work was funded by Smart Services Cooperative Research Centre.