This chapter has provided a comprehensive overview of self-regulated learning and four main aspects thereof: motivation, time management, social presence and awareness, and monitoring/feedback. Furthermore, seven principles of good practice in undergraduate education were presented.
The remainder of this work will focus on providing technology support for these four main aspects, which are therefore referred to as technology-supported learning aspects (TSLAs) throughout this thesis. The emphasis is on how technology can be used to enhance these aspects in the context of self-regulated learning in higher education (see Figure2.7.1). While there is substantial prior research on how these aspects can support student collaboration, little work has been conducted in hybrid settings (traditional teaching with project-based learning and/or student collaboration) or in environments where the focus is on individual project work only. One reason might be that group dynamics are more obvious and can be observed more easily in purely project-based or collaborative settings, that is, in learning environments entirely focussed on group work. The four main TSLAs are summarised in the following paragraphs.
Self-Regulated Learning
(Zimmerman , 2011)
Seven Principles
(Chickering & Gamson, 1987 )
Time Management
Motivation
Progress Awareness
Monitoring
(Educational Strategy )
Technology-Supported Learning Aspects
Figure 2.7.1: Technology-supported learning aspects (TSLAs) and how they relate to self-regulated learning and the Seven Principles
Time management was found to be an essential soft skill for university students. It is associated with less stress, higher self-confidence and control over time, higher qual- ity output, and increased academic performance. However, it is still a common issue encountered by many students. A number of different strategies for effective time man- agement such as “Getting Things Done” were devised to mitigate these problems. Time management is also an important factor in project-based learning contexts where the focus is on learner autonomy, self-regulation, and motivation. Besides traditional time management applications, which were designed for the professional workplace, a number of approaches have been made to provide software tailored to student needs. Prominent examples are simple timetabling tools, mobile applications, and groupware systems used in project-based learning. Few of these approaches have been evaluated empirically. In self-regulated learning, time and project management are important for task analysis, goal setting, and strategic planning in the forethought phase, and also for task strategies and following the strategic plan in the performance phase, that is, when students work on their learning tasks.
Motivation is an equally important factor for learning. It is influenced by the degree of learner autonomy and content relevance. Motivated learners were also found to be less likely to procrastinate. In section 2.2.1, two different kinds of motivation (intrinsic and extrinsic) were introduced, while section2.2.3outlined the extent to which the three schools of learning (behaviourism, cognitivism, and constructivism) foster learner motiv- ation. Motivation theory has also led to the development of several motivational models which are used in software aimed at detecting and instigating learner motivation. In self- regulated learning, students’ self-motivation beliefs are made up by students’ self-efficacy, that is, the confidence in their ability to achieve a result, their expectancy regarding the outcome, their interest in the task itself, and their goal orientation. Students can be focussed on learning the material (learning goal orientation) or on their achievement in relation to others (relative ability goal orientation). Empirical research on these two types of goal orientation have produced mixed results regarding their effect on students’ self-motivation beliefs. Some sources state that learning goal orientation is more effective
than relative ability goal orientation while others did not find any difference. Relative ability goal orientation is also influenced by information about other learners’ perform- ance in the same learning environment, which is described in the next paragraph. Two techniques for instigating and maintaining motivation are social presence and aware- ness which were introduced in section2.4. Social presence is important for enabling user interactions in virtual multi-user environments. It can be enhanced by disclosing contex- tual information, yielding to enhanced presence, which is claimed to have a motivating effect. Awareness goes beyond user interaction and enables coordination, information sharing, feelings of connectedness and empathy, group formation,community building, and motivation. More specifically, user interactions with a learning system are captured, visualised, and interpreted by the same or other connected users. In the context of this work, the visualised data originates from progress feedback and is used for raising stu- dents’ awareness of their own progress in relation to others; this is referred to as progress awareness. In computer technology, social presence and awareness can be implemented using several techniques such as data visualisation, progress information disclosure in project-based learning contexts, and harnessing context data (for example GPS location data). Awareness also requires users to actively participate and contribute, which can be facilitated by using Web 2.0 technologies (see section 2.4.1) such as news feeds, com- menting tools, and discussion features. One aim of this work is to show how awareness technologies can be harnessed to support students’ self-observation in the performance phase and their self-judgement in the self-reflection phase.
Another important TSLA is monitoring which was introduced in section2.5. Monitoring is the process of generating feedback, both by the student and external sources. In self-regulated learning, the former is referred to as self-observation in the performance phase. More specifically, self-regulated students use metacognitive monitoring whilst performing learning activities, constantly recording the current state of learning tasks and whether they are on track towards the goal. This information is complemented by external feedback from mentors, teachers, and other students, affecting the learner’s self- evaluation and causal attribution in the self-reflection phase. This, in turn, affects their reaction in the next cycle of the learning process. Feedback generated in the monitoring process can be visualised as described above and lead towards students’ awareness of their own progress.
Finally, the seven principles for good practice in undergraduate education were presented. They are aimed at improving educational environments for the benefit of both learners and teachers. As such, they are important when designing software for this domain. Furthermore, all technology should be embedded into an educational strategy. This thesis also examines how technology can be used in self-regulated learning so that it is in line with the seven principles, and which of these technologies effectively support those principles.
Based on this review, and with regard to the TSLAs introduced in this section, the following predictions concerning expected effects of software tools on student time man- agement, motivation, and performance can be made:
1. Tools for time management such as schedules, calendars, and task lists support student time management, which is important for strategic planning and during task performance. They can also be used to enhance student self-monitoring by providing achievement and progress data. Expected effects are improved time management and higher performance.
2. Tools for capturing and visualising progress awareness data, for example news feeds, interactive tools, feedback submission tools, charts, and performance scores, support students’ relative ability goal orientation and self-monitoring, and are likely to positively affect student motivation and performance.
3. Monitoring tools enhance the generation of internal and external feedback and also support students’ self-observation and reflection. Therefore, they are expected to improve time management, motivation, and performance.
Survey of Students’ Technology Use
for Time Management
In order to understand what time management practices students use and to what ex- tent, a survey was conducted, aimed at evaluating the current use of mobile computing devices, calendaring software and their features, student study planning habits, and stu- dents’ opinion about potential features planned for software prototypes. The survey was conducted in June 2009 and targeted at all students in the School of Electronics and Computer Science (ECS) at the University of Southampton, which is also the intended target group for future research studies. ECS covers all disciplines in the fields electron- ics and computer science, and offers a whole range of undergraduate and postgraduate courses.
The survey itself is a questionnaire comprising 11 questions and divided into three parts (see Appendix A.1 for details), and students were expected to spend an average time of 10 minutes on answering it. Although no sensitive or personal data was gathered, the school’s Ethics Committee approval was required before the start of the survey. In order to facilitate and speed up the process, the questionnaire was provided online on the school intranet, and students had to log on using their school username and password. This was to rule out that students answer the questionnaire twice, and that any other students who are not in the target group participate. However, this login data was kept separately from the questionnaire results, so that the survey was completely anonymous. In total, 137 out of around 1200 students answered the questionnaire, however, the online survey system used in the study did not enforce that students answer all questions, which resulted in 1 up to 13 missing values dependent on the question. The highest number of missing cases (between 10 and 13) occurred in question 9, which asked them to rate the degree of helpfulness of 13 features planned for the software prototype. It is likely that students lost interest or became distracted towards the end of the questionnaire, possibly because of the high number of items in that question. In the following analysis, missing values were not taken into account.