The following chart is from a population of over 91,000 undergraduate university students studying via an LMS over a five year period. It shows the average hits on course sites for each grade for students whose teaching staff did and did not contribute to course discussion forums. The participation rate is higher and failure rate is 5% lower for courses where the teaching staff participated in course discussion forums. The limitations of this sort of de-contextualized data are well published and prevent the establishment of a causal relationship. However the distinct correlation is for me a very interesting indicator and is worthy of more investigation. In particular, I’m wondering if this can be linked to engagement and subsequently retention and attrition?

Staff participation in LMS discussion forums

The following is a piece of writing that may form the basis of a paper sometime next year as time permits. Its needs a great deal of work.

Introduction.

Learning management systems (LMS) have become almost ubiquitous in higher education in Australia with most universities using either a commercial or an open source variant. Whilst they have several widely published weaknesses, such as the ability to effectively provide participant interactions, their popularity among higher education institutions remains high and further research into their impact on students is required. The following paper draws upon data from the CQUniversity Indicators project to look at the effects of LMS hosted discussion forums on fully online (flex) students.

LMS.

The adoption of LMS as an approach to eLearning is almost universal (Coates, James, & Baldwin, 2005) and they have become perhaps the most widely used educational technologies used in higher education, only ranking behind the Internet and common office applications (West, Waddoups, & Graham, 2006). Some have said that the LMS dominance in the higher education sector is due to institutions adopting LMS simply because “everyone else is” (Northover, 2002) rather than on their educational merit. Whether this situation has developed for the benefit of the learner as opposed to the organization or instructor is arguable (Beer & Jones, 2008) but also somewhat irrelevant, considering that most institutions are now using an LMS to deliver eLearning.

A contributing factor to the fact that LMS are the dominant technology used for eLearning in universities could be the increase in demand for flexibility by students (Hinton & Bradshaw, 2004; Northover, 2002). There are increasing numbers, of adults who are employed in the workforce and are returning to university for interest or career advancement and life circumstances often prevent people in this category from committing to full time study (Hinton & Bradshaw, 2004). As a result, they often choose to undertake their studies via distance or flexible delivery modes that most universities now offer (Hinton & Bradshaw, 2004). These flexible modes are often delivered entirely via the LMS and are independent of place or time as opposed to face-to-face university courses where lectures and tutorials are held in specific locations at specific times and the learner is required to be present to participate. When undertaking a flexible course offering, the LMS is often the only mechanism by which the student can interact with course content, fellow students and their instructors. As the LMS is the only system a student in a flexible learning situation will be exposed to, it is important that the LMS effectively deliver the range of interactions that learners require in order to achieve their learning goals.

Interactions.

From the perspective of a student, learning online or otherwise can be described by three fundamental interactions (Moore, 1989).

• Learner-content.
• Learner-instructor.
• Learner-learner.

Moore (1989) states that learner-content interaction is a defining characteristic of education and is the process of intellectually interacting with content that changes the learner’s understanding, the learner’s perspective, or the cognitive structures of the learner’s mind. Whilst framed as a criticism for being too content focused, most LMS effectively provide learner-content interaction (Siemens, 2004b) and others have said that they may even be more effective  at facilitating learner-content interaction than traditional methods like face-to-face (Ladyshewsky, 2004). A potential explanation for this is that the learners can survey the content at their leisure and at their own pace in a manner that matches their individual learning style. A typical LMS provides many features by which an instructor can sequence and present content and its only recently that LMS vendors have started extending tools and offerings beyond simple content sequencing (Siemens, 2004b). LMS features that facilitate learner-content interactions vary between systems but broadly include features like announcements, gradebooks and access to instructor-uploaded files.

Learner-learner interaction can be one to one or one to many, can occur through group work, and can occur in or out of real time and is most often represented within an LMS by discussion forums that allow threaded, text based discussions to occur within a specific course.  Learner-instructor interaction is where the learner interacts with the teacher or expert and this interaction is facilitated by the LMS via email, asynchronous discussion forums or synchronous chat.

Moore (1989) describes the three basic interactions required for a given learning situation and it has been suggested that in general, LMS can effectively provide learner-content interactions. The main feature used by LMS to provide learner-learner and learner-instructor interactions is the discussion forum, although most LMS provide an email feature that can perform a similar function. However due to the difficulties in the day-to-day moderation of course emails in courses with large student numbers the email feature is not widely used by the Blackboard LMS at CQUniversity and is not included in this study. Similarly, the asynchronous communication tool provided by CQUniversity’s current version of Blackboard, is not widely used due to poor performance resulting from technical limitations with the tool.

Learning is social

Social constructivism as a learning theory emphasizes the importance of culture and context in understanding (Kim, 2006) and therefore suggests the importance of interpersonal communication in learning. Similarly, connectivism, which is a relatively new theory in education born from the internet age, suggests that learning and knowledge rests in a diversity of opinions and learning is a process of connecting specialized nodes or information sources (Siemens, 2004a). When considering connectivism as a learning theory Siemens (2004) says that a central tenet of most learning theories is that learning occurs inside a person and these theories do not address learning that occurs outside of people such as learning that is stored in, and manipulated by technology. Computer mediated communications or technology supported social networking is a key aspect to connectivism. The point being, that connectivism, is a learning theory born in the Internet age and greatly values technology supported interactions between participants in a learning situation.

It has been said that for deeper learning to occur, learning must be social, active, contextual, engaging and student owned (Carmean & Haefner, 2002). Others have suggested that the learning process is transitioning from cognitive theories based on the individual to theories that stress the importance of the social nature of learning (Dawson, 2006) . Dawson et al (2006) states, numerous authors have espoused the importance for developing social learning opportunities where students actively debate, exchange and clarify ideas with other peers. Irrespective of learning theory, there is little doubt that social interaction plays an important part in learning and for the fully online student in a university course, the LMS discussion forum is the main enabler for social discourse and interaction during their course.

LMS discussion forums.

Like most LMS hosted by universities, discussion forums are frequently used in online courses at CQUniversity, as a means of extending the class conversations beyond the time and place restrictions of the classroom. Other researchers have espoused the benefits of discussion forums, as they are ideal teaching tools for a student population who choose to study via distance because of their life circumstances. They can foster collaborative learning and provide the opportunity for students to interact with each other and the teachers. They engage students in debate and discourse that would normally not be available via distance learning (Hinton & Bradshaw, 2004). Others have said that the use of asynchronous online discussion forums can provide online learning communities with unprecedented learning opportunities (Hew & Cheung, 2003). Oliver (2000) goes on to say that creating collaborative and cooperative settings for learners provides many advantages for the designer and learners. As learners collaborate, they articulate their ideas and thinking and this contributes in large ways to developing their understanding.

An important point to note is that the emergence of community in the educational context has been demonstrated to enhance student learning through the implementation of an overarching pedagogical framework (Dawson, 2006). The LMS makes it very easy for a teacher to include a course discussion board and the “good practice” guidelines at CQUniversity even mandate that each course that is to be delivered by the LMS must include a space for spontaneous student communication (CQUniversity, 2009). Whilst there appears to be some benefit by providing students with such a space, a more valuable use of the technology would be to incorporate the discussion space into the overall course design where the conversation is supporting overall course design strategies.

Teachers and teaching.

An LMS allows the teaching staff to add resources and activities to an online course via a web interface with little or no knowledge of underlying web (html) technologies. Typically, course design and development is the responsibility of the teaching staff and this is an important to consideration when looking at the adoption of features with the Blackboard LMS at CQUniversity. If the teaching staff are responsible for the addition of resources and activities such as discussion forums, then the underlying pedagogy of the course is influenced by their experience with the teaching medium and their conception of teaching and learning. Therefore, LMS are not pedagogically neutral technologies, but rather through their very design, they influence and guide teaching (Coates et al., 2005). Another related point often overlooked by universities when conducting an LMS evaluation prior to implementation is it’s not the provision of features [in an LMS] but their uptake and use that really determines their educational value (Coates et al., 2005) and therefore their value to the university. Additionally, the fundamental measure of student experience with an LMS is the degree to which students use the system (Caruso, 2006).

The Indicators project overview

Academic analytics describes a method for mining and analyzing institutional data, such as the data captured by an LMS, for informing decision making and reporting purposes (Campbell & Oblinger, 2007). It is claimed that the use of academic analytics in higher education has the potential to improve teaching, learning and student success by a combination of awareness of patterns in the data by teaching staff and other predictive modeling techniques. The Indicators project at CQUniversity is aggregating data collected by the Blackboard LMS and the PeopleSoft student administration system. It is proposed that this will reveal patterns in the data that can link LMS features and patterns of behavior with student grades. Note that the Indicators project uses quantitative and automatic methods to extract and aggregate the data and this approach has shortcomings that need to be considered.

There are significant limitations in a purely quantitative analysis of captured data and this is especially true in a complex educational setting. Data mining can help reveal patterns and relationships but does not tell the user the value or significance of these patterns (Seifert, Updated 2004). Additionally, a systems scan of designer and user behavior within an LMS can never describe in full how staff and students are engaging in the use of online environments for teaching and learning (Heathcoate & Dawson, 2005). However it has been suggested that using captured LMS data can aid teachers in decisions about their courses (Campbell & Oblinger, 2007) and others have suggested that there are benefits in exposing the people ‘at the coal face’ to raw data as it allows them to move from an abstract representation of large data sets and spot patterns and anomalies (Snowden, 2008).

CQUniversity is especially complex in that a typical LMS course could be delivered via three different methods, on-campus, off-campus and multi-modal delivery, and delivered to three distinct student cohorts regional campus students, international students and flex students. These different delivery modes and cohorts will influence both the LMS features chosen by the teacher, user behavior within the system and consequently the data captured by the LMS. The project name, the Indicators, is an acknowledgement of the limitations of captured LMS data especially in the complex multi-campus teaching environment like CQUniversity. The data displayed in the following sections has been take from the Indicators database using a variety of technical means such as SQL and Perl. It includes data from over 4700 courses and over 500,000 students over a six-year period.

CQUniversity Flex Students and the LMS.

So far it has been established that there are three fundamental interactions required in a given learning situation, learner-content, learner-learner and learner-instructor, and that effective learning requires a degree of social interaction. Often, the LMS is the single mechanism via which a flex student will access their course and its associated interactions. The literature suggests that discussion forums are an important part of online courses, especially if they are embedded into the underlying pedagogy of the course (Marra, Moore, & Klimczak, 2004). LMS features have an effect on pedagogy and as the teaching staff are responsible for course design and feature adoption, their conceptions of teaching and learning also affect the course’s underlying pedagogy.

CQUniversity has three distinct student cohorts. Rockhampton and regional students are enrolled in courses that are delivered face-to-face at the Rockhampton or other regional campuses such as Mackay, Bundaberg and Gladstone. This paper refers to these students as regional students. Flex students are students who are enrolled in courses that are delivered either partly or wholly online. These students typically only interact with their course and colleagues via the LMS. The third group of students is international students studying at one of the international campuses such as Brisbane, Sydney or Melbourne. These students are not part of this study.

The following sections use student activity data from CQUniversity’s Blackboard LMS as gathered by the Indicators project, to test some of the concepts previously identified from the literature. As the flex students typically only interact via the LMS, the data on their activity is more accurate as it is not as polluted by face-to-face influences when compared to face-to-face students. In order to understand the effects that discussion forums have on flex students, it is important to obtain an overview of the flex student population and its importance to CQUniversity.

Figure 1. Flex students as a percentage of overall student population.

Figure 1 suggests that the proportion of CQUniversity students who are flex students is increasing.

Figure 2. The number of flex student-course units.

While Figure 1 shows that the proportion of flex students to overall student population is increasing, figure 2 shows the the overall flex student numbers is also increasing, albeit slowly. This trend is indicative of the increasing importance of flex students to CQUniversity and therefore the increasing importance of research into how flex students interact with the LMS.

Figure 3. Grade distribution of flex students at CQUniversity.

Figure 3 shows the distribution of grades across the flex student population at CQUniversity. Note that in this paper and for purposes of brevity and clarity,  grades refer to a refined version of the official CQUniversity grading system (CQUniversity, 2007) and uses only the most commonly used grades which are High Distinction (HD), Distinction (D), Credit (C), Pass (P), Fail (F).

Figures 1 and 2 showed the increasing importance of flex students to CQUniversity and as a result, the importance of the LMS in delivering the range of interactions required by flex students to meet their learning goals. The following sections address three points of discussion around the use of LMS by flex students. It does this by drawing upon data extracted from the Blackboard LMS at CQUniversity by the Indicators project. While these points are often attributed anecdotally, the Indicators data can now be used to provide empirical evidence to support the following statements.

1. Flex students are much more dependent on the LMS than face-to-face students.
2. LMS are content focused (Siemens, 2004b).
3. LMS discussion boards are particularly important for flex students.

Point 1. Flex students are much more dependent on the LMS than face-to-face students.

Figure 4. Average hits, forum posts and replies for flex students against grade.

These three tables show average flex student hits (red) on the LMS associated with grade and compared to face-to-face (blue) CQUniversity non-flex students. Activity is determined by measuring the amount of hits mouse clicks within a course site. For example the overall average hitcount in Figure 4 shows that a HD student will, on average, make 730 clicks within a course website while a HD non-flex (face-to-face) student makes 250 clicks.  Figure 4 shows that on average, flex students access the course sites approximately four times more than a non-flex student and are more likely to post and reply to discussion forums hosted by the LMS than equivalent face-to-face students with the same grade.

This systems scan of flex student behavior within CQUniversity’s Blackboard LMS tends to confirm the hypothesis that flex students are more reliant on the LMS than are students studying via face-to-face modes.

Point 2. LMS are content focused.

As mentioned above, it is not the provision of LMS features, but their uptake that really determines their educational value (Coates et al., 2005). As the teaching staff are responsible for building and maintaining LMS courses at CQUniversity, they have a significant influence on how LMS features will be implemented and therefore used. So whilst feature adoption may at first glance appear outside the scope of this document, it requires mention due to its important influence on LMS feature presence and utilization. While Siemens (2004) suggests that LMS are content focused, it is actually the staff who are responsible for the adoption of features and therefore influence the apparent tendency towards features that facilitate content interaction.

Figure 5. Feature adoption evolution of features supporting content and communication by LMS courses.

In this case, LMS features such as files, announcements and gradebook are regarded as content dissemination features while discussion forums, email and synchronous chat are features that support communication. Figure 5 shows the overall percentage of courses that use features supporting of learner-content interactions compared to features that support leaner-learner and learner-instructor interactions. Of note is the fact that features supporting learner-content interactions are, on average, adopted more than features that support the other interactions and this would tend to add weight to the previous argument by Siemens (2004) who suggests that LMS tend to provide more features that support content sequencing and presentation. The overall trend for both elements is increasing which could be indicative of teaching staff becoming more comfortable with the LMS and using more features or simple more courses having an online presence. However, figure 5 shows only the features that are present in the courses and does not indicate how those features are being used or their pedagogical application within the course.

Most studies into how LMS are being used have tended to focus on specific technical details with little consideration about the pedagogical implications that the LMS usage data indicates (Malikowski, Thompton, & Theis, 2007). Malikowski et al (2007) propose a model that equally considers technical features and research into how people learn. The model looks at LMS feature adoption over time and suggests that the teacher will tend to adopt LMS features in a linear fashion starting with features associated with content transmission, moving to more complex features as their experience with the teaching medium increases (Malikowski et al., 2007). While the detail of this model is outside the scope of this paper and is the subject for further research, it requires mention as teaching staff are responsible for LMS feature adoption and therefore influence the notion that LMS are content focused by their choice of LMS features. The following figure (figure 6) demonstrates the rate of adoption of the various LMS features, over time at CQUniversity and shows the dominance of content dissemination features such as files, announcements and gradebook.

Figure 6. LMS feature adoption for the Blackboard LMS at CQUniversity.

With CQUniversity’s Blackboard LMS there is an apparent bias towards features associated with information dissemination. This may be a concern as it is contrary to research showing that effective learning occurs when students learn with computers rather than from computers (Oliver, 2005).

Point 3. LMS discussion boards are important for flex students in particular.

Figure 7. Flex student usage across 61 million hits.

Figure 7 is showing us that 31% of flex student activity occurs within the discussion forums while the remaining 69% is activity on content such as files, folders and other LMS content tools. Whilst this does not tell us a great deal except that, on average a third of flex student activity within the LMS is spent in the discussion forum, it starts to expose how important the discussion forums are to flex students when compared to non-flex students as figure 8 indicates.

Figure 8. Non-flex student usage across 50 million hits.

The contrast between figures 7 and 8 is significant in that flex students would appear to visit discussion forums at more than twice the rate of their face-to-face equivalents. This is despite anecdotal evidence that suggests that most discussion forums in Blackboard are not necessarily utilized to meet specific pedagogical goals. The following figure is representative of four teachers who are known by the author to often use discussion forums in their courses to meet discrete pedagogical objectives and show a higher than average bias towards forum activity.

Figure 9. Flex student usage for teachers who promote discussion forum participation.

The previous section indicates an increased reliance on discussion forums for flex students. What hasn’t been established is if this reliance has an impact on both student success as indicated by grade, and the students’ perception of community.

The following two figures require some explanation as they use the notion of an average grade and low, medium and high forum use. Average grade is loosely based on a weighted gradepoint average calculation that is an internationally recognized measure for establishing equivalence across different grading systems (Monash University, 2009). The accuracy or validity of the average grade calculation used in the following two tables isn’t very important as it is the trend demonstrated by the data that supplies the reader with a clue to what the data represents. The number of HD grades is multiplied by seven, D grades by six, C grades by five, P grades by four and F grades by 1.5 and the total divided by the number of students in the course. The low, medium and high activity is simply calculated by looking at the total number of forum messages for each courses and grouping the courses by their message quantities. Low is the bottom 33%, medium is the middle 33% and high is the top 33%. Whilst not a statistically valid grade point average, it does illuminate a pattern in the data that indicates a relationship between student grade averages and the level of forum use within courses. The following grade averages were created using the gradepoint average described above for each group of students based on the levels of forum use in their courses.

Figure 10. Indicator of discussion forum usage on grade averages by course.

Figure 11, while appearing similar to figure 10, is different. Figure 10 looked at the grade averages of students in courses with high, medium and low degrees of forum activity. Figure 11 is looking at the grade averages of students where their individual forum activity is high, medium or low.

Figure 11. Indicator of discussion forum usage on grade averages by students.

The results in figure 10 and figure 11 are crucial in determining the value of LMS discussion forums to flex students. Figure 10 shows that, on average, courses that promote and encourage student participation in discussion forums generally demonstrate higher than average grades for flex students than courses that do not. Figure 11 shows that, again on average, flex students who tend to be more active on LMS discussion forums also tend to have higher grade averages that those that do not. This could simply be explained by saying students who are more likely to participate and visit the discussion forums are students who are on the whole, more engaged and motivated. This was checked and confirmed by using the same students as in figure 11 and looking at their overall hitcounts on the LMS that could be used as an indicator of engagement.

Figure 12. Overall hitcounts of students based on discussion forum engagement.

While being potentially indicative, Figure 12 tells us that the link between discussion forum participation and student success is inconclusive in that, while students who participated in courses that encourage forum participation and students who demonstrate a propensity to engage in forums tend to have higher grade averages, the same students are demonstrating a higher degree of engagement across all aspects of the LMS.

Conclusion.

LMS have become an almost ubiquitous technology in universities as an eLearning solution. Their dominance in higher education is attributable to an increasing demand for eLearning that is being driven by students requiring more flexible study options from universities. LMS have been described as being too content focused (Siemens, 2004b) and data from CQUniversity showing how LMS features are adopted and utilized adds weight to this argument by indicating that LMS features that support learner-content interactions are adopted more quickly and used the most. Student use of LMS features follows a similar trend with most activity occurring on LMS features that support content dissemination as opposed to other LMS elements that support participant communication and interaction.  There is an important social element to learning and this is especially important for flex or distance students whose only source of interaction with their course and fellow learners is via the LMS discussion forum feature. However, it is not the presence of these discussion forums in an LMS, but the way in which they are used that determines their value to the learner.

This study has shown that there appears to be some correlation between student activity on discussion forums and their resulting grades. However, the purely quantitative approach used by this study showed that students with higher than average activity on discussion forums also tended to demonstrate higher levels of activity on the course overall. This prevents an accurate determination into the exact effects of forums on student grades. Despite this, the general trend is that, in courses that encourage student discussion forum participation, students will generally have a higher average grade than courses that do not.

In summary, LMS discussion forums are important to flex students and there are indications that encouraging and facilitating participation leads to improved outcomes for the student. However further research is required to determine effective ways of embedding and facilitating discussion forums within course curriculums as well as identifying other elements of the LMS that impact flex student results.

References:

Beer, C., & Jones, D. (2008). Learning Networks: Harnessing the power of online communities for discipline and lifelong learning. Paper presented at the 2008 Lifelong Learning Conference. from http://hdl.cqu.edu.au/10018/13162

Campbell, J. P., & Oblinger, D. G. (2007). Academic Analytics. Educause Article.

Carmean, C., & Haefner, J. (2002). Transforming Course Management Systems into Effective Learning Environments [Electronic Version]. Educause, November/December 2002, from http://net.educause.edu/ir/library/pdf/ERM0261.pdf

Caruso, J. B. (2006). Measuring Student Experiences with Course Management Systems [Electronic Version]. Educause, 2006, from http://net.educause.edu/ir/library/pdf/ERB0619.pdf

Coates, H., James, R., & Baldwin, G. (2005). A critical examination of the effects of learning management systems on university teaching and learning. Tertiary education and management, 11(2005), 19-36.

CQUniversity. (2007). Grades and Results Policy (version 11).   Retrieved 29th September 2009, 2009, from http://policy.cqu.edu.au/Policy/policy.jsp?policyid=437

CQUniversity. (2009). CQUniversity’s Minimum Service Standards.   Retrieved 28/9/2009, 2009, from http://lmsip.cqu.edu.au/FCWViewer/getFile.do?id=28098

Dawson, S. (2006). Online forum discussion interactions as an indicator of student community. Australian Journal of Educational Technology, 22(4), 495-510.

Heathcoate, L., & Dawson, S. (2005). Data Mining for Evaluation, Benchmarking and Reflective Practice in a LMS. E-Learn 2005: World conference on E-Learning in corporate, government, healthcare and higher education.

Hew, K. F., & Cheung, W. S. (2003). Models to evaluate online learning communities of asynchronous discussion forums. Australian Journal of Educational Technology, 19(2), 241-259.

Hinton, L., & Bradshaw, J. (2004). Benefits of An Online Discussion List in A Traditional Distance Education Course. Turkish Online Journal of Distance Education – TOJDE, 5(3).

Kim, B. (2006). Social Constructivism.   Retrieved 20th September 2009, 2009, from http://projects.coe.uga.edu/epltt/index.php?title=Social_Constructivism

Ladyshewsky, R. K. (2004). Online learning versus face to face learning: What is the difference? Paper presented at the Teaching and Learning Forum.

Malikowski, S., Thompton, M., & Theis, J. (2007). A model for research into course management systems: bridging technology and learning theory. Journal of educational computing research, 36(2)(2007), 24.

Marra, R. M., Moore, J. L., & Klimczak, A. K. (2004). Content analysis of online discussion forums: A comparative analysis of protocols. Educational Technology Research and Development, 52(2), 23-40.

Monash University. (2009). Grade Point Average and Weighted Average Mark.   Retrieved 2nd October, 2009, 2009, from http://www.adm.monash.edu.au/service-centre/gpa-wam.html

Moore, M. G. (1989). Three types of interaction. The American Journal of Distance Educaton, 3(2).

Northover, M. (2002). Online discussion boards – friend or foe? Paper presented at the Ascilite 2002. from http://www.ascilite.org.au/conferences/auckland02/proceedings/papers/193.pdf

Oliver, R. (2005). Using blended learning approaches to enhance teaching and learning outcomes in higher education. Paper presented at the International Association of University Presidents’ Teaching Showcase, Joondalup, WA.

Seifert, J. W. (Updated 2004). Data Mining: An Overview. Retrieved. from http://www.fas.org/irp/crs/RL31798.pdf.

Siemens, G. (2004a). Connectivism: A learning theory for the digital age. from http://www.elearnspace.org/Articles/connectivism.htm

Siemens, G. (2004b). The wrong place to start learning. LMS. elearnspace. everything elearning, from http://www.elearnspace.org/Articles/lms.htm

Snowden, D. (2008). The dogmas of the quiet past. Cognitive Edge Retrieved 4/8/2009, 2009, from http://www.cognitive-edge.com/blogs/dave/2008/10/the_dogmas_of_the_quiet_past_1.php

West, R. E., Waddoups, G., & Graham, C. R. (2006). Understanding the experiences of instructors as they adopt a course management system. Educational Technology Research and Development, 55(1), 1-26.

[2] Hitcount is the total number of hits.

In recent times, an important factor that requires consideration when discussing student engagement is the method of course delivery in universities. Some courses are delivered face-to-face; some via a blend of online and face-to-face and others are delivered fully online. In a traditional face-to-face class, students attend lectures and tutorials, and can participate in learning activities while in the presence of the instructor and their peers. A fully online course is typically delivered via the web with all the interactions between the learners, content and instructors facilitated by web based technologies, while blended courses use a mix involving face-to-face teaching augmented by web or online components.

The mode of course delivery defines the environment in which the student learns and encompasses the systems and dynamics that facilitate and enable student engagement (Coates, 2006). It is reasonable to assume that the mode of delivery will have an influence on how students engage in their learning environment. As an example of how the course delivery mode could influence student engagement, fully online students tend to be older and have competing demands and priorities in their lives when compared to their on-campus counterparts (Chen et al., 2008; Dutton, Durron, & Perry, 2002). As distance learning online is the fastest growing segment of postsecondary education its important to evaluate its effect on learner engagement (Chen et al., 2008).

Coates, H. (2006). Student Engagement in Campus-based and Online Education. Retrieved 23rd October 2009, from http://www.cqu.eblib.com.ezproxy.cqu.edu.au/EBLWeb/patron/

Chen, P.-S. D., Gonyea, R., & Kuh, G. (2008). Learning at a distance [Electronic Version]. Journal of online education, 4. Retrieved October 2009, from http://innovateonline.info/index.php?view=article&id=438&action=login

Most of the research into measuring student engagement prior to the widespread adoption of online, or web based classes, has concentrated on the simple measure of attendance (Douglas & Alemanne, 2007). While class attendance is a crude measure, in that it is only ever indicative of participation and does not necessarily consider the quality of the participation, it has nevertheless been found to be an important variable in determining student success (Douglas, 2008). It could also be said that class attendance is used as a metric for engagement, simply because it is one of the few indicators of engagement that are visible, or external to the student. For example, student motivation is often linked closely with engagement and has been defined as an internal state or condition that activates behaviour and gives it direction (Huitt, 2001). Class participation could be seen as an indicator of behaviour activated by a students’ motivation and can also be measured in online education, albeit with the same limitations concerning the quality of the participation.

Douglas, I. (2008, 14 December 2008). Measuring Participation in Internet Supported Courses. Paper presented at the 2008 International Conference on Computer Science and Software Engineering, Wuhan, China.

Douglas, I., & Alemanne, N. D. (2007). Measuring Student Participation and Effort. Paper presented at the International Conference on Cognition and Exploratory Learning in Digital Age, Algarve, Portugal.

Huitt, W. (2001). Motivation to Learn [Electronic Version]. Educational Psychology Interactive. Retrieved 31st October 2009, from http://chiron.valdosta.edu/whuitt/col/motivaton/motivate.html

This is the follow on from the previous post on student engagement

Online technologies are starting to make a serious impression on patterns of learning and teaching in higher education and learning management systems (LMS) are at the forefront of this technological movement (Coates, 2006). LMS are becoming ubiquitous at universities around the world, adding a virtual dimension to even the most traditional campus-based institution (Coates, James, & Baldwin, 2005). They are being used for presenting online or technology-enhanced classes and are not pedagogically neutral shells for course content as they influence pedagogy by presenting default formats designed to guide the instructor toward creating a course in a certain way (Lane, 2009). If LMS are affecting pedagogy, then they are obviously affecting student study habits and learning and therefore engagement (Coates et al., 2005).

Whilst LMS have the potential to influence student engagement, research into how they do so is largely in its infancy, and is often based on assumptions about campus learning environments (Coates, 2006). However, one important factor identified in the literature indicates that much or all of the interactions enabled by the LMS is asymmetric which means that students who require substantial instructor direction may have problems with an environment that demands a certain level of self discipline (Douglas & Alemanne, 2007). Importantly, whether online or otherwise, student motivation is a, or perhaps the, key factor influencing the level of engagement in a course.

Additionally there is research that suggests course level and discipline has an effect on student grades and withdrawal rates when the course is delivered by LMS (Hornik, Saunders, Li, Moskal, & Dzuiban, 2008). This would indicate that not all courses are equal when considering their applicability to LMS delivery. High paradigm courses such as physics and chemistry demonstrate higher grades and lower withdrawal rates than low paradigm courses like social sciences and literature (Hornik et al., 2008). Arguably, this may indicate lower levels of student engagement for low paradigm courses than for high paradigm courses. The same research suggests that course level has an influence on student grades and satisfaction delivered by an LMS. Introductory courses, such as first years courses, were compared to advanced level courses; second and third year; and demonstrated different levels of student satisfaction and grades, especially when linked to the course’s level of paradigm development (Hornik et al., 2008).

Bulger, M. E., Mayer, R. E., Almeroth, K. C., & Blau, S. D. (2008). Measuring Learner Engagement in Computer-Equipped College Classrooms. Journal of Educational Multimedia and Hypermedia, 17(2), 129-143.

Chen, P.-S. D., Gonyea, R., & Kuh, G. (2008). Learning at a distance [Electronic Version]. Journal of online education, 4. Retrieved October 2009, from http://innovateonline.info/index.php?view=article&id=438&action=login

Coates, H. (2006). Student Engagement in Campus-based and Online Education. Retrieved 23rd October 2009, from http://www.cqu.eblib.com.ezproxy.cqu.edu.au/EBLWeb/patron/

Coates, H. (2007). A model of online and general campus-based student engagement. Assessment & Evaluation in Higher Education, 32(2), 121-141.

Coates, H., James, R., & Baldwin, G. (2005). A critical examination of the effects of learning management systems on university teaching and learning. Tertiary education and management, 11(2005), 19-36.

Douglas, I., & Alemanne, N. D. (2007). Measuring Student Participation and Effort. Paper presented at the International Conference on Cognition and Exploratory Learning in Digital Age, Algarve, Portugal.

Hornik, S., Saunders, C. S., Li, Y., Moskal, P. D., & Dzuiban, C. D. (2008). The Impact of Paradigm Development and Course Level on Performance in Technology-Mediated Learning Environments. Informing Science. The international journal of an emerging transdiscipline, 11(11).

Krause, K.-L. (2005, 21-22 September 2005.). Understanding and promoting student engagement in university learning communities. Paper presented at the Sharing Scholarship in Learning and Teaching: Engaging Students, James Cook University, Townsville.

Krause, K.-L., & Coates, H. (2008). Students’ engagement in first-year university. Assessment & Evaluation in Higher Education, 33(5), 493 – 505.

Kuh, G. D. (2001). Assessing What Really Matters to Student Learning. Inside the national survey of student engagement. [Electronic Version]. Retrieved 22nd October 2009, from http://cpr.iub.edu/uploads/Assessing_What_Really_Matters_To_Student_Learning_(Kuh,%202001).pdf

Lane, L. M. (2009). Insidious Pedagogy: How course management systems affect teaching [Electronic Version], 14, from http://firstmonday.org/htbin/cgiwrap/bin/ojs/index.php/fm/article/view/2530/2303

Stovall, I. (2003). Engagement and Online Learning [Electronic Version]. UIS Community of Practice for E-Learning. Retrieved October 2009, from http://otel.uis.edu/copel/EngagementandOnlineLearning.ppt

The following is the start of a series of posts that I’m using as preparation for an assessment piece. Hopefully these posts will help organize my thoughts and positively contribute to the structure of the paper. Note that this post will change frequently as it gets fine tuned.

In higher education, engagement has become a catch-all term most commonly used to describe a compendium of behaviours characterizing students (Krause, 2005). It has even been suggested that student engagement could be used as an indicator of institutional teaching quality (Kuh, 2001). Furthermore it has been said that at a certain level of analysis, engagement is taken to provide a singularly sufficient means of determining whether students are engaging with their study and university learning community in ways likely to promote high-quality learning. (Krause & Coates, 2008). However, measuring engagement and its link to learning is challenging (Bulger, Mayer, Almeroth, & Blau, 2008). This is especially true when the term engagement is often used in a broad terms to describe a range of behaviours that learners exhibit. An investigation into what engagement is, and what factors influence engagement, is required before metrics for its measurement can be determined.

Stovall (2003) suggests that engagement is defined by a combination of a student’s time on task and their willingness to participate in activities. Others say that engagement is the quality of effort students themselves devote to educationally purposeful activities that contribute directly to desired outcomes (Krause & Coates, 2008). Additionally, Chen (2008) says that engagement is the degree to which learners are engaged with their educational activities and that engagement is positively linked to a host of desired outcomes, including high grades, student satisfaction, and perseverance (Chen et al., 2008). Other studies define engagement in terms of interest, effort, motivation and time-on-task and suggest that there is a causal relationship between engaged time, that is, the period of time in which students are completely focused on and participating in the learning task, and academic achievement (Bulger et al., 2008).

A basic tenet of the research into engagement is that student’s activity and involvement in their learning tasks is related to their academic achievement. While there doesn’t appear to be a single definition for engagement, a definition put forward in 2007 aggregates the literature to provide the following elucidation. “Engagement is seen to comprise active and collaborative learning, participation in challenging academic activities, formative communication with academic staff, involvement in enriching educational experiences, and feeling legitimated and supported by university learning communities” (Coates, 2007)

A complicating factor that requires consideration when discussing student engagement is the method of course delivery. Some courses are delivered face-to-face, some via a blend of online and face-to-face and others fully online. There is some indication that distance-learning students outperform or perform on par with on-campus students on measures such as student-faculty interactions and higher-order, integrative and reflective learning (Stovall, 2003). However distance-learning students often demonstrate lower levels of engagement when it comes to active and collaborative learning (Stovall, 2003). Possibly due to the difficulty of such an indirect comparison, the degree to which distance learners are engaged in their educational activities relative to campus-based learners is unresolved (Chen et al., 2008).

Chen et al. (2008) states that most of the work demonstrating positive outcomes in distance learning has focused on older students who are more motivated and have the self discipline to manage effectively the unstructured nature of the distance learning environment. While this may be true, research has been largely based on assumptions about campus learning environments that ignore the implications of online learning (Coates, 2006).

Bulger, M. E., Mayer, R. E., Almeroth, K. C., & Blau, S. D. (2008). Measuring Learner Engagement in Computer-Equipped College Classrooms. Journal of Educational Multimedia and Hypermedia, 17(2), 129-143.

Chen, P.-S. D., Gonyea, R., & Kuh, G. (2008). Learning at a distance [Electronic Version]. Journal of online education, 4. Retrieved October 2009, from http://innovateonline.info/index.php?view=article&id=438&action=login

Coates, H. (2006). Student Engagement in Campus-based and Online Education. Retrieved 23rd October 2009, from http://www.cqu.eblib.com.ezproxy.cqu.edu.au/EBLWeb/patron/

Coates, H. (2007). A model of online and general campus-based student engagement. Assessment & Evaluation in Higher Education, 32(2), 121-141.

Krause, K.-L. (2005, 21-22 September 2005.). Understanding and promoting student engagement in university learning communities. Paper presented at the Sharing Scholarship in Learning and Teaching: Engaging Students, James Cook University, Townsville.

Krause, K.-L., & Coates, H. (2008). Students’ engagement in first-year university. Assessment & Evaluation in Higher Education, 33(5), 493 – 505.

Kuh, G. D. (2001). Assessing What Really Matters to Student Learning. Inside the national survey of student engagement. [Electronic Version]. Retrieved 22nd October 2009, from http://cpr.iub.edu/uploads/Assessing_What_Really_Matters_To_Student_Learning_(Kuh,%202001).pdf

Stovall, I. (2003). Engagement and Online Learning [Electronic Version]. UIS Community of Practice for E-Learning. Retrieved October 2009, from http://otel.uis.edu/copel/EngagementandOnlineLearning.ppt

Bachelor of Professional Communication Learning Network: Creating an Online Community for Lifelong Learning

Ken Clark

CQUniversity, Australia

Colin Beer

CQUniversity. Australia

One of the shaping influences in the student journey is the Learning Management System (LMS) used by  universities. The Bachelor of Professional Communication (BProfComm) Project at CQUniversity aims to provide students, staff, and industry practitioners with a discipline wide, online learning network, enabled by Web 2.0 technology. This may alleviate some of the inherent problems associated with the LMS, and in so doing, may aid in the construction of discipline based and professional networks. This document is reporting on the development phase of what an educational action research project and its subsequent failure to engage with students.

Background

Academics from the Professional Communication Program have, in 2008, built a ‘learning portal/network’ (http://webfuse.cqu.edu.au/BProfComm/index.html) where Blackboard incorporated additional features like career information; skill share with professional colleagues working in the industry; feeds from the various blogs, wikis, and news specific to the industry; and peer sharing of information, blogs, and other information pertinent to the students as they progress through the program.  This was found to be impossible to do within the confines of CQUniversity’s (CQUni) current Blackboard LMS (currently Blackboard 6.3, as CQUni are moving to Moodle as the only LMS in 2010). Due to the proprietary, closed nature of Blackboard, it does not easily allow the integration of tools that are not approved by both Blackboard and CQUni, especially, to the degree that has been proposed by this project.

Henze, Dolog and Nejdi (2004) proposed that adaptive hyper media systems be built taking into account the different needs of the students to facilitate learning.  Adaptive educational hypermedia systems are able to adapt various visible aspects of the hypermedia systems to the individual requirements of the learners and are very promising tools in the area of eLearning.  Especially in the area of e-Learning it is important to take the different needs of learners into account in order to propose learning goals, learning paths, help students in orienting in the e-Learning systems and support them during their learning progress.

At the moment this technology is only in its infancy at CQUniversity .  Learning portals are built as part of the Learning Management Systems within a defined academic learning space, creating duplication of data within a particular degree structure such as the Bachelor of Professional Communication.  The situation has been, in some small way, rectified in later versions of Blackboard available to Institutions especially the various web 2.0 features that are being incorporated within these later versions, blogs, wikis, podcasts, and RSS feeds added as building blocks in version 8, and built into Blackboard in version 9.

Utilizing the idea of an adaptive dynamic space is one way that can be found to avoid duplication and to create a learning space that is specific to a program, not just one that links to individual subjects.  The concept of an adaptive dynamic space originated in the examination of the Curriculum Design and Development Unit (CDDU) collaborative website (Wiki) at CQUniversity and the main focus of that Wiki can be enlarged to incorporate program offerings, and subsidiary data flows, within those programs.

“[H]yperlinking” is the foundation of the web. As users add new content, and new sites, other users discover the content and link to it binding it into the structure of the web. Much as synapses form in the brain, with associations becoming stronger through repetition or intensity, the web of connections grows organically as an output of the collective activity of all web users (O’Reilly 2005).

What O’Reilly is highlighting is the web’s power, and our power, as web users, to harness the collective wisdom that resides in hyperspace.  The dynamic potential  of the hypermedia systems is one aspect that universities are not utilizing as LMS tend to be a one way, dissemination models of user interaction.

The Problem

A number of problems with using CMS (LMS) in distance learning have been reported, e.g. students may feel isolated due to the limited contact with the instructor and other students, can get disorientated in the course hyperspace, may lose their motivation, and often find it difficult to manage without appropriate institutional support (Mazza & Dimitrova 2005).

CQUniversity has, as part of its online learning and teaching responsibilities, adopted Blackboard and Webfuse as the Learning Management Systems (LMS).  While these are good for the delivery of most courses, the systems do not offer the flexibility and dynamism that is current in web development and course delivery.  One situation that has arisen is that there is a lot of duplication of data into the Bachelor of Professional Communication (BProfComm).  The disciplines that teach into the BProfComm currently are Public Relations, Journalism, Multimedia, Visual Media, Film Studies, Media and Cultural Studies, Marketing and Human Resource Management.   Each discipline, duplicates to some extent, the way that students collect data, and transmit data within the discipline and within the degree.  Duplication like this is wasteful for students, it is time-consuming for staff, and it is a simplistic way to build a learning centred environment that is not student centred.

Learning centres are dispersed within their own discipline, they are basic and built on Web 1.0 technology, and there is little dynamic interaction with the vast networks, media outlets, weblogs, and social communities that have developed over the last couple of years.  As Beer and Jones (2008, p. 3 of 6) argue, “if a student or staff member wishes to engage in any form of e-learning they must use the system that has been selected by the institution … the technology available to individuals has been outstripping the functionality and usability of the technology provided by institutions.”

There is currently no sense of ownership of place, or space, for learning, or ‘for guiding the development of a learning centred learning environment’ (Clark & Maher, 2001, p, 2) in the current system.  As such, there is dissonance between the end user and the LMS designer and this dissonance between the needs of a systems users and its embedded world view lead to a number of problems. The dissonance becomes a gap between the users and the system. This gap prevents the adoption of certain approaches and can create additional workload as people attempt to work around it.  Eventually, this dissonance gap will lead users to attempting to use alternate means (Jones 2008). Avoiding the dissonance between the user and the system is what has been attempted in this design.

Limitations of the LMS

The current LMS is basically a static page, and while it can have Really Simple Syndication (RSS) feeds incorporated into its structure it does not have the look and feel of a dynamic learning space that has real world counterparts.  The value for a university organisation is that LMS as used provide a sequencing structure that is manageable by administrators and academics (Siemens 2004). The difficulty is in incorporating current Web 2.0 technology such as podcasts, RSS feeds, social blogging, Wikis, social bookmarking, and other web appliances into the above LMS due to the limitations inherit in the philosophy or model used by LMS.

At a fundamental level, the model used by learning management systems is based on the assumption that the instructor or institution is the sole conduit through which learning will occur. This model maybe less the result of deliberate design and more based on the era in which the LMS was created as it predates social media and Web2.0. The LMS model was established in the Web1.0 era where information was transmitted and consumed as opposed to Web2.0 where the web has become a platform or network where content is created, shared, re-purposed, remixed and passed along (Downes 2005). Some limitations of LMS in general include content focused, organizational and instructor centric, course/term boundaries, does not readily support reflection on prior learning, does not readily support informal learning, and the IT culture itself has a centralized model of delivery akin to Web 1.0, and the functionality of features available to general internet users is outstripping what organizations can provide. Some of the more specific limitations of the LMS are:

• Content focus: Most LMS effectively provide learner-content interaction (Siemens 2004) and there is even some evidence to suggest they do this more effectively than traditional methods such as face-to-face (Ladyshewsky 2004), however, the tools they provide for learner-instructor and learner-learner are basic at best.
• Organizational and instructor focus: According to the Organization for economic cooperation and development the use of ICT within tertiary education has impacted more on administrative services than on fundamentals of learning and teaching (OECD 2005).  Siemens (2004) also points out that “Learning Management Systems give value to organizations by providing a means to sequence content and create a manageable structure for instructors and administrators”, thus enhancing the productivity of the technical team.
• Course based: An LMS is designed to provide tools for an instructor to deliver a single course for a single term (Beer & Jones 2008)
• IT Culture: Decisions made by IT departments are generally made on the assumption of keeping the management and control of technology centralised within an organisation (Mossberg 2007). Consequently if a student or instructor wish to engage in any form of eLearning they must use the system that has been selected by the institution. However, the technology available to individuals has been outstripping the functionality and usability of the technology provided by institutions (Johnson and Liber 2008).  As Kennedy, Judd, Churchward and Gray (2008) attest, “It cannot be ignored that substantial proportions of incoming university students are using and reading blogs, are taking photos with their mobile phones, are regularly using social networking software such as MySpace, are communicating via web conferencing, and are sharing all sorts of digital files using both their mobile phones and the web.”
• Informal Learning and situated learning: Often the most valuable learning takes place serendipitously by random chance (Siemens 2004). Typically learning management systems have clear boundaries such as course terms and enrolment that actually inhibit and discourage the development of informal and lifelong learning.

One of the main issues is to provide a place, a virtual centre, where the students have a sense of ownership, and have control over their learning environment. Clark and Maher (2001, p. 2) state that,

Today, we have the ability to create very sophisticated and complex interactive virtual environments … These virtual environments are populated by communities, which are able to interact and communicate with each other in many forms.  These virtual environments have the shapes, form, structures and functionality that are akin to the physical world.

If they have the shape, form and functionality of the physical world then they should have the immediacy of the physical world as well, with the feel of that immediacy.   The network envisages the interaction of students, and the wider public, in its growth and development providing the site in which learning can occur.   We propose a framework that is built on what Maher and Clark  (2001. p. 6) describe as a “model for virtual learning … [where] the technology aspect of a learning environment can be supported by a virtual worlds, the learning theory … is constructivist, and the design model … is situatedness.”  In other words, principles used in the design of this portal are drawn from a situated learning approach, where learning is embedded “within and inseparable from participating in a system of activity, deeply determined by … particular physical and cultural setting[s]” (Nelson & Erlandson 2007, p. 622).

Design Goals

At the moment 62% of the students in the Bachelor of Professional communication program are flex or distance students, so one of the main foci of the project is to enhance the learner’s experience by constructing an online learning network or community of practice that utilizes freely available Web 2.0 concepts and technologies in order to improve the sociability and reduce the isolation effect that these students in particular may experience. It is also proposed that the online learning network model will overcome the inherit limitations of learning management systems in general, and improve the learner’s experience through a combination of the following factors:

• Enhanced student engagement through meaningful social interactions with other learners, industry practitioners and teaching staff.
• Informal learning through social interactions with others in the field of endeavour.
• Enhanced learner reflection through their introduction to new technologies that have the potential to facilitate learner reflection.
• Exposure to a reusable and evolutionary online resource that can promote lifelong learning.

The theory behind the model is constructivist, making explicit the learning experience of students and takes into account the situational context in which learning takes place. What is envisaged is a place for interaction, where the learning is authentic and meaningful, where data is gathered to form collaborations between the teacher, student, graduates, industry, and the wider community (Maher & Clark 2001).   The BProfComm network is designed specifically for the context in which the students find themselves.

Instead of students, and staff, utilizing static web pages and links to construct learning spaces, the concept is to construct a Learning Network where the information for all BProfComm students is brought to the one place, building a portal for guiding and developing the construction of lifelong learning driven by Web 2.0 technology, such as RSS feeds, social bookmarking (folksonomies), blogging, and other formal and informal learning supports on the one page, making that page a dynamic collection accessible for everyone in the BProfComm.  Staff can, for instance, create a collection of tagged pages via Del.icio.us and feed them through Pipes (a data aggregator) to sort and deliver them to the Network in a custom feed.  The intriguing notion is that one web portal can facilitate the bringing together of independent disciplines into a transdisciplinary place which is learning centred and designed specifically for the context.

As well as this, and much more importantly, it provides a space where students can become the researchers, teachers, and disseminators of their own creations.  What the Network has the capacity to do is to imbue students with a sense of intellectual purpose, instil in them a desire to make a difference, provide them with opportunities to reach a wider audience, and furnish them with the tools to break new ground. By recasting students as researchers and teachers, we invite them to participate in what is arguably the most exciting and fulfilling aspect of university life: the production of new knowledge (Sword & Leggott 2007, p. 1. Journalism students can feed their stories, photo-media students can feed their portfolios, PR students can start to develop their own PR kits, and it can be the one place where students can control what happens to their intellectual outputs.

Methodology

The basic premise for the methodology is Educational Action Research, designed in a collaborative process trying to find a way of overcoming the lack of the LMS, and to incorporate academics, technical staff, and industry peers in an online network designing with student learning, and skill enhancement in mind.  With this in mind a small group was brought together incorporating two academics within the Bachelor of Professional Communication Program and one technician to try to build what was envisaged.

Implementation

It was decided to host the online learning network on CQUniversity’s own Webfuse system for several reasons. Blackboard does not lend itself to the flexibility required to incorporate some of the freely available tools that are key to the project such as RSS (really simple syndication), Blogs and Wikis. On top of this it is very difficult to allow an external participant access to a Blackboard if they do not have a current CQUni student or staff account. One thing to note is that although we are hosting the project on Webfuse we are not using any of the features that it contains other than its ability to serve web pages to users.

At the outset of the construction of the Web 2.0 page the team made the assumption ‘that students are tech savvy, and aware of changes in the online environment’, therefore, they would be familiar with RSS feeds and what these entail.  As well as this the team focused on some preliminary research questions that are concerned with the basic assumption that was made:

1. If we build this network, will the students, academics and industry peers utilise the feeds?
2. How do we construct in such a way that we are assured of their interest and input?
3. Why a Web 2.0 site?   What does this add to the student learning experience that they cannot get elsewhere?

At that first meeting the only thing that was mentioned was that there was a ‘problem’ with the system but what was needed to fix it seemed nebulous, but the team has some basic ideas of what would be needed.  The team wanted ’something’ that incorporated news feeds, career advice, and current information from industry (what that was, was not elaborated on).  Some of the basic requirements for the learning network are that it has to be low maintenance, it has to be easy to use, the technology and tools have to be freely available (open source), and that it has to be designed in such a way that students, staff and colleagues find it useful and applicable to their personal situation to try to get away from the ‘build it and they will come’ concerns of the dot.com boom.

Work by the CDDU, and in particular their work into personal learning environments, informed some of the strategies employed in this project. This unit has attempted to utilise Web 2.0 appliances where possible, ensuring a collegial approach in their role that supports staff and students in the use of various educational technologies. They make extensive use of RSS feeds to both receive information and to dynamically populate their website.

The underlying design strategy for the BProfComm project is to connect people and information in a way that is useful and simple. The key ingredient for doing this is RSS. RSS allows the user to automatically receive updates from around the Internet without having to actively go and visit sites to see if they have been updated. Most websites and applications, and in particular Blogs and Wikis, now produce RSS feeds that can be subscribed to. It is also believed that by exposing staff and students to RSS they will gain some valuable information literacy that has the ability to save them time in other areas of their lives.

Some consideration was given to the technologies that students currently use and it could be inferred that what they are using is what they feel most comfortable with. According to research completed by Kennedy et al. (2007) email is the technology that is most used by the students so in the interest of minimizing the effects of cognitive load that would result by having the students learn new software packages it was decided to utilize a freely available service called Mailbucket that is an email to RSS gateway. The students, staff or industry practitioners could simply send an email to the email address provided and this would be reflected in the RSS feeds available on the site.

There are several advanced uses for RSS that make it a valuable tool when creating a site such as the project. The first of which is the ability to take an RSS feed and display it as part of your web page. This allows the page to display constantly changing, or dynamic, content without any action by the designer in a style that matches the web site. The second is a product developed by Yahoo Inc called Yahoo Pipes. Pipes allow you to filter and manipulate multiple feeds and reproduce the output as a single RSS feed. We are using at least seven pipes to feed the information from the various sources into the project site.

According to Beer & Jones (2008) one of the requirements of an online learning network is, “a home page to assert their existence and describe their domain and activities”. In this case we chose to host our site using the Webfuse system at CQUni. Hosting it on this system allowed us complete control over the content and the program code that drives the site that Blackboard can not do. There are seven categories which equates to seven RSS feeds that comprise the output from the site (Figure 1 below)

• News Feed. This is an aggregated feed taken from five new broadcasters’ sites that is filtered on key words such as public relations, journals journalism.
• Job Vacancies. This is an aggregated feed take from various job vacancy sites around the country.
• Our Talk. Another aggregated feed that combines all of the Blogs that belong to teaching staff and reproduces this as a single RSS feed.
• Industry Folk. At the moment our two participating industry practitioners are actively maintaining their own Blogs that are aggregated here.
• Our Links. This is a feed take directly from the social bookmarking site Delicious.com. Any webpage that is tagged by users with BProfComm will appear in this feed.
• Group Talk. This is a freely available email to RSS gateway that participants without Blogs can use to lodge questions or comments to the entire community.
• Question Feed. This feed will be used predominately for students to direct questions to the participating industry representatives.

Figure 1: Seven RSS Categories that flow from the site

The feeds and the subscription links appear on the home page of the project where the participants can initially visit to subscribe to the feeds contained within. Subscribing removes the need for the participants’ to visit the site in order to receive any new postings that may have occurred. Students and staff are encouraged to use Blogging as a means to provide input into the community and a way to comment on current events in the field. Further work needs to be done on information literacy. Demonstrating the usefulness and ease of use of tools such as RSS, Blogs and Wikis is something that will be given higher priority throughout the project with plans for a modular, reusable support section under development. This section is used by other staff to educate users in the use of particular technologies that they are considering as part of their curriculum. Informing users about privacy and explaining steps they need to take to ensure their identity security in a Web 2.0 world is an essential facet. Features like strong passwords and restricting access to all but explicitly exempt Blog postings will need to be explained in detail to the people using the site.

Interestingly, most of the technologies employed in this project are open, which means that membership is not dictated by the institution and is open to the general public. This raises some serious issues that have significant bearing upon the viability of the project. Issues such as privacy, information security and spam need to be addressed before the site opens for business. Because we are using Yahoo pipes for the aggregation and filtering of RSS feeds, the Blogs and news feeds that supply the information have to be explicitly created by the project designers so the ability to spam these feeds is very limited. However, there currently are feeds being fed into the project such as the email to RSS gateways and the Delicious feeds that are coming directly from the sources without any sort of filtering or moderation by teaching staff.

Conclusion

As described, the project is basically a list of RSS feeds that contain information pertinent to the professional communications discipline, and it is not working. Less than ten students have accessed the site, and no meaningful conversation has occurred and no idea exchange happened via the mechanisms described by this project. Part of the failure has been the ‘cyber-optimistic’ of the designers, influenced in part by anecdotal evidence that students are at the forefront of technology, and partly by our own experience in using technology.  As Bates (2000) states, More and more, learners will have developed extensive experience and skills in using information technologies in their nonacademic lives, and they will be increasingly unforgiving of institutions that seem out of touch with developments in the “real” world. Learners are likely to reject higher education institutions that do not integrate technology into the curriculum because of the perceived negative impact on their employability after graduation if they are not exposed to the use of technology.

Our experience has been that students have ‘extensive experience and skills using …technology’, they will use technology that they see useful, but they will not use technology if they see no benefit.   We built it, and students did not come.

We are well aware of the limitation of the “build it and they will come” model that we used. The philosophic approach we took is one of safe fail where we address each failure not with downcast expressions but as a motivation to re-access and change our approach. The technical back-end that drives the site is built from lightweight, modular technologies and as a result we can change major components of the project quickly as required or as suggested by the users of the system. This follows what appears to be a design philosophy used by a great many Web 2.0 applications where you do not wait until all of the bugs are ironed out of the system before it is released to the user community, known as “release early, release often” and affords a very agile, user focused design strategy.

Further investigation is required into privacy and security including consultation with staff from ethics and compliance, however, in the mean time we are recording all RSS feeds automatically in order to identify unsolicited content and establish processes to prevent it. Up until the writing of this document there have not been any signs of unsolicited content making it into the feeds that power the site.

Far from being a failure there is increasing interest from industry peers, and academic staff, to utilize the Project site so that it informs the development process of the Program.  It may also be useful in creating a forum for collegiality, and social cohesion between academics and industry, as well as providing a focus for sustaining the same.  More work will need to be done in examining this aspect.

Reference List

Bates, A.W. (2000). Managing Technological Change: Strategies for college and university leaders. Jossey-Bass.

Beer, C. & Jones, D. (2008). Learning networks: Harnessing the power of online communities for discipline and lifelong learning. In D. Orr, P.A. Danaher, G. Danaher & R.E. Harreveld (Eds.). Lifelong Learning: reflecting on successes and framing futures. Keynote and refereed papers from the 5th International Lifelong Learning Conference.  Rockhampton: Central Queensland University Press. http://hdl.cqu.edu.au/10018/13162.

Chickering, A. and Gamson, Z. (1991). Applying the Seven Principles for Good Practice in Undergraduate Education. New Directions for Teaching and Learning, 47, Fall 1991, San Francisco: Jossey-Bass Inc.

Clark, S., & Maher, M. (2001). The Role of Place in Designing a Learner Centered Virtual Learning Environment. Computer Aided Architectural Design Futures Conference, Eindhoven University of Technology, Eindhoven, Holland, 8-11July.  http://people.arch.usyd.edu.au/~mary/Pubs/2001pdf/CF2001.pdf.

Cross, J. (2003). Informal Learning – the other 80%. Internet Time Group, May 08 2003. http://internettime.com/Learning/The%20Other%2080%25.htm.

E-learning in Tertiary education. Organization for economic cooperation and development, December 2005. http://www.oecd.org/dataoecd/55/25/35961132.pdf.

Henze, N., Dolog, P., & Nejdl, W 2004, “Reasoning and Ontologies for Personalized E-Learning in the Semantic Web”, Educational Technology & Society, 7 (4), 82-97).

Kennedy, G., Dalgarno, B., Gray, K., Judd, T., Waycott, J.,  & Bennett, S.  (2007).The net generation are not big users of Web 2.0 technologies: Preliminary findings.  In ICT: Providing choices for learners and learning. Proceedings Ascilite Singapore 2007 (pp. 517-525).

Kennedy, G. E., Judd, T. S., Churchward, A., Gray, K. & Krause, K.L. (2008). First year students’ experiences with technology: Are they really digital natives? Australasian Journal of Educational Technology, 24(1), 108-122. http://www.ascilite.org.au/ajet/ajet24/kennedy.html

Ladyshewsky, R.  (2004). Online learning versus face to face learning: What is the difference? Teaching and Learning Forum 2004. Curtin University of Technology,

http://lsn.curtin.edu.au/tlf/tlf2004/ladyshewsky.html.

Jones, D. (2008). The dissonance gap in systems and LMS evaluations. The Weblog of (a) David Jones. http://davidtjones.wordpress.com/2008/11/17/the-dissonance-gap-in-systems-and-lms-evaluations/.

Mazza, D. (2005). CourseVis: A Graphical Student Monitoring Tool for Supporting Instructors in Web-Based Distance Courses.

http://www.comp.leeds.ac.uk/vania/umuas/coursevis.html.

Nelson, B. & Erlandson, B. (2007). Managing Cognitive Load in Educational Multi-user Virtual Environments: Reflection on Design Practice. Education Tech Research, 56, 619-641.

O’Reilly, T. (2005).  What Is Web 2.0 Design Patterns and Business Models for the Next Generation of Software. O’Reilly.com.

http://www.oreillynet.com/pub/a/oreilly/tim/news/2005/09/30/what-is-web-20.html.

Siemens, G. (2004). Learning Management Systems: The wrong place to start learning.  http://www.elearnspace.org/Articles/lms.htm.

Sword, H. and Leggott, M. (2007). Backwards into the Future: Seven Principles for Educating the Ne(x)t Generation. Innovate: Journal of Online Education, 3(2). http://www.innovateonline.info/index.php?view=article&id=389&action=article.

Winter, R. (1996). Some Principles and Procedures for the Conduct of Action Research. New Directions in Action Research. London: Falmer Press. 16-17.

Author contact details:

Please cite as: Clark, K. and Beer, C. (2009). Bachelor of Professional Communication Learning Network: Creating an Online Community for Lifelong Learning. In Same places, different spaces. Proceedings ascilite Auckland 2009. http://www.ascilite.org.au/conferences/auckland09/procs/clark.pdf

Copyright © 2009 Ken Clark & Colin Beer

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A learning management system (LMS) enables teaching staff to add resources or activities to an online course via a web interface with little or no knowledge of the underlying web (html) technology. Often the design and development of this course is the responsibility of the teaching staff and this is an important consideration when looking at the adoption of features within an LMS over time. If it is the teaching staff who are adding resources and activities to a course, then their experience with the teaching medium and their conception of teaching influences the features that will be used in a particular course. Additionally, Siemens (2004) says its only recently, and in limited ways, that LMS vendors have begun extending tools and offerings beyond simple content sequencing and discussion forums.

I realize that this is an over-generalization but let’s say that LMS tools and features tend to favour content dissemination type tools. The staff teaching via an LMS were themselves most often taught via a “lecture” or “sage on the stage” modality. Does this mean that pattern entrainment comes into play and they would tend to teach in a similar way that they were taught?

The following is a figure demonstrating feature adoption over time in one particular LMS. Whilst potentially another over-generalization, I’ve grouped features that support content dissemination and features that support communication to see if there is a trend.

Content and Communication Feature Adoption

It has been said that for deeper learning to occur, learning must be social, active, contextual, engaging and student owned (Carmean & Haefner, 2002). Others have suggested that the learning process is transitioning from cognitive theories based on the individual to theories that stress the importance of the social nature of learning (Dawson, 2006) . Dawson et al (2006) states, numerous authors have espoused the importance for developing social learning opportunities where students actively debate, exchange and clarify ideas with other peers. Irrespective of learning theory, there is little doubt that social interaction plays an important part in learning and for the fully online student in a university course, the LMS discussion forum is the main enabler for social discourse and interaction during their course.

The following figures demonstrate the difference between on-campus and distance students in how they interact with the LMS.

What isn’t shown here is that when forum discussions are embedded into the course to meet specific course objectives as opposed to just providing a space for spontaneous student interaction, the proportion of the course that is forum activity increases.

Carmean, C., & Haefner, J. (2002). Transforming Course Management Systems into Effective Learning Environments [Electronic Version]. Educause, November/December 2002, from http://net.educause.edu/ir/library/pdf/ERM0261.pdf

Dawson, S. (2006). Online forum discussion interactions as an indicator of student community. Australian Journal of Educational Technology, 22(4), 495-510.

An quick extract from something I’m currently working on about LMS features that support content and LMS features that support communication. The following chart shows the evolution of these features over time in one particular LMS and indicates the dominance of content related features.

The following chart demonstrates the break down of distance student hits on these features.

This dominance of content features would appear to be a problem as it is contrary to research showing that effective learning occurs when students learn with computers rather than from computers (Oliver, 2005). Others have suggested that the learning process is transitioning from cognitive theories based on the individual to theories that stress the importance of the social nature of learning (Dawson, 2006) .

References.

Dawson, S. (2006). Online forum discussion interactions as an indicator of student community. Australian Journal of Educational Technology, 22(4), 495-510.

Oliver, R. (2005). Using blended learning approaches to enhance teaching and learning outcomes in higher education. Paper presented at the International Association of University Presidents’ Teaching Showcase, Joondalup, WA.