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A recent study has turned up some surprising things regarding NZ internet usage.

“Fresh data from AUT University, compiled for the World Internet Project places New Zealand as the country with the highest internet penetration of any of the countries surveyed.

Run out of California, the project compares internet use in 30 countries including the United States, Britain, Canada and Australia.”  (NZ Herald, 10 August, 2008)

That certainly wasn’t my impression before now.

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The world’s first significant virtual massage conference will run over a six day period from the 17th of November to the 22nd of November.  Many of the most influential figures in the world of massage today will be speaking including

  • Leon Chaitow
  • Ruth Werner
  • Thomas Meyers
  • John Upledger
  • Bonnie Pruden
  • Marion Rosen
  • Steve Capelli

As far as I’m concerned, this makes the conference unmissable.

Access to the presentations can be gained from as little as US$59, with full access only US$199.  According to the website it’s also possible to make arrangements for your students to participate in some events as part of their course of study.

Can’t wait…..

In recent years, much educational research has been done based on the principles of cognitive load theory and other cognitive learning theories (Clark & Meyer, 2004).  This work has provided an empirical base for the design of online learning experiences which Clark and Meyer have applied in their development of a set of principles of e-learning design (2004).  These principles are summarised in Fig 3 on the following page.

It has been demonstrated that designing learning experiences based on these principles improves educational outcomes for students (Clark & Meyer, 2004), however much of Clark and Meyer’s work has focussed on incorporating multi-media within the design of learning experiences.  While the use of rich multi-media environments clearly has more potential to engage students, and improve learning (Clark & Meyer, 2004), there are some issues with the provision of an optimal multi-media environment for learning. These issues relate primarily to financial resources and accessibility.

Unfortunately the process of creating multi-media resources is expensive relative to the creation of text-based resources (Rumble, 2001), and the financial resources available to educational institutions are often limited.   This may be less of a factor in the future.  There is a move towards the use and re-use of open-educational resources (OER) within the education industry, and as multi-media learning resources become more available the development costs of producing a media-rich educational programme will decrease.  At present in the massage therapy field there are few educational institutions involved in the creation of OERs, although development in this area has begun (Massage Therapy Educational Resources, 2008).

There are also issues of accessibility.  Multi-media resources such as video and audio contain much more data than text-based resources.  This can lead to frustration on the part of a computer user who has a slower internet connection.   Ideally online learning resources should provide the user with the option of either text and images, or multi-media.

These limitations mean that online educational resources for massage therapy must initially be largely text-based.  Text-based media is not ideal for an audience with a predominant kinaesthetic learning preference, however this issue can be moderated by educational design.  Theoretical material should be interspersed with exercises which require the student to apply their learning to a pseudo-real-world context such as case-based learning.  Students may be directed from their online environment to engage in real-world activities such as interviewing massage therapists who are already practising.  There are already some quality online learning resources available in the anatomy, physiology and pathology areas.  As the pool of open education massage therapy educational resources develops, educators can begin to develop the rich clinical simulations and interactive media which will ultimately be more appealing to kinaesthetic students

The online learning environment should be designed to facilitate communication both between the instructor(s) and the students, and between the students themselves.  There are many platforms to support communication in the online learning environment including email, email groups, voice-over-internet-protocols services (such as MSN messenger, and Skype), social networking platforms (such as Facebook and Bebo), web-conferencing services (such as elluminate, and dimdim), blogs, and discussion boards to name some of the more commonly used services.  Choosing the mix of communication channels that are to be used in the programme is the first element of design, but choosing strategies and processes to facilitate communication is also important.  Gilly Salmon’s 5-stage model (2004) is a useful guide to facilitation of communication in online study

Aldridge, S. Rowley, J. (1998). Measuring customer satisfaction in higher education. Quality assurance in education, 6(4), 197.  Retrieved August 18, 2008 from Proquest database.

Arbaugh, J., Benbunan-Fich, R. (2006) An investigation of epistemological and social dimensions of teaching in online learning environments. Academy of management learning & education 5(4), 435-447.

Benbunan-Fich, R., Arbaugh, J. (2005). Separating the effects of knowledge construction and group collaboration in learning outcomes of web-based courses.  Information & Management 43 (2006), 778-793.

Bonk, C., Zhang, K. (2006). Introducing the R2D2 Model: Online learning for the diverse learners of this world. Distance Education. 27( 2), p. 249-264

Bryant, F. (2003). Determining the attributes that contribute to satisfaction among marketing students at the university level: an analysis of the traditional/lecture method versus the internet mode of instruction.  Retrieved August 18, 2008 from Proquest database.

Burd, B., Buchanan, L. (2004). Teaching the teachers: teaching and learning online. Pierian Press, Michigan, USA. A full text of this article is available at http://www.emeraldinsight.com/0090-7324.htm.

Caplan, D., Graham, R. (2008). The development of online courses. In T. Anderson (Eds.), The theory and practice of online learning (2nd ed., p. 245-264). Canada: AU Press, Athabasca University.

Clark, R., & Mayer, R. (2004). E-Learning and the science of instruction: Proven guidelines for consumers and designers of multimedia learning. CA, USA: Pfeiffer.

Connor, C. (2004). Developing self-directed learners. Oregan, USA: Northwest Regional Educational Laboratory. Retrieved on November 11, 2007 from http://www.nwrel.org/planning/reports/self-direct/index.html

Diaz, D. (2002). Online dropout rates revisited. Retrieved September 29, 2007 from http://www.technologysource.org/article/online_drop_rates_revisited/

Drago, W., Wagner, R. (2004). VARK preferred learning styles and online education. J Management Research News, 27(7), 1-13. Barmarick Publications

Eom, S., Wen, J. (2006). The Determinants of Students’ Perceived Learning Outcomes and Satisfaction in University Online Education: An Empirical Investigation. Decision Sciences Journal of Innovative Education, 4(12).

Ertmer, P., Stepich, D. (2004). Examining the relationship between higher-order learning and students’ perceived sense of community in an online learning environment. Retreived August 15, 2008 from http://ausweb.scu.edu.au/aw04/papers/refereed/ertmer/paper.html.

Fleming, N. (2006). VARK – a guide to learning styles. Retrieved August 5, 2008 from http://www.vark-learn.com/english/index.asp

Halsne, A., Gatta, L. (2002). Online Versus Traditionally-delivered Instruction: A Descriptive Study of Learner Characteristics in a Community College Setting. Online Journal of Distance Learning Administration, V(I), Retrieved February 25, 2007 from http://www.westga.edu/~distance/ojdla/spring51/halsne51.html.

James, R. (2001). Students’ changing expectations of higher education and the consequences of mismatches with the reality. Paper for OECD-IMHE conference Management responses to changing student expectations. QUT, 24 September 2001. Retrieved September 4, 2008 from http://www.cshe.unimelb.edu.au/people/staff_pages/James/James-OECD_IMHE.pdf.

Kanuka, H., Anderson, T. (1998). Online social interchange, discord, and knowledge contruction. J Distance Education 13(1), 57-74.  Retrieved September 3, 2008 from http://www.jofde.ca/index.php/jde/article/view/137/412

Massage Therapy Educational Resources (2008). Retrieved September 3, 2008 from http://www.wikieducator.org/Massage_Therapy_Educational_Resources

McQuillan, D. (2007). Managing technology glitches in online education.  Retrieved August 31, 2008 from https://massageonline.wordpress.com/2007/10/08/managing-technology-glitches-in-online-education/

Meyer, K. (2003). The web’s impact on student learning. Retrieved from http://www.thejournal.com/articles/16350 on March 30, 2007.

Paas, F., Renkl, A., Sweller, J. (2004). Cognitive load theory: instructional implications of the interaction between information structures and cognitive architechture. Instructional science 32, 1-8.  Retrieved August 31, 2008 from http://www.cdli.ca/~bmann/0_ARTICLES/CogLoad_Paas04.pdf

Panko, K. (2007). Chickering & Gamson’s 7 principles. Retreived August 20, 2008 from http://itg.yale.edu/chickering–gamsons-7-principles.html.

Pillay, H., Irving, K., & Tones, M. (2007). Validation of the diagnostic tool for assessing Tertiary students’ readiness for online learning. Higher Education Research & Development, 26:2, 217 – 234

Roskowski, M., Ricci, R. (2005). Measurement of importance in a student satisfaction questionnaire: comparison of the direct and indirect methods for establishing attribute importance. J College student retention 6(3), 251-271.

Rumble, G. (2001). The costs and costing of networked learning.  Assynchronous Learning Networks 5(2).  Retrieved August 15, 2008 from http://sloan-c.org/publications/jaln/v5n2/pdf/v5n2_rumble.pdf.

Salmon, G. (2004). The 5-stage model. Retrieved on 18 November, 2007 from http://www.atimod.com/e-moderating/5stage.shtml

Shea, P., Fredericksen, E., Pickett, A., Pelz, W., & Swan, K. (2001). Measures of learning effectiveness in the SUNY learning network. In J. Bourne, & J. Moore (Eds.), Online Education – Volume 2 – Learning Effectiveness, Faculty Satisfaction and Cost Effectiveness – Proceedings of the 2000 Summer Workshop on Asynchronous Learning Networks. Massachusetts, USA: Sloan Centre for Online Education.

Smith, G., & Ferguson, D. (2005). Student attrition in mathematics e-learning. Australasian Journal of Educational Technology, 21:3, 323-334. Retrieved on September 29, 2007 from http://www.ascilite.org.au/ajet/ajet21/smith.html.

Summers, L. (2007) Multiple Learning Styles in Web-based Courses. Retrieved March 3 2007 from http://www.webct.com/OTL/ViewContent?contentID=2334144.

Tang, M., Byrne, R. (2007). Regular versus online versus blended: a qualitative description of the advantages of electronic modes and a quantitative evaluation.  International journal on e-learning 6(2), 257-266.

Tricker, T. (2008). Student expectations – how do we measure up? Retrieved September 4, 2008 from http://www.inter-disciplinary.net/tricker%20paper.pdf.

Williams, W., Ceci, S. (1997). How’m I doing? Problems with student ratings of instructors and courses.  Change 29(5); Retrieved August 15, 2008 from ProQuest database.

The majority of massage students at Otago Polytechnic are assessed as being kinaesthetic learners on the VARK learning styles questionnaire (Fleming, 2006). Many sources consider the online learning environment ill-suited to kinaesthetic learners.

Visual and reader-writer learners seem to be more attracted to the online environment compared to aural and kinaesthetic learners (Halsne & Gatta, 2002; Drago & Wagner, 2004).

However once the students are enrolled, there are inconsistencies in the literature. Eom & Wen (2006) find that students with kinaesthetic and aural learning preferences experience less satisfaction and perceive that they had worse outcomes in online courses relative to reader/writers and visual. Drago & Wagner (2004) however find that there are no significant differences between kinaesthetic learners and the rest of the population for similar measures.

Meyer (2002) asserts that visual learners are more successful online than aural or kinaesthetic learners,
however Neuhauer (2002) finds no relationship between learning preferences and success.

What are we to make of these inconsistencies? Perhaps the differences are a result of course design.

Some online activities are likely to appeal to kinaesthetic learners more than others (Bonk & Zhang, 2006). Practical application is said to be key in the kinaesthetic learner’s educational process (Bonk & Zhang, 2006; Burd & Buchanan, 2004). Two approaches which may be of benefit to kinaesthetic students are the use of case-based learning, and alternating chunks of theoretical learning with exercises which require the students to practically apply their learning. Interactive graphical environments such as drag-and-drop interfaces, virtual reality environments, simulations and gaming interfaces are also likely to appeal to kinaesthetic learners (Summers, 2007), although the development costs involved in these types of learning environments are significantly higher than more traditional text-based instruction (Rumble, 2001).

A review of the literature relevant to student satisfaction and achievement in online education has identified five areas which are important to consider.

  • Instructional pedagogy
  • Quality of instruction
  • Interaction and communication
  • The online learning environment
  • Individual learner qualities.

The dominant educational philosophy associated with online education is social constructivism (Kanuka, Anderson, 1998), however it is not clear if this is the optimal pedagogical model for online or blended delivery.  In a study of MBA programmes, Benbunan-Fich and Arbaugh found that if the educational process involved either group collaboration or knowledge construction, learning outcomes were improved (2005).  When constructivism and knowledge transmission (objectivism) were considered independently of other factors students who were involved in constructivist learning perceived that their learning was less than those who are taught with an objectivist method when in fact their actual learning was greater (Benbunan-Fich & Arbaugh, 2005).  When collaborative approaches were combined with individual learning approaches, the students learning was greatest when collaborative approaches were used, which was consistent with their perceptions (Benbunan-Fich & Arbaugh, 2005). However the same authors found that the gains made with constructivist learning and collaborative learning were not additive.  There was no significant difference in achievement between courses which used either constructivist approaches, collaborative approaches or a combination of the two.  Given that student’s perceived learning was maximised when knowledge transmission & group-oriented approaches were combined (Arbaugh & Benbunan-Fich, 2006), and that this combination of pedagogical themes was one of the combinations that optimised student achievement, these research findings suggest that the combination of knowledge transmission and collaborative learning is the logical pedagogical model to use in the design of online courses.

Factors which have been found to be significant relating to the quality of instruction are clear expectations of coursework requirements (Comm and Schmidt, 1988 as cited in Bryant, 2003) and how to proceed through the course (Shea et al., 2001), as well as receiving prompt, high quality feedback from the instructor (Shea et al., 2001).

Many authors have described the importance of  social contact and social processes in online learning (Laurillard, 1997 as cited in Caplan & Graham, 2008; Shea et al., 2001; Pillay et al., 2007).   According to Pillay, Irving and Tomes “social interaction within the [online learning environment] supports and motivates students to complete their work and seek out new learning experiences” (2007, p. 218).  Other authors have identified the level of interaction with classmates (Shea et al, 2001; Benbunan-Fich & Arbaugh, 2005) & and the instructor (Bryant, 2003) as key factors contributing to student satisfaction.  A high level of interaction has also been found to contribute to student achievement (Pillay, Irving, Tomes, 2007; Benbunan-Fich, Arbaugh, 2007).  Conversely dissatisfaction with the level of interaction with the learning community and/or the instructors has been found to contribute to poor outcomes for students (Pillay et al., 2007). Providing detailed feedback as close as possible to the performance of the assessed behaviour contributes to good outcomes for students (Shepard, 2000 as cited in Caplan & Graham, 2008).  This evidence provides strong support for the use of formative online tests that provide feedback on performance immediately following the test (Prensky, 2001 as cited in Caplan & Graham, 2008).  However this will generally not be all that is needed, as this type of testing is generally only able to provide feedback on the memorisation of individual units of knowledge rather than the complex integration of concepts which is important for higher level learning.  Regular, timely feedback from the learning facilitator will also therefore be necessary.

The nature of the online learning environment appears to be a significant factor in student satisfaction, learning and achievement.  Researchers within the SUNY learning network found that having a simplified online interface contributed to student satisfaction (Shea et al., 2001).  According to the principles of cognitive load theory this should reduce cognitive load, and result in improved learning (Paas, Renkl, Sweller, 2003). Cognitive load theory provides a useful, well researched model for the design of online learning experiences (Paas, Renkl,  Sweller, 2004; Clark & Mayer, 2004). An online learning environment can be designed in accordance with cognitive learning processes (Clark & Mayer, 2004), and the degree to which design is tied into cognitive learning processes is predictive of student achievement (Pillay et al., 2007; Clark & Mayer, 2004).  Dysfunctional learning activities have been found to contribute significantly to dissatisfaction (Pillay, Irving, Tomes, 2007) and poor educational outcomes for students (Pillay et al., 2007; Clark & Mayer, 2004).  Online learning activities may be dysfunctional due to poor design, a lack of testing, or technology failures.  Instructional design and testing is more important in an asynchronous learning environment when compared to a classroom because of the lack of feedback.  In a classroom environment you are often able to dynamically mould the classroom experience based on your perceptions of how the learning activities are working (or not working) with your group of students.  In an asynchronous learning environment the activities that you have designed are more static.  This is yet more support for the inclusion of technologies which facilitate communication and feedback.  Technology failures are also a significant contributor to dysfunctional learning experiences.  Strategies for managing this type of technology risk include having a plan A and a plan B, having a back-up communication channel (including VOIP, audioconferencing, email-group, a point of contact such as a facilitator’s cell-phone, facilitator having everyone’s phone numbers), ensuring that the learning facilitator is able to contact the server administrators in the case of server failure (McQuillan, 2007).  If a real-time educational experience such as web-conferencing is planned, having two or more facilitators may be advisable so that one person is free to concentrate on resolution of any technology problems while another facilitator can concentrate on facilitating the educational experience (McQuillan, 2007).  Students can have their own technical computer difficulties which can act as a barrier to their learning (Shea et al., 2001).  Pillay et al. found that students who had a course with a flexible rate of learning achieved more highly than those in courses which were relatively more static (2007).

Qualities of the individual learner have also been found to be related to student achievement.  According to Clark and Mayer (2004) online students need to have metacognitive skills.  These are the ability to set learning goals, to determine how to reach their goals, and to make adjustments where necessary. Students with poor metacognitive skills need more direction whereas students with good metacognitive skills tend to be more self-sufficient learners. This skill-set has been described elsewhere (Connor, 2004) as the qualities of a “self-directed learner”. While computer literacy prior to taking part in an online course has been found by some authors to be uncorrelated with satisfaction and learning (Shea et al., 2001), this presumably depends on a combination of the level of technical ability required to negotiate the online learning environment, the computer support which is available to students, and individual students self-efficacy with respect to computers.  Pillay, Irving and Tomes found that students with a low level of computer self-efficacy were more inclined to feel anxiety when required to use computer applications.  This anxiety leads users to interpret events more negatively than non-anxious users and therefore contributes to dissatisfaction (2007).  The same authors found that computer self-efficacy is enhanced by the development of computer skills suggesting that educators involved in online study should consider the incorporation of computer literacy training within or associated with their programmes.  Other researchers have found the level of satisfaction with the level of computer support to be predictive of satisfaction with online learning as a whole (Shea et al, 2001).  Pillay et al, found that  computer literacy and computer self-efficacy were positively correlated with educational outcomes for students (2007).  While computer skill is not necessary for participants in online courses, computer self-efficacy  and computer supports are.

To be effective in this aim of improving student satisfaction and achievement, it is important to have an understanding of the key factors which are thought to be associated with these outcomes.

Whether a consumer is satisfied or dissatisfied with a service is related to a comparison of the expectations of what the clients feel the service provide should offer to their perceptions of what the service provider actually offers (Aldridge, Rowley, 1998). In the case of education if the student perceives that the educational experiences provided meet their expectations they will be satisfied. If the benefits of the service that are perceived by the student do not meet their expectations then they will be dissatisfied. In our aim to improve student satisfaction, it would seem important to consider the expectations of our students.

In recent years students (and parents) expectations of what they can expect from their studies has increased markedly (James, 2001; Tricker, 2008). Contemporary student expectations can be considered in three major categories – quality instruction, interaction and communication and the learning environment.

Expectations relating to the quality of instruction include an expectation that course content is aligned with real-world employment prospects (Tricker, 2008), that instructors are qualified at an appropriate level (Tricker, 2008), that adequate learning supports exist (Tricker, 2008), and that information provided to the students is accurate and clear. In particular students expect quality information relating to learning goals, courses, assessment procedures, complaint procedures, and transparency of assessment and grading practices (Ramsden, 1992 as cited in James, 2001; McInnis, 2001 as cited in James, 2001; Tricker, 2008).

With respect to interaction and communication, students expect honest, respectful two-way communication between them and the educational provider which includes consultation about the learning experience and demonstrates concern for their progress (Tricker, 2008; Ramsden, 1992 as cited in James, 2001).

The expectations of students with respect to the learning environment concern flexibility and choice in the range of subjects available, delivery modes and time spent on-campus, as well as access to cutting edge technology (McInnis, 2001 as cited in James, 2001; Tricker, 2008).

In a survey of academic staff in Australian universities the staff surveyed stated that they found that students expected to play a more passive role in their learning than in previous years (James & McInnis 2001 as cited in James, 2001).

Many of these expectations are aligned with best practice principles of higher education (Caplan & Graham, 2008), however the last finding is concerning. It’s also worth considering that while the above expectations are the average, individual students expectations of higher education are bound to vary.

There is some evidence to suggest that students typically have a very low level of understanding of what study in a particular area entails (James, Baldwin, McInnis 1999) as cited in James, 2001). This ignorance of subject material and course requirements is likely to lead to a gap between the student’s expectations and experience, and is a likely cause of dissatisfaction.

Given the fact that an educational experience is unlikely to exactly match the expectations of a new student, and that this is likely to lead to dissatisfaction in some areas, it has been suggested that educational institutions should take an active approach to managing and moulding student expectations (Tricker, 2008). There is evidence to suggest that an ongoing two-way dialogue between the provider and the consumer of the educational experience can act to shape student expectations to become more realistic (James, 2001).

While it is worthwhile knowing what the overall expectations of the student body are with respect to their educational experience, this set of expectations does not necessarily describe expectations for all student groups. The expectations of legal students are likely to be different from the expectations of students of massage therapy or mechanical engineering. Likewise the expectations of student cohorts are likely to change from year to year. For this reason, it may be advisable to measure the expectations of students from year to year, and across disciplines. The Template and the Quality Evaluation Student Template are instruments that have been found to measure expectations with a high level of accuracy, and the information provided from the use of these instruments has been found to be extremely useful in the management of student expectations and experience (Tricker, 2008).

>> PART TWO >>

I’ve just been reading through a fascinating analysis of student expectations of higher education.

James, R. (2001).  Students’ changing expectations of higher education and the
consequences of mismatches with the reality

Here’s a wee snippet

Broadly, the findings of the CSHE research suggest many applicants are not in a good position to judge the appropriateness of programs for them or to assess the features of courses overall. Many prospective students base their planning on quite limited, subjective information. We found that many prospective students do not rigorously seek information and their information-seeking skills are often modest. As a consequence, university applicants’ draw on chance encounters and questionable sources when shaping their thoughts about suitable courses. Many prospective students seem to work on a superficial set of ideas about curricula being more or less ‘applied’, ‘analytical’, ‘practical’ or ‘hands on’. In most cases, they accept on faithwhat they are told and are highly susceptible to the serendipity of word-of-mouth testimony.”  (James, Baldwin,McInnis 1999 as cited in James, 2001)

I find this interesting because it implies that some of the best marketing we could do would involve getting out there and educating the public as to what our profession does, and what the process of studying towards our relevant qualification involves.

But this is by no means the only material of interest in the article.  It’s worth a read.

In a search of research databases, the researcher was unable to find any research articles which dealt with massage therapy education and blended delivery. This study aims to produce the first results in this area.

Student satisfaction and achievement in an online learning context

It has been reported from many sources (Diaz, 2002; Smith & Ferguson, 2005) that the rate of attrition in online courses is greater than that of traditional face-to-face courses. Pillay, Irving and Tones (2007) found that students are often less satisfied by online learning environments than classroom environments. Interestingly, a study done with students in the State University of New York (SUNY) learning network found that the completion rates of their online courses were not significantly different from their face-to-face classes, and that their online students were at least as satisfied as their F2F students (Shea et al., 2001). Student satisfaction seems to be correlated with course completion rates.

If the factors which predict satisfaction and achievement, and also attrition and non-achievement can be identified, the needs of online learners should be able to be more easily accommodated.

The SUNY learning network study identified a very strong correlation between student satisfaction and student perception of their learning (Shea et al., 2001), and other studies have shown the same relationship (Williams & Ceci, 1997). Perceived learning is not however the same as actual learning. Several studies have shown perceived learning and actual learning to be relatively uncorrelated (Ertmer & Stepich, 2004; Williams & Ceci, 1997; Benbunan-Fich & Arbaugh, 2005).

Some may question whether student perception of learning is an important thing to consider given the apparent gap between perceived and actual learning. However in this time of low educational margins, student attrition is a matter of strategic importance for any programme (especially in vocational learning where the number of students in each cohort may be as low as 15-20). It is less expensive to keep an existing customer than to recruit a new customer (Babin & Griffin, 1998; Oliver, 1993 as cited in Roskowski & Ricci, 2005). It is therefore advisable for an educational institution to focus on improving both student satisfaction, and student achievement.

Much of the research relevant to the research query considered here compares online learning with learning in a traditional face-to-face context. How does this relate to learning within a blended delivery context? Tang & Byrne (2007) found that students involved in blended delivery programmes were more satisfied by them than either purely online or purely face-to-face programmes. Interestingly, they also found that there were no significant differences in actual learning between the three delivery methods. This finding is supported by multiple studies comparing online and classroom-based learning (Bryant, 2003).

References

Research Aims

The research project has a number of related aims.

1. To review on an ongoing basis the experience (satisfaction vs. dissatisfaction) and achievement of students in the blended programme

2. To implement changes to improve student experience and achievement.

3.Is blended learning effective in massage education?

Background

 

In recent years an increasing number of educational institutions have begun to offer their courses by online or blended delivery. Massage educators have been slow to adopt these contemporary approaches to learning, but there are now a number of educational institutions offering massage therapy education either purely online or with a blended style of delivery (Remedial massage, 2008; How can you, 2008). Within New Zealand a number of educational institutions are considering the exploration of educational options within this area (J. Morgan, personal communication June 14, 2008; B. Bernie, personal communication June 14, 2008; H. Lofthouse, personal communication June 29, 2008; T. Rodgers, personal communication June 14, 2008). Many massage education providers consider online and/or blended delivery education for massage therapy to be inferior to traditional class-room-based delivery models (P. Charlton, personal communication June 14, 2008; T. Rodgers, personal communication June 14,2008; A. Palmer, personal communication June 14, 2008).

The online environment is rapidly changing, and a course which aims to utilise the richness of contemporary online applications may often be involved in the use of a technology in a way which has not been documented previously. An experimental educational delivery style is therefore called for, where the teachers involved in online education trial the use of an online application with a group of students in a particular way, then assess how effective this educational experience has been. The integrated group of technologies which are used to deliver the course is described here as the online learning environment.

The Otago Polytechnic massage therapy programme has recently undergone the transition from a purely face-to-face delivery style to a blended delivery style. The programme’s delivery style is making use of contemporary online applications such as wikis, blogs, collaborative document editing, voice-over-internet-protocols (such as MSN messenger and skype). This is new ground for massage therapy education, and in many ways for education in general. The department feels that there is a need to monitor the student’s experience and achievement in this new context and to make changes to improve that experience over time.

Literature review