Technology for Learning Engagement

one of the greatest challenges of a blended learning approach is to generate student engagement outside traditional face-to-face classes: there is a tendency for students to attend classes, but see the online components as optional (University of North Texas, 2005).

 Media richness theory is one of the oldest lines of investigation into media preferences. This theory assumes that people behave rationally and will select different media for different communication tasks based upon the characteristics of the media(FN1,2,3,4). According to the theory, rich-media is best for equivocal communication. That is, an ambiguous exchange of subjective or potentially conflicting viewpoints(FN2). In this usage, rich-media is generally defined as multi-channel, synchronous communication with wide language variety and high personal focus. Lean-media, which is normally asynchronous and single-channel, is best for situations where the communicator is seeking to transfer known facts to another or to request facts for specific questions(FN2).

 Research by Rao(FN10) modifies media richness theory somewhat and concludes that tasks with a high socio-emotional component are sensitive to media differences while those that are emotionally neutral and task oriented are not sensitive to media differences.

 Recent research by Miller and Roche(FN11) examined the question of media preference using a very pragmatic approach that effectively splits the difference between media richness theory and the socio-emotional work by Rao. Two important assumptions were made by this research. First, there will always be multiple media choices and the set of available choices is dynamic. Consequently, it is possible that communicators will switch media toots over time based upon personal preference. Second, a medium is only viable if it is concurrently available to all communicators. So, availability trumps suitability and personal preference. This research surveyed a large population to determine the common factors that influence medium choice. The results identified and assigned importance ratings to nine key factors that affect users' preference for communication tools. The analysis of these factors indicate that a combination of media characteristics, media availability, and user convenience influence medium selection. While this confirms Rao's assertions to a certain extent, it also reemphasizes the role that media characteristics play in medium selection and introduces the notion that multiple factors influence media selection.

Methods    We used the free open-source virtual learning environment Moodle. The open source ethos, where all users may contribute and improve the product in response to need and experience, is compatible with knowledge-sharing principles of academia.

Twelve research questions were developed for this study. The questions, converted to a form suitable for a survey instrument, are shown below.    Q1: For casual communication with peers. I prefer to communicate___.    Q2: For casual communication with my instructors, I prefer to communicate___.    Q3: For formal communication with peers, I prefer to communicate___.    Q4: For formal communication with my instructors. I prefer to communicate___.    Q5: For time sensitive communication with peers. I prefer to communicate___.    Q6: For time sensitive communication with my instructors. I prefer to communicate___.    Q7: For the communication of short messages with peers. I prefer to communicate___.    Q8: For the communication of short messages with instructors. I prefer to communicate___.    Q9: For communication of a complex topic with peers. I prefer to communicate___.    Q10: For communication of a complex topic with my instructors. I prefer to communicate___.    Q11: For personal communication with peers. I prefer to communicate___.    Q12: For personal communication with my instructors. I prefer to communicate___.    For all questions, the available answers were:in by by by by text by by mail No person telephone instant voicemail message Email (U.S. preference message postal service)

 We used four kinds of data to evaluate website usage and effectiveness:

i) A printed questionnaire, with questions requiring either scored response or written comments, was given to students after they had finished their end-of-term exam, a strategy that ensures a >95% response rate. Many of the questions were identical in 2004 and 2005 to allow direct comparison before and after the introduction of the virtual learning environment (VLE).ii) To test whether students who received regular reminders about eLearning exercises in face-to-face classes were more likely to undertake online tasks, the tutors of half of the tutorial groups actively encouraged web access and checked if students had completed the SAQs. Formal assessment scores and website access rates were compared using an unpaired t-test (experimental group N= 45, control group N=48).iii) We monitored VLE usage through detailed website access logs which recorded student name, time and date of access, and pages viewed.iv) We tested for a correlation between individual participation in eLearning activities and performance in the formal assessment items for the course, using general linear models to examine the relationship between access rates, SAQ completion rates, SAQ scores, scores in multiple choice tests, and overall score for the course.

The intent of these questions was to determine 1) do students have a preferred medium for communicating with the instructor, 2) do students have a preferred medium to interact with other students, 3) does context impact media choice, and 4) are the preferences the same for student to instructor versus student to peer communication.

 A survey instrument was developed to include the twelve questions along with four questions to capture non-identifying student characteristics (i.e., gender, major, freshman through senior classification, and comfort with technology). The questionnaire was administered to students currently attending classes in a state supported college of business administration.

the student population is best described as 'traditional,' in that they are typically eighteen to twenty-four years old and are working toward their first degree. All students in the business program have at least rudimentary Internet and computer skills. In addition, instructors are required to hold regular office hours and all students and instructors have active email accounts, so both the 'in-person' and the primary technology-based communication channels are guaranteed to exist for all participants.

We demonstrated a strong increase in web access rates between 2004, when online material was presented in a non-interactive, text-based format, and 2005, when the online material was an interactive VLE

The percentage of students who used the website every week (the target rate) tripled to nearly 30%. Increase in website access did not simply reflect the fact that some information was now disseminated exclusively online: all parts of the VLE were accessed by at least 20% of the class, with up to 70% of students viewing information that was also available in the printed handbook. Similarly, the increase in access was not due to a change in the information available: the text of the online lecture support was similar in both 2004 and 2005, only the mode of presentation changed. We also showed that, although students frequently requested downloadable lecture slides, these 'non-blended' lecture support files had much lower access rates than the 'interactive' lecture support. On average, over two thirds of the class completed the interactive online lessons, but less than a third of the class downloaded the Powerpoint slides

 Table 1 indicates that students do indeed have distinct preferences for communication media. Further, the choice of media appears to differ based upon who the communication is with and the context within which the communication takes place.

 The results in table 1 indicate that students strongly prefer the rich-media, synchronous communication provided by face-to-face interaction in situations where communication with a high socio-emotional component takes place--namely, in the contexts where the message is complex, formal, or personal. This is true for no less than 72% of the respondents.

Student perceptions of the usefulness of the website material increased when the online material was presented as a VLE: the percentage of students giving the website the target score for usefulness increased from 16% to 26%. So the same information was given a higher score for usefulness when presented in an interactive format that promoted regular access to course materials. There was no negative feedback about the lack of a textbook or poor preparation for formal assessments in 2005, as there had been in 2004 when the online material was accessed at a much lower rate. These observations show that by successfully embedding the VLE into the structure of the course, students were actively encouraged to study in their own time, and this contributed positively to their ability to complete the course.

Casual conversation, by its nature, would tend to have a high socio-emotional component, and yet, the student preference for casual conversation with the instructor is almost evenly split between 'in-person' (49.6%) and 'email' (43.6%). These two communication media are on opposite ends of the rich-media to lean-media continuum. This pattern is absent in Q1 ('casual with peers') where 53.0% prefer 'in-person' communication while only 15.8% selected 'email'. Clearly, medium choice is not determined strictly by the socio-emotional content of the message.

A second noteworthy result concerns alignment with media richness theory, The analysis of some responses directly adhere to the notion that students are rational and will select a media based upon its ability to best carry the message in a particular context.

 A third interesting finding is evidenced by the differences in the results between some of the paired context questions. For example, Q1 and Q2 ask the same question about casual conversation with peers and with the instructor. The same is true for Q3 and Q4, Q5 and Q6, etc. If medium selection were based solely on the characteristics of the media or the socio-emotional content of the message, one would expect the percentage results between these paired questions to be roughly equal. They are not in several cases. For example, in Q1 and Q2, 16.2% of the respondents prefer the telephone for casual conversation with peers while only 1.2% would select this medium to communicate with the instructor. In the same question pair, 15.8% of students prefer to use email for casual peer communication while 43.6% use email for the same type of communication with the instructor.

Face-to-face encouragement to undertake web-based activities did not increase web usage: the experimental and control groups did not differ significantly in their web access rates (t=0.002, p=0.98) nor in the number of SAQs completed (t=-0.481, p=0.632). However, web access rates for online lessons and SAQs tended to peak on the days of subsequent lectures, throughout the three weeks that they were available online. This suggests that attending face-to-face classes stimulates online access. Data from web logs suggest that it was not necessary to use a limited shelf-life to encourage prompt access, because the majority of the class accessed online material in the week following the lecture, with little evidence of a peak in access just before the lessons were taken offline.

 There was no apparent correlation between number of web-pages accessed and student performance in the course (slope=0.136, p=0.62, d.f. = 89). However, there was a significant positive correlation between participation in online self-assessment activities and performance in formal assessment tasks.

There are two possible explanations of this result: undertaking the SAQs improved student performance on tests, or good students who perform well in tests are also those who seize the opportunity for self-assessment. Either way, it corroborates the widespread support amongst the student body for SAQs as an effective study tool. Furthermore, performance in SAQs was linked to performance in formal assessments. Figure 3b shows that, of the students that completed one or more SAQs, the percentage of correct SAQs was significantly positively associated with the average score on the multiple-choice tests (slope = 0.569, p=0.001, df=76). Students can therefore regard the SAQs as an accurate indicator of their future performance in formal assessment.

Although all online lessons were non-compulsory, an average of two-thirds of the dass completed each online lesson, the majority doing so within a week of the relevant lecture. Students made use of different media for accessing information about the course, using the web pages even when the information was available in printed format. The SAQs were the most successful part of the website, demonstrating that students will embrace the opportunity for regular self-assessment. Over half the class reported that they did the SAQs "often" or "every week", and SAQ completion rates were linked to performance in formal assessment. Online multiple-choice questions provided students with continuous feedback on comprehension and performance, a service that could not easily be replicated in a non-electronic medium.

Students were noticeably more self-sufficient when the course support material was presented as an interactive VLE, and staff found they had to spend much less time fielding questions about assessment items. Unlike the previous year, when the same supporting information was available but was used less often by students, there were no negative comments about the lack of a core text, or poor preparation for formal assessments.

Of the eight questions with significant results, the two factors that exert the most influence on media choice are student comfort with technology and gender. One or both of these factors show up in seven of the eight significant question scenarios. This indicates that the combination of student gender and technology comfort play a major role in determining media choice. Generally speaking, the results show that students who feel more technically competent are less likely to select the 'in-person' medium. At the same time, males tend to prefer 'in-person' communication over females within the same context.

A second notable result of the analysis presented by Table 2 is that student interaction with the instructor tends to be more influenced by gender and comfort with technology than the same interaction with peers. Four of the six instructor related scenario questions indicate significant influence by both the comfort and gender independent variables. A fifth instructor scenario (Q10) is influenced by gender along with the 'emphasis major' factor. This consistency implies that the influence technology comfort and gender exert is magnified in almost all contexts when the communication is with the instructor. This is particularly true concerning student gender. Male students are consistently more likely to select the 'in-person' medium over female students regardless of context when the communication is with the instructor.

The implications of these results are that factors other than the characteristics of the medium and the content of the message significantly influence media choice in student-to-peer versus student-to-instructor communication. Evidently, the interaction is more complicated than cither traditional media richness or socio-emotional theory predict.

Statistical analysis of the data from the survey indicate that students strongly prefer communicating 'in-person' for complex, formal, and personal messages with both instructors and peers. In addition, there is a distinct preference away from face-to-face communication when the message is short or time sensitive. Further analysis show that students tend to select media "rationally" (i.e., in line with the major theories) for communication with peers. Specifically, they appear to take the characteristics and availability of the medium, their personal comfort with technology, and the context of the message into consideration. The same cannot be said for communication with the instructor. The data indicate that students are significantly influenced by their gender and their personal comfort with technology. Males tend to prefer face-to-face interaction with the instructor more so than females. In addition, the more comfortable the student is with technology, the less likely they are to prefer 'in-person' communication. These results help explain some of the seemingly irrational media preferences concerning communicating with the instructor.

hen group projects are used, the groups could be formulated based upon the ability to meet in person and overall comfort with technology, rather than randomly.

Engagement theory is based upon the idea of creating successful collaborative teams that work on ambitious projects that are meaningful to someone outside the classroom. These three components, summarized by Relate-Create-Donate, imply that learning activities: occur in a group context (i.e., collaborative teams) are project-based have an outside (authentic) focus (Kearsley & Schneiderman, 1999).

Engagement theory is based upon the idea of creating successful collaborative teams that work on ambitious projects that are meaningful to someone outside the classroom. These three components, summarized by Relate-Create-Donate, imply that learning activities: occur in a group context (i.e., collaborative teams) are project-based have an outside (authentic) focus (Kearsley & Schneiderman, 1999).