Anne Wade (M.L.I.S.) is Manager and Information Specialist at the CSLP. Her expertise is in information literacy, information storage and retrieval, and research strategies. She has been a lecturer in the Information Studies Program in the Department of Education, Concordia University for over a decade; is Convenor of Campbell’s Information Retrieval Methods Group; a member of Campbell’s Education Coordinating Group and an Associate of the Evidence Network, UK. Wade has worked and taught extensively in the field of information sciences for twenty years.

This study investigated the change in the relationship between pedagogy, computer-use and students' perceptions about course-effectiveness over time. Students from a Canadian university completed a questionnaire in two different years (2003 = 1,834 participants and 2007 = 1,866 participants). Of greatest interest were characteristics of technology that interact with pedagogy to achieve positive learning outcomes. A factor analysis revealed a three-factor solution: "course-structure," "active-learning," and "computer-use." Multiple regression analysis showed that the three variables are predictive of perceived course effectiveness, with "course-structure" being most predictive in both years. "Computer-use" was least predictive with the 2003 sample while it was second in predictive power with the 2007 sample, most likely reflecting increased technology integration in post-secondary education. When comparing use of various applications in "Arts" versus "Science" courses, results indicated higher computer technology use in 2007 for all applications with arts courses while only web-based computer applications increased in use with the science courses. Separate regression analyses were conducted for each type of program while comparing the two different study years with results indicating that "course-structure" is the most stable predictor. Findings reveal that while pedagogy seems to be of highest importance to students, the relationship between computer use and perceived course effectiveness is changing over time. Implications are discussed and suggestions for future research are presented.

This systematic review builds upon the work of Authors (2006) and McGreal and Anderson (2007). It seeks to provide a synthesis and discussion of publicly available government policy documents with regard to e-learning in Canada. There is general consensus, both in public opinion and in the research literature, that the educational practices associated with rapidly advancing computer information technologies are gaining popularity and are expected to be increasingly effective in enhancing learning. The purpose of this review is to uncover and describe areas of commonality and inconsistency in e-learning policy documents dated from 2000 to 2010, and to determine where discussions about e-learning are lacking. In total, 138 policy documents from Canadian provinces and territories and several federal agencies were retrieved and analyzed using prescriptive and emergent coding approaches. The review confirmed that Canadian policy makers view technology as offering potential benefits to learners, but also revealed a troubling lack of specific details, consistency and coordination in facilitating the development of e-learning to fulfill these optimistic expectations.

Wikis are part of what is known as Web 2.0, or the read-write web, describing technology that have the potential to provide learners with tools that promote knowledge building through collaboration, social negotiation, and the reviewing and revising of ideas. When building a wiki, learners engage in a process of forethought, performance, and reflection, requiring that they be cognitively active with the learning material and carefully evaluate the accuracy of their understanding. This study examined the effects of contributing to a wiki combined with varying levels of pedagogical support using a 2 x 2 factorial design: Wiki (no-wiki / wiki) x Pedagogical Support (low / high). The sample consisted of 98 students in 4 sections of an introductory macroeconomics course at a large urban technical college in western Canada. While there is still much to understand regarding the impact of using wikis to support and foster meaningful learning the results of this study produced several important findings and practical implications. The results found that while there was no significant difference between wiki-users and the control group for achievement and overall perceived course effectiveness, there were advantages ascribed to the wiki groups. With respect to motivation, the results found that wiki-users coupled with higher levels of pedagogical support rated intrinsic goal orientation, task value, and self-efficacy significantly higher than the control group. When comparing the two wiki conditions it was found that learners in the wiki high pedagogical support condition rated task value significantly higher than those in the wiki low pedagogical support condition though with small effect sizes. Finally, preliminary descriptive data yielded profound differences between the two wiki groups with regard to their primary intention: collaboration. High levels of support appeared to stifle dialogue. Differences in how learners approached the task of building the wiki under different levels of pedagogical support were observed suggesting that even in a flexible, learner controlled environment, the instructor's suggested structure will have a large impact on how the tool is used. Implications for practice and future research are discussed

Current practices in industries such as aerospace attempt to aggregate information from a wide area as part of their decision making process. However, collecting knowledge that is critical to a project is often daunting and time consuming. This paper describes the conceptualization and early development of a framework consisting of a semantic knowledge engine, archivist tool, and knowledge-mapping tool using a wiki front-end as a means for users to enter knowledge using a familiar web-based interface.

This paper reports the findings of a Stage I meta-analysis exploring the achievement effects of computer-based technology use in higher education classrooms (non-distance education). An extensive literature search revealed more than 6,000 potentially relevant primary empirical studies. Analysis of a representative sample of 231 studies (k = 310) yielded a weighted average effect size of 0.28 surrounded by wide variability. A mixed effects model was adopted to explore coded moderators of effect size. Research design was found to be not significant across true, quasi- and pre-experimental designs, so the designs were combined. The variable “degree of technology use” (i.e., low, medium, and high) was found to be significant, with low and medium use performing significantly higher than high use. For the variable “type of use” (i.e., cognitive support tools, presentational tools, and multiple uses), cognitive support (g+ = 0.40) was greater than presentational and multiple uses.

In this chapter, we describe the process of modeling different theory-, research-, and best-practicebased learning designs into IMS-LD, a standardized modeling language. We reflect on the conceptual and practical difficulties that arise when modeling with IMS-LD, especially the question of granularity and the necessary and sufficient elements of learning design. We propose a four-layer model both to ensure the quality of the modeling process and as a necessary step towards a ‘holistic’ consideration and integration of the design process. These discussions speak to the core of IMS-LD integration, address the question of usability and end-user friendliness, and urge that more research and design needs to be conducted not only to mainstream (a) the use of IMS-LD and related visual instructional design languages, but also (b) the debate on appropriate and best instructional design practices.

This review provides a rough sketch of the evidence, gaps and promising directions in e-learning from 2000 onwards, with a particular focus on Canada. We searched a wide range of sources and document types to ensure that we represented, comprehensively, the arguments surrounding e-learning. Overall, there were 2,042 entries in our database, of which we reviewed 1,146, including all the Canadian primary research and all scholarly reviews of the literature. In total, there were 726 documents included in our review: 235 – general public opinion; 131 – trade/practitioners’ opinion; 88 – policy documents; 120 – reviews; and 152 – primary empirical research. The Argument Catalogue codebook included the following eleven classes of variables: 1) Document Source; 2) Areas/Themes of e-learning; 3) Value/Impact; 4) Type of evidence; 5) Research design; 6) Area of applicability; 7) Pedagogical implementation factors; 8) A-priori attitudes; 9) Types of learners; 10) Context; and 11) Technology Factors. We examined the data from a number of perspectives, including their quality as evidence. In the primary research literature, we examined the kinds of research designs that were used. We found that over half of the studies conducted in Canada are qualitative in nature, while the rest are split in half between surveys and quantitative studies (correlational and experimental). When we looked at the nature of the research designs, we found that 51% are qualitative case studies and 15.8% are experimental or quasi-experimental studies. It seems that studies that can help us understand “what works” in e-learning settings are underrepresented in the Canadian research literature. The documents were coded to provide data on outcomes of e-learning (we also refer to them as “impacts” of e-learning). Outcomes/impacts are the perceived or measured benefits of e-learning, whereas predictors are the conditions or features of e-learning that can potentially affect the outcomes/impacts. The impacts were coded on a positive to negative scale and included: 1) achievement; 2) motivation/satisfaction; 3) interactivity/ communication; 4) meeting social demands; 5) retention/attrition; 6) learning flexibility; and 7) cost. Based on an analysis of the correlations among these impacts, we subsequently collapsed them (all but cost) into a single impact scale ranging from –1 to +1. We found, generally, that the perception of impact or actual measured impact varies across the types of documents. They appear to be lower in general opinion documents, practitioner documents and policy making reports than in scholarly reviews and primary research. While this represents an expression of hope for positive impact, on the one hand, it possibly represents reality, on the other. Where there were sufficient documents to examine and code, impact was high across each of the CCL Theme Areas. Health and Learning was the highest, with a mean of 0.80 and Elementary/Secondary was the lowest, with a mean of 0.77. However, there was no significant difference between these means. The impact of e-learning and technology use was highest in distance education, where its presence is required (Mean = 0.80) and lowest in face-to-face instructional settings (Mean = 0.60) where its presence is not required. Network-based technologies (e.g., Internet, Web-based, CMC) produced a higher impact score (Mean = 0.72) than straight technology integration in educational settings (Mean = 0.66), although this difference was considered negligible. Interestingly, among the Pedagogical Uses of Technology, student applications (i.e., students using technology) and communication applications (both Mean = 0.78) had a higher impact score than instructional or informative uses (Mean = 0.63). This result suggests that the student manipulation of technology in achieving educational goals is preferable to teacher manipulation of technology. In terms of predictor variables (professional training, course design, infrastructure/ logistics, type of learners [general population, special needs, gifted], gender issues and ethnicity/race/religion/aboriginal, location, school setting, context of technology use, type of tool used and pedagogical function of technology) we found the following: professional development was underrepresented compared to issues of course design and infrastructure/ logistics; most attention is devoted to general population students, with little representation of special needs, the gifted students, issues of gender or ethnic/race/religious/aboriginal status; the greatest attention is paid to technology use in distance education and the least attention paid to the newly emerging area of hybrid/blended learning; the most attention is paid to networked technologies such as the Internet, the WWW and CMC and the least paid to virtual reality and simulations. Using technology for instruction and using technology for communication are the two highest categories of pedagogical use. In the final stage, the primary e-learning studies from the Canadian context that could be summarized quantitatively were identified. We examined 152 studies and found a total of 7 that were truly experimental (i.e., random assignment with treatment and control groups) and 10 that were quasi-experimental (i.e., not randomized but possessing a pretest and a posttest). For these studies we extracted 29 effect sizes or standardized mean differences, which were included in the composite measure. The mean effect size was +0.117, a small positive effect. Approximately 54% of the e-learning participants performed at or above the mean of the control participants (50 th percentile), an advantage of 4%. However, the heterogeneity analysis was significant, indicating that the effect sizes were widely dispersed. It is clearly not the case that e-learning is always the superior condition for educational impact. Overall, we know that research in e-learning has not been a Canadian priority; the culture of educational technology research, as distinct from development, has not taken on great import. In addition, there appears to have been a disproportionate emphasis on qualitative research in the Canadian e-learning research culture. We noted that there are gaps in areas of research related to early childhood education and adult education. Finally, we believe that more emphasis must be placed on implementing longitudinal research, whether qualitative or quantitative (preferably a mixture of the two), and that all development efforts be accompanied by strong evaluation components that focus on learning impact. It is a shame to attempt innovation and not be able to tell why it works or doesn’t work. In this sense, the finest laboratories for e-learning research are the institutions in which it is being applied. Implications for K-12 Practitioners When implemented appropriately, technology tools are beneficial to students’ learning, and may facilitate the development of higher order thinking skills. Student manipulation of technology in achieving the goals of education is preferable to teacher manipulation of technology. Teachers need to be aware of differences between instructional design for e-learning as compared to traditional face-to-face situations. Immediate, extensive, and sustained support should be offered to teachers in order to make the best out of e-learning. Implications for Post-Secondary Some educators suggest that e-learning has the potential to transform learning, but there is limited empirical research to assess the benefits. Post-secondary education would benefit from a Pan-Canadian plan to assess the impact of e-learning initiatives. It is important that instructional design match the goals and potential of e-learning. Research is needed to determine the feasibility and effectiveness of such things as learning objects and multimedia applications. Properly implemented computer mediated communication can enrich the learning environment; help reduce low motivation and feelings of isolation in distance learners. E-learning appears to be more effective in distance education, where technology use is required than in face-to-face instructional settings. Implications for Policy Makers Effective and efficient implementation of e-learning technologies represents new, and difficult, challenges to practitioners, researchers, and policymakers. The term e-learning has been used to describe many different applications of technology, which may be implemented in a wide variety of ways (some of which are much more beneficial than others). School administrators must balance the needs of all stakeholders, and the cost-benefit ratios of technology tools, in deciding not only which technologies to use, but also when and how to implement new technologies. Traditional methods of instructional design and school administration must be adjusted to deal with the demands of distance education and other contexts of technology use. Professional education, development, and training for educators must ensure that teachers will be equipped to make optimal pedagogical use of new methods.

The purpose of this research is to investigate the relationship between computer technology's role and students' perceptions about course effectiveness. Students from two universities (one Canadian, n = 1465; one American, n = 831) completed a 71–item questionnaire addressing different aspects of their learning experience in a given course. Factor analysis revealed a 3–factor solution: “course-structure,” “active-learning and time-on-task,” and “computer-use.” Regression analysis indicated that the 3 variables are predictive of perceived course effectiveness at both sites, with the presence of an interaction between location and “computer-use” and “course-structure” on students' perceptions about course effectiveness. Findings reveal that student perceptions directly reflect the 14 APA learner-centered principles on which the instrument was based.

This study investigated the relationship between the amount of computer technology used in post-secondary education courses, students’ perceived effectiveness of technology use, and global course evaluations. Survey data were collected from 922 students in 51 courses at both the graduate and undergraduate levels. The survey consisted of 65 items broken down into seven areas, namely: (1) student characteristics, (2) learning experiences and course evaluations, (3) learning strategies, (4) instructional techniques, (5) computer use in course, (6) perceived effectiveness of computer use and (7) personal computer use. Contrary to expectations, no significant relationship was found between computer use and global course evaluations, nor was there a relationship between perceived effectiveness of computer use and global course evaluations. However, the results did yield a positive relationship between global course evaluations and the learning experiences that students engaged in. Students also indicated that they valued the use of computer technology for learning. Descriptive statistics on questions related to personal computer use show a strong favorable response to computer use and: facilitation of learning, value-added aspects such as usefulness to other classes and/or career, learning material in a more meaningful way, and working in groups with other students.

This study investigated the role that computer technology plays in transforming the learning process in higher education. Specifically, we looked at the relationship between computer-technology use, active learning, and perceived course effectiveness. The sample consisted of 1966 students in 81 graduate and undergraduate classes at a large, urban university. The survey categories were: 1) learner preferences; 2) course structure; 3) active learning; 4) time on task; 5) learning with technology; 6) perceived effectiveness of computer use; 7) context of computer use; and 8) overall perceived course effectiveness. Results suggest that there is a relationship between computer technology, active learning, and perceived course effectiveness. Students who use computer technology a lot appear to benefit the most from active learning.