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  1. 1. THINGS YOU SHOULD KNOW ABOUT… mobile apps for learning What is it? Scenario Tabitha has been studying the influence of changing climate patterns on animal migrations. As part of her senior project, she has been monitoring hummingbirds, which have been seen in increasing numbers locally in past years. Tabitha is observing two sites in her neighborhood where they have been seen and one where they have not. She sets up motion-sensitive cameras at each of the three sites—one at the local botanic garden, a second near a honeysuckle bank in an undeveloped wooded area, and a third near heavy perennial plantings on the back side of the community center. The cameras are set to record video of anything that moves, so she aims them high enough to ensure human traffic will not set them off. Whenever video is recorded, a message with a URL to access the video is sent to her smartphone. She consequently spends her free moments during the day—waiting for class to start or standing in line at lunch—viewing video on the screen of her mobile, trying to decide if there has been hummingbird activity. She also visits the camera locations daily, recording information on temperature and humidity. She uses her smartphone to upload these observations to a database and to compare the day’s weather data with that of previous years. Her first sighting comes five days into the study. She is scanning the video on her way to class when she sees a streak across the screen that she is sure is a hummingbird. Excited, she checks the data from the previous four years and notes her sighting is two days earlier than the average. For her, the most exciting moment of her project comes after hummingbirds have been present for more than a week at two of her sites. A male hummingbird soars right in front of her as she checks temperature readings at the wooded location, her third site. Excited, she pulls out her mobile to check the hummingbird habitat maps. She thinks the bird is a full half-mile northeast of where his species had been spotted previously. Tabitha will need to do further research, but she believes she might have evidence confirming that the migration patterns continue to shift. Mobile learning, or m-learning, can be any educational interaction delivered through mobile technology and accessed at a student’s convenience from any location. The software that underlies m-learning includes not only mobile applications designed specifically for learning purposes, but also those designed for other uses—such as geolocation, data access, readers, and maps—but that can be adapted for educational purposes. M-learning hardware may include mobile phones, handheld PCs, tablets, the iPad, and netbooks, as well as devices such as the iPod touch that are able to run mobile applications. Because m-learning utilizes a variety of devices, many of which are ubiquitous in the lives of students, it can foster student engagement and offer opportunities to make learning integral to daily life. How does it work? The applications used in mobile learning generally focus on brief interactions of perhaps five minutes or less, using simple navigation and graphics to accommodate multiple screen sizes. Such applications enable the quick review of information rather than prolonged or deep learning—as such, they are better suited for activities such as a status check, a request for just-in-time information, or as a student response tool in the classroom. M-learning projects, by contrast, can involve complex tasks that employ multiple applications to track down complex data sets or complete assignments that involve solving multidimensional problems. Some exercises contain collaborative elements or game play, employing a variety of tools like social networking, calendars, customized calculators, simulations, or augmented reality. M-learning endeavors frequently fall into categories like data collection or application of location-based information, such as checking a map to see whether project team members are nearby. These m-learning activities can be used on a growing list of devices, though the prevalence on campus of smartphones with a data plan—which allow users to run applications on the phone’s operating system, browse the web, and send and receive e-mail— makes them attractive options for course projects that are supported with mobile technology. That said, the smartphone category represents a range of devices and software, and new classes of mobile tools are emerging, such as HP’s Slate and Apple’s iPad, that will likely introduce new options and opportunities. Who’s doing it? As an early m-learning adopter, Abilene Christian University has chosen to focus on Apple devices, distributing either an iPhone or iPod touch to each incoming freshman. Instructors can leverage applications from the Apple iTunes store for learning purposes including field activities, while a dedicated portal offers campus © 2010 EDUCAUSE This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License. http://creativecommons.org/licenses/by-nc-nd/3.0/ educause.edu/eli more >>
  2. 2. THINGS YOU SHOULD KNOW ABOUT… Mobile apps for learning news and calendars to keep students engaged in the learning community. Also focusing on the Apple platform, Seton Hill University announced plans to offer an iPad to every full-time student in fall 2010, a technology chosen both for its mobility and the promise of easy future access to e-textbooks. A joint outreach program undertaken by Carnegie Mellon University and the University of California, Berkeley, called Mobile and Immersive Learning for Literacy in Emerging Economies (MILLEE) seeks to support a group of English teachers in rural India with m-learning applications designed for grade-school students. The children access these activities via their mobile phones to work on English skills in the classroom as well as in the fields on days when they help with farm work. Why is it significant? As learning management systems adapt to the mobile platform, m-learning may become a common tool for exploration by tech-savvy faculty. The use of mobile devices seems a natural fit for distributed learning and field activities in that handheld technology can not only accompany the learner almost anywhere but also provide a platform that is rapidly evolving and always connected to data sources. Learning management systems may drive campuses to recognize the potential of this always-on, anyplace technology that lowers the physical boundaries to learning and extends the classroom. Ease of use offered by mobile devices supports lifelong learning, and because the devices themselves are integrated into everyday life, they facilitate authentic learning. Ultimately, it might be the ubiquity of these student-owned devices that ensures their use as teaching and learning tools. The rising popularity of smartphones should promote the development of cloud-based applications that work on multiple devices. While some m-learning applications may be provided by colleges and universities, mobile technology in the main provides an inexpensive layer of functionality to the institution, capitalizing on an infrastructure that is increasingly supported by cloud services and by the technology that students bring to campus. What are the downsides? Hardware for mobile learning represents a wide range of platforms, screen sizes, and functionality, and no clear standards exist for development that address all of the tools available. As a result, colleges and universities can find infrastructure issues tricky to resolve. The cost of smartphones and data plans is out of reach for some students, and adoption and ownership is uneven. While the screen size on many mobile devices enforces simplicity of design, the small screens and keys are difficult for some to use effectively, and the additional strain on battery life imposed by mobile apps can be frustrating. Because m-learning is an emerging market, there remains a dearth of applications designed specifically for learning, and repurposing existing lesson materials for the mobile platform might add to faculty workload. The eclectic mix of devices and mobile formats, which are generally subject to student and faculty choice, could delay m-learning development, and standards may be slow to emerge in an environment where manufacturers are often trying to decide whether to merge their mobile devices with slates, tablets, or e-readers. Finally, while the devices can go anywhere with students, they might not engage students for long periods of time, as mobile learning activities are subject to frequent interruptions. Where is it going? New kinds of devices are emerging, blurring the distinctions between phones, PDAs, e-readers, and other types of hardware. Future mobile technologies will be able to present textbooks, create data visualizations, aid library research, and foster contextual learning. Regardless of the directions taken by mobile manufacturers, newer incarnations of these devices are sure to provide easier access and better support for multimedia creation and collaborative applications. Field learning from art appreciation to zoology may soon find support from mobile devices pulled from a student pocket and used on the spot to check data, snap a photo, record location data, make a blog entry, or enter a question on the class discussion board. This rapid access to data, available wherever and whenever questions arise, could change our learning landscape, altering the way we solve problems. What are the implications for teaching and learning? The cell phone is currently the most common platform for mlearning, lending itself to collaborative and project-based efforts that leverage its potential to support the communication requirements of a team. Where wireless networks are available, or where smartphones with data plans have access to cell networks, mobile lessons and exercises can leverage the ability to gather information from a variety of interdisciplinary sources in a wide array of formats while exploiting the value of location-based learning. In developing countries where mobile devices are available at a fraction of the cost of other computing hardware, m-learning has extended the infrastructure of distance education to outlying areas that have previously been poorly served. Regardless of the hardware employed, as demand requires that more applications be re-authored for mobile formats, institutions may find it necessary to overhaul data-sharing and content-delivery techniques to support the mobile platform. EDUCAUSE is a nonprofit membership association created to support those who lead, manage, and use information technology to benefit higher education. A comprehensive range of resources and activities is available to all EDUCAUSE members. The association’s strategic directions include focus in four areas: Teaching and Learning; Managing the Enterprise; E-Research and E-Scholarship; and the Evolving Role of IT and Leadership. For more information, visit educause.edu. May 2010
  3. 3. BRIEF Framing Mobile Initiatives to Measure Impact October 2012 Veronica Diaz, PhD, Associate Director, EDUCAUSE Learning Initiative »» A well-developed framework and effective measurement strategy are important considerations, whether you are embarking on a mobile learning project for the first time or are in your third or fourth phase of the project. »» It is not uncommon for institutions to begin their mobility work in learning and teach- ing support (for example, providing mobile access to course schedules), sometimes outside an instructional context. Doing so builds tolerance and understanding of mobile applications with students, a tolerance that can be leveraged for learning in the classroom »» While today’s studies may explore integration with existing technologies and basic use, tomorrow’s studies may look at applications tailored to learner environments and needs. Introduction There is no shortage of data illustrating the proliferation of mobile devices and mobile activity in the general population. This diffusion of devices, applications, and activity extends to the teaching and learning community, right down to the classroom level (see Figure 1). Yet, mobile technologies, and even more so, mobile pedagogies are still considered very much an emerging area in higher education. It is critical that some sort of measurement strategy accompany our experimental and pilot programs. But measuring the ability of mobile teaching and learning initiatives to support such amorphous things as student learning, student engagement, and additional time on task can prove to be very challenging. In this brief, I propose a set of frameworks, drawn from the literature, to begin identifying and deconstructing the components we might measure in our mobile learning initiatives. It is important to distinguish between the components we choose to measure and the way in which we measure them. Here, the focus is on the desired mobile learning experience itself, on which we’ll want to be able to report after our work has concluded. For instance, we may engage in direct observations to understand how an iPad is being used in class to solve a problem. Observation is the method in this example, while problem solving is part of the educause.edu/eli pedagogical framework that we’ve developed for the initiative. A well-developed framework and effective measurement strategy are important considerations, whether you are embarking on a mobile learning project for the first time or are in your third or fourth phase of the project. You Are Here Before considering a measurement strategy, I recommend taking one step back to categorize the kind of mobility work in which your organization is involved. In their literature review, Naismith, Sharples, and Ting (2005) propose these six classifications and examples for mobile learning:1 „„ Behaviorist: activities promoting learning as a change in learners’ observable actions. This category describes learning that happens or is supported by the reinforcement of an association between a particular stimulus and a response. „„ Constructivist: activities in which learners actively construct new ideas or concepts based on both their previous and current knowledge. In this category, learning is an active process. „„ Situated: activities promoting learning within an authentic context and culture. In this category, learning can be enhanced by ensuring it takes place in a real-world ©2012 EDUCAUSE. CC by-nc-nd. 1
  4. 4. Figure 1. Student Ownership of Technology Devices Hardware Technology ownership: A majority of undergraduates own about a dozen devices 55% 55% 56% eReader Games Computer WebHandheld Desktop cam Smart phone HDTV 53% 62% 66% 70% 75% 81% 87% 38% 8% 11% iPad Netbook 12% Essential technology: Percentage of students who said these technologies are “extremely valuable” for academic success 57% 64% Computer Thumb drive Desktop 73% Printer 78% 81% Wi-Fi Computer Laptop 37% of students have used smartphones for academics in the past year iPod Games Thumb Stationary drive DVD player Printer Computer Laptop Count the ways: How smartphone owners use their devices for academics E-mailing professors Checking grades 66% 62% Texting other students about coursework 61% Looking up information on the Internet in class 45% Texting professors 19% The data in this infographic comes from the ECAR National Study of Undergraduate Students and Information Technology, 2011. The full study highlights additional student perspectives captured in an online survey administered in 2011. context. An example here could be contextaware applications because they draw on surrounding environments to enhance the learning activity. „ „Col l a b o rat ive : a c t ivit ie s p romoti n g learning through social or other interaction. Collaborative learning is based on the role of social interactions in the process of learning, and mobile devices offer new opportunities to engage in collaborative learning. „„ Informal and lifelong: activities that support learning outside a dedicated learning environment and formal curriculum. This category includes activities that are embedded in everyday life, thus emphasizing the value of mobile technologies in supporting them. „„ Learning and teaching support: activities that assist in the coordination of learners and resources for learning activities. This category includes activities or applications that are not instructional in nature but that support instruction and thus learning. For example, access to the learning management system, schedules, library resources, or student support services. Using these categories can help us further clarify existing current mobile learning efforts and also suggest opportunities for future work. For instance, it is not uncommon for many institutions to begin their mobility work in the learning and teaching support category (for example, providing mobile access to course schedules), sometimes outside an instructional context. But doing so builds tolerance and understanding of mobile applications with our students, a tolerance that can be leveraged for learning in the classroom. Another way to organize institutional mobile learning activities is by the degree to which they are integrated into the curriculum. I propose three levels: „„ Level 1: Service-related mobile content (e.g., access to the schedule or course offerings, library resources and services, campus tram whereabouts) educause.edu/eli 2
  5. 5. „„ Level 2: Generic mobile instructional appli- and guidelines for the components of a mobile experience to consider before developing or launching a pilot or evolving an existing project. „„ Level Case 1: Identifying Focus Areas Because mobile teaching and learning is still an emergent area, many studies are exploratory in nature. In other words, they don’t establish any specific criteria for measurement or identify areas for examination. They simply insert technology and applications into the learning environment and observe how instructors and learners are using them. While it’s fine and even desirable to have an exploratory component in a pilot, it’s important to identify areas of focus or outcomes that you want to report on when the study is finished. In their study on assessing mobile learning in a large blended classroom, Wang et al. identified several areas for analysis:3 cations (e.g., use of student response systems, Twitter, or the learning management system) 3: Discipline-specific, customized mobile learning (e.g., mobile applications or tools that are developed to support a particular set of learning objectives within a discipline) As noted earlier, many institutions begin development of mobile content and resources in areas that support students in a non-instructional way, as described in level 1. Others support learning through the use of mobile applications that are openly available at little or no cost to the user (level 2). Some examples of this include backchannel tools like Twitter or Poll Everywhere. Another example might be enabling students to access information (grade book) or content (assignments, readings) in the mobile-enabled learning management system. These uses are distinguished by the fact that they can be used by any discipline and may be applied in a variety of ways. Level 3 describes the use of mobile applications and devices to support specific discipline-based learning objectives. In other words, this level supports the development of pedagogies that specifically make use of the affordances of mobile learning. For instance, Carleton College developed a mobile digital flashcard program to support the educational goal of helping language learners expand their French vocabulary— an area of persistent need.2 Level 3 activity is more costly but often yields the highest returns in the areas of improved learning, increased student engagement, and additional time on task. Institutions do not typically begin their mobile work here, but when they do this kind of work, they collaborate with instructors, instructional designers, and technology developers to create customized mobile software and applications. Organizing mobile activities and efforts according to the levels or categories described above can support planning and strategy by understanding where current mobility work is taking place and by helping institutions set goals for where they want to go in future phases of mobility. The development and use of frameworks to measure activity at each level is, of course, critical in moving forward and informing those directions. Frameworks for Measuring Impact In this section, I draw from four studies or cases of institutional work in the area of mobile learning. Each case offers some ideas „„ Student enjoyment and learning „„ Student interaction with other students „„ Student interaction with instructors „„ Impression of the mobile learning environment „„ Effect on study habits The researchers designed survey questions (see the study for additional information on the surveys) organized around measures of activity, efficiency, outcomes, and organization. They also set out to measure student satisfaction, level of interaction (student-student, studentinstructor), and sustainability of student participation in mobile learning activities. After collecting and analyzing the quantitative and qualitative feedback, they established seven reliable evaluative dimensions for the study of mobility’s effects on learners: overall satisfaction, course organization, course activities, student interaction, instructor interaction, relationship to content, and sustainability. Each of these is described in detail in the study, which provides an excellent framework for a mobility study. Case 2: Challenges and Goals Identifying areas for study is only the first step in evaluating mobile learning. Vavoula and Sharple suggest several challenges and opportunities and further contribute to our framework:4 „„ Capturing learning contexts and learning across contexts: Learning that happens in a variety of spaces, inside and outside a classroom, is more challenging to capture than that which is situated in a fixed, physical learning environment. “This study suggests that mobile learning research attempt to educause.edu/eli 3
  6. 6. capture the location of learning and the layout of the space (where); the social setting (who, with whom, from whom); the learning objectives and outcomes (why and what); the learning method(s) and activities (how); and the learning tools (how).” „„ Identifying learning gains: Many mobile learning studies set out to “improve student learning” but struggle to isolate the effect of mobility on learning and to define gains in learning. In other words, how will you know students learned more because of a mobile application, and how will you measure how much more they learned as a result? This study suggests we be very specific about what we’re looking for and identify a few behaviors—for example, where learners show responsibility for and initiate their own learning (e.g., by writing), are actively involved in learning (e.g., spending additional time on a task), or make links and transfer ideas and skills (e.g., by comparing information). „„ Tracking behavior: Although rare, some studies “monitor” student activity on mobile devices with the use of tracking software. This can be unreliable and present ethical issues. An alternate approach is to ask students to contribute to a daily or weekly journal about their mobile learning experience: what they did, what went well, what was challenging, and so forth. Doing so can help to assess the dimensions established in case 1 above. „„ The technology itself: Mobile technology today spans a variety of devices, from the small flip phone to tablets and even netbooks. Studies should include some component related to the usability of the devices themselves and also to the extent to which they are integrated into the learners’ technology constellation. In other words, how well do the devices and the applications used work with other technologies used on a daily basis? Is the experience seamless, cumbersome, or incompatible? How could it be improved? „„ The big picture: Mobile learning has the potential to expand the learning environment well beyond the walls of the institution. Vavoula and Sharples suggest the use of Price and Oliver’s impact studies: anticipatory, ongoing, and achieved. “Anticipatory studies relate to pre-intervention intentions, opinions, and attitudes; ongoing studies focus on analyzing processes of integration; and achieved studies are summative studies of technology no longer novel.” This phased approach is valuable as we plan the future phases of our mobile studies. While today’s studies may explore integration with existing technologies and basic use, tomorrow’s studies may look at applications tailored to learner environments and needs. As the technology evolves and matures, so should our studies. „„ Formal and informal learning: Mobile tech- nology is blurring the lines between formal and informal learning because it enables students to access and interact with their learning environment and networks anywhere, anytime. Students will have to help us understand these contexts as they continue to evolve into highly personalized environments. As these come into focus, we’ll better understand how and where support is needed. Case 3: Mobile Learning and Instructional Design Traxler and Kukulska-Hulme, based on their extensive review of mobile learning initiatives, suggest several characteristics of a good mobile learning experience.5 In this list, we could supplant mobile technology with any technology, which demonstrates these are universal instructional design principles. As such, these could be used to develop a rubric to measure our local mobile learning work. It should also be noted that this list is particularly relevant when a technology is new or emergent and may be less so as it evolves and becomes increasingly ubiquitous. „„ Proportionate: What is the proportion of time spent learning and applying the technology with the actual learning experience or learning benefit? A cost/benefit analysis is suggested, which will, to some extent, depend on the tools (device and applications) you use and the extent to which students are familiar with them. „„ Fit: How appropriate is the mobile tech- nology to the learners, to the learning, and to the course delivery mode? Is there a good fit between the technology and the desired outcome, between the technology and the tools students already have or know, and between the technology and the style of the instructor? Is the technology well integrated into the students’ personal learning environment? „„ Alignment: To what extent are the learning goals mapped to the technology’s affordances? It might be helpful to make these connections for students, especially if the technology or its application is experimental. „„ Unintended results: Since mobile learning is still relatively new, it will be useful to find educause.edu/eli 4
  7. 7. a way to identify unexpected outcomes— a qualitative approach will likely be most effective. Doing so will help inform future phases of mobile initiatives. „„ Consistency: How consistent is the tech- This case offers several key questions for our consideration: „„ What previously unavailable digital (on mobile devices) content and resources will we make available to students? nology’s application (and results) across learners? Is the use or application reliable? How consistent is it across devices and technologies used? „„ How will students be introduced or oriented These five components can be integrated into a mobile learning framework and into the very design of the initiative. They can be fashioned into a rubric to be used as we design, evaluate, and evolve our pilots. will it be organized? In other words, will the materials be held in a single repository, or will there be a portal to access content from a variety of sources? As the volume of content increases, we need to be mindful of how the learning environment is structured and how that structure enables learning. If the environment is cumbersome and complex, students are not likely to use it. Case 4: The Student Experience In a case study of a medical school’s mobile learning experience, Nestel et al. highlight several findings that are worth considering as we build our mobile initiatives.6 The institution in the study offered a graduate medical program where students largely spent their first year on campus, while the remaining three years were spent almost entirely in clinical settings. All students were issued a mobile device at the start of the program and worked inside a virtual learning environment that made use of two main teaching and learning tools, Blackboard and Interlearn, for course management and facilitation of interaction online, along with various other licensed software. There were 57 students in the entering cohort for the case study, and through student questionnaires and interviews, the study sought to address two questions: In what ways does mobility support learning, and what areas need development? This institution sought to enhance students’ learning experience through the use of mobile technology to provide access to the Internet, software, and information repositories and also to enable information sharing within and between cohorts. In this case, students had access to more than 10 different sources (e.g., lecture notes, problem-based learning materials, external weblinks, summative assessments, and so forth). These goals are not uncommon in mobile initiatives, and many institutions will provide students with a significant amount of digital content to support their learning. Students in the study offered a few suggestions for improvement. They asked for more robust resources and for more electronic learning resources (especially audiovisual resources), along with more flexibility in accessing the materials. Since there was so much content, they felt they would have benefitted from guidelines and support on managing their virtual learning environments. to the content and the environment within which it resides? „„ Where will this content reside, and how „„ How will students manage their resources? How are students able to interact and engage with the content? Are they able to annotate, download, share, or highlight the content? How long are they able to access the materials, from how many devices, and in what ways? Some of these issues can and should be addressed together with students. Students can help us create or understand their learning environments and the features they need to make the best use of them. As mobile technologies enable the proliferation of content and resources, effective information management becomes critical. Implications for Planning Earlier in this brief I noted the distinction between the components we wish to measure and the way in which we go about measuring them. Once we have developed the components of the mobile experience or the framework, we can then explore approaches for measurement. For instance, we might determine that the best way to identify unintended results is through focus groups, live observations, and journal analysis. Alternatively, you might measure the impact of a particular mobile technology on student comprehension of a particular concept through the use of pre-tests and post-tests or a comparison group. The idea is that once you have a framework established, a variety of measurement approaches and methodologies are available, but the framework must come first. Each of the cases above contributes some advice for planning: „„ Capture and analyze learning in the context in which it occurs. „„ Assess the usability of the technology and educause.edu/eli 5
  8. 8. how it affects students’ personal learning experience. „„ Look beyond measurable cognitive gains into changes in the learning process and practice. „„ Consider organizational issues in the adop- tion of mobile learning practice and its integration with existing practices. „„ Span the life cycle of the mobile learning innovation that is evaluated, from conception to full deployment and beyond. And finally, when working with emerging technologies, it’s important to remember to evolve our studies and frameworks as the technology evolves. These approaches should not be static, but should change as the adoption of the technology and corresponding pedagogies mature. Constructing our research so we are informing future phases is always important, but it is especially important when working with an emergent technology. Notes 1 Laura Naismith, Mike Sharples, and Jeffrey Ting, “Evaluation of CAERUS: A Context-Aware Mobile Guide,” 2005, http://www.mlearn.org.za/CD/papers/ Naismith.pdf. 2 “Closing in on Vocabulary Acquisition: Testing the Use of iPods and Flashcard Software to Eliminate Performance Gaps,” SEI Case Study, EDUCAUSE Learning Initiative, March 2012, http://net.educause .edu/ir/library/pdf/SEI1201.pdf. 3 Minjuan Wang, Daniel Novak, and Ruimin Shen, “Assessing the Effectiveness of Mobile Learning in Large Hybrid/Blended Classrooms,” h t t p : //w w w. d o c s t o c . c o m /d o c s / 3 8 9 6 4 5 6 3 / Assessing-the-Effectiveness-of-Mobile-Learning-inLarge-HybridBlended. 4 Giasemi N. Vavoula and Mike Sharples, “Challenges in Evaluating Mobile Learning,” Proceedings of mLearn 2008, available from http://www.mlearn.org/ mlearn2008/. 5 John Traxler and Agnes Kukulska-Hulme, “Evaluating Mobile Learning: Reflections on Current Practice,” http://www.mlearn.org.za/CD/papers/Traxler.pdf. 6 Debra Nestel, Andre Ng, Katherine Gray, Robyn Hill, Elmer Villanueva, George Kotsanas, Andrew Oaten, and Chris Browne, “Evaluation of Mobile Learning: Students’ Experiences in a New Rural-Based Medical School,” BMC Medical Education 10, no. 57, 2010, http://www.biomedcentral.com/1472-6920/10/57. Read this QR Code to do the next activity, please. The EDUCAUSE Learning Initiative (ELI) is where teaching and learning professionals come to learn, lead, collaborate, and share in the context of an international forum. Members benefit from the expansive emerging technology research and development that takes place collaboratively across institutions. To learn more about ELI, visit educause.edu/eli. educause.edu/eli 6