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Barbara Lindsey

2010 Horizon Report » Executive Summary - 0 views

  • The annual Horizon Report describes the continuing work of the New Media Consortium’s Horizon Project, a qualitative research project established in 2002 that identifies and describes emerging technologies likely to have a large impact on teaching, learning, or creative inquiry on college and university campuses within the next five years.
  • six emerging technologies or practices are described that are likely to enter mainstream use on campuses within three adoption horizons spread over the next one to five years.
  • In the seven years that the Horizon Project has been underway, more than 400 leaders in the fields of business, industry, technology, and education have contributed to this long-running primary research effort. They have drawn on a comprehensive body of published resources, current research and practice, their own considerable expertise, and the expertise of the NMC and ELI communities to identify technologies and practices that are beginning to appear on campuses or are likely to be adopted in the next few years.
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  • Each topic is introduced with an overview that describes what it is, followed by a discussion of the particular relevance of the topic to education, creativity, or research. Examples of how the technology is being, or could be applied to those activities are given. Finally, each section closes with an annotated list of suggested readings and additional examples that expand on the discussion in the report and a link to the tagged resources collected during the research process
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    The annual Horizon Report describes the continuing work of the New Media Consortium's Horizon Project, a qualitative research project established in 2002 that identifies and describes emerging technologies likely to have a large impact on teaching, learning, or creative inquiry on college and university campuses within the next five years.
Barbara Lindsey

New Mobile Learning Case Studies - Digital Education - Education Week - 0 views

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    Can only read the summaries for free. 
Barbara Lindsey

Convenience, Communications, and Control: How Students Use Technology | Resources | EDU... - 0 views

  • They are characterized as preferring teamwork, experiential activities, and the use of technology
  • Doing is more important than knowing, and learning is accomplished through trial and error as opposed to a logical and rule-based approach.2 Similarly, Paul Hagner found that these students not only possess the skills necessary to use these new communication forms, but there is an ever increasing expectation on their part that these new communication paths be used
  • Much of the work to date, while interesting and compelling, is intuitive and largely based on qualitative data and observation.
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  • There is an inexorable trend among college students to universal ownership, mobility, and access to technology.
  • Students were asked about the applications they used on their electronic devices. They reported that they use technology first for educational purposes, followed by communication.
    • Barbara Lindsey
       
      All self-reported. Would have been powerful if could have actually tracked a representative sample and compared actual use with reported use.
  • presentation software was driven primarily by the requirements of the students' major and the curriculum.
  • Communications and entertainment are very much related to gender and age.
  • From student interviews, a picture emerged of student technology use driven by the demands of the major and the classes that students take. Seniors reported spending more time overall on a computer than do freshmen, and they reported greater use of a computer at a place of employment. Seniors spent more hours on the computer each week in support of their educational activities and also more time on more advanced applications—spreadsheets, presentations, and graphics.
  • Confirming what parents suspect, students with the lowest grade point averages (GPAs) spend significantly more time playing computer games; students with the highest GPAs spend more hours weekly using the computer in support of classroom activities. At the University of Minnesota, Crookston, students spent the most hours on the computer in support of classroom activities. This likely reflects the deliberate design of the curriculum to use a laptop extensively. In summary, the curriculum's technology requirements are major motivators for students to learn to use specialized software.
  • The interviews indicated that students are skilled with basic office suite applications but tend to know just enough technology functionality to accomplish their work; they have less in-depth application knowledge or problem solving skills.
  • According to McEuen, student technology skills can be likened to writing skills: Students come to college knowing how to write, but they are not developed writers. The analogy holds true for information technology, and McEuen suggested that colleges and universities approach information technology in the same way they approach writing.6
  • he major requires the development of higher-level skill sets with particular applications.
    • Barbara Lindsey
       
      Not really quantitative--self-reported data back by selected qualitative interviews
  • The comparative literature on student IT skill self-assessment suggests that students overrate their skills; freshmen overrate their skills more than seniors, and men overrate their skills more than women.7 Our data supports these conclusions. Judy Doherty, director of the Student Technologies Resource Group at Colgate University, remarked on student skill assessment, "Students state in their job applications that they are good if not very good, but when tested their skills are average to poor, and they need a lot of training."8
  • Mary Jane Smetanka of the Minneapolis–St. Paul Star Tribune reported that some students are so conditioned by punch-a-button problem solving on computers that they approach problems with a scattershot impulsiveness instead of methodically working them through. In turn, this leads to problem-solving difficulties.
  • We expected to find that the Net Generation student prefers classes that use technology. What we found instead is a bell curve with a preference for a moderate use of technology in the classroom (see Figure 1).
    • Barbara Lindsey
       
      More information needs to be given to find out why--may be tool and method not engaging.
  • It is not surprising that if technology is used well by the instructor, students will come to appreciate its benefits.
  • A student's major was also an important predictor of preferences for technology in the classroom (see Table 3), with engineering students having the highest preference for technology in the classroom (67.8 percent), followed by business students (64.3 percent).
  • Humanities 7.7% 47.9% 40.2
  • he highest scores were given to improved communications, followed by factors related to the management of classroom activities. Lower impact activities had to do with comprehension of classroom materials (complex concepts).
  • I spend more time engaged in course activities in those courses that require me to use technology.
  • The instructors' use of technology in my classes has increased my interest in the subject matter. 3.25 Classes that use information technology are more likely to focus on real-world tasks and examples.
  • Interestingly, students do not feel that use of information technology in classes greatly increases the amount of time engaged with course activities (3.22 mean).12 This is in direct contrast to faculty perceptions reported in an earlier study, where 65 percent of faculty reported they perceived that students spend more time engaged with course materials
  • Only 12.7 percent said the most valuable benefit was improved learning; 3.7 percent perceived no benefit whatsoever. Note that students could only select one response, so more than 12.7 percent may have felt learning was improved, but it was not ranked highest. These findings compare favorably with a study done by Douglas Havelka at the University of Miami in Oxford, Ohio, who identified the top six benefits of the current implementation of IT as improving work efficiency, affecting the way people behave, improving communications, making life more convenient, saving time, and improving learning ability.14
    • Barbara Lindsey
       
      Would have been good to know exactly what kinds of technologies were meant here.
  • Our data suggest that we are at best at the cusp of technologies being employed to improve learning.
  • The interactive features least used by faculty were the features that students indicated contributed the most to their learning.
  • he students in this study called our attention to performance by noting an uneven diffusion of innovation using this technology. This may be due, in part, to faculty or student skill. It may also be due to a lack of institutional recognition of innovation, especially as the successful use of course management systems affects or does not affect faculty tenure, promotion, and merit decisions
  • we found that many of the students most skilled in the use of technology had mixed feelings about technology in the classroom.
  • What we found was that many necessary skills had to be learned at the college or university and that the motivation for doing so was very much tied to the requirements of the curriculum. Similarly, the students in our survey had not gained the necessary skills to use technology in support of academic work outside the classroom. We found a significant need for further training in the use of information technology in support of learning and problem-solving skills.
  • Course management systems were used most by both faculty and students for communication of information and administrative activities and much less in support of learning.
  • In 1997, Michael Hooker proclaimed, "higher education is on the brink of a revolution." Hooker went on to note that two of the greatest challenges our institutions face are those of "harnessing the power of digital technology and responding to the information revolution."18 Hooker and many others, however, did not anticipate the likelihood that higher education's learning revolution would be a journey of a thousand miles rather than a discrete event. Indeed, a study of learning's last great revolution—the invention of moveable type—reveals, too, a revolution conducted over centuries leading to the emergence of a publishing industry, intellectual property rights law, the augmentation of customized lectures with textbooks, and so forth.
  • Both the ECAR study on faculty use of course management systems and this study of student experiences with information technology concluded that, while information technology is indeed making important inroads into classroom and learning activities, to date the effects are largely in the convenience of postsecondary teaching and learning and do not yet constitute a "learning revolution." This should not surprise us. The invention of moveable type enhanced, nearly immediately, access to published information and reduced the time needed to produce new publications. This invention did not itself change literacy levels, teaching styles, learning styles, or other key markers of a learning revolution. These changes, while catalyzed by the new technology, depended on slower social changes to institutions. I believe that is what we are witnessing in higher education today.
  • The institutions chosen represent a nonrepresentative mix of the different types of higher education institution in the United States, in terms of Carnegie class as well as location, source of funding, and levels of technology emphasis. Note, however, that we consider our findings to be instructive rather than conclusive of student experiences at different types of Carnegie institutions.
  • Qualitative data were collected by means of focus groups and individual interviews. We interviewed undergraduate students, administrators, and individuals identified as experts in the field of student technology use in the classroom. Student focus groups and interviews of administrators were conducted at six of the thirteen schools participating in the study.
Barbara Lindsey

Teaching in Social and Technological Networks « Connectivism - 0 views

  • Students are not confined to interacting with only the ideas of a researcher or theorist. Instead, a student can interact directly with researchers through Twitter, blogs, Facebook, and listservs. The largely unitary voice of the traditional teacher is fragmented by the limitless conversation opportunities available in networks. When learners have control of the tools of conversation, they also control the conversations in which they choose to engage.
  • Traditional courses provide a coherent view of a subject. This view is shaped by “learning outcomes” (or objectives).
  • This cozy comfortable world of outcomes-instruction-assessment alignment exists only in education. In all other areas of life, ambiguity, uncertainty, and unkowns reign.
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  • However, in order for education to work within the larger structure of integrated societal systems, clear outcomes are still needed.
  • How can we achieve learning targets when the educator is no longer able to control the actions of learners?
  • I’ve come to view teaching as a critical and needed activity in the chaotic and ambiguous information climate created by networks. In the future, however, the role of the teacher, the educator, will be dramatically different from the current norm. Views of teaching, of learner roles, of literacies, of expertise, of control, and of pedagogy are knotted together. Untying one requires untying the entire model.
  • Most likely, a teacher will be one of the more prominent nodes in a learner’s network. Thoughts, ideas, or messages that the teacher amplifies will generally have a greater probability of being seen by course participants.
  • A curatorial teacher acknowledges the autonomy of learners, yet understands the frustration of exploring unknown territories without a map. A curator is an expert learner. Instead of dispensing knowledge, he creates spaces in which knowledge can be created, explored, and connected.
  • The curator, in a learning context, arranges key elements of a subject in such a manner that learners will “bump into” them throughout the course. Instead of explicitly stating “you must know this”, the curator includes critical course concepts in her dialogue with learners, her comments on blog posts, her in-class discussions, and in her personal reflections. As learners grow their own networks of understanding, frequent encounters with conceptual artifacts shared by the teacher will begin to resonate.
    • Barbara Lindsey
       
      Can you see this as a viable possibility?
  • When I first started learning about the internet (pre-web days), I felt like I had stepped into a alternate realm with its own norms of behaviour and conduct. Bulletin boards and chat rooms presented a challenging mix of navigating social protocols while developing technical skills. By engaging with these conversation spaces – and forming a few tentative connections with others – I was able to find a precarious foothold in the online medium.
  • Today’s social web is no different – we find our way through active exploration. Designers can aid the wayfinding process through consistency of design and functionality across various tools, but ultimately, it is the responsibility of the individual to click/fail/recoup and continue.
  • Social structures are filters. As a learner grows (and prunes) her personal networks, she also develops an effective means to filter abundance. The network becomes a cognitive agent in this instance – helping the learner to make sense of complex subject areas by relying not only on her own reading and resource exploration, but by permitting her social network to filter resources and draw attention to important topics. In order for these networks to work effectively, learners must be conscious of the need for diversity and should include nodes that offer critical or antagonistic perspectives on all topic areas. Sensemaking in complex environments is a social process.
  • Imagine a course where the fragmented conversations and content are analyzed (monitored) through a similar service. Instead of creating a structure of the course in advance of the students starting (the current model), course structure emerges through numerous fragmented interactions. “Intelligence” is applied after the content and interactions start, not before. This is basically what Google did for the web – instead of fully defined and meta-described resources in a database, organized according to subject areas (i.e. Yahoo at the time), intelligence was applied at the point of search. Aggregation should do the same – reveal the content and conversation structure of the course as it unfolds, rather than defining it in advance.
    • Barbara Lindsey
       
      This would really change how courses are currently taught. How would current course, program, departmental, school-wide assessments, evaluations react?
  • Educators often have years or decades of experience in a field. As such, they are familiar with many of the concepts, pitfalls, confusions, and distractions that learners are likely to encounter. As should be evident by now, the educator is an important agent in networked learning. Instead of being the sole or dominant filter of information, he now shares this task with other methods and individuals.
  • Filtering can be done in explicit ways – such as selecting readings around course topics – or in less obvious ways – such as writing summary blog posts around topics. Learning is an eliminative process. By determining what doesn’t belong, a learner develops and focuses his understanding of a topic. The teacher assists in the process by providing one stream of filtered information. The student is then faced with making nuanced selections based on the multiple information streams he encounters. The singular filter of the teacher has morphed into numerous information streams, each filtered according to different perspectives and world views.
  • During CCK08/09, one of Stephen’s statements that resonated with many learners centers on modelling as a teaching practice: “To teach is to model and to demonstrate. To learn is to practice and to reflect.”
  • Apprenticeship learning models are among the most effective in attending to the full breadth of learning. Apprenticeship is concerned with more than cognition and knowledge (to know about) – it also addresses the process of becoming a carpenter, plumber, or physician.
  • Without an online identity, you can’t connect with others – to know and be known. I don’t think I’m overstating the importance of have a presence in order to participate in networks. To teach well in networks – to weave a narrative of coherence with learners – requires a point of presence.
  • In CCK08/09, we used The Daily, the connectivism blog, elearnspace, OLDaily, Twitter, Facebook, Ning, Second Life, and numerous other tools to connect with learners. Persistent presence in the learning network is needed for the teacher to amplify, curate, aggregate, and filter content and to model critical thinking and cognitive attributes that reflect the needs of a discipline.
  • We’re
  • We’re still early in many of these trends. Many questions remain unanswered about privacy, ethics in networks, and assessment. My view is that change in education needs to be systemic and substantial. Education is concerned with content and conversations. The tools for controlling both content and conversation have shifted from the educator to the learner. We require a system that acknowledges this reality.
  • Aggregation had so much potential. And yet has delivered relatively little over the last decade.
  • Perhaps we need to spend more time in information abundant environments before we turn to aggregation as a means of making sense of the landscape.
  • I’d like a learning system that functions along the lines of RescueTime – actively monitoring what I’m doing – but then offers suggestions of what I should (or could) be doing additionally. Or a system that is aware of my email exchanges over the last several years and can provide relevant information based on the development of my thinking and work.
    • Barbara Lindsey
       
      Would you welcome this kind of feedback on your private exchanges?
Barbara Lindsey

A Brief Summary of the Best Practices in Teaching - 1 views

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    Could have done a much better job of making this text more readable. Focuses on how to optimize lecture-style learning environments.
Barbara Lindsey

Learning Reimagined: Participatory, Peer, Global, Online | DMLcentral - 1 views

  • I have found that in both my traditional physical classrooms and online environments, the chances of successful outcomes are multiplied when every person in the group makes a commitment to active participation in helping others learn.
  • When a sufficient number of people jump in and start contributing and building on one another's contributions, it becomes clear to all that it's not just about the teacher's performance and the student's ability to complete assignments. It's about our joint effort to make the whole of our encounter more valuable than just the sum of our individual learning.
  • I type roles on the whiteboard and show how to use the whiteboard tools to enter, format and move around elements. Roles include searchers, chat summarizers, session summarizers, mindmap leaders, session bloggers. I ask co-learners to write their own names on the whiteboard next to the roles they want to take, show them how to create break-out rooms to coordinate their collaborations, and ask the summarizers to feed their output to the bloggers, who take responsibility for posting a reflective summary of the session later
    • Barbara Lindsey
       
      How about we try this out in our online sessions?
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  • It's confusing at first, but it is also flowing.
  • Yes, we're a collective intelligence, which is exhilarating, but we're a toddler collective intelligence, stumbling around learning to walk and trying to figure out where we're going at the same time. A number of new skills are required in short order. Information and communication flow through multiple simultaneous channels. The enterprise is challenging - that's part of the exercise. Taking my direction from George Siemens' ideas about networked learning ("we emphasize that early course experiences tend to be overwhelming and chaotic") I assure co-learners early and often that we can relax, accept and even embrace the chaos, and regard our networked attempts to make sense of it as the scaffold for our co-learning. 
  • Instead of seeking to put every fact in its place in an existing well-ordered taxonomy, why not seek to learn together by asking questions about what puzzles us, then organizing our discussions and mining them for knowledge?
  • Sometimes, I get into predicaments and don't know how to quit a webtour or place people in breakout rooms. So I calmly start exploring possible solutions, talking about it as I try to recover. While doing so, I also talk about the importance of exploring close enough to the edge to fall over it frequently. I model tolerance for error, learning from error, pushing the envelope of tech. Indeed, I've found that the earlier I can break something and fix it in public, the better. We talk about what works and what doesn't, discard what doesn't suit our purposes, push a tool further if it helps us learn together. It requires regular doses of humility to abandon what seemed like a bright idea at the time.
  • The objective is a culture of conversation that troubleshoots practical skills, explores theoretical underpinnings, dissects social implications.
  • Our internal social bookmarks enable us to create a mini-collective-intelligence by gathering resources about our discussion topics, selecting or writing descriptive snippets, assigning tags. The emerging tag-cloud serves as an index to the resources.
  • Wiki-work is about collaborative authoring.
  • In the process of using these tools to try to make sense together, we co-construct our learning. The last week of the course is about re-examining our learning process, reiterating the most important things we've learned, and redesigning the parts of the process that didn't work so well.
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    fall 2011 syllabus
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