special guest Steven Bell, Associate Librarian at Temple University Libraries
Tuesday, February 27 when the #DLNchatcommunity got together to discuss: What Is the Role of Libraries in Digital Learning Innovation?
“it will definitely be a more sustainable initiative if it is collaborative—-whether it’s OER, open access journals, etc…if the library wants to go alone it will go fast but if it goes with others it will go much further.”
The #DLNchat community concurred there are ample opportunities for library-led collaborations in digital learning across campus. “Curation is key
OER = “Faculty + Librarians + Digital Media Experts = Engaging Content 4 learners.”
considering exactly that-how to create “librarians on demand” to meet students and faculty in dining halls, coffee shops, study lounges or wherever they may be conducting their scholarly work.
It requires that companies become what we call digital masters. Digital masters cultivate two capabilities: digital capability, which enables them to use innovative technologies to improve elements of the business, and leadership capability, which enables them to envision and drive organizational change in systematic and profitable ways. Together, these two capabilities allow a company to transform digital technology into business advantage.
We found that the elements of leadership capability have endured, but new elements of digital capability have come to the fore.
While strong leadership capability is even more essential than ever, its core elements — vision, engagement, and governance — are not fundamentally changed, though they are informed by recent innovations. The elements of digital capability, on the other hand, have been more profoundly altered by the rapid technological advances of recent years.
Experience design: Customer experience has become the ultimate battleground for many companies and brands.
Customer intelligence: Integrating customer data across silos and understanding customer behavior
Emotional engagement: Emotional connections with customers are as essential as technology in creating compelling customer experiences.
As ever, well-managed operations are essential to converting revenue into profit, but now we’re seeing a shift in the focus of digital transformation in this arena.
Core process automation: Amazon’s distribution centers deliver inventory to workers rather than sending workers to collect inventory. Rio Tinto, an Australian mining company, uses autonomous trucks, trains, and drilling machinery so that it can shift workers to less dangerous tasks, leading to higher productivity and better safety.
Connected and dynamic operations: Thanks to the growing availability of cheap sensors, cloud infrastructure, and machine learning, concepts such as Industry 4.0, digital threads, and digital twins have become a reality. Digital threads connecting machines, models, and processes provide a single source of truth to manage, optimize, and enhance processes from requirements definition through maintenance.
Data-driven decision-making: from backward-looking reports to real-time data. Now, connected devices, new machine learning algorithms, smarter experimentation, and plentiful data enable more-informed decisions.
Transforming Employee Experience
Augmentation: Warnings that robots will replace humans have given way to a more nuanced and productive discussion.
Workers in Huntington Ingalls Industries’ shipyard use augmented reality to help build giant complex vessels such as aircraft carriers and submarines. They can “see” where to route wires or pipes or what is behind a wall before they start drilling into it.
Future-readying: providing employees with the skills they need to keep up with the pace of change. In the past few years, this has given rise to new models of managing learning and development in organizations, led by a new kind of chief learning officer, whom we call the transformer CLO
Flexforcing: To respond to fast-paced digital opportunities and threats, companies also need to build agility into their talent sourcing systems. As automation and AI applications take over tasks once performed by humans, some companies are multiskilling employees to make the organization more agile.
Transforming Business Models
three elements supporting business model transformation: digital enhancements, information-based service extensions, and multisided platforms.
Neck and neck for the top spot in the LMS academic vendor race are Blackboard—the early entry and once-dominant player—and coming-up quickly from behind, the relatively new contender, Canvas, each serving about 6.5 million students . The LMS market today is valued at $9.2 billion.
Digital Authoring Systems
Faced with increasingly complex communication technologies—voice, video, multimedia, animation—university faculty, expert in their own disciplines, find themselves technically perplexed, largely unprepared to build digital courses.
instructional designers, long employed by industry, joined online academic teams, working closely with faculty to upload and integrate interactive and engaging content.
nstructional designers, as part of their skillset, turned to digital authoring systems, software introduced to stimulate engagement, encouraging virtual students to interface actively with digital materials, often by tapping at a keyboard or touching the screen as in a video game. Most authoring software also integrates assessment tools, testing learning outcomes.
With authoring software, instructional designers can steer online students through a mixtape of digital content—videos, graphs, weblinks, PDFs, drag-and-drop activities, PowerPoint slides, quizzes, survey tools and so on. Some of the systems also offer video editing, recording and screen downloading options
Adaptive Learning
As with a pinwheel set in motion, insights from many disciplines—artificial intelligence, cognitive science, linguistics, educational psychology and data analytics—have come together to form a relatively new field known as learning science, propelling advances in a new personalized practice—adaptive learning.
MOOCs
Of the top providers, Coursera, the Wall Street-financed company that grew out of the Stanford breakthrough, is the champion with 37 million learners, followed by edX, an MIT-Harvard joint venture, with 18 million. Launched in 2013, XuetangX, the Chinese platform in third place, claims 18 million.
Former Yale President Rick Levin, who served as Coursera’s CEO for a few years, speaking by phone last week, was optimistic about the role MOOCs will play in the digital economy. “The biggest surprise,” Levin argued, “is how strongly MOOCs have been accepted in the corporate world to up-skill employees, especially as the workforce is being transformed by job displacement. It’s the right time for MOOCs to play a major role.”
In virtual education, pedagogy, not technology, drives the metamorphosis from absence to presence, illusion into reality. Skilled online instruction that introduces peer-to-peer learning, virtual teamwork and other pedagogical innovations stimulate active learning. Online learning is not just another edtech product, but an innovative teaching practice. It’s a mistake to think of digital education merely as a device you switch on and off like a garage door.
United States digital literacy frameworks tend to focus on educational policy details and personal empowerment, the latter encouraging learners to become more effective students, better creators, smarter information consumers, and more influential members of their community.
National policies are vitally important in European digital literacy work, unsurprising for a continent well populated with nation-states and struggling to redefine itself, while still trying to grow economies in the wake of the 2008 financial crisis and subsequent financial pressures
African digital literacy is more business-oriented.
Middle Eastern nations offer yet another variation, with a strong focus on media literacy. As with other regions, this can be a response to countries with strong state influence or control over local media. It can also represent a drive to produce more locally-sourced content, as opposed to consuming material from abroad, which may elicit criticism of neocolonialism or religious challenges.
p. 14 Digital literacy for Humanities: What does it mean to be digitally literate in history, literature, or philosophy? Creativity in these disciplines often involves textuality, given the large role writing plays in them, as, for example, in the Folger Shakespeare Library’s instructor’s guide. In the digital realm, this can include web-based writing through social media, along with the creation of multimedia projects through posters, presentations, and video. Information literacy remains a key part of digital literacy in the humanities. The digital humanities movement has not seen much connection with digital literacy, unfortunately, but their alignment seems likely, given the turn toward using digital technologies to explore humanities questions. That development could then foster a spread of other technologies and approaches to the rest of the humanities, including mapping, data visualization, text mining, web-based digital archives, and “distant reading” (working with very large bodies of texts). The digital humanities’ emphasis on making projects may also increase
Digital Literacy for Business: Digital literacy in this world is focused on manipulation of data, from spreadsheets to more advanced modeling software, leading up to degrees in management information systems. Management classes unsurprisingly focus on how to organize people working on and with digital tools.
Digital Literacy for Computer Science: Naturally, coding appears as a central competency within this discipline. Other aspects of the digital world feature prominently, including hardware and network architecture. Some courses housed within the computer science discipline offer a deeper examination of the impact of computing on society and politics, along with how to use digital tools. Media production plays a minor role here, beyond publications (posters, videos), as many institutions assign multimedia to other departments. Looking forward to a future when automation has become both more widespread and powerful, developing artificial intelligence projects will potentially play a role in computer science literacy.
In traditional instruction, students’ first contact with new ideas happens in class, usually through direct instruction from the professor; after exposure to the basics, students are turned out of the classroom to tackle the most difficult tasks in learning — those that involve application, analysis, synthesis, and creativity — in their individual spaces. Flipped learning reverses this, by moving first contact with new concepts to the individual space and using the newly-expanded time in class for students to pursue difficult, higher-level tasks together, with the instructor as a guide.
Let’s take a look at some of the myths about flipped learning and try to find the facts.
Myth: Flipped learning is predicated on recording videos for students to watch before class.
Fact: Flipped learning does not require video. Although many real-life implementations of flipped learning use video, there’s nothing that says video must be used. In fact, one of the earliest instances of flipped learning — Eric Mazur’s peer instruction concept, used in Harvard physics classes — uses no video but rather an online text outfitted with social annotation software. And one of the most successful public instances of flipped learning, an edX course on numerical methods designed by Lorena Barba of George Washington University, uses precisely one video. Video is simply not necessary for flipped learning, and many alternatives to video can lead to effective flipped learning environments [http://rtalbert.org/flipped-learning-without-video/].
Fact: Flipped learning optimizes face-to-face teaching. Flipped learning may (but does not always) replace lectures in class, but this is not to say that it replaces teaching. Teaching and “telling” are not the same thing.
Myth: Flipped learning has no evidence to back up its effectiveness.
Fact: Flipped learning research is growing at an exponential pace and has been since at least 2014. That research — 131 peer-reviewed articles in the first half of 2017 alone — includes results from primary, secondary, and postsecondary education in nearly every discipline, most showing significant improvements in student learning, motivation, and critical thinking skills.
Myth: Flipped learning is a fad.
Fact: Flipped learning has been with us in the form defined here for nearly 20 years.
Myth: People have been doing flipped learning for centuries.
Fact: Flipped learning is not just a rebranding of old techniques. The basic concept of students doing individually active work to encounter new ideas that are then built upon in class is almost as old as the university itself. So flipped learning is, in a real sense, a modern means of returning higher education to its roots. Even so, flipped learning is different from these time-honored techniques.
Myth: Students and professors prefer lecture over flipped learning.
Fact: Students and professors embrace flipped learning once they understand the benefits. It’s true that professors often enjoy their lectures, and students often enjoy being lectured to. But the question is not who “enjoys” what, but rather what helps students learn the best.They know what the research says about the effectiveness of active learning
Assertion: Flipped learning provides a platform for implementing active learning in a way that works powerfully for students.
The Exposure Approach: we don’t provide a way for participants to determine if they learned anything new or now have the confidence or competence to apply what they learned.
The Exemplar Approach: from ‘show and tell’ for adults to show, tell, do and learn.
The Tutorial Approach: Getting a group that can meet at the same time and place can be challenging. That is why many faculty report a preference for self-paced professional development.build in simple self-assessment checks. We can add prompts that invite people to engage in some sort of follow up activity with a colleague. We can also add an elective option for faculty in a tutorial to actually create or do something with what they learned and then submit it for direct or narrative feedback.
The Course Approach: a non-credit format, these have the benefits of a more structured and lengthy learning experience, even if they are just three to five-week short courses that meet online or in-person once every week or two.involve badges, portfolios, peer assessment, self-assessment, or one-on-one feedback from a facilitator
The Academy Approach: like the course approach, is one that tends to be a deeper and more extended experience. People might gather in a cohort over a year or longer.Assessment through coaching and mentoring, the use of portfolios, peer feedback and much more can be easily incorporated to add a rich assessment element to such longer-term professional development programs.
The Mentoring Approach: The mentors often don’t set specific learning goals with the mentee. Instead, it is often a set of structured meetings, but also someone to whom mentees can turn with questions and tips along the way.
The Coaching Approach: A mentor tends to be a broader type of relationship with a person.A coaching relationship tends to be more focused upon specific goals, tasks or outcomes.
The Peer Approach:This can be done on a 1:1 basis or in small groups, where those who are teaching the same courses are able to compare notes on curricula and teaching models. They might give each other feedback on how to teach certain concepts, how to write syllabi, how to handle certain teaching and learning challenges, and much more. Faculty might sit in on each other’s courses, observe, and give feedback afterward.
The Self-Directed Approach:a self-assessment strategy such as setting goals and creating simple checklists and rubrics to monitor our progress. Or, we invite feedback from colleagues, often in a narrative and/or informal format. We might also create a portfolio of our work, or engage in some sort of learning journal that documents our thoughts, experiments, experiences, and learning along the way.
In 2014, administrators at Central Piedmont Community College (CPCC) in Charlotte, North Carolina, began talks with members of the North Carolina State Board of Community Colleges and North Carolina Community College System (NCCCS) leadership about starting a CBE program.
Building on an existing project at CPCC for identifying the elements of a digital learning environment (DLE), which was itself influenced by the EDUCAUSE publication The Next Generation Digital Learning Environment: A Report on Research,1 the committee reached consensus on a DLE concept and a shared lexicon: the “Digital Learning Environment Operational Definitions,
The key campus tech issues are no longer about IT (in the past e.g.: MS versus Apple). IT is the “easy part” of technology on campus. The challenges: people, planning policy, programs, priorities, silos, egos, and IT entitlements
How do we make Digital Learning compelling and safe for the faculty? provide evidence of impact, support, recognition and reward for faculty; communicate about effectiveness of and need for IT resources.
technology is not capital cost, it is operational cost. reoccurring.
Visualization:
underlying issues; can i do this? why should i do this? evidence of benefit?
the more things change, the more things stay the same. new equilibrium.
change: from what did you do wrong to how do we do better. Use data as a resources, not as a weapon. there is a fear of trying, because there is no recognition or reward
Machiavelli: 1. concentrate your efforts 2. pick your issues carefully, know when to fight 3. know the history 4. build coalitions 5. set modest goals – and realistic 6. leverage the value of data (use it as resource not weapon) 7. anticipate personnel turnover 8. set deadlines for decisions
Colleagues,
We apologize for the short notice, but wanted to make you aware of the following opportunity: provide
From Ken Graetz at Winona State University:
As part of our Digital Faculty Fellows Program at WSU, Dr. Kenneth C. Green will be speaking this Thursday, March 22nd in Stark 103 Miller Auditorium from 11:30 to 12:30 on “Innovation, Infrastructure, and Digital Learning.” We will be streaming Casey’s talk using Skype Meeting Broadcast and you can join as a guest using the following link: Join the presentation. This will allow you to see and hear his presentation, as well as post moderated questions. By way of a teaser, here is a recent quote from Dr. Green’s blog, DigitalTweed, published by Inside Higher Ed:
“If trustees, presidents, provosts, deans, and department chairs really want to address the fear of trying and foster innovation in instruction, then they have to recognize that infrastructure fosters innovation. And infrastructure, in the context of technology and instruction, involves more than just computer hardware, software, digital projectors in classrooms, learning management systems, and campus web sites. The technology is actually the easy part. The real challenges involve a commitment to research about the impact of innovation in instruction, and recognition and reward for those faculty who would like to pursue innovation in their instructional activities.”
Dr. Green is the founding director of The Campus Computing Project, the largest continuing study of the role of digital learning and information technology in American colleges and universities. Campus Computing is widely cited as a definitive source for data, information, and insight about IT planning and policy issues affecting higher education. Dr. Green also serves as the director, moderator, and co-producer of TO A DEGREE, the postsecondary success podcast of the Bill & Melinda Gates Foundation. He is the author or editor of some 20 books and published research reports and more than 100 articles and commentaries that have appeared in academic journals and professional publications. In 2002, Dr. Green received the first EDUCAUSE Award for Leadership in Public Policy and Practice. The EDUCAUSE award cites his work in creating The Campus Computing Project and recognizes his, “prominence in the arena of national and international technology agendas, and the linking of higher education to those agendas.”
The EDUCAUSE Learning Initiative has just launched its 2018 Key Issues in Teaching and Learning Survey, so vote today: http://www.tinyurl.com/ki2018.
Each year, the ELI surveys the teaching and learning community in order to discover the key issues and themes in teaching and learning. These top issues provide the thematic foundation or basis for all of our conversations, courses, and publications for the coming year. Longitudinally they also provide the way to track the evolving discourse in the teaching and learning space. More information about this annual survey can be found at https://www.educause.edu/eli/initiatives/key-issues-in-teaching-and-learning.
ACADEMIC TRANSFORMATION (Holistic models supporting student success, leadership competencies for academic transformation, partnerships and collaborations across campus, IT transformation, academic transformation that is broad, strategic, and institutional in scope)
ACCESSIBILITY AND UNIVERSAL DESIGN FOR LEARNING (Supporting and educating the academic community in effective practice; intersections with instructional delivery modes; compliance issues)
ADAPTIVE TEACHING AND LEARNING (Digital courseware; adaptive technology; implications for course design and the instructor’s role; adaptive approaches that are not technology-based; integration with LMS; use of data to improve learner outcomes)
COMPETENCY-BASED EDUCATION AND NEW METHODS FOR THE ASSESSMENT OF STUDENT LEARNING (Developing collaborative cultures of assessment that bring together faculty, instructional designers, accreditation coordinators, and technical support personnel, real world experience credit)
DIGITAL AND INFORMATION LITERACIES (Student and faculty literacies; research skills; data discovery, management, and analysis skills; information visualization skills; partnerships for literacy programs; evaluation of student digital competencies; information evaluation)
EVALUATING TECHNOLOGY-BASED INSTRUCTIONAL INNOVATIONS (Tools and methods to gather data;data analysis techniques; qualitative vs. quantitative data; evaluation project design; using findings to change curricular practice; scholarship of teaching and learning; articulating results to stakeholders; just-in-time evaluation of innovations). here is my bibliographical overview on Big Data (scroll down to “Research literature”: https://blog.stcloudstate.edu/ims/2017/11/07/irdl-proposal/ )
EVOLUTION OF THE TEACHING AND LEARNING SUPPORT PROFESSION (Professional skills for T&L support; increasing emphasis on instructional design; delineating the skills, knowledge, business acumen, and political savvy for success; role of inter-institutional communities of practices and consortia; career-oriented professional development planning)
FACULTY DEVELOPMENT (Incentivizing faculty innovation; new roles for faculty and those who support them; evidence of impact on student learning/engagement of faculty development programs; faculty development intersections with learning analytics; engagement with student success)
GAMIFICATION OF LEARNING (Gamification designs for course activities; adaptive approaches to gamification; alternate reality games; simulations; technological implementation options for faculty)
INSTRUCTIONAL DESIGN (Skills and competencies for designers; integration of technology into the profession; role of data in design; evolution of the design profession (here previous blog postings on this issue: https://blog.stcloudstate.edu/ims/2017/10/04/instructional-design-3/); effective leadership and collaboration with faculty)
INTEGRATED PLANNING AND ADVISING FOR STUDENT SUCCESS (Change management and campus leadership; collaboration across units; integration of technology systems and data; dashboard design; data visualization (here previous blog postings on this issue: https://blog.stcloudstate.edu/ims?s=data+visualization); counseling and coaching advising transformation; student success analytics)
LEARNING ANALYTICS (Leveraging open data standards; privacy and ethics; both faculty and student facing reports; implementing; learning analytics to transform other services; course design implications)
LEARNING SPACE DESIGNS (Makerspaces; funding; faculty development; learning designs across disciplines; supporting integrated campus planning; ROI; accessibility/UDL; rating of classroom designs)
MICRO-CREDENTIALING AND DIGITAL BADGING (Design of badging hierarchies; stackable credentials; certificates; role of open standards; ways to publish digital badges; approaches to meta-data; implications for the transcript; Personalized learning transcripts and blockchain technology (here previous blog postings on this issue: https://blog.stcloudstate.edu/ims?s=blockchain)
MOBILE LEARNING (Curricular use of mobile devices (here previous blog postings on this issue:
MULTI-DIMENSIONAL TECHNOLOGIES (Virtual, augmented, mixed, and immersive reality; video walls; integration with learning spaces; scalability, affordability, and accessibility; use of mobile devices; multi-dimensional printing and artifact creation)
NEXT-GENERATION DIGITAL LEARNING ENVIRONMENTS AND LMS SERVICES (Open standards; learning environments architectures (here previous blog postings on this issue: https://blog.stcloudstate.edu/ims/2017/03/28/digital-learning/; social learning environments; customization and personalization; OER integration; intersections with learning modalities such as adaptive, online, etc.; LMS evaluation, integration and support)
ONLINE AND BLENDED TEACHING AND LEARNING (Flipped course models; leveraging MOOCs in online learning; course development models; intersections with analytics; humanization of online courses; student engagement)
OPEN EDUCATION (Resources, textbooks, content; quality and editorial issues; faculty development; intersections with student success/access; analytics; licensing; affordability; business models; accessibility and sustainability)
PRIVACY AND SECURITY (Formulation of policies on privacy and data protection; increased sharing of data via open standards for internal and external purposes; increased use of cloud-based and third party options; education of faculty, students, and administrators)
WORKING WITH EMERGING LEARNING TECHNOLOGY (Scalability and diffusion; effective piloting practices; investments; faculty development; funding; evaluation methods and rubrics; interoperability; data-driven decision-making)
David Demaine, S., Lemmer, C. A., Keele, B. J., & Alcasid, H. (2015). Using Digital Badges to Enhance Research Instruction in Academic Libraries. In B. L. Eden (Ed.), Enhancing Teaching and Learning in the 21st-Century Academic Library: Successful Innovations That Make a Difference (2015th ed.). Retrieved from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2882671
At their best, badges can create a sort of interactive e-resume.
the librarian may be invited into the classroom, or the students may be sent to the Iibrary for a single research lesson on databases and search tem1s- not enough for truly high-quality research. A better alternative may be that the professor require the students to complete a series of badges- designed, implemented, and managed by the librarian- that build thorough research skills and ultimately produce a better paper.
Meta- badges are s impl y badges that indicate comp letion o f multiple related badges.
Authentication (determining that the badge has not been altered) and validation/verification (checking that the badge has actually been earned and issued by the stated issuer) are major concerns. lt is also important, particularly in the academic context, to make sure that the badge does not come to replace the learning it represents. A badge is a symbol that other skills and knowledge exist in this individual’s portfolio of skills and talents. Therefore, badges awarded in the educational context must reflect time and effort and be based on vetted standards, or they will become empty symbols
Digital credentialing recognizes “learning of many kinds which are acquired beyond formal education institutions .. . ; it proliferates and disperses author- ity over what learning to recognize; and it provides a means of translation and commensuration across multiple spheres” (Oineck, 2012, p. I)
University digital badge projects are rarely a top-down undertaking. Typi- cally, digital badge programs arise from collaborative efforts “of people agi- tating from the middle” (Raths, 2013).
a learning management system (LMS) is never the solution to every problem in education. Edtech is just one part of the whole learning ecosystem and student experience.
Therefore, the next generation digital learning environment (NGDLE), as envisioned by EDUCAUSE in 2015 … Looking at the NGDLE requirements from an LMS perspective, I view the NGDLE as being about five areas: interoperability; personalization; analytics, advising, and learning assessment; collaboration; accessibility and universal design.
Interoperability
Content can easily be exchanged between systems.
Users are able to leverage the tools they love, including discipline-specific apps.
Learning data is available to trusted systems and people who need it.
The learning environment is “future proof” so that it can adapt and extend as the ecosystem evolves.
Personalization
The learning environment reflects individual preferences.
Departments, divisions, and institutions can be autonomous.
Instructors teach the way they want and are not constrained by the software design.
There are clear, individual learning paths.
Students have choice in activity, expression, and engagement.
Analytics, Advising, and Learning Assessment
Learning analytics helps to identify at-risk students, course progress, and adaptive learning pathways.
The learning environment enables integrated planning and assessment of student performance.
More data is made available, with greater context around the data.
The learning environment supports platform and data standards.
Collaboration
Individual spaces persist after courses and after graduation.
Learners are encouraged as creators and consumers.
Courses include public and private spaces.
Accessibility and Universal Design
Accessibility is part of the design of the learning experience.
The learning environment enables adaptive learning and supports different types of materials.
Learning design includes measurement rubrics and quality control.
The core analogy used in the NGDLE paper is that each component of the learning environment is a Lego brick:
The days of the LMS as a “walled garden” app that does everything is over.
Today many kinds of amazing learning and collaboration tools (Lego bricks) should be accessible to educators.
We have standards that let these tools (including an LMS) talk to each other. That is, all bricks share some properties that let them fit together.
Students and teachers sign in once to this “ecosystem of bricks.”
The bricks share results and data.
These bricks fit together; they can be interchanged and swapped at will, with confidence that the learning experience will continue uninterrupted.
Any “next-gen” attempt to completely rework the pedagogical model and introduce a “mash-up of whatever” to fulfil this model would fall victim to the same criticisms levied at the LMS today: there is too little time and training to expect faculty to figure out the nuances of implementation on their own.
The Lego metaphor works only if we’re talking about “old school” Lego design — bricks of two, three, and four-post pieces that neatly fit together. Modern edtech is a lot more like the modern Lego. There are wheels and rocket launchers and belts and all kinds of amazing pieces that work well with each other, but only when they are configured properly. A user cannot simply stick together different pieces and assume they will work harmoniously in creating an environment through which each student can be successful.
As the NGDLE paper states: “Despite the high percentages of LMS adoption, relatively few instructors use its more advanced features — just 41% of faculty surveyed report using the LMS ‘to promote interaction outside the classroom.'”
But this is what the next generation LMS is good at: being a central nervous system — or learning hub — through which a variety of learning activities and tools are used. This is also where the LMS needs to go: bringing together and making sense of all the amazing innovations happening around it. This is much harder to do, perhaps even impossible, if all the pieces involved are just bricks without anything to orchestrate them or to weave them together into a meaningful, personal experience for achieving well-defined learning outcomes.
Making a commitment to build easy, flexible, and smart technology
Working with colleges and universities to remove barriers to adopting new tools in the ecosystem
Standardizing the vetting of accessibility compliance (the Strategic Nonvisual Access Partner Program from the National Federation of the Blind is a great start)
Advancing standards for data exchange while protecting individual privacy
Building integrated components that work with the institutions using them — learning quickly about what is and is not working well and applying those lessons to the next generation of interoperability standards
Letting people use the tools they love [SIC] and providing more ways for nontechnical individuals (including students) to easily integrate new features into learning activities
My note: something just refused to be accepted at SCSU
Technologists are often very focused on the technology, but the reality is that the more deeply and closely we understand the pedagogy and the people in the institutions — students, faculty, instructional support staff, administrators — the better suited we are to actually making the tech work for them.
++++++++++++++++++++++
Under the Hood of a Next Generation Digital Learning Environment in Progress
The challenge is that although 85 percent of faculty use a campus learning management system (LMS),1 a recent Blackboard report found that, out of 70,000 courses across 927 North American institutions, 53 percent of LMS usage was classified as supplemental(content-heavy, low interaction) and 24 percent as complementary (one-way communication via content/announcements/gradebook).2 Only 11 percent were characterized as social, 10 percent as evaluative (heavy use of assessment), and 2 percent as holistic (balanced use of all previous). Our FYE course required innovating beyond the supplemental course-level LMS to create a more holistic cohort-wide NGDLE in order to fully support the teaching, learning, and student success missions of the program.The key design goals for our NGDLE were to:
Create a common platform that could deliver a standard curriculum and achieve parity in all course sections using existing systems and tools and readily available content
Capture, store, and analyze any generated learner data to support learning assessment, continuous program improvement, and research
Develop reports and actionable analytics for administrators, advisors, instructors, and students
Asynchronous eCourse beginning November 14, 2016 and continuing for 5 weeks (includes an extension of 1 week for Thanksgiving)
Estimated Hours of Learning: 24 Certificate of Completion available upon request
Learning outcomes
After participating in this course, you will be able to:
incorporate ever-evolving definitions of digital literacy into learning opportunities
draw upon a variety of digital resources to create digital-learning opportunities
seek additional resources that you can use in your continuing efforts to keep up with new developments in digital literacy in libraries and other learning organizations
What is digital literacy? Do you know how you can foster digital literacy through formal and informal learning opportunities for your library staff and users?
Supporting digital literacy still remains an important part of library staff members’ work, but sometimes we struggle to agree on a simple, meaningful definition of the term. In this four-week eCourse, training/learning specialist Paul Signorelli will begin by exploring a variety of definitions, focusing on work by a few leading proponents of the need to foster digital literacy among people of all ages and backgrounds. He will explore a variety of digital-literacy resources – including case studies of how we creatively approach digital-literacy learning opportunities for library staff and users, and will explore a variety of digital tools that will help to encourage further understanding of this topic.
Now, who is ready to build their digital-literacy skills and help their users become digital literate as well?
eCourse Outline
Part 1: Digital Literacy: Initial Definitions and Explorations
An overview of various definitions of digital literacy
Several components of digital literacy
Exploring Doug Belshaw’s extensive work on defining and fostering digital literacy
Part 2: Digital Literacy: Crap Detection and Other Skills and Tools
Exploring Howard Rheingold’s approach to crap detection and other digital literacy/net literacy skills
Participation, collaboration, creativity, and experimentation as digital-literacy skills
Building our digital-literacy toolkit
Part 3: Digital Literacy in Learning
The varying digital literacy needs of our youngest students, of teens, and of adults
Exploring various online resources supporting our digital-literacy training-teaching-learning efforts
The myth of the digital native
Part 4: Fostering Digital Literacy: Creating Within a Digital Environment
Creating a framework to promote digital literacy
Designing workshops and other learning opportunities
Keeping up in an evolving digital literacy landscape
How this eCourse Works
The eCourse begins on Monday, November 14, 2016. Your participation will require approximately six hours a week, at times that fit your schedule. All activities take place on the website, and you will be expected to:
Read, listen to or view online content
Post to online discussion boards
Complete weekly assignments or activities
Instructor Paul Signorelli will monitor discussion boards regularly during the four-week period, lead group discussions, and will also answer individual questions. All interaction will take place on the eCourse site, which will be available 24 hours a day, 7 days a week. It’s recommended that students log into the site on the first day of class or within a few days for an overview of the content and to begin the first lesson.
User Requirements
Participants will need regular access to a computer with an internet connection for online message boards participation, viewing online video, listening to streaming audio (mp3 files), and downloading and viewing PDFs and PowerPoint files. ALA Editions eCourses are fully compatible with Windows and MacOs.
About the Instructor
Paul Signorelli, co-author of Workplace Learning & Leadership with Lori Reed, is a San Francisco-based writer, trainer, presenter, and consultant exploring, fostering, and documenting innovations in learning. Having earned an MLIS through the University of North Texas (with an emphasis on online learning), he remains active in the American Library Association, the New Media Consortium (educational technology), and the Association for Talent Development (formerly the American Society for Training & Development).
My note: Finally ALA is addressing a huge gap. Namely, letting conservative librarians dress information literacy with the appearance of “digital literacy.”
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more on digital literacy in this IMS blog:
