Thursday, September 4, 2014
Wednesday, September 3, 2014
Quantified Self : Higher Education New Market Opportunity - Tracking and Measuring Consumers Behaviors and Activities
Consumers Self Tracking of Their Behaviors and Actions People have always demonstrated interest in learning about themselves by tracking and measuring their behaviors and activities. Quantified self technologies tap into this interest in the form of mobile apps, wearable devices, and cloud-based services that make the data collection process much easier.
Quantified Self - New Market Growth Opportunity
Quantified self describes the phenomenon of consumers being able to closely track data that is relevant to their daily activities through the use of technology. The emergence of wearable devices on the market such as watches, wristbands, and necklaces that are designed to automatically collect data are helping people manage their fitness, sleep cycles, and eating habits.
New Mobile Applications - Future is Now!
Mobile apps also share a central role in this idea by providing easyto-read dashboards for consumers to view and analyze their personal metrics. Empowered by these insights, many individuals now rely on these technologies to improve their lifestyle and health. Today’s apps not only track where a person goes, what they do, and how much time they spend doing it, but now what their aspirations are and when those can be accomplished.
Capturing Life Every 30 Seconds
Novel devices, such as the Memoto, a camera worn around the neck that is designed to capture an image every half minute are enabling people to track their lives automatically. As more people rely on their mobile devices to monitor their daily activities, personal data is becoming a larger part of everyday life.
Bridge: Quantified Self - Self Actualization
People have always demonstrated interest in learning about themselves by tracking and measuring their behaviors and activities. Students already spend time in formal classroom settings gathering data about themselves or research topics. Quantified self technologies tap into this interest in the form of mobile apps, wearable devices, and cloud-based services that make the data collection process much easier.
Improving Health and Fitness
Popular incarnations of the quantified self movement have materialized in the form of health, fitness, and life streaming tools. The Fitbit, for example, is a small wristband that tracks wearers’ daily activities, including sleep patterns, steps taken, and calories burned.
Real-Time Tracking / Sleep and Diet
Through wireless and automatic syncing between the Fitbit and smartphones, tablets, and laptops, users can see real-time progress across their devices. The Jawbone Up wristband employs similar functionalities, allowing wearers to track sleep, movement, and dietary information that is automatically populated in the accompanying mobile UP app.
New Social Media Opportunity
The experience can easily turn into a social one as people can share their accomplishments with other users and team up to track and achieve specific goals. Other wearables that have garnered worldwide attention have deeply integrated self-tracking tools, including Google Glass and iWatch, but the high prices — and in some cases, the low availability — of these devices have some pundits concerned that quantified self technologies are a luxury for the upper class.
Early Adoption in Higher Education Institutions
The Quantified Self Institute, for example, is an initiative by the Hanze University of Applied Sciences in the Netherlands that brings international and regional partners together to conduct research on different methods of self-tracking. This organization is well positioned to lead the quantified self movement into higher education institutions with recommendations on effective applications.
Relevance for Teaching, Learning, or Creative Inquiry
With the growing use of mobile apps and wearable technology, individuals are creating an exponentially increasing amount of data. The quantified self movement is breaking ground by integrating these data streams in interesting ways. Self quantifiers, for example, can create healthier living plans after monitoring their sleep, exercise, diet, and other important patterns.
People and Pets
The new mobile app Whistle even enables people to do the same for their dogs. It is imaginable that if test scores and reading habits gleaned from learning analytics could be combined with other lifestyle tracking information, these large data sets could reveal how environmental changes improve learning outcomes.
Mobilizing Medical Care
Quantified self technology also has the potential to shape the future of some industries. In the medical field, for instance, doctors are using not only traditional medicine but also data that individuals self-collect, such as heart rate, blood pressure, and sugar levels.
Anticipating Health Problems
Advancements in the field could enable computers to search for patterns and help physicians more accurately diagnose or anticipate health problems before patients step foot into the building. Educators at the moment can only hypothesize about a new era of the academic quantified self, but interest is strong and growing.
Privacy Concerns
One of the current barriers for the mainstream adoption of this technology revolves around privacy concerns. The quantified self movement is about people sharing what they learn about themselves for the greater good, but there is a vulnerability to exposing personal information that will need to be addressed over the next four to five years.
Cost / Benefit Analysis
This could include a cost/benefit analysis about what data should be collected, what data should be shared, who should be responsible for making those decisions, and how to build the most effective and safe online communities of practice.
Johnson, L., Adams Becker, S., Estrada, V., Freeman, A. (2014). NMC Horizon Report: 2014 Higher Education Edition. Austin, Texas: The New Media Consortium.
The Future of Higher Education: Reshaping Universities Through 3D Printing
How 3D Is Accelerating Learning
One of the most significant aspects of 3D printing for education is that it enables more authentic exploration of objects that may not be readily available to universities. For example, anthropology students at Miami University can handle and study replicas of fragile artifacts, like ancient Egyptian vases, that have been scanned and printed at the university’s 3D printing lab.
3D Printing or Rapid Prototyping
Known in industrial circles as rapid prototyping,
3D printing refers to technologies that construct physical objects from threedimensional (3D) digital content such as 3D modeling software, computer-aided design (CAD) tools, computer-aided tomography (CAT), and X-ray crystallography.
Prints Tangible Object From a 3D Design
A 3D printer builds a tangible model or prototype from the electronic file, one layer at a time, through an extrusion-like process using plastics and other flexible materials, or an inkjet-like process to spray a bonding agent onto a very thin layer of fixable powder.
Any Desired Object - Created Layer by Layer
The deposits created by the machine can be applied very accurately to build an object from the bottom up, layer by layer, with resolutions that, even in the least expensive machines, are more than sufficient to express a large amount of detail.
Moving Parts - No Problem
The process even accommodates moving parts within the object. Using different materials and bonding agents, color can be applied, and parts can be rendered in plastic, resin, metal, tissue, and even food. This technology is commonly used in manufacturing to build prototypes of almost any object (scaled to fit the printer, of course) that can be conveyed in three dimensions.
Relevance for Teaching, Learning, or Creative Inquiry
One of the most significant aspects of 3D printing for education is that it enables more authentic exploration of objects that may not be readily available to universities. For example, anthropology students at Miami University can handle and study replicas of fragile artifacts, like ancient Egyptian vases, that have been scanned and printed at the university’s 3D printing lab.
Examine Rare Fossils Without Damaging
Similarly, at the GeoFabLab at Iowa State University, geology students and amateur enthusiasts can examine 3D printed specimens of rare fossils, crystals, and minerals without risk of damaging these precious objects.
Harvard Leverages 3D Printing for Microbatteries
Some of the most compelling progress of 3D printing in higher education comes from institutions that are inventing new objects. A team at Harvard University and University of Illinois at Urbana-Champaign recently printed lithium-ion microbatteries that are the size of a grain of sand and can supply power to very small devices such as medical implants and miniature cameras.
3D Printing - Medical Research Applications
In the field of medical research, innovation at the microscopic level is seeing increasing growth. Researchers at the University of Texas at Austin are caging bacteria in 3D-printed enclosures in order to closely approximate actual biological environments for the study of bacterial infections. Scientists at the University of Liverpool are developing 3D-printable synthetic skin that will closely resemble an individual’s age, gender, and ethnicity.
3D Gaining Traction in Higher Education
As 3D printing gains traction in higher education, universities are beginning to create dedicated spaces to nurture creativity and stimulate intellectual inquiry around this emerging technology.
Universities Already Implementing 3D Learning
Examples include North Carolina State University’s Hunt Library Makerspace, the 3DLab at the University of Michigan’s Art, Architecture, and Engineering Library, and the Maker Lab in the Humanities at the University of Victoria in British Columbia, Canada. These spaces, equipped with the latest 3D scanners, 3D printers, 3D motion sensors, and laser cutters, not only enable access to tools, but they also encourage collaboration within a community of makers and hackers.
Johnson, L., Adams Becker, S., Estrada, V., Freeman, A. (2014). NMC Horizon Report: 2014 Higher Education Edition. Austin, Texas: The New Media Consortium.
Learning Analytics - Leveraging Web-Tracking Tools to Improve Student Engagement
Applying web-tracking tools to improve student engagement and provide a high-quality, personalized experience for learners.
Using Big Data to Predict Student Behavior
Learning analytics is an educational application of “big data,” a branch of statistical analysis that was originally developed as a way for businesses to analyze commercial activities, identify spending trends, and predict consumer behavior.
Web-Tracking Tools to Tailor Learning Experience
As web-tracking tools became more sophisticated, many companies built vast reserves of information to individualize the consumer experience. Education is embarking on a similar pursuit into new ways of applying to improve student engagement and provide a high-quality, personalized experience for learners.
Learning Analytics - Informed Decisions
Learning analytics research uses data analysis to inform decisions made on every tier of the education system, leveraging student data to deliver personalized learning, enable adaptive pedagogies and practices, and identify learning issues in time for them to be solved.
Improving Educational Assessment With "Big Data"
Other hopes are that the analysis of education-related data on a much larger scale than ever before can provide policymakers and administrators with indicators of local, regional, and national education progress that can allow programs and ideas to be measured and improved.
Tracking and Ranking - Online Content Accessed
Adaptive learning data is already providing insights about student interactions with online texts and courseware. One pathway to creating the level of data needed for effective learning analytics is seen in creating student devices that will capture data on how, when, and in what context they are used, and thus begin to build school-level, national, and even international datasets that can be used to deeply analyze student learning, ideally as it happens.
Interest of Education Policymakers, Leaders and Practitioners
Since the topic first appeared three years ago in the far-term horizon of the NMC Horizon Report: 2011 Higher Education Edition, learning analytics has steadily captured the interest of education policymakers, leaders, and practitioners.
Same Tailored Consumer Experience as Amazon, Netflix and Google
Big data are now being used to personalize every experience users have on commercial websites, and education systems, companies, and publishers see tremendous potential in the use of similar data mining techniques to improve learning outcomes. The idea is to use data to adapt instruction to individual learner needs in real-time in the same way that Amazon, Netflix, and Google use metrics to tailor recommendations to consumers.
Transforming Education from "One Size Fits All"
Analytics can potentially help transform education from a standard one-size-fits-all delivery system into a responsive and flexible framework, crafted to meet the students’ academic needs and interests. For many years, these ideas have been a central component of adaptive software, programs that make carefully calculated adjustments to keep learners motivated as they master concepts or encounter stumbling blocks.
Visual and Analytic Reports
New kinds of visualizations and analytical reports are being developed to guide administrative and governing bodies with empirical evidence as they target areas for improvement, allocate resources, and assess the effectiveness of programs, schools, and entire school systems. As online learning environments increasingly accommodate thousands of students, researchers and companies are looking at very granular data around student interactions, building on the tools of web analytics.
Stanford Pioneering Education "Big Data" Analysis
Pearson Learning Studio, for example, provides an LMS infrastructure that is aggregating data from the millions of learners using their systems, with the aim of enabling school leaders and national policy makers to more effectively design personalized learning paths. Similarly, a group at Stanford University is examining vast datasets generated by online learning environments.
Stanford Lytic Lab - Analytics Dashboard
These efforts are taking place through the Stanford Lytic Lab, where researchers, educators, and visiting experts are currently building an analytics dashboard that will help online instructors track student engagement in addition to conducting a study of peer assessment in a MOOC on human-computer interaction, based on 63,000 peer-graded assignments.
Bill & Melinda Gates - $200,000 Funding
In April 2013, the Bill & Melinda Gates Foundation awarded Stanford more than $200,000 in funding to support the Learning Analytics Summer Institute, which provided professional training to researchers in the field.
Sophisticated Web-Tracking at Leading Institutions
Sophisticated web-tracking tools are already being used by leading institutions to capture precise student behaviors in online courses, recording not only simple variables such as time spent on a topic, but also much more nuanced information that can provide evidence of critical thinking, synthesis, and the depth of retention of concepts over time.
New Analytic Tools to Manage Growing Complexity
As behavior specific data is added to an ever-growing repository of student-related information, the analysis of educational data is increasingly complex, and many statisticians and researchers are working to develop new kinds of analytical tools to manage that complexity.
Predictive Analytics Reporting Framework
The most visible current example of a wide-scale analytics project in higher education is the Predictive Analytics Reporting Framework, which is overseen by the Western Interstate Commission for Higher Education (WICHE), and largely funded by the Bill & Melinda Gates Foundation.
16 Institutions = 1.7M Student Records + 8.1M Course Records
The 16 participating institutions represent the public, private, traditional, and progressive spheres of education. According to the WICHE website, they have compiled over 1,700,000 student records and 8,100,000 course level records in efforts to better understand student loss and student momentum.
Social Media - Researching Online Discussions
Companies such as X-Ray Research are conducting research in online discussion groups to determine which behavioral variables are the best predictors of student performance. The tools reflect the potential of analytics to develop early warning systems based on metrics that make predictions using linguistic, social, and behavioral data. Similarly, studies at universities are proving that pedagogies informed by analytics can prove the quality of interaction taking place online.
Solution: Visualization - Improving Student Engagement and Discussion
At Simon Fraser University in British Columbia researchers applied analytics to solve an issue that past experiments revealed — discussion forums used for online courses were not supporting productive engagement or discussion. They developed a Visual Discussion Forum in which students could visualize the structure and depth of the discussion, based on the number of threads extending from their posts. Learners in this study were also able to easily detect which topics needed more of their attention.
Johnson, L., Adams Becker, S., Estrada, V., Freeman, A. (2014). NMC Horizon Report: 2014 Higher Education Edition. Austin, Texas: The New Media Consortium.
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