Children who use smartphones, tablets, and video games for more than seven hours a day are more likely to experience premature thinning of the cortex, the outermost layer of the brain that processes thought and action, a 2018 study found. https://t.co/OJe6ZTBVkx
But others say banning laptops can be counterproductive, arguing these devices can create opportunity for students to discover more information during class or collaborate. And that certain tools and technologies are necessary for learners who struggle in a traditional lecture format.
Flanigan, who studies self-regulation, or the processes students use to achieve their learning goals, began researching digital distraction after confronting it in the classroom as a graduate instructor.
Digital distraction tempts all of us, almost everywhere. That’s the premise of Digital Minimalism: Choosing a Focused Life in a Noisy World by Cal Newport, an associate professor of computer science at Georgetown University.
The professor is upset. The professor has taken action, by banning laptops.
Bruff, whose next book, Intentional Tech: Principles to Guide the Use of Educational Technology in College Teaching, is set to be published this fall, is among the experts who think that’s a mistake. Why? Well, for one thing, he said, students are “going to have to graduate and get jobs and use laptops without being on Facebook all day.” The classroom should help prepare them for that.
When Volk teaches a course with 50 or 60 students, he said, “the idea is to keep them moving.”Shifting the focal point away from the professor can help, too. “If they are in a small group with their colleagues,” Volk said, “very rarely will I see them on their laptops doing things they shouldn’t be.”
Professors may not see themselves as performers, but if they can’t get students’ attention, nothing else they do matters. “Learning doesn’t happen without attention,” said Lang, who is writing a book about digital distraction, Teaching Distracted Minds.
One aspect of distraction Lang plans to cover in his book is its history. It’s possible, he said, to regard our smartphones as either too similar or dissimilar from the distractions of the past. And it’s important, he said, to remember how new this technology really is, and how much we still don’t know about it.
++++++++++
Study: Use of digital devices in class affects students’ long-term retention of information
A new study conducted by researchers at Rutgers University reveals that students who are distracted by texts, games, or videos while taking lecture notes on digital devices are far more likely to have their long-term memory affected and to perform more poorly on exams, even if short-term memory is not impacted, EdSurge reports.
Exam performance was not only poorer for students using the devices, but also for other students in classes that permitted the devices because of the distraction factor, the study found.
After conducting the study, Arnold Glass, the lead researcher, changed his own policy and no longer allows his students to take notes on digital devices.
A nationally representative Gallup poll conducted in March showed that 42% of K-12 teachers feel that the use of digital devices in the classroom are “mostly helpful” for students, while only 28% feel they are “mostly harmful.” Yet 69% of those same teachers feel the devices have a harmful impact on student mental health and 55% feel they negatively affect student physical health.
According to a 2016 study of college students, student waste about 20% of their class time for “non-class” purposes — texting, emailing, or using social media more than 11 times in a typical day. In K-12, increased dependence on digital devices often interferes with homework completion as well.
Though the new study focused on long-term retention, past studies have also shown that indicate a negative correlation between use of digital devices during class and exam scores. A 2015 study by the London School of Economics revealed that pupils in schools that banned cell phones performed better on exams and that the differences were most notable for low-performing students.
Using laptops in class harms academic performance, study warns. Researchers say students who use computers score half a grade lower than those who write notes
findings, published in the journal Economics of Education Review in a paper, based on an analysis of the grades of about 5,600 students at a private US liberal arts college, found that using a laptop appeared to harm the grades of male and low-performing students most significantly.
While the authors were unable to definitively say why laptop use caused a “significant negative effect in grades”, the authors believe that classroom “cyber-slacking” plays a major role in lower achievement, with wi-fi-enabled computers providing numerous distractions for students.
High schoolers assigned a laptop or a Chromebook were more likely to take notes in class, do internet research, create documents to share, collaborate with their peers on projects, check their grades and get reminders about tests or homework due dates.
Blended Learning – the idea of incorporating technology into the every day experience of education – can save time, raise engagement, and increase student retention.
Lets face it, our students are addicted to their phones. Like…drugs addicted. It is not just a bad habit, it is hard wired in their brains(literally) to have the constant stimulation of their phones.
If you are interested in the research, there is a lot out there to read about how it happens and how bad it is.
a Scientific American article published about a recent study of nomophobia – on adults (yes, many of us are addicted too).
Because the questionnaire data comprised both Likert scales and open questions, they were analyzed quantitatively and qualitatively. Textual data (open responses) were qualitatively analyzed by coding: each segment (e.g. a group of words) was assigned to a semantic reference category, as systematically and rigorously as possible. For example, “Using an iPad in class really motivates me to learn” was assigned to the category “positive impact on motivation.” The qualitative analysis was performed using an adapted version of the approaches developed by L’Écuyer (1990) and Huberman and Miles (1991, 1994). Thus, we adopted a content analysis approach using QDAMiner software, which is widely used in qualitative research (see Fielding, 2012; Karsenti, Komis, Depover, & Collin, 2011). For the quantitative analysis, we used SPSS 22.0 software to conduct descriptive and inferential statistics. We also conducted inferential statistics to further explore the iPad’s role in teaching and learning, along with its motivational effect. The results will be presented in a subsequent report (Fievez, & Karsenti, 2013)
The 20th century notion of conducting a qualitative research by an oral interview and then processing manually your results had triggered in the second half of the 20th century [sometimes] condescending attitudes by researchers from the exact sciences.
The reason was the advent of computing power in the second half of the 20th century, which allowed exact sciences to claim “scientific” and “data-based” results.
One of the statistical package, SPSS, is today widely known and considered a magnificent tools to bring solid statistically-based argumentation, which further perpetuates the superiority of quantitative over qualitative method.
At the same time, qualitative researchers continue to lag behind, mostly due to the inertia of their approach to qualitative analysis. Qualitative analysis continues to be processed in the olden ways. While there is nothing wrong with the “olden” ways, harnessing computational power can streamline the “olden ways” process and even present options, which the “human eye” sometimes misses.
Below are some suggestions, you may consider, when you embark on the path of qualitative research.
excellent guide to the structure of a qualitative research
Palys, T., & Atchison, C. (2012). Qualitative Research in the Digital Era: Obstacles and Opportunities. International Journal Of Qualitative Methods, 11(4), 352-367.
Palys and Atchison (2012) present a compelling case to bring your qualitative research to the level of the quantitative research by using modern tools for qualitative analysis.
1. The authors correctly promote NVivo as the “jaguar’ of the qualitative research method tools. Be aware, however, about the existence of other “Geo Metro” tools, which, for your research, might achieve the same result (see bottom of this blog entry).
2. The authors promote a new type of approach to Chapter 2 doctoral dissertation and namely OCR-ing PDF articles (most of your literature as of 2017 is mostly either in PDF or electronic textual format) through applications such as
Abbyy Fine Reader, https://www.abbyy.com/en-us/finereader/
OmniPage, http://www.nuance.com/for-individuals/by-product/omnipage/index.htm
Readirus http://www.irislink.com/EN-US/c1462/Readiris-16-for-Windows—OCR-Software.aspx
The text from the articles is processed either through NVIVO or related programs (see bottom of this blog entry). As the authors propose: ” This is immediately useful for literature review and proposal writing, and continues through the research design, data gathering, and analysis stages— where NVivo’s flexibility for many different sources of data (including audio, video, graphic, and text) are well known—of writing for publication” (p. 353).
In other words, you can try to wrap your head around huge amount of textual information, but you can also approach the task by a parallel process of processing the same text with a tool.
+++++++++++++++++++++++++++++
Here are some suggestions for Computer Assisted / Aided Qualitative Data Analysis Software (CAQDAS)for a small and a large community applications):
text mining: https://en.wikipedia.org/wiki/Text_mining Text mining, also referred to as text data mining, roughly equivalent to text analytics, is the process of deriving high-quality information from text. High-quality information is typically derived through the devising of patterns and trends through means such as statistical pattern learning. Text mining usually involves the process of structuring the input text (usually parsing, along with the addition of some derived linguistic features and the removal of others, and subsequent insertion into a database), deriving patterns within the structured data, and finally evaluation and interpretation of the output. https://ischool.syr.edu/infospace/2013/04/23/what-is-text-mining/
Qualitative data is descriptive data that cannot be measured in numbers and often includes qualities of appearance like color, texture, and textual description. Quantitative data is numerical, structured data that can be measured. However, there is often slippage between qualitative and quantitative categories. For example, a photograph might traditionally be considered “qualitative data” but when you break it down to the level of pixels, which can be measured.
word of caution, text mining doesn’t generate new facts and is not an end, in and of itself. The process is most useful when the data it generates can be further analyzed by a domain expert, who can bring additional knowledge for a more complete picture. Still, text mining creates new relationships and hypotheses for experts to explore further.
Pros and Cons of Computer Assisted Qualitative Data Analysis Software
+++++++++++++++++++++++++
more on quantitative research:
Asamoah, D. A., Sharda, R., Hassan Zadeh, A., & Kalgotra, P. (2017). Preparing a Data Scientist: A Pedagogic Experience in Designing a Big Data Analytics Course. Decision Sciences Journal of Innovative Education, 15(2), 161–190. https://doi.org/10.1111/dsji.12125
++++++++++++++++++++++++
literature on quantitative research:
St. Cloud State University MC Main Collection – 2nd floor
AZ195 .B66 2015
p. 161 Data scholarship in the Humanities
p. 166 When Are Data?
Philip Chen, C. L., & Zhang, C.-Y. (2014). Data-intensive applications, challenges, techniques and technologies: A survey on Big Data. Information Sciences, 275(Supplement C), 314–347. https://doi.org/10.1016/j.ins.2014.01.015
the Sloan Consortium defined hybrid courses as those that “integrate online with traditional face-to-face class activities in a planned, pedagogically valuable manner.” Educators probably disagree on what qualifies as “pedagogically valuable,” but the essence is clear: Hybrid education uses online technology to not just supplement, but transform and improve the learning process.
meetings with Chief Learning Officers, talent management leaders, and vendors of next generation learning tools.
The corporate L&D industry is over $140 billion in size, and it crosses over into the $300 billion marketplace for college degrees, professional development, and secondary education around the world.
Digital Learning does not mean learning on your phone, it means “bringing learning to where employees are.” In other words, this new era is not only a shift in tools, it’s a shift toward employee-centric design. Shifting from “instructional design” to “experience design” and using design thinking are key here.
1) The traditional LMS is no longer the center of corporate learning, and it’s starting to go away.
LMS platforms were designed around the traditional content model, using a 17 year old standard called SCORM. SCORM is a technology developed in the 1980s, originally intended to help companies like track training records from their CD-ROM based training programs.
the paradigm that we built was focused on the idea of a “course catalog,” an artifact that makes sense for formal education, but no longer feels relevant for much of our learning today.
not saying the $4 billion LMS market is dead, but the center or action has moved (ie. their cheese has been moved). Today’s LMS is much more of a compliance management system, serving as a platform for record-keeping, and this function can now be replaced by new technologies.
We have come from a world of CD ROMs to online courseware (early 2000s) to an explosion of video and instructional content (YouTube and MOOCs in the last five years), to a new world of always-on, machine-curated content of all shapes and sizes. The LMS, which was largely architected in the early 2000s, simply has not kept up effectively.
2) The emergence of the X-API makes everything we do part of learning.
In the days of SCORM (the technology developed by Boeing in the 1980s to track CD Roms) we could only really track what you did in a traditional or e-learning course. Today all these other activities are trackable using the X-API (also called Tin Can or the Experience API). So just like Google and Facebook can track your activities on websites and your browser can track your clicks on your PC or phone, the X-API lets products like the learning record store keep track of all your digital activities at work.
3) As content grows in volume, it is falling into two categories: micro-learning and macro-learning.
4) Work Has Changed, Driving The Need for Continuous Learning
Why is all the micro learning content so important? Quite simply because the way we work has radically changed. We spend an inordinate amount of time looking for information at work, and we are constantly bombarded by distractions, messages, and emails.
5) Spaced Learning Has Arrived
If we consider the new world of content (micro and macro), how do we build an architecture that teaches people what to use when? Can we make it easier and avoid all this searching?
“spaced learning.”
Neurological research has proved that we don’t learn well through “binge education” like a course. We learn by being exposed to new skills and ideas over time, with spacing and questioning in between. Studies have shown that students who cram for final exams lose much of their memory within a few weeks, yet students who learn slowly with continuous reinforcement can capture skills and knowledge for decades.
6) A New Learning Architecture Has Emerged: With New Vendors To Consider
One of the keys to digital learning is building a new learning architecture. This means using the LMS as a “player” but not the “center,” and looking at a range of new tools and systems to bring content together.
On the upper left is a relatively new breed of vendors, including companies like Degreed, EdCast, Pathgather, Jam, Fuse, and others, that serve as “learning experience” platforms. They aggregate, curate, and add intelligence to content, without specifically storing content or authoring in any way. In a sense they develop a “learning experience,” and they are all modeled after magazine-like interfaces that enables users to browse, read, consume, and rate content.
The second category the “program experience platforms” or “learning delivery systems.” These companies, which include vendors like NovoEd, EdX, Intrepid, Everwise, and many others (including many LMS vendors), help you build a traditional learning “program” in an open and easy way. They offer pathways, chapters, social features, and features for assessment, scoring, and instructor interaction. While many of these features belong in an LMS, these systems are built in a modern cloud architecture, and they are effective for programs like sales training, executive development, onboarding, and more. In many ways you can consider them “open MOOC platforms” that let you build your own MOOCs.
The third category at the top I call “micro-learning platforms” or “adaptive learning platforms.” These are systems that operate more like intelligent, learning-centric content management systems that help you take lots of content, arrange it into micro-learning pathways and programs, and serve it up to learners at just the right time. Qstream, for example, has focused initially on sales training – and clients tell me it is useful at using spaced learning to help sales people stay up to speed (they are also entering the market for management development). Axonify is a fast-growing vendor that serves many markets, including safety training and compliance training, where people are reminded of important practices on a regular basis, and learning is assessed and tracked. Vendors in this category, again, offer LMS-like functionality, but in a way that tends to be far more useful and modern than traditional LMS systems. And I expect many others to enter this space.
Perhaps the most exciting part of tools today is the growth of AI and machine-learning systems, as well as the huge potential for virtual reality.
7) Traditional Coaching, Training, and Culture of Learning Has Not Gone Away
8) A New Business Model for Learning
he days of spending millions of dollars on learning platforms is starting to come to an end. We do have to make strategic decisions about what vendors to select, but given the rapid and immature state of the market, I would warn against spending too much money on any one vendor at a time. The market has yet to shake out, and many of these vendors could go out of business, be acquired, or simply become irrelevant in 3-5 years.
9) The Impact of Microsoft, Google, Facebook, and Slack Is Coming
The newest versions of Microsoft Teams, Google Hangouts and Google Drive, Workplace by Facebook, Slack, and other enterprise IT products now give employees the opportunity to share content, view videos, and find context-relevant documents in the flow of their daily work.
We can imagine that Microsoft’s acquisition of LinkedIn will result in some integration of Lynda.com content in the flow of work. (Imagine if you are trying to build a spreadsheet and a relevant Lynda course opens up). This is an example of “delivering learning to where people are.”
10) A new set of skills and capabilities in L&D
It’s no longer enough to consider yourself a “trainer” or “instructional designer” by career. While instructional design continues to play a role, we now need L&D to focus on “experience design,” “design thinking,” the development of “employee journey maps,” and much more experimental, data-driven, solutions in the flow of work.
lmost all the companies are now teaching themselves design thinking, they are using MVP (minimal viable product) approaches to new solutions, and they are focusing on understanding and addressing the “employee experience,” rather than just injecting new training programs into the company.
Using Ursula Le Guin short story “The Ones Who Walk Away from Omelas,” has allowed Fruchter to make his computer science math classes entirely project-based, which in turn draws the interest of kids who might not have otherwise liked computer programming.
teaching computer programming with fiction into a curriculum called StoryCode. He classifies STEM fiction into three categories: explicit, science fiction and implicit STEM texts.
“When you can call a line of code a spell, then you are getting somewhere,” Fruchter said. After all, isn’t computer code basically modern magic?
+++++++++++++
Ursula K. Le Guin on Art, Storytelling, and the Power of Language to Transform and Redeem
https://www.brainpickings.org/2018/01/30/ursula-k-le-guin-walking-on-the-water/
The paradox, of course, is that because our notion of history is rooted in the written record, words are both our instrument of truth and our weapon of distortion. We use them both to reveal and to conceal — a duality which Hannah Arendt so memorably dissected in her meditation on lying in politics.
Storytelling is a tool for knowing who we are and what we want, too. If we never find our experience described in poetry or stories, we assume that our experience is insignificant.
Do you know any fact checking sites? Can you identify spot sponsored content? Do you understand syndication? What do you understand under “media literacy,” “news literacy,” “information literacy.” https://blog.stcloudstate.edu/ims/2017/03/28/fake-news-resources/
what is social media (examples). why is called SM? why is so popular? what makes it so popular?
use SM tools for your research and education:
– Determining your topic. How to?
Digg http://digg.com/, Reddit https://www.reddit.com/ , Quora https://www.quora.com
Facebook, Twitter – hashtags (class assignment 2-3 min to search)
LinkedIn Groups
YouTube and Slideshare (class assignment 2-3 min to search)
Flickr, Instagram, Pinterest for visual aids (like YouTube they are media repositories)
As social networking platforms proliferate and more interactions take place digitally, there are more opportunities for propagation of misinformation, copyright infringement, and privacy breaches.
Empathy as a critical quality for leaders was popularized in Daniel Goleman’s work about emotional intelligence. It is also a core component of Karol Wasylyshyn’s formula for achieving remarkable leadership. Elizabeth Borges, a women’s leadership program organizer and leadership consultant, recommends a particular practice, cognitive empathy.
What is library leadership? a library leader is defined as the individual who articulates a vision for the organization/task and is able to inspire support and action to achieve the vision. A manager, on the other hand, is the individual tasked with organizing and carrying out the day-to-day operational activities to achieve the vision.Work places are organized in hierarchical and in team structures. Managers are appointed to administer business units or organizations whereas leaders may emerge from all levels of the hierarchical structures. Within a volatile climate the need for strong leadership is essential.
Leaders are developed and educated within the working environment where they act and co-work with their partners and colleagues. Effective leadership complies with the mission and goals of the organization. Several assets distinguish qualitative leadership:
Mentoring. Motivation. Personal development and skills. Inspiration and collaboration. Engagement. Success and failure. Risk taking. Attributes of leaders.
Leaders require having creative minds in shaping strategies and solving problems. They are mentors for the staff, work hard and inspire them to do more with less and to start small and grow big. Staff need to be motivated to work at their optimum performance level. Leadership entails awareness of the responsibilities inherent to the roles of a leader. However, effective leadership requires the support of the upper management.
p. 36. Developments in Technology for Academic and Research Libraries
Digital strategies are not so much technologies as they are ways of using devices and software to enrich teaching, learning, research and information management, whether inside or outside the library. Effective Digital strategies can be used in both information and formal learning; what makes them interesting is that they transcended conventional ideas to create something that feels new, meaningful, and 21st century.
enabling technologies
this group of technologies is where substantive technological innovation begins to be visible.
Internet technologies.
learning technologies
social media technologies. could have been subsumed under the consumer technology category, but they have become so ever-present and so widely used in every part of society that they have been elevated to their own category. As well-established as social media is, it continues to evolve at a rapid pace, with new ideas, tools, and developments coming online constantly.
Visualization technologies. from simple infographics to complex forms of visual data analysis. What they have in common is that they tap the brain’s inherent ability to rapidly process visual information, identify patterns, and sense order in complex situations. These technologies are a growing cluster of tools and processes for mining large data sets, exploring dynamic processes, and generally making the complex simple.
p. 38 Big Data
Big data has significant implications for academic libraries in their roles as facilitators and supporters of the research process. big data use in the form of digital humanities research. Libraries are increasingly seeking to recruit for positions such as research data librarians, data curation specialists, or data visualization specialists
p. 40 Digital Scholarship Technologies
digital humanities scholars are leveraging new tools to aid in their work. ubiquity of new forms of communication including social media, text analysis software such as Umigon is helping researchers gauge public sentiment. The tool aggregates and classifies tweets as negative, positive, or neutral.
p. 42 Library Services Platforms
Diversity of format and materials, in turn, required new approaches to content collection and curation that were unavailable in the incumbent integrated library systems (ILS), which are primarily designed for print materials. LSP is different from ILS in numerous ways. Conceptually, LSPs are modeled on the idea of software as a service (SaaS),which entails delivering software applications over the internet.
p. 44 Online Identity.
incorporated the management of digital footprints into their programming and resources
simplify the idea of digital footprint as“data about the data” that people are searching or using online. As resident champions for advancing digital literacy,304 academic and research libraries are well-positioned to guide the process of understanding and crafting online identities.
Libraries are becoming integral players in helping students understand how to create and manage their online identities. website includes a social media skills portal that enables students to view their digital presence through the lens in which others see them, and then learn how they compare to their peers.
beacons are another iteration of the IoT that libraries have adopted; these small wireless devices transmit a small package of data continuously so that when devices come into proximity of the beacon’s transmission, functions are triggered based on a related application.340 Aruba Bluetooth low-energy beacons to link digital resources to physical locations, guiding patrons to these resources through their custom navigation app and augmenting the user experience with location-based information, tutorials, and videos.
students and their computer science professor have partnered with Bavaria’s State Library to develop a library app that triggers supplementary information about its art collection or other points of interest as users explore the space
AECT-OTP Webinar: Digital Badges and Micro-Credentials for the Workplace
Time: Mar 27, 2017 1:00 PM Central Time (US and Canada)
Learn how to implement digital badges in learning environments. Digital badges and micro-credentials offer an entirely new way of recognizing achievements, knowledge, skills, experiences, and competencies that can be earned in formal and informal learning environments. They are an opportunity to recognize such achievements through credible organizations that can be integrated in traditional educational programs but can also represent experience in informal contexts or community engagement. Three guiding questions will be discussed in this webinar: (1) digital badges’ impact on learning and assessment, (2) digital badges within instructional design and technological frameworks, and (3) the importance of stakeholders for the implementation of digital badges.
Dirk Ifenthaler is Professor and Chair of Learning, Design and Technology at University of Mannheim, Germany and Adjunct Professor at Curtin University, Australia. His previous roles include Professor and Director, Centre for Research in Digital Learning at Deakin University, Australia, Manager of Applied Research and Learning Analytics at Open Universities, Australia, and Professor for Applied Teaching and Learning Research at the University of Potsdam, Germany. He was a 2012 Fulbright Scholar-in-Residence at the Jeannine Rainbolt College of Education, at the University of Oklahoma, USA
Directions to connect via Zoom Meeting:
Join from PC, Mac, Linux, iOS or Android: https://zoom.us/j/8128701328
Or iPhone one-tap (US Toll): +14086380968,8128701328# or +16465588656,8128701328#
Or Telephone:
Dial: +1 408 638 0968 (US Toll) or +1 646 558 8656 (US Toll)
Meeting ID: 812 870 1328
International numbers available: https://zoom.us/zoomconference?m=EedT5hShl1ELe6DRYI58-DeQm_hO10Cp
Each student learns differently and assessment is not linear. Learning for different students can be a longer or shorter path.
representation graph:
assessment comes before badges
what are credentials:
how well i can show my credentials: can i find it, can i translate it, issuer, earner, achievement description, date issued.
the potential to become an alternative credentialing system to link directly via metadata to validating evidence of educational achievements.
DB is not an assessment, it is the ability to demonstrate the assessment.
They are a motivational mechanism, supporting alternative forms of assessment, a way to credentialize learning, charting learning pathways, support self-reflection and planning
When we learn something outside the comfort zone, we attempt to acquire knowledge or skills in an area where we’re lacking. Part of the discomfort derives from learning something we anticipate will be difficult. We have no idea how to do it, or we think it requires abilities we don’t have or have in meager amounts. Moreover, poor performance or outright failure lurk as likely possibilities.
I wonder if learning outside the comfort zone isn’t especially difficult for faculty. Theoretically, it shouldn’t be. We’ve devoted years to learning, but most of what we know resides in one area. We’re experts at learning more about what we already know and love. And we’re used to having our learning expertise recognized—by students, colleagues, and sometimes even at home. However, plop us down in a discipline unlike our own, task us with learning a skill we don’t have, and suddenly, we look and act exactly like our students. And that’s the very reason this kind of learning has all sorts of positive implications for teaching. It’s good every now and then to be reacquainted with feeling stupid.
My note. Eventually, I had to tell a [already departured] library director: it is better to throw stones in the swamp of mediocrity then to sink slowly into it. To the objection of my colleague that throwing stones does NOT improve the situation, I could only say: making ripples until someone more diplomatic will draw the attention means more then just slowing sinking into the swamp of mediocrity. That swamp is determined by the inability / unwillingness of faculty the leave their comfort zone.
In regard to the teacher, who has students memorize and recite a poem – I will never forget Herr Klenske, who made us memorize in 10th grade of high school “Erlkoening” (http://ingeb.org/Lieder/werreite.html). It made us hate him as much, as now I, at least, appreciate his unique approach to fostering to high school students persistence and will.
Top 10 IT Issues, 2017: Foundations for Student Success
Susan Grajek and the 2016–2017 EDUCAUSE IT Issues Panel Tuesday, January 17, 2017http://er.educause.edu/articles/2017/1/top-10-it-issues-2017-foundations-for-student-successThe 2017 EDUCAUSE Top 10 IT Issues are all about student success
Developing a holistic, agile approach to reduce institutional exposure to information security threats
That program should encompass people, process, and technologies:
Educate users
Develop processes to identify and protect the most sensitive data
Implement technologies to encrypt data and find and block advanced threats coming from outside the network via from any type of device
Who Outside the IT Department Should Care Most about This Issue?
End-users, to understand how to avoid exposing their credentials
Unit heads, to protect institutional data
Senior leaders, to hold people accountable
Institutional leadership, to endorse, fund, and advocate for good information security
Issue #2: Student Success and Completion
Effectively applying data and predictive analytics to improve student success and completion
Predictive analytics allows us to track trends, discover gaps and inefficiencies, and displace “best guess” scenarios based on implicitly developed stories about students.
Issue #3: Data-Informed Decision Making
Ensuring that business intelligence, reporting, and analytics are relevant, convenient, and used by administrators, faculty, and students
Higher education information systems generate vast amounts of data daily (including the classroom/LMS). This potentially rich source of information is underused. Even though most institutions have created reports, dashboards, and other distillations of data, these are not necessarily useful or used to inform strategic objectives such as student success or institutional efficiency.
Issue #4: Strategic Leadership
Repositioning or reinforcing the role of IT leadership as a strategic partner with institutional leadership
CIOs have two challenges in this regard. The first is getting to the table. Contemporary requirements for IT leaders position them well for strategic leadership.18 Those requirements include expertise in management and business practices, project portfolio management, negotiation, and change leadership. However, business-savvy CIOs can alienate some academics, particularly those opposed to administrators as leaders. Worse, not all CIOs are well-equipped for a position at the executive table.
Issue #5: Sustainable Funding
Developing IT funding models that sustain core services, support innovation, and facilitate growth
Two complications have deepened the IT funding challenge in recent years. The first is that information technology is now incontrovertibly core to the mission and function of colleges and universities. The second complication is that at most institutions, digital investments and technology refreshes have been funded with capital expenditures. Yet IT services and infrastructure are moving outside the institution, generally to the cloud, and cloud funding depends on ongoing expenditures rather than one-time investments.
Issue #6: Data Management and Governance
Improving the management of institutional data through data standards, integration, protection, and governance
Data management and governance is not an IT issue. It requires a broad, top-down approach because all departments need to buy in and agree. All stakeholders (data owners as well as IR, IT, and institutional leaders) must collaboratively develop a common set of data definitions and a common understanding of what data is needed, in what format, and for what purposes. This coordination, or governance, will enable constituents to communicate with confidence about the data (e.g., “the single version of truth”) and the standards (e.g., APLU, IPEDS, CDS) under which it is collected.
Institutions often choose to approach data management from three perspectives: (1) accuracy, (2) usability, and (3) privacy. The IT organization has a role to play in creating and maintaining data warehouses, integrating systems to facilitate data exchange, and maintaining standards for data privacy and security.
Issue #7: Higher Education Affordability
Prioritizing IT investments and resources in the context of increasing demand and limited resources
Uncoordinated, redundant expenditures supplant other needed investments, such as consistent classroom technology or dedicated information security staff. Planning needs to occur at the institutional or departmental level, but it also needs a place to coalesce and be assessed regionally, nationally, and in some cases, globally, because there isn’t enough money to do everything that institutional leaders, faculty, and others want or even need to do. Public systems are making some headway in sharing services, but for the most part, local optimization supersedes collaboration and compromise.
Issue #8: Sustainable Staffing
Ensuring adequate staffing capacity and staff retention as budgets shrink or remain flat and as external competition grows
As institutions become more dependent on their IT organizations, IT organizations are more dependent on the expertise and quality of their workforce. New hires need to be great hires, and great staff need to want to stay. Each new hire can change the culture and effectiveness of the IT organizations
Issue #9: Next-Gen Enterprise IT
Developing and implementing enterprise IT applications, architectures, and sourcing strategies to achieve agility, scalability, cost-effectiveness, and effective analytics
Buildings should outlive alumni; technology shouldn’t. IT leaders are examining core enterprise applications, including ERPs (traditionally, suites of financial, HR, and student information systems) and LMSs, for their ability to meet current and future needs.
Issue #10: Digital Transformation of Learning
Collaborating with faculty and academic leadership to apply technology to teaching and learning in ways that reflect innovations in pedagogy and the institutional mission
According to Michael Feldstein and Phil Hill, personalized learning applies technology to three processes: content (moving content delivery out of the classroom and allowing students to set their pace of learning); tutoring (allowing interactive feedback to both students and faculty); and contact time (enabling faculty to observe students’ work and coach them more).
+++++++++++++++++++++
more on IT in this IMS blog https://blog.stcloudstate.edu/ims?s=information+technology
