Instructional Design focuses on instruction, User Experience Design focuses on the user, and Learning Experience Design focuses on the learner. This is not to say that IDs don’t care about learners, or that UX designers do not work on educational products, or that LXDs spend no time thinking about instruction or users. The difference lies in who these designers orient their process towards the most – instruction, user, learner.
ID as a field tends to be more scientific and organized, following academic frameworks
UX tends to be both scientific and artistic in its approach. UX designers are informed by academic theories and frameworks, but are also flexible and artistic in finding engaging, intuitive solutions to usability issues.
LXD tends to be more artistic than scientific. While LX designers care about the learning process deeply though understanding of related learning theories and cognitive processes of learners, their primary focus is on designing visually stunning, useful, and engaging learning experiences.
IDs are typically working on products such as Courses, e-learning modules, curriculum, workshops. UX designers are typically working on products such as mobile apps, websites, digital games, software. LXDs are typically working on all these things – courses, apps, AND other forms of learning experiences which could take the form of museum exhibits, summer camps, AR interactive booklets, children’s books, movies, toys and games or any other medium that can be used to generate a learning experience.
software tools are just like paintbrushes, they don’t make an artist. Some popular paintbrushes for IDs are Adobe Captivate, Articulate Storyline, Brainshark. For UX designers some popular tools are Adobe XD, Sketch, Figma, Balsamiq. For LXDs everything Adobe Creative Cloud has to offer – and many other ID/UX tools as well (depending on what the experience design needs) come in handy.
For IDs, one of the popular frameworks is ADDIE: Analyze, Design, Development, Implement, Evaluation
For UX designers, a popular framework quoted often is Design Thinking: Empathize, Define, Ideate, Prototype, Test
For LXDs, Neils floor outlines this LXD process: Question, Research, Design, Build, Test, Improve, Launch
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.
The CX programs of the future will be holistic, predictive, precise, and clearly tied to business outcomes
Why use a survey to ask customers about their experiences when data about customer interactions can be used to predict both satisfaction and the likelihood that a customer will remain loyal, bolt, or even increase business?
AI is being used to monitor students and their work. The most prominent uses of AI in higher education are attached to applications designed to protect or preserve academic integrity through the use of plagiarism-detection software (60%) and proctoring applications (42%) (see figure 1).
The chatbots are coming! A sizable percentage (36%) of respondents reported that chatbots and digital assistants are in use at least somewhat on their campuses, with another 17% reporting that their institutions are in the planning, piloting, and initial stages of use (see figure 2). The use of chatbots in higher education by admissions, student affairs, career services, and other student success and support units is not entirely new, but the pandemic has likely contributed to an increase in their use as they help students get efficient, relevant, and correct answers to their questions without long waits.Footnote10 Chatbots may also liberate staff from repeatedly responding to the same questions and reduce errors by deploying updates immediately and universally.
AI is being used for student success tools such as identifying students who are at-risk academically (22%) and sending early academic warnings (16%); another 14% reported that their institutions are in the stage of planning, piloting, and initial usage of AI for these tasks.
Nearly three-quarters of respondents said that ineffective data management and integration (72%) and insufficient technical expertise (71%) present at least a moderate challenge to AI implementation. Financial concerns (67%) and immature data governance (66%) also pose challenges. Insufficient leadership support (56%) is a foundational challenge that is related to each of the previous listed challenges in this group.
Current use of AI
Chatbots for informational and technical support, HR benefits questions, parking questions, service desk questions, and student tutoring
Research applications, conducting systematic reviews and meta-analyses, and data science research (my italics)
Library services (my italics)
Recruitment of prospective students
Providing individual instructional material pathways, assessment feedback, and adaptive learning software
Proctoring and plagiarism detection
Student engagement support and nudging, monitoring well-being, and predicting likelihood of disengaging the institution
Robot colleges have de-skilled instruction by paying teams of workers, some qualified and some not, to write content, while computer programs perform instructional and management tasks. Learning management systems with automated instruction programs
The assumption is that managing work this way significantly reduces costs, and it does, at least in the short and medium terms. However, instructional costs are frequently replaced by marketing and advertising expenses to pitch the schools to prospective students and their families.
The business model in higher education for reducing labor power and faculty costs is not reserved to for-profit colleges. Community colleges also rely on a small number of full-time faculty and armies of low-wage contingent labor.
In some cases, colleges and universities, including many brand name schools, utilize outside companies, online program managers (OPMs), to run their online programs, with OPMs like 2U taking up as much as 60 percent of the revenues.
Stanley Fish, the literary theorist and veteran administrator, and a visiting professor of law at Yeshiva University, in New York City, thinks that most if not all academic-freedom controversies are simply unnecessary. His argument boils down to academic freedom as “the freedom to do the academic job” — no more, no less.
The assumption antagonists make, says Tiede, is that if a professor expresses a view in a public forum, she or he must be indoctrinating students. But to take punitive action, he says, a college should have to prove that there is inappropriate indoctrination in the pedagogical setting.
academic freedom diminishes not so much as a result of oppression but as stable academic jobs simply disappear. To balance their books, colleges are increasingly culling tenure lines and consolidating or eliminating departments. To fill the gap, in remote or hybrid programs, they share courses or even entire academic majors from other institutions.
“This measure will provide additional options for students and the recently unemployed to engage with higher education across a wider range of fields, which will help further the position of the nation and our workforce to move out of the economic downturn,” a department spokesman said.
“There is some crossover between the terms ‘micro-credential’ and ‘short course’; both are generally something shorter than a full qualification. The short courses are a type of micro-credential. The short course is a credit-bearing micro-credential, meaning that it can be used to ‘stack’ into a full qualification at a later time.”
” The Australian Cyber Security Growth Network said the cyber security workforce had grown by 4000 to 26,500 since 2017. The sector grew by 6 per cent a year, compared with overall national growth of 2 per cent a year.”
Sixty-eight percent of students were also in favor of some combination of in-person and online courses. On the faculty side, 57 percent said they would prefer teaching hybrid courses post-pandemic — slightly more than those who preferred teaching fully online.
both students and faculty agreed: Roughly two-thirds across the board said they would like to use more tech and digital course materials in the future.
Virtual Reality (VR) training tools are here to help, ensuring that healthcare professionals can be trained remotely, immersively, and more thoroughly than traditional methods for both front-line medicine and in specialist procedures.
Their VR platform uses personalized prediction software and “gamification and varied content formats to engage users and embed knowledge”, and has been used to “deliver typically labor-intensive training quickly and at scale”
“VR enables medics to immerse themselves in these infrequent scenarios, and can reduce skill fade by 52% and improve learning retention rates by up to 75% (compared to 10% for traditional methods),”
Simulated virtual learning can also ease the psychological burden of notoriously intensive medical training and place more emphasis on wellbeing.
