liberal arts

More people than ever are trying to get into college classes in Illinois prisons. Getting a seat hasn’t gotten any easier. [West]

On 09/22/2026, in colleges, communities of practice, community colleges, liberal arts, society, sociology, student-related, United States, universities, by Daniel Christian

More people than ever are trying to get into college classes in Illinois prisons. Getting a seat hasn’t gotten any easier. — from college-inside.beehiiv.com by Charlotte West
The college waitlist in Illinois has grown 80% since last year, with 3,700 people waiting and 2,600 enrolled.

Excerpt from highlights:

Illinois waitlists are outpacing seats. The college waitlist has grown 80% since last year, with 3,700 people waiting and 2,600 enrolled. Read [the] full story, published with WBEZ Chicago’s Prisoncast!
Wisconsin’s prisons hit a record population, straining access to programs, reports our partner Wisconsin Watch.
Delaware Tech is ending its prison education program after graduating current students, reports the Delaware News Journal.

How to Reduce Cognitive Load in Digital Lessons — from educationtechnologysolutions.com by etsmagazine

A digital lesson can be beautifully designed and still make learning unnecessarily hard.

Students may be asked to watch a video, remember an instruction, find a link, switch tabs, interpret unfamiliar icons and submit a response—all before they have dealt with the idea the lesson was meant to teach.

That friction is often mistaken for rigour. It is not. Productive difficulty comes from thinking about the content. Avoidable difficulty comes from navigating the lesson.

The goal is not to make learning effortless. It is to spend students’ limited attention on the knowledge and skill that matter.

The above article links to:

Managing cognitive load optimises learning — from edresearch.edu.au
Implications for policymakers

Several items re: the changes needed within higher education

On 09/14/2026, in 21st century, adjunct faculty, business side of he, career development, change, changing business models, collaboration, colleges, communities of practice, community colleges, corporate / business world, cost of getting a degree, culture, dangers of the status quo, entrepreneurship, expectations, experimentation, faculty/staff, future of higher education, game-changing environment, generational differences, higher education, ideas, innovation, instructional design, leadership, learning ecosystem, Learning Experience Design, liberal arts, lifelong learning, new business models, reinvent, skills, society, staying relevant, strategy, student-related, surviving, teaching & learning, traditional / tradition, United States, universities, youth, by Daniel Christian

Below are several items that were either mentioned by Matt Tower or I came across them via offshoots of items that he linked to:

Future Universities Alliance Names Inaugural Innovation Sandbox Cohort — from provost.duke.edu
Program incubated by Duke brings together higher education innovators from 23 countries for year-long peer exchange

The Future Universities Alliance has selected 49 institutions from 23 countries for the inaugural cohort of its Innovation Sandbox, a 12-month peer learning program for higher education leaders advancing ambitious, institution-level innovation.The cohort brings together founders of new universities, administrators and faculty leading high-stakes changes within established institutions, and leaders of proven models exploring how their innovations can travel to new contexts. Participants were chosen through a competitive process that drew applicants from around the world in its inaugural year.

A makeover for college: No gym, no meal plan and two years of work — from npr.org by Jon Marcus

An entirely new college is being planned here to change not only how higher education is delivered, but at what price. It also proposes to highlight ways the current business model no longer works, as evidenced by the 152 colleges and universities that have closed or merged since 2016, and the 442 others that a new projection says are at risk.

So deeply entrenched are the problems confronting higher education that a growing chorus of innovators says the easiest way to fix them is to begin again from scratch.

All undergraduates should get work-based learning, v-cs say — from timeshighereducation.com by Jack Grove. NOTE: this item is behind a paywall.
Bold plan to support graduate employment would require placements for 1.4 million students annually

“Using AI to create the practice opportunities online students need” [Miller Perkins] + other items re: AI in our learning ecosystems

On 08/19/2026, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, assessment, business, career development, colleges, communications, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, Emotion, engineering, experimentation, faculty/staff, game-changing environment, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, leadership, learning, learning agents, learning ecosystem, Learning Experience Design, learning spaces, liberal arts, mathematics, online learning, personalized/customized learning, productivity / tips and tricks, professional development, student-related, teachers, teaching & learning, technologies for your home, tools, training / L&D, UK, United States, universities, vendors, workplace, youth, by Daniel Christian

Using AI to create the practice opportunities online students need— from timeshighereducation.com by Kathy Miller Perkins
For disciplines that depend on interpersonal skills such as communication, leadership, negotiation and mediation, AI can provide elusive experiential learning, particularly in asynchronous environments

What if AI’s greatest educational value lies not in generating answers but in generating experiences?

The result surprised me. Students did not simply interact with the AI, they meaningfully engaged with it. Many reported that the experience felt valuable precisely because the simulated conversation partner pushed back. Unlike classmates who sometimes hesitate to challenge one another, the AI consistently maintained its position. Students had to work harder, listen more carefully and apply the communication strategies they had spent weeks learning. And, importantly, they practised.

Here’s how to show students what responsible AI use looks like — from timeshighereducation.com by Andrew Firr and Alex Fenton
Well-designed assessments can highlight generative AI’s limitations, where it can provide support and what responsible practice looks like. Andrew Firr and Alex Fenton offer strategies

We have been exploring ways to offer this in our Level 7 module for MSc engineering management students, many of whom come from the Global South. Assessment is built around a practical design problem: students examine how a real campus process operates, where delays occur, evidence they observe and how a feasible redesign might improve the system – in a 3,000-word essay.

They can use AI for planning and providing clarity, but not for generating the evidence on which the analysis rests. Invented observations, measurements, screenshots or unverifiable citations are prohibited. The assessment design reinforces this through a case study, diagram, fact-checking exercise and a short AI use statement.

Requiring an AI use statement encourages students to reflect on their processes. We ask which tool they used, how they used it, how they checked the output and which parts of the work depended on their own evidence and judgement. It reminds them that evidence must be theirs and that citations must be manually verified.

Slow math: Kids may learn more when AI makes them review mistakes — from hechingerreport.org by Jill Barshay and Kristin Fasiang
A randomized experiment involved more than 6,000 Tennessee middle school students learning fractions

In an experiment involving more than 6,000 middle schoolers in Tennessee, students learned slightly more math when an AI tutor walked them through their mistakes and then required them to demonstrate the same skill correctly three times in a row before moving on.
…
The winning combination wasn’t the addition of AI tutoring alone, but AI tutoring plus repetition, with the idea that students needed to stick with the skill to demonstrate some level of mastery. The students who practiced math with this AI-enhanced “mastery learning” approach scored about 3 percentage points higher than students receiving conventional computerized instruction. The advantage was small.

I Built a Team of AI Bots That Write Feedback Better than Me. Here’s How. — from drphilippahardman.substack.com by Dr Philippa Hardman
Aka, how to make learners love AI-assisted feedback, rather than loathe it.

This wasn’t hidden from the cohort. For reasons I’ll come to below, I always tell my cohorts at the very start that an AI assistant will be helping me draft their feedback. The aim wasn’t to remove me from the process, but to find out whether AI could help me to deliver feedback at a volume and quality that I simply couldn’t maintain without AI.

Spoiler: the experiment worked — but not for the reason I expected. In this post, I’ll share exactly what I built, tell you how to build a version for your course and reveal the three conditions that decide whether learners trust AI-assisted feedback or quietly stop reading it.

TL;DR: the spec for my feedback assistant is long not because the model needs persuading, but because it’s where my judgement lives. Every rule in it is a decision AI would otherwise make by itself, with limited expertise. A spec doesn’t make the model smarter — it makes expertise and judgement legible enough for the model to follow.

Of the five stages of AI grief, some managers are stuck in denial— from timeshighereducation.com by Shadi Mohamed
Acceptance is not surrender. It is about getting beyond a policing obsession and rethinking what assessment aims to measure, says Shadi Mohamed

In that moment of institutional blindness, it struck me: universities are not merely struggling with a technological adoption curve. They are grieving the demise of the modern university’s economic and institutional logic.

To understand the scale of this threat posed by AI, consider what the internet did to journalism. Newspapers thrived by bundling together classified advertising with quick news hits, sports scores and opinion columns, using that reliable revenue to fund the expensive social necessity of investigative reporting. The rise of internet advertising did not kill journalism outright but it shattered the bundle, leaving the expensive core product without its historical financial engine.

Universities operate on a similar logic, bundling content delivery, assessment, credentialling, research and professional formation. But generative AI is now commodifying the most visible parts of that package. When AI can deliver personalised explanations instantly and generate the essays and reports we use to measure student capability, the traditional degree loses its role in the labour market as a proxy for understanding. If the bundle breaks, the economic model that funds our deeper purposes is in peril.

Bring playfulness into teaching for collaboration and creativity — from timeshighereducation.com by Isabel Taurel
In learning, playfulness is often overlooked. Yet it could be key to embedding the soft, ‘human’ skills students will need for the future. Isabel Taurel shows how

The same is true in higher education. Students who are able to rediscover a playful mindset leave the classroom with something far more valuable than a good grade. They develop confidence, are more willing to contribute unusual ideas and learn how to adapt when the unexpected happens. These are precisely the qualities employers increasingly tell us they need.

Yet the creative and cultural industries demonstrate their growing value. Success increasingly depends on collaboration, adaptability and creative confidence, all qualities that are fostered through arts-based learning and increasingly sought in every kind of workplace.

Playfulness isn’t a distraction from serious learning. It’s one of the most powerful ways we have of preparing students for a future in which the most valuable skills may be the most deeply human ones: listening, presence, responsiveness, imagination and a capacity to create meaning together.

Student Voices: Technology as a Future Learning Partner — from campustechnology.com by Mary Grush
A Q&A with Eli Blouin and Mark Frydenberg

Key Takeaways

With advanced technologies, we’re moving from accessing learning resources to participating in technology learning partnerships.
Technology learning partners participate in the learning process by asking questions and giving feedback, not just information search results.
Tomorrow’s technology learning partners will understand the whole learner — including knowledge gaps and personal learning style.
Student experiences with AI and other technologies today will inform the next generation of human/machine learning partners.

Grush: What do you think may be among the most meaningful changes in, say, the next five years?

Blouin: When I think of what will improve in the next five years — and I truly believe it’s where we’re ultimately heading — I think it will be the technology learning partner’s ability to gain a full picture of the learner. The technology will be able to take absurd amounts of context — and data — and understand the learner as a whole: where their gaps are, what they need to learn, how they learn, and how to create content tailored to a particular student. In an instant it would be able to assess, to test knowledge, and know the student as a whole person. That would be an ideal learning partner.

The 5 college majors students are betting on right now [Borden]

On 08/10/2026, in adjunct faculty, business, colleges, community colleges, computer science, drama/theater, faculty/staff, higher education, learning ecosystem, liberal arts, music, psychology, student-related, teaching & learning, United States, universities, by Daniel Christian

The 5 college majors students are betting on right now — from linkedin.com by Taylor Border

The AI-native university, AI literacy, AI and accessibility + other items re: AI in our learning ecosystems

On 07/22/2026, in 21st century, 24x7x365 access, accessibility / UDL, Artificial Intelligence/Agents/LLMs/and Related, colleges, communities of practice, community colleges, corporate / business world, corporate universities / corporate training, data related items, education technology, emerging technologies, experimentation, faculty/staff, game-changing environment, generational differences, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, learning, learning ecosystem, Learning Experience Design, liberal arts, lifelong learning, personalized/customized learning, productivity / tips and tricks, student-related, teachers, teaching & learning, training / L&D, trends, United States, universities, by Daniel Christian

AI & Accessibility: 5 Practical Ways to Use LLMs to Support Inclusive Learning — from learningguild.com by Dr. Athena Joyce Stanley (B.A., M.A.E., Ph.D.)

The following strategies focus on how instructional designers can design for accessibility by embedding or enabling AI-supported tools within learning experiences. These approaches move beyond access to content and begin to support access to understanding, expression, and participation.
…
Personalized Clarification Through AI Copilots
Learners often need additional explanation, but may hesitate to ask questions in live sessions or require more individualized support.

Instructional designers can integrate AI copilots, LLM-powered conversational interfaces, into learning environments to provide on-demand clarification. These tools can act as digital coaches, helping learners understand concepts through simplified explanations and relevant examples.

This approach supports learners who benefit from additional processing time and personalized guidance.

Sample Prompt (for IDs Configuring Copilot Behavior)
You are a workplace learning coach.

Explain the following concept in a clear, simple way:

- Use plain language
- Provide one practical, job-relevant example
- Avoid jargon unless necessary (and define it if used)

Then ask one follow-up question to check for understanding.

Jeff’s posting on LinkedIn.

Teaching AI Literacy with Susan Ray — from intentionalteaching.buzzsprout.com by Derek Bruff and Susan Ray

Per Derek Bruff:
In my conversation with Susan, we talk about that syllabus activity, as well as the AI transparency journals she asks her students to keep during her courses. We also talk about how her personal background prepared her to navigate the challenges and opportunities that AI has posed to her teaching, how she approaches assessing student learning in this age of AI—especially in her online asynchronous courses—and much more.

Building the AI-Native University: Student Success and Lifelong Learning — from coursera.org

In this episode, you’ll discover:

Why building an AI-native campus requires a data-first foundation
How to build an “achievement architecture” for lifelong success
How faculty-built AI tutors cut one program’s course attrition from 40% to 10%
What it means to be a lifelong learning companion

We’re Raising the First AI Generation. They’re Pushing Back. (Rebecca Winthrop, Brookings) — from humanistxyz.substack.com by Allison Dulin Salisbury
“Young people harbor real anger about AI because they’re already experiencing its consequences in their schools, relationships, job prospects, and feeds.”

As Rebecca told me:

“Kids harbor real anger. They’re pissed about climate impacts. They’re upset about job prospects. They’re outraged about AI being used to plagiarize writing and produce counterfeit artwork. Their relationships are being affected, and they’re seeing deepfakes in their feeds.”

Our conversation explores what follows from taking those concerns seriously. We discuss cognitive stunting, the case for small, purpose-built AI models over frontier models in education, why students should spend far more time in explorer mode, and how schools can cultivate agency, curiosity, and independent thinking in an age of AI.

The interview ends with one of Rebecca’s most practical recommendations: every school should have a student AI council, not as a symbolic gesture, but with real influence over the tools their schools adopt, the ways they’re used, and the data students are asked to hand over.

Every generation of technology seems to relearn the same lesson: build with people, not for them. AI should be no exception.

Why recruiters can’t find workers and new grads can’t find jobs (it’s not AI) — from washingtonpost.com by Jon Marcus
Experts say a major labor shortage looms because of population shifts and a mismatch between new graduates’ skills and employers’ needs.

Recent college graduates complain they can’t find entry-level jobs because artificial intelligence is taking over.

Yet, tech recruiter Matt Walsh and other experts say the growth of AI and the struggle to find entry-level work mask a bigger problem: The United States is facing what’s projected to become the largest labor shortage in its history.

In sectors such as semiconductor production, the problem isn’t AI or too few jobs, said Walsh, CEO of the Phoenix-based search firm Blue Signal.

“It’s ridiculous,” he said. “There just aren’t enough people.”

Economists warn that the worsening labor problem, due in part to a skills shortage and population shifts, will be vast and reach beyond tech.

Among the trends that have been leading to this moment: a mismatch between the careers college graduates are pursuing and the jobs employers are struggling to fill. Far fewer students are majoring in health care fields than are needed to meet demand, for instance.

“We have pumped so many young people into business and finance” when what’s really in demand are graduates in other fields, Hetrick said. “It’s like a factory producing these workers like widgets, even though society is saying, ‘We really don’t need them.’ And the factory just keeps pumping them out.”

Higher Education Can’t Wait for the Future to Arrive (Lev Gonick, Arizona State University) [Salisbury]

On 07/07/2026, in 21st century, 24x7x365 access, career development, change, changing business models, collaboration, colleges, community colleges, competency-based learning/education, faculty/staff, future, future of higher education, game-changing environment, heutagogy, higher education, innovation, instructional design, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, liberal arts, more voice more choice more control, skills, society, student-related, teaching & learning, trends, United States, universities, vision/possibilities, by Daniel Christian

Higher Education Can’t Wait for the Future to Arrive (Lev Gonick, Arizona State University) — from humanistxyz.substack.com by Allison Dulin Salisbury
“The biggest risk we face as a sector is assuming we can wait out AI.”

We have an opportunity right now to reorient the university around student experience—not as an aspiration, but as a necessity. I’m calling this shift TechEd, which I explore in detail in my LinkedIn series The TechEd Revolution.

AI poses a fundamental shift in how technology might empower students to own their discovery and educational journey, and to drastically reduce the friction that makes college so unappealing to so many.

To that end, we need to urgently redesign systems and opportunities around skills and competencies. That work should be far more advanced than it currently is. And one of the hardest challenges is rethinking how we operate as a workforce in academia.

The Current State of Play: AI in Higher Education and the Road Ahead [Gamby, Kil, Koblic, LeBlanc, Moldoveanu & Siemens]

On 06/29/2026, in 21st century, Artificial Intelligence/Agents/LLMs/and Related, business side of he, career development, change, colleges, community colleges, corporate / business world, culture, emerging technologies, ethics, expectations, experimentation, faculty/staff, game-changing environment, generational differences, higher education, ideas, innovation, instructional design, intelligent systems, IT in HE, leadership, learning, learning agents, learning ecosystem, Learning Experience Design, liberal arts, morals/values, organizational change, pace of change, parents/guardians, personalized/customized learning, policy, reinvent, relationships, skills, society, strategy, student-related, teaching & learning, trends, United States, universities, vision/possibilities, by Daniel Christian

The Current State of Play: AI in Higher Education and the Road Ahead — from er.educause.edu by Tanya Gamby, David Kil, Rachel Koblic, Paul LeBlanc, Mihnea Moldoveanu and George Siemens

The conventional explanation for this strategic vacuum points to the speed of technological change; it is moving too fast for institutions built for deliberation. That is true. . . and incomplete. The deeper issue is cultural. In fairness to higher education, many industries are struggling to keep up with the pace of AI advances. Higher education, however, moves even more slowly and is not built for the kind of transformational speed now underway. Getting institutional stakeholders to engage, rethink the work, and move faster may be the central challenge facing presidents and chancellors today, and that’s saying a lot in such volatile times.

From DSC:
I highlighted this paragraph because it hits upon the key item involved here — culture. “The deeper issue is cultural.” I think that’s a very true statement.

Part of the culture and setup of many institutions includes giving faculty members full rein of their classes and their departments. Faculty members have a great deal of leeway and power in how they do things. So trying to get X faculty members to get on board — including the Department Chairs — is not an easy task.

Another part of culture involves being willing — or not — to change in the first place. Some institutions are like Google and are used to making changes and being more innovative. But those institutions are not the norm, at least in my experience. And this doesn’t even address another topic the article mentioned — the pace of these changes. As the authors point out, most institutions of traditional higher education are not equipped to deal with the current pace of change (nor are most of our other types of institutions and our corporations as well).

I’m going to end this posting with another brief excerpt from the article:

Institutions rooted in human relationships, committed to truth-seeking, and oriented toward the full development of persons play a central role. AI cannot manufacture the experience of mattering to another human being. It cannot model intellectual courage or ethical discernment. It cannot build the kind of community in which students discover who they are and what they believe.

These are not small things. They are, in fact, the things most worth doing. At their best, colleges and universities are not only preparing better workers but shaping individuals and strengthening society.

AI’s getting expensive for us these days

On 06/23/2026, in Adobe, Artificial Intelligence/Agents/LLMs/and Related, business side of he, change, changing business models, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, cost of getting a degree, Daniel S. Christian, education technology, emerging technologies, experimentation, faculty/staff, funding / grants, game-changing environment, graphics, higher education, human-computer interaction (HCI), innovation, intelligent systems, IT in HE, learning ecosystem, liberal arts, library / librarians, new business models, Open AI, platforms, student-related, teaching & learning, technologies for your home, tools, trends, United States, universities, by Daniel Christian

From DSC:
I used to be able to bring up Firefly on the web and use it “free” of charge — I didn’t have to go purchase tokens or credits. (I was actually paying for the Adobe Creative Cloud Pro suite of tools…so it wasn’t really free.)

But the other day I was trying to figure out what the latest pricing is at Adobe with that suite of tools and the use of credits for AI-based features. They say Adobe Creative Cloud Pro users get 4000 credits a month. Well, I have that suite and I’m still getting prompted to purchase credits. Firefly for individuals runs from $9.99 (2,000 credits/month) to $139.91 per month (50,000 credits per month). Not inexpensive, right? Below are other items along these lines.

The Era of Affordable AI Is Over. What Comes Next? — from builtin.com by Ameya Kanitkar
AI providers are shifting to usage-based billing for their services. AI fluency is more important now than ever to make the most of your tools to avoid unnecessary spending.

Summary: The era of cheap, flat-rate AI is ending as providers shift to usage-based billing. Every prompt now carries a direct cost, turning casual use into major budget risks, as seen when Uber depleted its 2026 AI budget in four months. Leaders must now track real-time value and token efficiency.

For a brief window, companies had access to the most transformative technology in a generation at the cost of a streaming subscription. Tools like ChatGPT put AI within reach of anyone with a browser and time for experimentation, while GitHub Copilot came in at just $10 a month, with token costs remaining relatively low. In the beginning, experimentation felt cost-effective, easy and relatively low-risk.

But that era is ending, and the bill is coming due faster than a lot of enterprise leaders anticipated.

The Fable of AI in Education — from downes.ca by Stephen Downes
Marc Watkins, Rhetorica, Jun 17, 2026

Tokenomics will be a hot topic of discussion on university campuses because, as Marc Watkins notes in this article, there is no realistic path forward to providing all students with access to advanced AI.

From this posting on LinkedIn.com from Dr. Nick Jackson:

And now there is a third layer emerging. Institutions are waking up to a systems-level question they are likely not remotely prepared for. Who pays for AI? How are budgets managed when there are unclear token consumption pricing models? How is AI procured? Who decides what tools get used and by whom and who gets access and at what level?

.

What a disco ball teaches us about learning and leadership [Flannery]

On 06/19/2026, in Bias | Diversity Equity & Inclusion (DE&I), colleges, community colleges, education, higher education, ideas, instructional design, K-12 related, leadership, learning, learning ecosystem, Learning Experience Design, liberal arts, neurodivergent/special needs, student-related, teaching & learning, UK, universities, by Daniel Christian

What a disco ball teaches us about learning and leadership — from timeshighereducation.com by Lauren Flannery
By acknowledging that perspectives are evolving and relational, educators and leaders can encourage contribution and connection without sacrificing what makes people distinct

It also shows us that difference does not always need to be resolved. In teaching, learning and leadership, the aim is not to create uniformity but to create conditions in which different people can contribute, connect and shine without losing what makes them distinct.

In classrooms, inclusion is sometimes approached as ensuring access to the same knowledge, resources and opportunities for all students. The beach ball helps here: it encourages us to explore multiple perspectives. But the disco ball pushes us further to explore how learning environments can support students to bring their experiences, identities and knowledge into the room – not to smooth them out but to draw from them.

Designing for multiple perspectives also means recognising that expressing an opinion is not only about confidence; it is also about conditions. People are more likely to speak when they feel their contribution will be heard without being dismissed, appropriated or flattened. Creating those conditions may involve discussing uncertainty, welcoming challenge, slowing down decision-making or making space for quieter forms of participation. The aim is not to make everyone agree, but to allow different reflections to interact in ways that generate richer understanding.

If AI Eats the Entry-Level Job, Where Do Young People Learn to Work? (Ryan Craig, Achieve Partners) — from humanistxyz.substack.com by Allison Dulin Salisbury; via Ryan Craig
“The public should not be subsidizing colleges whose students lack relevant, paid, in-field work experience.”

That is the trap at the center of this conversation: everyone wants to hire someone with three years of experience, and almost no one wants to provide those three years.

And Ryan’s policy prescription is unusually concrete: pay employers to hire and train apprentices, following the countries that have scaled apprenticeship far faster than the U.S.; require colleges receiving federal student aid to provide relevant, paid, in-field work experience; and build a market of intermediaries that can make the whole thing operational.

Ryan’s view is that higher education remains critically important. But college without meaningful work experience may become a much worse bet, especially for students who cannot afford to guess wrong.

A screenplay written by a Calvin Prison Initiative student while incarcerated is now screening at film festivals across the country. — from linkedin.com by the Calvin Prison Initiative

From DSC:
I used to work with Calvin film and media professor Geert Heetebrij — who was behind this endeavor. I went to the same church that he and his family attended. I can’t say enough good things about him. He’s just fantastic! By the way, he was there for me when twelve of us didn’t survive the fourth round of layoffs at Calvin (back then it was Calvin College). He periodically — but consistently — checked in on me as the job search continued. He prayed for me (and for my family). His steadfast encouragement meant a lot to me.

I also worked with Sam Smartt, who was also mentioned in the article. Go Geert! Go Sam! And go Calvin for continuing to do your prison ministries! You were one of the first to do this, if not thee first.

Learning Ecosystems

Bring playfulness into teaching for collaboration and creativity [Taurel]

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