Category: LRNT 523

Charmaine and Jennifer – Activity 5

From a professional perspective, as we are both instructors, AI is being integrated into the education and employment sector. Education now has aspects of AI into the curriculum design and employment has incorporated AI into “rising expectations around speed, quality and self-sufficiency” (Bansal, 2026). The selected articles reflect the impacts that AI may have on education and the job market.

Article #1:  AI was supposed to destroy jobs. Where’s the carnage?

The article argues AI is reshaping work not by eliminating jobs but by transforming their content, structure, and skills demands. Labour economists like Nicole Bachaud (in Bansal, 2026) emphasize that the workforce is experiencing a “rising bar rather than a shrinking pool,” with a shift from job scarcity to skills-matching. AI is driving a gradual move toward contract and freelance arrangements, consolidating roles, and discouraging new hiring for tasks that can be automated. Robert Seamans categorizes AI’s impact into three groups:  jobs made obsolete, jobs created, and jobs changed with the biggest group being the third. This mirrors past technological shifts like computers and the internet. The biggest disruption is qualitative rather than quantitative; the expectations for workers are rising, with 74% of employers viewing AI skills as a strong advantage and 13% requiring them across the entire company, creating pressure for candidates to arrive already practical or advanced on day one.

Article 2: What is really happening to jobs? Separating AI hype from reality

Author Neale Mahoney dives into a policy brief of whether AI is affecting the labor market. Based on various studies, further research is needed as time is required to determine if AI does in fact impact employment. Below are areas that Mahoney used to base her study on:

1.      AI’s impact on the aggregated employment is likely small right now

• According to Neale there is no evidence that AI has caused significant job loss right now.

 2.      A tough market for recent graduates may be partly due to AI

• In 2022 there has been a decline in hiring entry-level workers in AI-exposed occupations. Impacting younger workers.

 3.      AI’s impact on worker productivity is mixed but generally positive

• Studies show that AI generally speeds up productivity and completion based on task, context and skill level.

4.      Firm adaptation has accelerated but unevenly across the economy

• “AI varies across economies due to methodology and sample composition. Large corporations like to adapt compared to smaller firms” (Mahoney et al., 2026)

 5.      Early evidence is hardly the last word on AI’s impact

• “Technological advances typically take years, even decades to transform business and labor markets”

What would Clark and Kozma say?

According to Kozma’s (1994) argument, when you combine media with learning, more mental links are made.  He would agree that integrating media into education would assist students in the workforce. Kozma (1994) states “we will understand the potential for a relationship between media and learning when we consider it as an interaction between cognitive processes and characteristics of the environment” (p. 8).

The above two articles further Clark’s (1994) stance that although AI was incorporated into the workplace and education, it was neither the result of an increase or decrease in employment or productivity. Clark’s (1994) main argument is that media does not influence learning and believes that instructional methods not media drive learning. As stated by Clark (1994), “media and their attributes influence cost or speed of learning but only the use of adequate instructional methods will influence learning” (p. 27).  

AI Disclaimer: We used AI to make sure we were on the right track.

References:

Bansal, V. (2026, August 12). AI was supposed to destroy jobs. Where’s the carnage? The Guardian. https://www.theguardian.com/technology/2026/aug/12/ai-job-destruction

Clark, R. E. (1994). Media will never influence learning. Educational Technology Research and Development, 42(2), 21-29. https://www.jstor.org/stable/30218684

Kozma, R. B. (1994). Will media influence learning? reframing the debate. Educational Technology Research and Development, 42(2), 7-19. https://www.jstor.org/stable/30218683

Mahoney, N., McEntarfer, E., & Wahal, K. (2026, July). What is really happening to jobs? Separating AI hype from reality. Stanford Institute for Economic Policy Research. https://siepr.stanford.edu/publications/policy-brief/what-really-happening-jobs-separating-ai-hype-reality

Clayton M. Christensen (1952 – 2020) was a theorist, Harvard Business School professor, and co-founder of the Clayton Christensen Institute. He developed three influential frameworks: Disruptive Innovation, which explains how new entrants reshape industries; Jobs-to-be-Done (JTBD), which interprets behaviour through the progress people seek; and Modularity theory, which shows how system architecture shapes competition and adoption. His frameworks remain central for understanding technological and institutional change in 2026.

I selected Christensen because few theorists offer a unified explanation for both technological transformation and organizational inertia. Although widely applied, his  theories face critiques: some disruption cases lack empirical consistency, incumbents often adapt more successfully than predicted, and the theory fits less well in public-sector contexts where incumbents cannot be displaced and value networks restrict innovation. These critiques refine—rather than diminish—the conditions under which disruption occurs, especially in regulated fields like education.

Christensen’s work has influenced health care, education, and global development by challenging legacy cost structures, one-size-fits-all schooling, and aid-centric poverty strategy. Pope (Jan 2026) argues that AI is enabling new architectures with radically different cost structures, while the Christensen Institute (Jan 2026) notes that automation and economic uncertainty pressuring traditional models. These trends reflect Christensen’s modularity theory: AI-native platforms decouple tasks, automate components, and lower integration costs, allowing entrants to compete on speed and modular performance rather than full-stack capability.

Christensen advances a view of learning as differentiated, non-linear process, and driven by JTBD-style intrinsic motivation. He argues that modular and blended architectures support personalized learning, but only when the surrounding value network—credentialing, funding, assessment, accountability—changes. This explains why blended and competency-based models have struggled to disrupt traditional schooling and why, in 2026, AI tutoring systems are being layered onto existing structures rather than transforming them.

I plan to use AI as a jumping off point for where to start looking for relevant articles about Clayton Christensen. I will check all sources that are provided to ensure credibility. I will also use it as a way to check that I didn’t miss anything. My first draft was close to 600 words, not ideal. I put what I wrote into AI and asked for suggestions on how to make it more concise. I took some suggestions, others I did not.

References

How Clayton Christensen’s theory of disruptive innovation helps explain the rise of Positionless Marketing

https://www.researchgate.net/publication/215915528_Meeting_the_Challenge_of_Disruptive_Change

Three predictions for 2026 on development, disruption, and entrepreneurship

https://www.acceptmission.com/blog/disruptive-innovation-christensen-theory

About Clayton Christensen

https://journals.sagepub.com/doi/10.1177/003172171009200407

https://www.edweek.org/teaching-learning/disruptive-innovation-in-educationhttps://www.fredpope.com/blog/innovation/What_Christensen_Would_Tell_SaaS

Immediate relevance

Chapter 9 – 2002 – Learning Management Systems (LMS)

Pretty much every school whether it be high school, college, or university is using some form of LMS. Even though the layouts and ways of doing things may be somewhat different, the abilities are similar. Weller states that their benefits include reliability, institutional support, and standardization. I use Blackboard Ultra where I work and it is constantly being updated and changed to meet the growing needs of what is required by the institutions. Some of these changes are beneficial, some are not. The LMS allows me to see submissions, who has logged in and when, track attendance and grades, and post announcements and assignments. Students are able to complete assignments and tests, see due dates and grades, and communicate with faculty and classmates.

Conflicts with or Contradicts

Chapter 16 – 2009 – Twitter and Social Media

I work at a college and all upcoming events and anything newsworthy is posted via social media. Weller states the benefits include democratization, visibility, engagement, and research dissemination. This can be great for getting the word out there, connecting people around the world allowing for support and a sense of community, and for locating help resources for topics such as mental illness. Weller warns that there are risks including harassment, context collapse, platform monopolies, and blurred personal or professional boundaries. Social media has been linked to negative effects such as anxiety and depression, social comparison, sleep disruption, addictive feedback loops, cyberbullying, and isolation. It seems somewhat contradictory to advertise a mental health workshop or session on social media that can ultimately lead to things like depression. There is also the point that students are told not to use social media in class as it is distracting to them while at the same time asked to look at current posts. This puts students between a rock and a hard place.

I find it surprising how many different years took credit for the start of educational technology. Now, with that said, I don’t know if I was aware of how far back it actually went.

I find The Web and Constructivism to fit the categories of compelling and problematic.

The main argument for the web is that its invention and early adoption fundamentally reshaped educational technology by enabling open publishing, global communication, and resource sharing. This laid the foundation for all subsequent ed tech developments. Berners-Lee’s four foundational technologies created a universal, open system that was “designed as a communication system, around principles of robustness, decentralization and openness” (p. 16). For distance education, the web removed the broadcast bottleneck and lowered the cost of entry for universities. The web is the foundational technology for LMS, OER, MOOC, blogs, analytics, and social media.

Constructivism’s main argument is that it became the dominant pedagogical lens for early web-based learning because of the web’s affordances (non-linearity, communication, abundant resources) demanded models beyond traditional lecture-based instruction. The theory behind constructivism is that it emphasizes learners constructing knowledge through experience and social interaction instead of just lectures and textbooks. There has been a shift in the way many educators teach going from a “sage on the stage” approach to a “guide on the side,” which helped educators leverage the web’s participatory nature. There were, however, limitations such as it not fitting all disciplines, discovering that learning can be ineffective without guidance, and some of the implementations were superficial. While constructivism marked the first widespread attempt to align pedagogy with the affordances of digital technology, it was a conceptual engagement rather than a purely technical one.

When I searched back to when educational technology started, it was back in ancient times with oral communication and paintings on cave walls. I think that it is important to reference from that time, however I think that would make for a rather large book.