Beyond Media and Method: A Connectivist View of Learning

Article 1: Nelson and Microsoft’s Partnership 

Article: Nelson and Microsoft Partnering to Transform Education in Canada

In March 2017, Nelson and Microsoft announced a partnership intended to “transform education in Canada” (Nelson, 2017). A Microsoft Windows device equipped with content provided by Nelson, Canada’s largest K-12 educational publisher, would be supplied to every student and teacher in Canada. The media release, written by Nelson and published by PR Newswire, claims that the use of Microsoft Azure’s machine-learning and analytics capabilities would “optimize the device’s learning path to improve student outcomes” (Nelson, 2017).

Techno-Deterministic Thinking

The announcement presents technology as a way to “solve many of the challenges in the shifting educational landscape” (Nelson, 2017) and makes a direct connection between technological affordances and improved learning outcomes. However, learning is more complicated than optimizing a content pathway. Student motivation, teaching practices, assessment, relationships, prior knowledge, and the learning environment all influence how well a student learns (Weller, 2020).

“We are excited about how this partnership will drive innovation in the Canadian market and beyond.”

Salcito (Nelson, 2017)

Furthermore, the release is brief, and its omissions are not neutral. While technology is positioned as a primary driver of innovation, the article says little about how teachers will meaningfully integrate these tools into curriculum and classroom activities. As a piece of promotional content from a major technology company, it presents a simplified story of educational transformation that leaves out much of the context that might complicate its narrative such as pedagogy, student agency, or institutional context. 

Clark’s Perspective

While the press release claims that merging “Microsoft’s technology with Nelson’s pedagogical content” on Windows devices will “transform student learning” (Nelson, 2017), Clark (1994) would critique this as a fundamental “confusion of technologies” where a delivery medium is mistaken for an instructional method (p. 23). Hardware and analytics are “mere vehicles” (p. 22) and any learning gains originate from the embedded pedagogical strategy, not the media. Under Clark’s replaceability challenge, if identical results can be produced using alternative media, then the Microsoft-Nelson technology itself is not the causal agent (Clark, 1994, p. 22).

Kozma’s Perspective

Robert Kozma (1994) frames educational technology as a “design science” that creates new possibilities for learning (p. 1) and would likely view the release optimistically. Rejecting the “delivery truck” view, Kozma argues that a medium’s intentionally designed affordances enable specific pedagogical methods (p. 8) which would otherwise be difficult to implement. In the Nelson–Microsoft partnership, Windows devices, Nelson’s content, and Azure analytics provide processing capabilities intended to support students when they encounter learning difficulties (Nelson, 2017). Kozma’s argument suggests that such capabilities can enable instructional methods that would otherwise be difficult to implement (1994, p. 13). However, Kozma emphasizes that technology does not automatically guarantee learning; rather, it creates potential that only succeeds when media and method are thoughtfully integrated with the educational, social and cultural context (Kozma, 1994, p. 16).

Article 2: Coursera and Udemy’s Project Helix

Article: Announcing Project Helix: A skills platform for the AI era

In May 2026, Coursera and Udemy, two platforms often used for workplace learning, officially merged. In Announcing Project Helix: A Skills Platform for the AI Era, Supanc (2026), Chief Product Officer, presented the joint vision for an AI-powered learning platform designed to identify skills gaps, personalize learning pathways, assess employee capabilities, and connect learning outcomes to business objectives. 

Techno-Deterministic Thinking

The article positions AI as a key solution to workforce learning and development challenges. Rather than simply describing the platform’s features, the article suggests that AI-driven personalization, assessment, and skills intelligence can accelerate skill development, improve workforce readiness, and contribute to positive business outcomes. This framing places significant emphasis on the technology itself as a driver of organizational and educational change.

“Continuous, personalized feedback and adaptive practice engage and progress learners more rapidly from basic comprehension to mastery.”

Supanc (2026)

Clark’s Perspective

Clark (1994) would likely challenge the article’s assumption that AI itself is responsible for improved learning and workforce performance. According to Clark (1994), employees improve because they practice, receive feedback, apply skills and engage in effective instructional activities. The AI platform helps to deliver these experiences in a cost effective and scalable way, but it does not cause learning. In the context of AI, Clark’s (1994) critique remains relevant because AI’s capabilities are ultimately programmed into it through algorithms designed by humans. Therefore, the instructional approach exerts a greater influence on learning than the technology itself (Clark, 1994).

Kozma’s Perspective

Kozma (1994) would likely view Project Helix more favorably because he argues that the medium’s characteristics shape the learning experience. AI features like adaptive learning pathways, AI role-playing, personalized feedback, and learning embedded within daily work create learning opportunities that are impractical or difficult to achieve through traditional training methods. Rather than viewing AI as a simple delivery vehicle, Kozma (1994) would argue that AI can actively shape the learning experience through personalization, adaptation, and feedback. Consequently, while Clark’s argument may still apply to more passive media like books and videos, AI blurs the distinction between medium and method (Kozma, 1994).