By Christopher Ross and Florian Progin
Introduction
Techno-determinism presents technology as the direct cause of changes in learning, regardless of pedagogy or context. This post examines a press release and a mass-media article through the opposing lenses of the Great Media Debate: Clark’s (1994) position that media are causally inert vehicles for instruction, and Kozma’s (1994) counter-argument that a medium’s specific capabilities can participate in cognition when a design connects them to a task.
The first is a press release written by Tricia Davis-Muffett (2025), Senior Director at Google for Education, promoting Gemini for Education, a suite of AI-powered tools supported by success stories from US-based institutions. The second is a mass-media article, an unsigned report from The News International (2024) republished on Khan Academy Pakistan’s own site, covering the launch of the AI tutor Khanmigo with the stated aim of transforming the country’s educational landscape.
Gemini for Education
Article: How Gemini for Education accelerates learning for over 10 million college students
Starting with its title, Davis-Muffett’s (2025) post provides multiple examples of how Gemini for Education “accelerates” learning, is used to “transform” teaching, and can “help students grasp underlying concepts rather than simply providing answers” through a feature the post names Guided Learning. Gemini is consistently the subject of the main verb in these claims.
Teachers appear in the post, but in a specific and limited role: as people whose time the tool saves, and as a fallback the tool stands in for. Davis-Muffett’s own narration states that “professors love that it helps them save time and provides students with in-the-moment assistance,” and one named professor, Dr. Elisa Sobo, is quoted describing the tool as functioning “like having a teaching assistant that the students can go to when the teacher is not available.” At no point does the post describe a teacher, named or otherwise, making a pedagogical decision about how Gemini is used. The decisions that are described belong to institutions: a university is described as one of the first “to go all in on Google,” a system makes “AI fluency a shared expectation.” The techno-determinism here is not that teachers are erased from the story; it is that the decision-maker the post credits is procurement, not pedagogy.
Clark’s View
Clark (1994), restating his 1983 position, holds that media “are mere vehicles that deliver instruction but do not influence student achievement any more than the truck that delivers our groceries causes changes in our nutrition” (p. 22, quoting Clark, 1983, p. 445). The instructional method causes learning; the medium only affects cost, access, and speed of delivery. His replaceability test follows directly: if the same learning gain could come from a different medium, such as a human teaching assistant delivering the same guidance, the medium was never the cause.
Applied here, the “teaching assistant” comparison in the Gemini post concedes Clark’s point without meaning to. If Gemini is doing the work a human teaching assistant would otherwise do, the relevant question is not whether an AI or a person delivers the help, but whether the underlying method, how a specific misconception gets addressed, would produce the same result regardless of who or what delivers it. The post never makes that comparison. It also conflates the logistical benefits of Google’s tool, access, scale, and cost, with an actual influence on learning: the success metrics cited are adoption figures (“10 million college students,” “over 1,000 U.S. higher education institutions”), which Clark would distinguish sharply from evidence of learning. The strongest argument in Gemini’s favour, on Clark’s own terms, is that Google offers it free of charge to accredited institutions, exactly the cost and access advantage his framework allows a medium to claim, without that advantage saying anything about whether students learn differently because of it.
Kozma’s View
Kozma (1994) would resist the premise that “Gemini causes learning” is even the right question. His framework, developed through the ThinkerTools (White, 1993, as cited in Kozma, 1994) and Jasper Woodbury (Cognition and Technology Group at Vanderbilt, 1992, as cited in Kozma, 1994) examples, distinguishes a medium’s technology (its physical capability), symbol systems (how it represents information), and processing capabilities (what it can do with those symbols) (p. 12). The relevant question for Guided Learning is not whether Gemini has capabilities in some general sense, but which specific processing capability is doing the cognitive work, and whether it interacts with a documented mechanism the way White’s dynamic force-vector representations did in ThinkerTools.
On that standard, the post falls short in a specific way: it names an outcome without describing a mechanism. Kozma’s reply to Clark’s replaceability test is his distinction between necessary and sufficient conditions (p. 13): Clark demands necessary conditions before a medium counts as a real variable, but Kozma argues a design science should instead ask what conditions are sufficient to produce learning for given students and tasks. The post never specifies those conditions, so it cannot be tested against Kozma’s standard either. Guided Learning’s capability could matter, in the way computer-based dynamic symbol systems mattered in ThinkerTools, but the post gives no evidence that it does, only that people used it and access widened.
Khanmigo in Pakistan
Article: Khan Academy Pakistan launched, brings AI-powered tutor “Khanmigo” to country
The article quotes Osman Rashid, chairperson of KAP, saying: “Khan Academy Pakistan is more than an initiative; it is a commitment to our children and our future. By integrating AI and localized content, we aim to use Khanmigo to transform the educational landscape of Pakistan, ensuring that every child, regardless of their circumstances, has access to quality learning.” Sal Khan frames it as bringing “the power of AI to tackle the unique challenges faced by students and teachers.” The article also describes “tools and training for teachers to enhance classroom learning,” and states that “for teachers, Khanmigo offers valuable resources like automated lesson planning and personalized feedback tools, making it easier to manage classroom tasks and focus on student engagement.” Teachers are named more often here than in the Gemini post, but the pattern is similar once the roles are separated: training and support are things teachers receive, while lesson planning, arguably the central instructional-method decision in teaching, is described as automated. The article’s own account of the pilot confirms the sequence: it will launch “starting with teachers and gradually extending to students,” with teachers positioned as recipients of the tool before students are, not as designers of how it gets used.
Clark’s View
Clark’s replaceability test, introduced above, applies here too: could the same learning gains come from a cheaper, non-AI intervention, such as a trained volunteer tutor or a well-designed workbook? If so, the medium is not the cause. Clark’s framework also grants Khanmigo something real: media can change the cost and reach of instruction without changing what is learned. A free AI tutor reaching students who would otherwise have no tutor at all is exactly the case his theory permits praising, and Rashid’s own sentence is careful in a way Davis-Muffett’s is not: “transform the educational landscape” is immediately qualified as “ensuring that every child, regardless of their circumstances, has access to quality learning,” an access claim, not an outcomes claim. On Clark’s terms, that is close to an honest use of the medium’s actual advantage. The overreach in this article sits elsewhere, in the framing that AI itself will “tackle the unique challenges faced by students and teachers,” which assigns the tool a role in solving pedagogical problems Clark would insist depends on method, not access.
The automated lesson-planning detail sharpens this. If lesson planning, deciding what gets taught and how, is handled by the tool, then the method Clark says is the actual cause of learning has been placed inside the medium rather than left to the teacher’s judgment. That does not resolve the debate in Khanmigo’s favour. It relocates the question: is the automated lesson plan itself a good method, tested against Clark’s replaceability standard, or is it merely a faster way to produce a lesson plan a teacher could have written? The article does not say.
Kozma’s View
Kozma would ask what Khanmigo’s specific processing capability is, and whether the article describes any interaction between that capability and a documented cognitive process, the standard he applied to ThinkerTools and Jasper. The article comes closer to naming one than the Gemini post did: Khanmigo “acts as a personal tutor for students, providing personalized assistance and helping them understand complex concepts at their own pace.” Self-paced, personalized processing is a real candidate capability in Kozma’s framework. But the article asserts it rather than evidencing it. It does not describe which concepts, for which students, produced which change, the kind of detail White’s force-vector representations or the Jasper videodisc’s random-access review supplied in Kozma’s own examples. Kozma’s closing question, “in what ways can we use the capabilities of media to influence learning for particular students, tasks, and situations” (p. 18), is precisely what this gap leaves unanswered. The article names the population, Pakistani students and teachers, and gestures at a capability, but never the task or mechanism connecting the two.
Conclusion
Clark and Kozma fail both texts on different grounds, which is itself informative. Clark’s test asks what method is actually doing the causal work, and both texts describe teachers primarily as recipients of what the tool provides rather than as agents deciding how it is used; the Khanmigo article goes further, describing the central method decision, lesson planning, as something the tool now performs. Kozma’s test asks for a documented interaction between a specific capability and a specific task, and neither text supplies one: both name an outcome (accelerated learning, transformed education) without describing a mechanism sufficient to produce it for particular students and situations.
Thirty years after Clark and Kozma’s exchange, the argument has not been settled. It has been restated by a company and a newspaper covering that company’s launch event, in each case because the evidence needed to satisfy either standard was left out of the story being told.
AI Transparency Statement
We used AI (Claude) in two different ways. Florian wrote his sections himself and used Claude as a language reviewer and as a sounding board to discuss the Clark and Kozma readings. Christopher used Claude to research candidate sources, fetch and verify primary material, and draft sections of this post. The AI-assisted drafts went through two verification passes, not one, and both caught real errors, which is worth stating plainly rather than implying the first check was sufficient. The first pass revised an early sentence stating that the Gemini post makes no mention of teachers, which a live fetch showed was too broad: the post does mention professors, although in a limited role, as discussed above. A second, independent pass caught three further problems in the AI-drafted sections that the first one missed: a quote wrongly attributed to a named professor that was actually the article’s own narration, a wrong title for a named individual, and a truncated quote that had reversed the point its full sentence actually makes. All three are corrected above. A final read-through checked the remaining direct quotations from the Gemini post against the source and corrected two that did not match its exact wording. We also confirmed, through direct verification against the raw source and a cross-check against the original newspaper report, that the Khanmigo material is a news article republished by Khan Academy Pakistan rather than the company’s own press release, which changed the citation. We reviewed and take ownership of the final analysis. The Clark and Kozma sections were checked against the full text of both 1994 papers rather than summaries of them.
Reflection
The uncomfortable finding of this assignment was not that a first draft contained an error. It was that a review pass we trusted also contained errors, of the same kind, in the same post about being careful with sources. A misattributed quote is a small thing to get wrong and an easy thing for a marker to catch, and it happened after we had already congratulated ourselves for catching a different mistake. The lesson that generalizes: verification is not a single gate a piece of writing passes through once. It is a standard the writing has to keep meeting on a second and third look, especially once a first correction has made everyone, including us, more confident than the evidence yet justified. What verification did not do was shortcut the theoretical reading. Getting Kozma’s argument right, specifically his distinction between technology, symbol systems, and processing capabilities, and his necessary-versus-sufficient-conditions reply to Clark, required reading his full 1994 paper directly. A plausible paraphrase of that argument, which is what an early unverified pass had offered, was close enough to sound right and wrong enough to have misrepresented him.
References
Clark, R. E. (1994). Media will never influence learning. Educational Technology Research and Development, 42(2), 21–29. https://doi.org/10.1007/BF02299088
Davis-Muffett, T. (2025, September 8). How Gemini for Education accelerates learning for over 10 million college students. The Keyword, Google. https://blog.google/outreach-initiatives/education/gemini-education-higher-ed/
The News International. (2024, December 27). Khan Academy Pakistan launched, brings AI-powered tutor “Khanmigo” to country. https://www.thenews.com.pk/print/1265827-khan-academy-pakistan-launched-brings-ai-powered-tutor-khanmigo-to-country (republished by Khan Academy Pakistan at https://khanacademypakistan.org/_us_news/khan-academy-pakistan-launched-brings-ai-powered-tutor-khanmigo-to-country/)
Kozma, R. B. (1994). Will media influence learning? Reframing the debate. Educational Technology Research and Development, 42(2), 7–19. https://doi.org/10.1007/BF02299087