The Matthew effect describes reinforcing inequality: those with more end up benefiting more, whilst those with less, benefit less. It comes from the biblical verse in the Gospel of Matthew: "For to everyone who has, more will be given, and he will have abundance; but from him who does not have, even what he has will be taken away.". In EdTech, there is a repeated promise of the technological affordance of low-cost scalability allowing for democratised access to education, thereby helping those from underprivileged backgrounds. However, it seldom works out that way [[@wattersTeachingMachinesHistory2023|(Watters, 2023)]]. There are often a myriad of reductive assumptions that are made: * **Access to infrastructure**, for example charging [[@amesCharismaMachineLife2019|(Ames, 2019)]] * **Education can be supported through providing access to content,** which ignores aspects like [[Self regulation|self regulation]] * **Technological literacy of teachers/students** * **Design for one culture can generalise to others** * **Technology is additive**, rather it transforms the learning ecology [[@postmanFiveThingsWe1998|(Postman, 1998)]] * **Ignoring the systemic perspectives,** for example policy changes [[@reichFailureDisruptWhy2020|Reich (2020)]] posits there are three main myths about the democratising potential of EdTech, that continues the Matthew effect: 1. Technology disrupts systems of inequality *(rather it reproduces the inequality embedded in systems)* 2. Free and open technologies promote equality *(rather free things benefit those with the means to take advantage of them)* 3. Expanding access will bridge digital divides *(rather social and cultural barriers are the chief obstacles to equitable participation)* # References Ames, M. G. (2019). _The charisma machine: The life, death, and legacy of one laptop per child_. Mit Press. Postman, N. (1998). _Five things we need to know about technological change_. Watters, A. (2023). _Teaching Machines: The History of Personalized Learning_. MIT Press. --- TODO * decide whether to include this ... are the criticisms well thought out? * Whilst I agree with the general reductiveness of thought leading to failed implementations, I still retain an element of technological solutionism (as of 23/8/2025). If we look at some of these reductive assumptions: * **Access to infrastructure:** with innovation, access to electricity, phones and internet, is becoming cheaper and more widespread. * **Education can be supported through providing access to content:** prior deterministic teaching machines or dissemination of media, lacks the technological affordance of providing both contextually-aware and flexible responses, which LLMs are now capable of performing. Hence, they may be able to support aspects of tutoring such as [[Self regulation|self regulatory support]]. * **Technological literacy of teachers/students:** the flexibility of LLMs can allow for the production of very simple interfaces akin to a conversation with another human. * **Design for one culture can generalise to others:** models can be trained to converse in different native language in their styles, which can generalise the technology amongst cultures (given access to enough training data). * **Technology is additive:** whilst this is not true in many areas like classrooms, it can be moreso additive if replacing the prior existence of nothing, for example, if students did not spend time at home studying since the parsing through solely content was too difficult. * **Ignoring the systemic perspectives:** the scalability of technology if implemented well can bring some ideals of bottom-up change. * *However, for each one of my counters should come with big maybes and I do notice the reductionism present in each of these. But, I posit it more so to promote an optimistic middle ground perspective, neither like the techno-evangelists nor like those that see technology as destined to repeat its trend of faling. Perhaps new technologies with new affordances, implemented right, can disproportionately benefit those with less and break the edtech Matthew effect.*