Randomised control trials are currently the definitive gold standard approach for formal educational experiments. Although conclusions from these experiments are highly credible, their relatively slow experimentation rate, high expense and rigid framework can be seen to limit scope on: 1. $\textit{metrics}$: automation of the consistent rigorous computation of hundreds of metrics for every experiment; 2. $\textit{concurrency}$: fast automated releases of hundreds of concurrent experiments daily; and 3. $\textit{safeguards}$: safety net tests and ramping up/rolling back treatments quickly to minimise negative impact. This paper defines a framework for categorising different experimental processes, and places a particular emphasis on technology readiness. On the basis of our analysis, our thesis is that the next generation of education technology successes will be heralded by recognising the context of experiments and collectively embracing the full set of processes that are at hand: from rapid ideation and prototyping produced in small scale experiments on the one hand, to influencing recommendations of best teaching practices with large-scale and technology-enabled online A/B testing on the other. A key benefit of the latter is that the running costs tend towards zero (leading to `free experimentation'). This offers low-risk opportunities to explore and drive value though well-planned lasting campaigns that iterate quickly at a large scale. Importantly, because these experimental platforms are so adaptable, the cumulative effect of the experimental campaign delivers compounding value exponentially over time even if each individual experiment delivers a small effect.
翻译:虽然这些实验的结论非常可信,但是它们相对缓慢的实验率、高支出和僵硬的框架可以认为限制了以下范围:1. $\ textit{ meters}$:对每项实验一致严格计算数百度的自动化;2. $ textit{conformination}$:每天迅速自动释放数百项同时进行的实验;3. $\ textit{ 安全警卫}$:安全网测试和快速提升/回滚处理以最大限度地减少负面影响。本文界定了将不同实验过程分类的框架,并特别强调技术准备。根据我们的分析,我们的理论是,通过承认实验背景和集体接受当前全部过程将预示下一代教育技术成功:一方面从快速构想和大规模实验产生的数百项并行实验;以及3. 美元:安全网测试和快速提升/回流处理以尽量减少负面影响。本文确定了一个框架,将不同实验过程分类,并特别强调技术准备就绪。 后一种关键的好处是,如果每次实验的成本是持续到持久实验性的实验,那么这些实验将带来一个巨大的风险。