A recent Learning Design Meetup on effective practices in self-paced learning invited attendees to consider what self-paced learning means to us, the challenges it poses, and what effective practices can look like. The following blog picks up some personal reflections inspired by the session. You can also watch the full recording where Amelia Di Paolo and Maryanne Vorreiter share their own examples of self-paced learning in practice.
To begin, a bit of history
Educational technologies have been promised as the ‘future of education’ since 1926, when Sidney Pressey introduced the first teaching machine – essentially, a multiple-choice question device. When B. F. Skinner presented a new educational contraption in the 1950s, the term ‘teaching machine’ gained real traction. It is estimated that more than two million machines were sold door-to-door in the United States during the 1950s and 1960s. The promise? Effective learning for all.
The machines displayed small amounts of information; the student filled in a blank, checked the answer and progressed until the course was complete. Many came to believe this was the ‘teaching machine’ Skinner was advocating, but whilst the commercially sold machines looked like Skinner’s, they did not follow the same principles. In fact, no machine sold at the time actually did what Skinner proposed as a technology – as he himself pointed out then, and as education historians later confirmed (Watters, 2021).
New technologies, familiar principles
Copying the appearance of the machine led nowhere, but understanding the principles that underpin technologies did. That is what made – and still makes – the difference in creating quality courses. Skinner’s machines followed very specific principles, grouped under the name Programmed Instruction. When Pieretti (2021) conducted a comprehensive study on this technology, key principles were identified which may start to sound familiar as you read them:
- Clear learning objectives, describing what the student should be able to do, guide the design of the course
- Successive approximations towards the objective, starting from what the student already knows
- Progression at the student’s own pace
- Clear presentation of each piece of information
- Active participation by the student at all times
- High probability of correct responses to sustain motivation
- Mastery of each step as a condition for advancing
- Gradual transfer to conditions similar to real-life demands, with progressive removal of prompts and supports
- Immediate feedback for each response
- Recording of responses to allow review and continuous improvement of the program
These principles echo throughout many contemporary frameworks: the centrality of learning objectives and immediate feedback, active learning methodologies, mastery learning, etc.
Other solutions followed the ‘teaching machines’: self-instruction manuals, cassette tapes and VHS recordings of classes. From the 1980s, computers and the internet laid the foundations of what we have today, amplified by the recent boom in AI. A self-paced course might be designed to just mimic recorded lectures, or generate video with animated characters ‘singing’ the content in a few clicks, with the help of AI. But learning designers can be more intentional, not only making the most of available technologies, but also applying principles that truly help people learn – with or without the singing characters.
Self-paced principles, reloaded
To design an effective self-paced course, it is essential to go beyond appearances. A good self-paced course today is not simply a polished video lesson or a series of YouTube ‘shorts’. It is a course that:
- Defines clear learning objectives, describing the relevant skills students should be able to demonstrate after completion
- Allows students to begin from what they already know and progress in steps towards the objectives
- Respects individual pacing, enabling revision and alternative pathways when necessary
- Uses clear, accessible language suited to the learners
- Requires active engagement at each stage, not just watching or listening
- Structures steps to ensure a high probability of success, supporting motivation
- Demands mastery of each topic before moving forward
- Gradually approximates the learner to real-world conditions, while fading supports
- Provides immediate, specific feedback for every active response
- Records performance data so that educators and course designers can analyse and improve the experience continuously
I have played with the 1950s principles of Programmed Instruction here to point out criteria that still serve as a strong guide for creating online self-paced courses today, whether using AI, branching scenarios, or other resources. The how of teaching and producing an excellent self-paced course can vary greatly: it depends on what needs to be learned, who the learners are, and what resources are available.
Lost no more: rediscovering our foundations
Teaching means arranging specific conditions that make learning new ways of acting in the world possible; ways that benefit learners themselves and the communities they are part of. The effectiveness of a course (in which students learn, persist, and enjoy the experience) depends far less on the technology itself and far more on a commitment to what truly matters in education: the foundations of what it means to teach and to learn.
Good learning design understands the theory and principles of learning. The celebrated flexibility of self-paced courses is only powerful when guided by principles including (but not limited to) clear objectives, stepwise progression, active engagement, and timely feedback. Without such principles, ‘self-paced’ can quickly turn into ‘self-lost’; and in a format where learners rely on the course design to guide their journey, these foundations are what transform independence into genuine progress.
Further reading
Gusso. H.L. (2022a). Don’t Throw the Educational Principles Out with the Obsolete Technology. Em: MacKenzie, A. et. al. (2022). Dissolving the Dichotomies Between Online and Campus-Based Teaching: a Collective Response to The Manifesto for Teaching Online (Bayne et al. 2020). Postdigital Science and Education, 4, 271–329. https://doi.org/10.1007/s42438-021-00259-z
Pieretti, A. A. R. (2021). Principles of Behavior Analysis underlying Programmed Instruction and the Personalized System of Instruction (Doctoral dissertation). Graduate Program in Experimental Psychology: Behavior Analysis, Pontifical Catholic University of São Paulo. https://tede2.pucsp.br/handle/handle/25785
Skinner, B.F. (1968). The Technology of Teaching. B.F. Skinner Foundation.
Watters, A. (2021). Teaching Machines: The History of Personalized Learning. MIT press.