Sunday, October 10, 2021

Mosher and Goddfredson - 5 moments of learning need

Bob Mosher is the Chief Learning Evangelist, at APPLY Synergies  and has been an active and influential leader in the learning and training industry for over 30 years. He is renowned worldwide for his pioneering role in new approaches to learning. Dr. Conrad Gottfredson is a founding partner, and the Chief Learning Strategist at APPLY Synergies, a 5 Moments of Need company, that specialises in helping learning professionals design, develop, maintain, and measure effective learning and performance support. Gottfredson and Mosher have given learning in the workflow some needed focus and definition.

Performance support

Gottfredson and Mosher build on the fact that most learning takes place on the job and not on training courses. In Innovative Performance Support (2011) they recommended a whole raft of techniques, tools and tech which can be used to implement performance support. Their arguments are that it reduces costs on formal training, while at the same time increasing performance and productivity. Time to improved performance is increased, along with managing cognitive load and transfer. A positive side effect is that expensive internal support and help-desks can also be reduced. They claim a performance first approach can reduce time to competence, by half. It also makes people feel better in their jobs and that helps retention. 

Workflow learning

A training mindset is about building an ‘instructional’ system, mainly courses and being an instructional ‘order taker’ determines what’s on your menu - time-based courses. The shift they recommend is to move away from this service mentality, to being a partner to help learning and development solve problems. 

People don’t need general principles or courses on printing, they need to know ‘how to’ fix the printer problem they have at that moment. So you have to identify the actual workflow, to get to the authentic performance needs, then design for those real processes and support, with an ascending range of options available to the learner.

For Mosher and Gottfredson transfer is also important, not by throwing them over the fence at the end of a course but integrating what you’ve learnt into the knowledge and work you do.

Five Moments of Need

Jumping straight into an analysis that extracts knowledge from SMEs is a mistake, as it leads to over-formal courses that deliver too much, in courses, at the wrong time, in the wrong place. One should design learning around these needs first with some detailed analysis of the critical tasks involved in those needs and focus on what they need to know.

Learning should meet these needs and deliver to the right people, at the right time, in the right context. In organisations this means in the workflow, at the point-of-need. Gottfredson and Mosher's famous five moments of learner need are:

  1. New - learning for first time

  2. More - wanting to learn more

  3. Apply - trying to remember and apply

  4. Solve - something goes wrong

  5. Change - something changes

Most first think of new and more but apply, solve and change tend to be more common. This is where delivery must be orchestrated, as it also needs to be a combination of pull and push. 

Digital coach

Failure really matters in work, for the individual and organisation. Learning in the flow of work means learning from those hesitancies, failures and mistakes. A Digital Coach or EPSS, allows the learner to take the relevant steps to overcome failure, as they do their work. A workflow map unpacks context and the Digital Coach supplies the resources. 

As all resources are not created equal, there is a hierarchy of support, from the simple to complex. One must always look towards delivering the minimal amount of support to reach your given goal.

At its simplest there’s the 2-click, 10 second access to support in response to the five moments of need. Then there’s steps support (quick and detailed). This is followed by, supporting knowledge, documents, policies, procedures, job aids, FAQs, articles and so on.

Only if these resources have been exhausted do you move to real-time learning such as e-learning. And of all else has been tried - it’s people, email, chats, social networks, communities of practice.


Gottfredson and Mosher’s five moments of need have been used to underpin the development of performance support technology, the sort of technology that Gery envisioned. More than that, their precise identification of the needs of real learners in the workflow have been fundamental in helping shape Learning Experience Platforms (LXPs) that push and pull learning in the workflow. Above all they have pushed learning and development into waking up to the challenge that learning is a process, that for most, takes place in the context of work, by doing. This shift in mindset was given some concrete recommendations in terms of implementing solutions to real needs.


Gottfredson, C. and Mosher, B., 2021. The 5 Moments of Need | A Performance-First Approach.  

Gottfredson, C. and Mosher, B., 2011. Innovative performance support: Strategies and practices for learning in the workflow. McGraw Hill Professional.

Monday, October 04, 2021

Pressey (1888-1979) - first teaching machine

 Sidney Pressey was the first to design and create a Teaching Machine, nearly 40 years before Skinner, which presented content, took input from learners and provided feedback. He saw technology as offering an ‘industrial revolution’ in learning, allowing some tasks to be automated, reducing the burden on teachers.

Learning theory

He saw himself as an early cognitivist psychologist, decades before it replaced behaviourism as the dominant school in psychology and saw learning not in terms of simple reinforcement but a more complex process involving internal, cognitive features of the brain such as language, thought, reflection and writing. He refused to accept learning theory based on the reductionist behaviourism of animal psychologists such as Pavlov, the behaviourist evangelist Watson or Skinner, who he knew personally, and had little time for learning theory that excluded consciousness, language and mental phenomena. His teaching machines reflected this learning theory.

Teaching machines

Although there were Victorian precedents, the true origin of teaching machine was the relatively unknown figure of Pressey, who came up with his idea in 1915. He had to shelve the idea, as the First World War intervened, until he finally filed a patent in 1926. This was the first known machine to deliver content, accept input and deliver feedback. He is therefore the true originator of the first teaching machine.

His first machine used old typewriter parts to present multiple-choice questions with four options. The learner pressed a key for the right answer and the results were stored on a counter. It had the three necessary conditions for a teaching machine, the presentation of content, input by users and feedback. 

His second machine had the innovation of not moving on until you got the right answer and he continued to innovate with teaching machines into the late 1950s. Pressey understood that such machines could be used for both teaching and testing. You could set the machine, using a simple lever, to only move on if the learner got the right answer or alternatively assess by recording all of their answers, right and wrong. 

Using the second machine was easy, the learner simply pressed one of five keys (1-5), it had a small window that showed the numbers of questions asked and a window on the side showing the number of questions they got correct. In teaching mode the learners had to continue until the correct answer was chosen and the next question appeared. The question’s number did not change until it was answered correctly and the window on the side showed the number of tries. He argued that this was quick, gave immediate results so that the learner didn’t have to wait days for results and saved the teacher time from the drudgery of marking, also eliminating marking errors. He also argued that this could free teachers to teach in a more inspirational manner. The learner could also repeat the experience until they got full mastery. You could quickly reset for the next student in seconds or the next test and could cope with up to 100 questions. These arguments are sound. An interesting attachment to the main machine delivered a candy if you passed a threshold number of correct answers (the threshold could be changed on the machine via a dial). All for under $15. Unfortunately, his timing was bad and the Great Depression put an end to his dream of manufacturing and popularising individualised learning.

Learning theories

Pressey has very specific views on learning theory, more towards cognitive psychology than pure behaviourism. Errors or the correction of misconceptions were, for him, fundamental to learning, hence his fondness for multiple choice questions, which had 4/5 wrong answers. He saw learning as a complex process where relatively stable, cognitive structures had to be created. This had to be achieved through the analysis of errors, along with individualisation, diagnosis and feedback. Learning, for Pressey, was not a form of reinforcement, as with animals but involved uniquely human mediation through language, speaking, listening, reading and writing. It was a deeply cognitive process. He was the antithesis of Skinner, whose teaching machine was designed around positive reinforcement, hence his avoiding multiple choice questions, where the wrong answers (negative stimuli) outnumbered the right answer, that were actually given to the student, in advance of them having to think. Skinner saw this as weak learning and didn’t buy the idea that the study of wrong answers was anything but a distraction and, more seriously, seeding confusion in terms of what was learned.

Blended Learning

He even formulated an early theory of Blended Learning, which he called, rather clumsily, ‘Adjunct Autoinstruction’. This involved the combination of programmed learning through technology and human teaching. He never saw his Teaching Machines as replacing teachers but as merely adjunct ways of extending teaching and testing. Indeed, the whole point was to free teachers from the mundane tasks of basic learning and marking.


Pressey was convinced that education had to be reformed and called for an ‘industrial revolution’ in learning, based on the use of technology. He suffered a breakdown when his devices failed to sell and felt that the education system was closed to innovation. Skinner went on to build his own versions of mechanical Teaching Machines but by the 1960s mechanical teaching machines had had their day. As mechanical devices they were clunky and relied on discs, barrels, levers and buttons, all hardware and no software. They had little real effect on learning technology in the long-term, other than objects of obscure interest by commentators 


Pressey S.L. 1933. Psychology and the new education. Harper.

Pressey S.L. & Janney J.E. 1937. Casebook of research in education. Harper.

Pressey S.L; Janney J.E. & Kuhlen R.G. 1939. Life: a psychological survey. Harper.

Pressey S.L; Robinson F.P & Horrocks J.E. 1959. Psychology in education. Harper.

Benjamin, L. T. (1988). A history of teaching machines. American Psychologist, 43(9), 703–712.

Mellan, I., 1936. Teaching and educational inventions. The Journal of Experimental Education, 4(3), pp.291-300.

Petrina, S., 2004. Sidney Pressey and the automation of education, 1924-1934. Technology and Culture, 45(2), pp.305-330.

Ferster, B., 2014. Teaching machines: Learning from the intersection of education and technology. JHU Press.

Sunday, October 03, 2021

Roediger and Karpicke - Retrieval practice and effortful learning

Henry L. Roediger (Washington University in St. Louis) and Jeffrey D. Karpicke (Purdue University) have been at the forefront of the research on retrieval practice. For centuries memories were seen as objects to be retrieved but neutral for learning. Few saw that act of retrieval as a learning experience in itself, something that produced learning. They can be said to have put retrieval practice, as a learning strategy, on the map by confirming the efficacy of free recall over rereading, stimulating research in the area.

Testing Effect (Retrieval Practice Effect)

In their Testing-enhanced learning (2006) paper they showed that repeated tests substantially increased retention relative to learners who simply restudied the prose material. Restudying had a better short-term effect but retrieval practice, 2 days and 1 week later showed a significant difference. Roediger et al. (2011) then did a study on text material covering Egypt, Mesopotamia, India and China, in the real context of real classes in a real school, a Middle School in Columbia, Illinois. Retrieval tests, only a few minutes long, produced a full grade-level increase on the material that had been subject to retrieval.

The first solid research on the Testing effect was by Abbot (1909), then Gates (1917), who tested children aged 8-16 on short biographies. Some simply re-read the material several times, others were told to look up and silently recite what they had read. The latter, who actively retrieved knowledge, showed better recall. Spitzer (1939) made over 3000 11-12 year olds read 600 word articles then tested students at periods over 2 months. The greater the gap between testing and the original exposure or test, the greater the forgetting. The tests themselves seemed to halt forgetting. 

Tulving (1967) took this further with lists of 36 words, with repeated testing and retrieval. The retrieval led to as much learning as the original act of studying. This shifted the focus away from testing as just assessment to testing as retrieval, as an act of learning in itself and Karpicke and Roedegir’s work in 2006 and 2009. McDaniel (2011) did a further study on science subjects, with 16 year olds, on genetics, evolution and anatomy. Students who used retrieval quizzes scored 92% (A-) compared to 79% for those who did not. More than this, the effect of retrieval lasted longer, when the students were tested eight months later. 

Karpicke and Blunt (2011) also showed that retrieval practice is superior to concept or mind-mapping. Spaced, retrieval practice is even better (Karpicke & Bauernschmidt, 2011). It has been shown to be effective at all levels in education; elementary, middle-school, Universities and in adult medical education.

The work by Kornell (2009) also shows that even unsuccessful testing is better. Retrieval testing gives you better internal feedback and works even when you get few or no correct answers. Testing, even before you have access to the material, as a learning experience, also helps learning. Once again, Huestler and Metcalfe (2012) asked learners what worked best and they were largely wrong.

Illusions of competence

In their 2006 research, Karpicke and Roediger used rereading as the control, as that is what most learners do, see Karpicke, Butler and Roediger (2009), and in doing so uncovered a fascinating supplementary finding. In a survey of 117 students they asked them to list their study strategies, then also choose from a list of set strategies. The majority chose rereading as a strategy with relatively few using self-testing or free recall. They christened this the ‘illusion of competence’. Just as Bjork had done in asking students about practice techniques, they found that students think they will do better by repeated study and not free recall practice, yet the evidence shows the students were wrong. This lack of metacognitive awareness severely limits the ability of learners to learn.

Make It Stick

Make It Stick (2014) by Brown, Roediger and McDaniel takes a wider view. It is the result of over ten years of focused research on 'Applying Cognitive Psychology to Enhance Educational Practice'. It is practical and gives plenty of advice on both how to teach and how to learn, the point being that knowing how to learn is a necessary condition for good teaching.

Researchers like Bjork, Karpicke, Rodeiger and McDaniel claim that most good learning theory is counterintuitive. Most students are misled by teachers and institutions into the wrong strategies for studying; reading, highlighting, underlining and rereading. This feels productive but the evidence suggests it is a largely ineffective strategy for learning. It turns out that we are very poor judges of our own learning. The optimal strategies for learning are in the 'doing' and some of that doing is counterintuitive. We think we are mastering something but this is an illusion of mastery. It is easy to think you’re learning when the going is easy – re-reading, underlining and repetition but it doesn’t work. To learn effectively, you must make the going harder. They also explain why the research is not about rote learning, the charge that is usually levelled against them.

The real force behind successful learning is effortful learning. By effort they mostly mean retrieval practice. Practically, they recommend regular, low-stakes testing for teachers and learners, not ‘teaching to the test’ as summative assessment but regular formative exercises, where recall is stimulated and encouraged. Test little and often – that is what makes effortful learning stick.This is not testing as assessment, it is testing to learn. Interesting research is also presented for the idea that having a go at retrieval, even when you make mistakes and errors, is better than simply getting the exposition. 

They also recommend spaced practice, especially spaced retrieval practice and interleaving and delayed feedback.


It is not that retrieval practice doesn;t work only that it only works for limited types of learning, such as factual recall, and that the effect fades, even disappears for more complex material. Many of the trials are on verbal information, word-pairs and so on. An associated problem is the difficulty in designing retrieval practice and transferring it to the classroom or online environment. It is ebay to design low-level practice.


Their work has gathered a great deal of attention, especially in schools and stimulated other research on different audiences with different types of material and in different contexts. Movements such as ResearchED have promoted the research and its spread in recent books on teaching practice, and online, has been significant.


Brown, P.C., 2014. Make it stick. Harvard University Press.

Abbott, E. E. (1909). On the analysis of the factors of recall in the learning process. Psychological Monographs, 11, 159–177.

Gates, A. I. (1917). Recitation as a factor in memorizing. Archives of Psychology, No. 40, 1-104. 

Spitzer, H. F. (1939). Studies in retention. Journal of Educational Psychology, 30, 641-656. 

Tulving, E. (1967). The effects of presentation and recall of material in free-recall learning. Journal of Verbal Learning and Verbal Behavior, 6, 175􏰀184.

Huelser, B.J. and Metcalfe, J., 2012. Making related errors facilitates learning, but learners do not know it. Memory & cognition, 40(4), pp.514-527.

McDaniel, M. A., Agarwal, P. K., Huelser, B. J., McDermott, K. B., & Roediger, H. L. (2011). Test-enhanced learning in a middle school science classroom: The effects of quiz frequency and placement. Journal of Educational Psychology, 103, 399-414

Karpicke, J.D., & Bauernschmidt, A. 2011. Spaced retrieval: Absolute spacing enhances learning regardless of relative spacing. Journal of Experimental Psychology: Learning, Memory, and Cognition, 37(5), 1250-1257. 

Karpicke, J.D. and Blunt, J.R., 2011. Retrieval practice produces more learning than elaborative studying with concept mapping. Science, 331(6018), pp.772-775.

Saturday, October 02, 2021

Clark - Media, direct instruction, analysis, agents, games and AI in learning

Richard E. Clark is Professor Emeritus of Educational Psychology and Technology at the University of South California. He has produced a huge corpus of research and writing on technology and workplace learning and has put in a huge effort to bridge the gap between known theory, its boundaries, and practice. With a focus on instruction and not media, he has produced valuable work on performance gaps and how to do a thorough analysis using Cognitive Gap Analysis, to determine optimal training. His interest in learning technology has led to conclusions on everything from visual agents to games, in learning. He is also an advocate for the use of AI in training.

Learning from media

Clark asks us not to confuse methods of instruction with media and famously claimed 

in Clark (1983), considering research on learning from media, that there is no significant difference, in terms of benefits, between using different media to deliver instruction. His argument is that non-media methods, for example, instructional methods, different content, or assessment plans can be presented by any medium including teachers. What he does say is that different media can affect the number and variety of students who can access learning and, of course, that some media are more scalable and cost-effective than others (Clark, 2012).

Direct Instruction versus Constructivism

Evidence from learning theory, in particular the limitations of working memory, suggest that direct instruction may be more effective than unguided or lightly guided learning experiences. Guidance can be tapered off as learners gain competence and expertise. This is a direct challenge to the constructivist approach recommended by Bruner and Papert, that learners must discover or construct essential information for themselves. While the constructivist ‘description of learning’ may be accurate, the research shows Kirschner, Sweller, & Clark (2006) that the instructional methods recommended by constructivists are flawed.

Cognitive Task Analysis

In Turning Research Into Results: A guide to selecting the right performance solutions (2012) Clark focuses on the diagnosis of performance gaps in terms of; Knowledge and skills, Motivational and Organisational gaps. He then separates the use of  Job aids from Training and then Education. 

The solution, he recommends, is Cognitive Task Analysis (CTA), which is a front-end process to improve design. He sees this as the weakest part of most current analysis models. Research has found that experts are often unaware of what they actually do, as around 70% is executed automatically, without much self-awareness or reflection. The job of the learning designer is to uncover that 70%.

He starts with the selection of experts. You need experts who have been doing this for a while with proven success, who are not just trainers. 

  1. Interviewing experts, focus on sequence and tasks, the action (physical) and decision steps (psychological). Listening matters here. Get transcripts of these interviews. An important extra is to ask where trainees have difficulties. Where do they get stuck? 

  2. Edit transcripts to get descriptions that are meaningful to trainers.

  3. Interview experts (3-4) separately, and ask each what they think was missed.

  4. Go back to 1 say what 2 & 3 said and ask them to agree on one version.

  5. Collapse separate versions into one final version.

  6. Collect information about equipment, standards and examples from experts.


His emphasis on motivation has always been a strong characteristic of his work. Motivation is not just what people need to learn, it can also be negative or harmful. People, for example, are often overconfident and reject advice. He sees four critical motivational features: 

  1. Values mismatch (for what they’re doing) that are meaningful to them. There’s huge variation. 

  2. Lack of self-confidence or self-efficacy.

  3. Disruptive emotions - being anxious, angry, depressed, negative, all stop people from learning

  4. Barriers that knock people, negative evaluations, attribution failures

Animated agents

Clark (2005) doubts that virtual, animated agents add any value in learning as the research shows a mix of results from well-designed studies. While guidance and attention may be focussed by agents they can also distract and place extra cognitive load on learners. Research is required that compares agents and non-agents in same designed learning experiences.

Games for learning

Clark sees no clear definition of what constitutes a ‘game’ and the research as insubstantial. Previous meta analyses of games have failed to include unpublished studies containing no significant gain results, which is what he believes is the most likely outcome in a well designed study. Games that use the discovery method of learning are, he claims, less effective than fully guided instruction for novice to intermediate learners and he thinks that the learning benefits, when found in games, are the product of instructional methods that can be presented, without the extra design and costs, in non-game contexts. They are a distraction from real, evidence-based instructional methods. In fact, games may result in less mental effort invested in learning because of the belief that they make learning ‘easier’. He concludes that less expensive instructional designs may be preferable and that increased motivation in games may actually hinder learning. He is also sceptical about the emphasis put on social learning and their implementation in chat rooms.

AI and learning

Clark is using AI to automate the CTA process and believes that all of training and development will, at some time, become AI supported. This will decrease the cost of front-end analysis and design, forcing it to become more evidence-based, free from biases and overcome the resistance that human beings bring to the table. This will, in his words “be a revolution”.


With MAyer, Clark has a reputation for rigorous adherence to research and evidence, providing guidance for practitioners in the design of learning experiences. Although online learning is often still blind to research-driven practices, Clark remains a rich and deep resource for professionals in the field.


Clark, R. E. (2012) Learning from media: Arguments, analysis and evidence, second edition. Greenwich Conn: Information Age Publishing.

Clark, R. E. (2011). Games for Instruction?. Presentation at the American Educational Research Association, New Orleans, LA

Clark, R. E. (May-June 2007) Learning from serious games? Arguments, evidence and research suggestions.  Educational Technology.  56 – 59

Clark, R. E. and Choi, S. (2005). Five design principles for experiments on the effects of animated pedagogical agents.  Journal of Educational Computing Research. 32(3). 209-225.

Sweller, J., Kirschner, P. A., & Clark, R. E. (2007). Why minimally guided teaching techniques do not work: A reply to commentaries. Educational Psychologist, 42(2), 115-121

Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based experiential and inquiry-based teaching. Educational Psychologist, 41(2), 75-86

Elen, J., Clark, R.E. and Lowick, J., 2006. Handling complexity in learning environments: Research and theory. In : (p. 283e297). Oxford: Elsevier.

Clark, R.E. ed., 2001. Learning from media: Arguments, analysis, and evidence. IAP.

Clark, R. E. (1983) Reconsidering research on learning from media., Review of Educational Research, 53(4), 445-459

Friday, October 01, 2021

Baldwin - Learning and evolution, may be one of the most significant learning theorists ever

You may never have heard of the philosopher and psychologist James Mark Baldwin. Yet he may be one of the most significant learning theorists ever. He was a psychologist who set up one of the first laboratories of experimental psychology, in Toronto, which influenced Paiget. He also introduced what is called the ‘Baldwin Effect’ into evolutionary theory. This profound and radical idea puts ‘learning’ into the evolutionary process and has been recently revived. Just as Darwin and Wallace struck upon the same idea at the same time, Baldwin had two Wallaces, in Henry Fairfield Osborne and Conwy Lloyd Morgan. All three published the same ideas in 1895-96.

Baldwin Effect

The Baldwin Effect is the theory that learned behavior, and not just environment and genes, influences the direction and rate of the evolution of psychological and physical traits. Note that this is not Lamarckism, as it does not claim that acquired characteristics are passed on genetically, only that the offspring of an adaptive trait (physical or psychological) may be genetically better at learning. This creates the opportunity, as it creates the conditions and successful population survival, for standard selection to take place. It means that behavioural learning, which can take place culturally can eventually shape the genetics of a species.

The Baldwin effect therefore places ‘learning’ on a larger theoretical canvas, lying at the heart of evolutionary theory. Learning is no longer just a cognitive ability, albeit a complex one with many different systems of memory involved, but a feature that defines the very success of our species.

Growth of Baldwin effect

The theory has some impressive supporters, including Aldous Huxley, AI expert Geoffry Hinton, Nowlan, Dennett and Deacon. Evolutionary psychology, in particular, has had a profound influence on the resurrection of the idea. Hinton and Nolan revived the idea in How Learning Can Guide Evolution (1987) and Richard Richards who published Darwin and the Emergence of Evolutionary Theories of Mind and Behaviour (1996), in the same year. But it is Daniel Dennett who has done most to popularize the idea in Consciousness Explained (1991) and Darwin’s Dangerous Idea (1995).  Dennett posits the Baldwin idea that learned behavior, especially sustainable innovative behaviours, if captured in substantial genetic frequency, can act as what he calls a ‘sky crane’ in evolution. Weber and Depew have since published an excellent explanatory and supportive book Evolution and Learning: The Baldwin Effect Reconsidered (2007).

Deacon proposed that the Baldwin effect accounts for the rapid evolution of the mind and language. As Wittgenstein showed, a private language makes no sense as meaning is use. As soon as a small number start and continue to develop language skills it confers significant adaptive advantage and confers a real runaway advantage to the users. This ability to learn new skills may be the key to our species having moved beyond fixed, genetic determinism. More than just language, adaption to new environments, responding to climatic and food pressures and other changes that require quicker adaption through selected learning, may have played a role in the rapid success of Homo Sapiens. Dennett proposes the actual creation of selective pressure on others by sustained learned behaviour. 


In an interesting development Geoffry Hinton and Steven Nowlan (1996) claimed to have demonstrated, through computer technology (simulations) that learning could shape evolution. The Baldwin effect, may, through its own efficacy have created the technological conditions for its own proof! The brain, through consciousness, may have created a fast developing structure that in turn accelerates learning and thus evolution. It remains a controversial but increasingly supported idea.


Weber, B. H., and Depew, D. J. (2003). Evolution and learning: The Baldwin effect reconsidered. Cambridge, Mass: MIT Press.

Hinton, G.E. and Nowlan, S.J., 1996. How learning can guide evolution. Adaptive individuals in evolving populations: models and algorithms, 26, pp.447-454.

Laurent, J., 1990. Robert J. Richards, Darwin and the Emergence of Evolutionary Theories of Mind and Behaviour. Social Studies of Science, 20(1), pp.161-165.

Dennett, D. C. (1995). Darwin's dangerous idea: Evolution and the meanings of life. New York: Simon and Schuster.

Dennett, D. C. (1991). Consciousness explained. Boston: Little, Brown and Co.

Baldwin, J. M. (1973). Social and ethical interpretations in mental development. New York: Arno Press.

Baldwin, J.M., 1896. A new factor in evolution (Continued). The American Naturalist, 30(355), pp.536-553.

Mill - Utilitarianism, associationism and women’s rights

John Stuart Mill saw education as a means to the end of achieving happiness for the individual and happiness as a whole. Hot-housed as a child, and educated by his Scottish father the philosopher John Mill and Jeremy Bentham, his Godfather, he was kept apart from other children, reading Greek and Latin at age 8. As a teenager he suffered from depression, which he in part saw arising from the intensity and isolation of his education. He felt as though his purely rational education had not allowed him to develop feelings such as sympathy and appreciation of the real world. Finding Wordsworth helped him overcome this tendency to immediately rationalise and analyse the world.

He was one of the most significant intellectual figures in England in the mid-nineteenth century, as a philosopher, politician and economist. He also played a significant role in the advancement of women’s rights.

Empiricism and associationism

As an empiricist, he saw sensory experience as the raw data from which all else arises, even logic and mathematics. This meant he saw the mind as a tabla rasa, ready to be filled with sensations that lead to all manifestations of consciousness and thought. It is the scientific approach making inductive inferences from experience that should be used to build a view of education.

His associationist psychology meant the association of small pieces of data, sense data or feelings, to form our view of the world. This came from Locke, Hume and Hartley and forms the basis of his empiricism and belief in the strength of the scientific method.


From his Godfather, Jeremy Bentham, he saw Utilitarianism (1863), expressed in the formula ‘the greatest happiness for the greatest number of people’ as an empirical theory based on the observation that this is what all people actually desire - happiness. This is not to say that one should pursue one’s own happiness at the expense of others,as the greater good is a sure source of happiness for the individual. Although he did believe that some forms of happiness were higher than others and , unlike Bentham, saw feelings as important guides in moral, aesthetic and other judgements.

Utility is intimately connected with liberty and in On Liberty (1859) he is keen to press the idea that one cannot infringe upon the rights of others to pursue their happiness, unless their actions cause ‘harm’. State and social control were to be resisted. As they infringe upon the development of the individual. This debate around freedom of expression is still relevant today, along with the ‘harm principle’ and influenced his views on education.


Education was the means to attain true happiness, not in the simple sense of hedonistic pleasures but the higher forms of happiness. He refused to believe that most learners were innately incapable of being fully educated. In his Autobiography, he was also critical of the idea that one should only teach what learners enjoy, as this appeals to a primitive view of the lower pleasures of ‘fun’ and prevents access to the higher pleasures and happiness of subtler, elevated subjects. This hinders rather than helps learning as it prevents the learner from reaching their fullest potential and happiness. Above all education should teach children to become autonomous being and and to think for themselves.

Education should have a strong moral purpose, to overcome the selfish pursuit of pleasures at the expense of others. Moral education must encourage the capability of appreciating that the happiness of others, the greater and common good, leads also to the happiness of the individual within that society and culture. The taking on of public duties and active participation in society and democracy was important.

In On Liberty (1859) he proposes compulsory, universal education for every citizen, including women, all the way up to University entrance. Although he was critical of the idea that such education should be provided by the state, as that could result in compulsory coercion and control, which was counter to his views on freedom and liberty. One notable example of his aversion to education coercing learners, was his view that religion, as a subject of opinions, should not be taught in schools.

Women’s rights

In The Subjection of Women (1869), he calls upon his utilitarian and libertarian principles to defend the emancipation of women from the social pressures to conform to what men think. Women are forced to lead less happy lives because they are not free to pursue their own happiness, almost in a state of slavery. Here, he also called for the abolition factual  slavery.

He makes the case for absolute equality, especially in the freedom giving process of education that would give women, as citizens, freedom and independence. 


Mill’s influence has been immense in politics, notably his ideas on freedom of expression and liberty. He is still read and quoted at length on these issues to this day and these issues in education, especially in the campus culture clashes, are still with us. His influence on education is not via his purely empiricist views but his appeal for compulsory, universal education was realised, at least in the developed world, along with the inclusion of women, especially in Higher Education. Mill played a key role in the latter.

His focus on happiness also influenced the recent rise of positive psychology, through Seligman and others, although much of that debate seems to ignore the deep and sophisticated interest taken on that topic in the 19th century.


Mill, J.S. and Stillinger, J., 1873. Autobiography.

Mill, J.S., 2018. (1869) The subjection of women. Routledge.

Mill, J.S. and Bentham, J., 1987. (1863) Utilitarianism and other essays. Penguin UK.

Mill, J.S., 1989. (1859)  'On Liberty' and Other Writings. Cambridge University Press.