Robert Gagné took instructional design in a new direction in the 1970s, and made his own unique – and occassionally eccentric – contributions to the field of technology-enhanced learning.
From war zone to classroom
In a previous article we looked at B. F. Skinner’s work on operant conditioning, and we saw his teaching machines in action. Skinner’s innovations have had a long-lasting influence in the fields of psychology and education, and traces of his ideas can still be detected in aspects of educational practice today.
By the 1970s, the American educational psychologist Robert Gagné had developed a more principled blueprint for the design of learning programmes (Gagné, 1974). His ideas were forged during his early research experiences in wartime military contexts. In the post-war years, he refined them while working as a civilian researcher with the US Air Force and Navy. Gagné’s instructional model was intended to meet a demand for rapid, large-scale training of personnel in the use of new and complex weapons and equipment.
The model was based on the idea that different kinds of learning outcomes required specific instructional techniques. Gagné identified five broad categories of learning objectives, which he felt represented the general kinds of capabilities that humans could develop through instruction.
The five categories were:
- intellectual skills;
- cognitive strategies;
- verbal information;
- motor skills;
The nine instructional events
To make use of Gagné’s learning design blueprint, instructors first needed to decide which of these five categories their own learning goals fell into. When the category had been identified the instructor could implement a series of nine ‘instructional events’ that Gagné had developed. The sequence was tailored to produce a particular learning objective.
The instructional events were derived from cognitive information processing theory, and consisted of the following steps:
- activating motivation;
- informing the learner of the objective;
- stimulating recall of prior knowledge;
- presenting the stimulus;
- providing learning guidance;
- eliciting performance;
- providing feedback on performance;
- enhancing retention;
- promoting the transfer of knowledge to other contexts.
This animated video cleverly illustrates the main features of Gagne’s model, it’s well worth a watch.
At face value, the model certainly looks like a useful approach to learning design, and it is certainly not without merit. But as Diana Laurillard has pointed out (2002), one of the greatest weaknesses of Gagné’s instructional design theory is that it is not based on relevant empirical evidence. The nine instructional events, for example, are derived from experiments in cognitive psychology and not from authentic contexts of academic instruction.
“These studies of, for example, short-term memory are carried out in experimental situations, and in isolation from all the other components Gagné includes in the learning process. They are used to infer possible constructs to describe how the human brain works. These are then transferred to the context of an academic learning task, as though the transfer were unproblematic.” (Laurillard, 2002: 65)
Nevertheless, Gagné did place a greater emphasis on the individuality of learners in the instructional process than Skinner did. He was influenced by cognitive psychology, which emphasised the processes going on inside a learner’s mind which created learning. From this perspective, Gagné recognised that learners bring things with them to a learning activity (previous experiences, attitudes and prior knowledge, for example) that have a significant influence on the learning process itself. An instructor needed to understand these conditions of learning, he realised, and optimise the learning interaction accordingly.
To use Gagné’s terminology, these internal conditions must then be paired with the correct external conditions as manifested in the form of the stimuli, the type of instruction given (Gagné, 1985). In other words, the programme should be adjusted to the learner’s needs.
Gagné had not completely shaken off the behaviourist influences that rumbled deep in the historical background of psyschology. His approach to learning still focused on shaping behaviour, and it was therefore behaviourist in essence. Like Skinner’s teaching machine, Gagné’s model would perhaps be best suited to a drill-and-practice type of instruction – a method that works well when training people to operate military equipment, for example.
The rigid pre-structured framework of the learning design left little room for pedagogical elements that we now recognise as important for successful learning experiences. Andrew Ravenscroft has pointed out, for example, that learners had no control over pace, timing and sequence (2003). Neither were they encouraged to engage in higher-level reasoning, reflection, exploration or creativity.
But despite its limitations, Gagné’s work made an enormous impact in the field of computer-assisted learning, particularly in North America. His system became the foundation of the instructional design approach to e-learning development that continues to be influential in the field today. Many training programmes and online courses currently in use are based to some degree on Gagné’s conditions of learning and his nine instructional events.
In a future article we’ll look at some of the more recent learning theories that have helped shape current practices in technology-enhanced learning design. If you’d like to learn more about Gagné’s work or the history of instructional design, the texts listed below are a great place to start.
Gagné, R. M. (1974) Essentials of Learning and Instruction. Hinsdale, IL: Dryden Press.
Gagné, R. M. (1985) The Conditions of Learning and the Theory of Instruction. New York: Holt, Rinehart and Winston.
Laurillard, D. (2002) Rethinking University Teaching: A Conversational Framework for the Effective Use of Learning Technologies (2nd Edition). London: Routledge.
Ravenscroft, A. (2003) From Conditioning to Learning Communities: Implications of fifty years of research in e-learning interaction design. ALT-J 11 (3): 4-18.