In defence of inquiry-based pedagogies
Robert Stevens explores different pedagogies to support effective and efficient teaching and learning.
Debate has raged for more than a century about which pedagogical approach is better – direct instructional guidance or minimally guided, for example, inquiry-based instruction.
An example of a direct instructional guidance is Direct Instruction. Direct Instruction aims to accelerate learning through clearly scripted direct instruction by the teacher and scaffolded practice aimed at student involvement and error reduction (van den Broek, 2012).
An example of inquiry-based (and minimally guided) instruction is Socratic Pedagogy. Matthew Lipman and Ann Sharpe developed and refined a dialogue-based inquiry approach to teaching critical thinking called Philosophy for Children – a paradigm example of Socratic Pedagogy. The approach is based on a ‘community of inquiry’ in which children learn critical and creative thinking by listening to one another with respect, working with one another, building on one another’s ideas, challenging one another to supply reasons for otherwise unsupported opinions, assisting each other in drawing inferences from what has been said, seeking to identify one another’s assumptions and suggest alternatives (Lipman, 2003).
In this paper, I will suggest that the question ‘Which of the two pedagogies is better?’ is the wrong question.
Kirschner, Sweller and Clark argue that direct instructional guidance is superior to unguided or minimally guided instruction. Minimally guided instruction is less effective and less efficient than instructional approaches that place a strong emphasis on guidance of the student learning process (Kirschner et al., 2006). This claim is based on two further arguments:
- Unguided or minimally guided instructional approaches ignore the structures that constitute human cognitive architecture.
- Evidence from empirical studies over the past half-century supports the relative efficiency of direct instructional guidance.
In relation to the first of these arguments, Kirschner and his colleagues define direct instructional guidance as providing information that fully explains the concepts and procedures that students are required to learn (that involves change in long term memory). Kirschner and his colleagues argue that minimally guided instruction does not take account of characteristics of working memory, long-term memory, or the relations between them. They argue human perception and cognition are critically dependent on long-term memory. When processing novel information, working memory is very limited in duration and in capacity. Minimally guided instruction overly taxes our limited working memory, so that long-term memory is not changed. All instruction aims to alter long-term memory. If nothing has changed in long-term memory, nothing has been learned.
In relation to the second argument Kirschner and his colleagues cite evidence that controlled experiments almost uniformly indicate that when dealing with novel information, learners should be explicitly shown what to do and how to do it.
Guided Instruction – better for what?
Kirschner and his colleagues claim that minimally guided instruction is less effective and less efficient than instructional approaches that place a strong emphasis on guidance of the student learning process (Kirschner et al., 2006). If we see pedagogies as tools for learning, this claim is on a par with the assertion that a hammer is less effective and efficient than a screwdriver. In response to this claim, we might ask ‘for what?’ For driving in nails, a hammer is better. For adjusting screws, a screwdriver is better. So, for what is strongly guided instruction better? It appears that Kirschner and his colleagues are claiming that strongly guided instruction is better than minimally guided instruction for memorisation and recall of novel content. It would also be better for teaching and learning the technical aspects of reading, writing and numeracy.
Is direct instructional guidance more effective and efficient in teaching and learning of problem solving? Kirschner and his colleagues suggest a direct instructional guidance using worked examples is a more efficient and effective way of teaching and learning problem solving than minimal guidance. Where an activity involves solving problems with one right answer and one tried and true way of reaching that answer, direct instructional guidance may be the best way to facilitate learning in that activity. But where there is no agreed solution to a problem, where the problem is complex and messy, or where there is no generally accepted algorithm for solving that problem, perhaps a less direct approach is called for, such as philosophical dialogue, problem based learning or project based learning.
A worked example of a solution to a philosophical problem, for example, a mathematical paradox, is not really feasible since there are no agreed solutions to these problems. Nonetheless, studying philosophical problems and investigating various solutions to them, can provide valuable insights into key concepts at the core of a range of disciplines.
Deep and surface learning
Surface learning involves initiation to new ideas. It begins with the development of a conceptual understanding, and then, at the right time, labels and procedures are explicitly introduced to give structure to concepts. Surface learning is the introductory level of learning (Hattie, Fisher & Frey, 2017 p. 23).
The deep phase of learning provides students with opportunities to consolidate their understanding and make deeper connections among ideas (Hattie, Fisher, & Frey, 2017 p. 30).
Students move to deep learning when they plan, investigate, and elaborate on their conceptual understandings, and then begin to make generalisations. It involves students taking surface knowledge (which includes conceptual understanding) and, through the intentional instruction designed by the teacher, seeing how their conceptual understanding links to more efficient and flexible ways of thinking about the concept (Hattie, Fisher, & Frey, 2017 p. 32). Deep learning focuses on recognising relationships among ideas. During deep learning, students engage more actively and deliberately with instruction in order to discover and understand the underlying structure of the subject under consideration.
Direct Instruction might be an appropriate approach to surface learning.
Hattie notes that the deeper phase of learning is accomplished when students work collaboratively with their peers, practising together, through inquiry-based or dialogic approaches. Practices associated with deep learning include: Constructing viable arguments and critiquing the reasoning of each other and displaying, explaining and justifying ideas and arguments using precise language in written or oral communication. This practice requires students to engage in active discourse. Discourse reaches beyond discussion because it includes ways of representing, thinking, talking, agreeing and disagreeing (Hattie, Fisher & Frey, 2017 p. 136).
Hattie and his colleagues distinguish direct instruction from dialogical instruction. Through direct instruction students learn from:
(a) watching clear, complete demonstrations of how to solve problems with accompanying explanations and accurate definitions;
(b) practising similar problems sequenced according to difficulty; and
(c) receiving immediate corrective feedback.
Through a more minimally guided dialogical instruction, students learn from:
(a) actively engaging in problem solving, persevering to solve novel problems;
(b) participating in a discourse of conjecture, explanation and argumentation;
(c) engaging in generalisation and abstraction, developing efficient problem solving strategies and relating their ideas to conventional procedures; and to achieve fluency with these skills,
(d) engaging in some amount of practise (Hattie, Fisher & Frey, 2017).
Hattie notes that differences between the direct and dialogic methods are the types of tasks students are invited to complete and the role of classroom discourse, collaborative learning and feedback (Hattie, Fisher & Frey, 2017).
Hattie suggests that Direct Instruction is more appropriate for surface learning. Dialogical Instruction is more appropriate for deeper learning.
Hattie has found that Direct Instruction has an effect size of 0.59. Dialogic Instruction has an effect size of 0.82 - double the effect size of 0.4, which is generally regarded as one year’s teaching for one year’s growth. Dialogic Instruction is a form of what Kirschner and colleagues would classify as minimally guided instruction or inquiry learning. Yet it has a higher effect size than Direct Instruction. Sijin Yan and colleagues recently found in a meta-analysis of ten studies of school aged children that Philosophy for Children has an effect size of 0.58 on students cognitive learning outcomes and 1.06 on reasoning skill (Yan, Walters, Wang & Wang, 2018). This is in tension with Kirschner and his colleagues’ claim that ‘controlled experiments almost uniformly indicate that when dealing with novel information, learners should be explicitly shown what to do and how to do it’.
Not either or but both and
Hattie observes that the higher effect size of Dialogic Instruction does not mean that teachers should always choose this approach over another. It should never be an either/or situation. Rather it should be a both/and situation. The art of teaching involves teachers choosing the right approach at the right time to ensure learning, and understanding how both dialogic and direct approaches have a role to play throughout the learning process, but in different ways.
Nor should teachers confine their practice to direct and dialogic pedagogies.
People learn through the following activities: reading; writing; listening; discussing; experimenting; modelling; designing; making. Pedagogies can be seen to consist of combinations of these learning activities, and can be distinguished by the activity they emphasise. An activity-centred approach to the design and analysis of learning situations views activity as a mediator between tasks, tools and resources, interpersonal relationships and learning outcomes (Goodyear & Carvalho, 2014).
The following table outlines pedagogies distinguished in terms of the learning activities that characterise them.
Characterising learning activity
Learning by design
Manipulating an object to think with
Table 1: Pedagogies and learning activities
The art of teaching involves understanding what strategies to implement when and for what purpose.
Each of these pedagogies is tried and true and have been practised for generations. They have different purposes. Why should we privilege any one over another?
Using dialogic instruction (to promote deep learning) with direct instruction (to promote surface learning) enables us to meet Kirschner and colleagues’ challenge to explain how inquiry based or dialogic instruction circumvents the limits of working memory when dealing with novel information. It does so by combining with direct instruction to go deeper. Direct instruction provides a surface knowledge as a basis for deeper knowledge, gained through dialogic instruction.
Is direct instructional guidance superior to minimally guided instruction for teaching skills? Again, it depends which skills we are talking about.
Kirschner and his colleagues seem to suggest that memorisation and learning is a passive process of seeing or hearing and remembering – such as memorisation of nonsense syllables by rote. Learning/remembering how to do something (as Kirschner and his colleagues recognise) requires practising that skill, as distinct from simply memorising instructions about how to do it. It may facilitate memory/learning to be shown how to do something, but it is practise that mediates memory and learning. Kirshner and his colleagues suggest that learning is passive assimilation of information (content). Knowledge is transmitted from teacher to student. But in learning, especially learning how, practise makes perfect. When it comes to learning how to do something we learn by doing it - and often doing it together in a community of practice. We learn to ride a bike in small part by guided instruction and in large part by practise and often together in a community of practice. Many skills we learn by mucking in and giving it a go, often with minimal guidance, though the degree of guidance depends on the activity being learned.
Learning to play chess well does not typically involve direct instructional guidance. Beyond learning the rules of chess, mostly by direct instruction, learning to play chess well requires playing lots of games and studying the (sometimes annotated) games of experts. Learning chess well may benefit from studying worked examples, and from coaching, but this involves the study (playing over) of games or stages of games. Chess players build up their long term memory by practise – playing (or playing over) thousands of games.
We learn chess together. Learning chess cannot be an entirely solitary exercise. We typically play chess with a human (or human designed) opponent. Masters write books on chess (generally lightly annotated games).
In learning some skills – such as the technical aspects of writing, for example, spelling and punctuation – direct instructional guidance facilitates practise. In learning other skills – such as creative writing, re-expressing and refining a text, or writing poetry – practise makes perfect, and beyond helpful hints and tips, direct guidance is not all that helpful.
In teaching students how to think well, a teacher may be able to model critical and creative thinking. But it is practise – in a community of inquiry – that makes perfect here, too.
Guidance and practise are key components in learning a skill. But the intensity of the guidance necessary varies from skill to skill. In most cases, though, a large amount of practise is necessary, often in a community of practice.
Direct instructional guidance is an appropriate pedagogy for memorisation of content, and for teaching technical skills and procedures. It is suitable for teaching students how to solve problems with clearly defined solutions. It is suitable for teaching surface knowledge.
Inquiry based pedagogies are suited to learning more complex and contested concepts and for teaching skills that are learned largely by practice in a community of practice. It is suited to cultivating deep content knowledge, and addressing problems that do not have widely agreed solutions.
Direct instructional guidance and minimally guided instruction should be practiced along with other pedagogies in a complementary way – not either or, but both and.
Goodyear, P. & Carvalho, L. (2014). ‘Framing the analysis of learning network architectures’. In L. Carvalho & P. Goodyear, The architecture of productive learning networks pp. 48-70. New York: Routledge.
Hattie, J.A., Fisher, D.B. and Frey, N. (2017). Visible learning for mathematics grades K-12: What works best to optimise student learning. California, United States of America: Corwin.
Kirschner, P.A., Sweller, J. and 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.
Lipman, M. (2003). Thinking in education. New York: Cambridge University Press.
van den Broek, G. (2012). ‘Innovative research based approaches to learning and teaching.’ OECD Education Working Papers, No. 79, OECD Publishing. http://dx.doi.org/10.1787/5k97f6x1kn0w-en
Yan, S., Walters, L.M., Wang, Z, Wang, C. (2018). ‘Meta-Analysis of the effectiveness of philosophy for children programs on student cognitive outcomes.’ Analytic Teaching and Philosophical Practice, 39(1), 13-33.
How to cite this article – Stevens, R. (2019). In defence of inquiry-based pedagogies. Scan, 38(3).