Inquiry vs direct teaching for interdisciplinary STEM


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Inquiry vs direct teaching for interdisciplinary STEM

Posted by Prof. Russell Tytler on August 9, 2019

By Russell Tytler, Chair of Science Education

Current advocacy of STEM represents a reform movement to increase engagement of students with the STEM disciplines (Marginson, Tytler, Freeman & Roberts, 2013), and to develop ‘STEM skills’ that will prepare students for life in the 21st century. Such skills overlap with generic competences that are increasingly represented in global curriculum framing (OECD, 2018), such as complex and creative problem solving, critical thinking, design thinking, mathematical reasoning, interpersonal and collaborative skills, and trans-disciplinarity.

What does this focus on interdisciplinarity and STEM skills mean for teaching and learning approaches? At face value, one might expect that the focus on developing students as agile and flexible problem solvers would imply inquiry pedagogies in which students are encouraged to develop agency in collaborative problem solving and investigation. This is, indeed, a strong strand of the project-based approaches based around design challenges often associated with STEM activities, where teachers report a growing confidence with student-focused pedagogies (Tytler, Williams, Hobbs & Anderson, 2019). However, there is evidence that these interdisciplinary activities, while engaging for students, fail to develop the deeper level understandings in the core disciplines of mathematics and science (Honey et al., 2014; Lehrer, 2016), where curriculum planning needs to attend to the progressive development of foundational ideas (Tytler, Prain & Hobbs, 2019).

Counter to this STEM move towards project based, inquiry pedagogies, a strong strand of Australian curriculum planning involves advocates teaching strategies ( that at face value run counter to calls for the development of creativity, critical judgments, and student agency, advocating the ‘explicit teaching’ and ‘worked examples’ that are indeed the norm in current classroom practice. This is not to say that direct teaching does not have its place for aspects of learning of knowledge and skills. in teaching. There is evidence on both sides of the explicit teaching/inquiry debate. I argue that the renewed focus on competences and interdisciplinary thinking tips the balance towards the inquiry end of the scale, for mathematics and science as well as STEM project work. To make sense of how to approach this, we need to make sense of the key issues at stake in this competing advocacy of direct teaching vs inquiry pedagogies.

Direct teaching vs inquiry – how real is the debate?

A core aspect of this controversy concerns the extent of teacher framing of student learning. This debate, broadly, is what underlies the ‘reading wars’ between advocates of learning to read through meaningful contexts, and those who advocate a systemic and explicit approach to phonics. In STEM subjects including mathematics we can see it in Kirschner and Sweller’s advocacy of the ‘worked example’ (Kirschner, Sweller & Clark, 2006) vs. the more open problem-solving approaches of educators like Peter Sullivan (Sullivan, Mousley & Zevenbergen, 2006). In science, the debate has two dimensions; one concerning the advocacy of open inquiry investigative work vs. the strongly guided practical activity that currently dominates practice, and the second concerning the degree to which the teacher frames students’ thinking and discussion in introducing new concepts.

What is really at stake in these debates? What is the evidence that proponents cite in support of their case? As Alan Luke (2014) points out, direct instruction in early literacy education has its roots in behaviourism and runs counter to constructivist notions of engaging with the cultural context, including students’ values and prior ideas, of learning in classrooms. Luke makes the point, however, that in the short term, and particularly for skills-based learning, such direct instructional interventions can be shown to work. According to Hattie’s analysis, they also have the capacity to galvanise collaborative planning for teachers around clarity of success indicators. Luke however points out that deeper levels of engagement with learning do not prosper under these regimes, raising questions about the need for more varied approaches as students achieve basic skills.

The evidence

Proponents of direct instruction (Kirschner, 2009; Kirscher & Sweller, 2006) argue that constructivist-based inquiry pedagogies have been shown to be ineffective, yet arguments for them refuse to die. They claim evidence from many studies comparing direct with inquiry teaching. Yet there are also review studies that argue for the effectiveness of inquiry teaching (Anderson, 2002; Furtak, Seidel, Iverson & Briggs, 2012). Kapur (2008) coined the term ‘productive failure’ to describe the deeper learning that subsequently resulted from students grappling with open ended problems, despite initial lack of success, compared to students taught explicitly. Other researchers (Warshauer, 2015) have referred to the ‘productive struggle’ that is necessary for deeper learning in mathematics, referring back to Piaget and Dewey for theoretical underpinnings.

There are two problems with comparative studies of direct teaching and inquiry teaching. First, what is meant by these terms is not well defined. In particular, inquiry as a contrast is taken in some comparative studies to represent a pedagogy where the teacher offers no assistance at all and students are unreasonably asked to discover ideas that took centuries for scientist to invent. These are not representative of the range, or even the core of inquiry approaches. Second, attention needs to be paid to the particularities of the intended learning outcomes and how these might affect the instructional approach. Direct teaching seems sensible for teaching facts, for instance, or for introducing and practicing skills, but what of higher-level outcomes where knowledge involves significant conceptual shifts?

What are the core differences that are at stake?

A much-quoted exemplification of direct teaching principles are Barak Rosenshine ‘Principles of Instruction’ ( which are based on analysis of high performing classrooms. These are shown in the left-hand column of Table 1. A key plank in Rosenshine’s and others’ argument for direct approaches is one of efficiency in content coverage. Rosenshine was explicit about a key aspect of these teachers’ practice: “(Many of) the most effective teachers … went on to hands -on activities, but always after, not before, the basic material was learned”. Thus he articulates a key distinction between direct teaching, and inquiry approaches generally; whether students are ‘taught’ canonical concepts or practices before, or after they grapple with problems or engage with exploratory activity.

In a recent critique of a set of ‘high impact teaching strategies’ based on such meta-analyses of teacher practice (Prain & Tytler, 2017, Nov) we pointed out the lack of a coherent sense of pedagogy accompanying such reductive versions of teaching, and the lack of attention to relational and motivational aspects of classroom practice. In Rosenshine’s list, there is a similar lack of attention to the wider setting of learning processes such as student agency and choice.

In a recent project examining support of student reasoning by acknowledged quality teachers of primary science, we found commonalities in practice in broad agreement with the list above, but we would couch these in very different form. We argued (Chen & Tytler, 2017) that their practice represented diverse approaches to inquiry teaching. Based on this work, we could rewrite Rosenshine’s list through a guided inquiry lens, also including analyses of practice relating to reasoning analyses (Tytler, Murcia, Hsiung & Ramseger, 2017), and teacher discursive moves (Tytler & Aranda, 2015). This alternative analysis is represented in the right-hand column of Table 1.

Rosenshine’s Principles of Instruction

Guided Inquiry version

1. Begin a lesson with a short review of previous learning

Tap into students current / prior knowledge including from previous learning

2. Present new material in small steps with student practice after each step

Prepare students for staged exploratory tasks so their deliberations are productive

3. Ask a large number of questions and check the responses of all students

Orchestrate discursive moves that include questions that elicit ideas, encourage clarification, and extend student thinking.

4. Provide models

Strategically enable productive representational invention or extension of provided models.

5. Guide student practice

Orchestrate class agreement on productive ideas and representational practices.

6. Check for student understanding

Continually monitor student ideas as a fundamental aspect of teaching-learning.

7. Obtain a high success rate

Provide tasks that challenge students but differentiate.

8. Provide scaffolds for difficult tasks

Orchestrate scaffolds for difficult conceptual moves.

9. Require and monitor independent practice

Orchestrate and monitor individual and group practices

10. Engage students in weekly and monthly review

Provide culminating tasks that assess students’ learnings.

Table 1: A comparison of direct teaching, and guided inquiry principles, based on Rosenshine’s study, and on a comparative study of quality teaching

A key distinction between these versions of classroom practice lies in whether students explore before, or after an explanation is presented or generated. Given the argument on efficiency of learning, how can we articulate more clearly what may be the benefits of prior exploration of problems before solutions are presented/agreed upon? This is particularly pertinent in the context of advocacy of competence-based curricula and calls for a focus on interdisciplinary STEM practices.

In our current research (Tytler, 2019), which involves the teaching of primary school mathematics and science in an interdisciplinary setting (, we take a lead from how mathematicians and scientists develop and use ideas, and ask ‘how can classroom practices in some way simulate knowledge building in the real world’. This implies the need to allow space for students to explore and to create and test ideas in a meaningful and supportive environment. Thus, we seem to be enlisting elements of both direct teaching, and of inquiry. How can we balance these ideas?

We draw on the insight that knowledge building in science and mathematics involves the creative invention and establishment of representational systems (models, visual representations, graphs and other data visualisations, mathematical and scientific symbols). These, as well as the language forms in which explanations, reports, proofs and argumentation occur, constitute the multi modal literacies of science and of mathematics. Learning can be viewed as a process of induction into these disciplinary literacies, and command of these literacies (being able to create and use models, diagrams, mathematical symbols and processes) is what is needed for disciplinary knowledge to be flexibly used in reasoning and problem solving in authentic interdisciplinary settings.

In our pedagogy, students construct representations in response to structured and meaningful challenges. They actively explore and work with science and mathematics ideas through material exploration, in a process where the teacher strategically sequences the tasks and actively monitors and shapes student thinking and representing.

For instance, Grade 4 children investigating whether a probot moves at constant speed were supported to invent, compare and refine ways of representing distance travelled over successive time intervals. Grade 1 children invented ways of measuring counts of living things, sampling across habitats, displaying data and mapping sampling locations.

We and our colleagues argue (Tytler, Prain, Hubber & Waldrip, 2013; Lehrer & Schauble, 2012) that this process steeps students in authentic knowledge building, or epistemic processes of the discipline. In mathematics for instance they develop key constructs such as measure, sample, data modeling and spatial reasoning through guided investigation rather than as procedures to be learnt independent of meaningful inquiry.

In astronomy, students investigated and represented shadow movement and related this to 3D models and then drawings of earth-sun relations.

In this process of sequenced investigation and representational invention, comparison and revision, we have found high levels of student engagement and representational competence. The discussions are rich, they make meaningful choices, and are grounded in processes of scientific investigation and argumentation. They are in an important sense doing rather than learning about science and mathematics.

In terms of the direct teaching- inquiry debate, the approach shares many of the features of quality direct teaching – deliberative structuring and framing of activities, clarity of intended outcomes, continuous monitoring of students’ inputs and ideas, and overt scaffolding through task design and targeted questioning. Key differences include greater trust in the generative nature of students’ ideas and the weight given to these; invitation of students into the purposes of the knowledge; openness to variation in student practices; opportunities for imaginative projection and robust discussion leading to communal agreement on key ideas; orchestration, critique and revision of students’ invented representations; and attention to the purposes of modeling and representational work compared to presentation of ideas as pre-packaged practice.

Direct teaching advocates the gradual ceding of control to students after they have been taught techniques, and monitoring of their work, rather than our staged process of exploration, invention, evaluation and revision. The payoff, we argue, is that students come to know the disciplinary ideas in richer ways. We have found, however, that the approach requires of teachers both significant knowledge of the science and mathematics, and command of a pedagogy involving negotiation and refinement of student ideas, compared to ‘telling’. It also takes more time. However, if we are serious about developing STEM skills for interdisciplinary problem solving, we argue there are no shortcuts.


Anderson, R. (2002). Reforming science teaching: What research says about inquiry. Journal of Science Teacher Education, 13(1), 1–12.

Chen, H-L S., & Tytler, R. (2017). Inquiry Teaching and Learning: Forms, Approaches, and Embedded Views Within and Across Cultures. In M. Hackling, J. Ramseger, & H-L S. Chen (Eds), Quality Teaching in Primary Science Education: Cross-cultural perspectives (pp. 93-122). Dordrecht, Netherlands: Springer. DOI: 10.1007/978-3-319-44383-6_5

Furtak, E. M., Seidel, T., Iverson, H., & Briggs, D. C. (2012). Experimental and quasi-experimental studies of inquiry-based science teaching: A meta-analysis. Review of Educational Research, 82(3), 300-329.

Kapur, M. (2008). Productive failure. Cognition and instruction26(3), 379-424.

Kirschner, P. A. (2009). Epistemology or pedagogy, that is the question. In S. Tobias & T. M. Duffy (Eds.). Constructivist instruction: Success or failure? (pp. 144-157). New York, NY: Routledge.

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 psychologist41(2), 75-86.

Lehrer, R., & Schauble, L. (2012). Seeding evolutionary thinking by engaging children in modeling its foundations. Science Education, 96(4), 701-724.

Luke, A. (2014). On Explicit and Direct Instruction

Marginson, S., Tytler, R., Freeman, B., & Roberts, K. (2013). STEM: Country Comparisons International comparisons of science, technology, engineering and mathematics (STEM) education. Canberra: Australian Council of Learned Academies. Retrieved at:

OECD (2018). The future of education and skills: Education 2030. Paris: OECD

Prain, V., & Tytler, R. (2017, November 9). Simplistic advice for teachers on how to teach won’t work.

Sullivan, P., Mousley, J., & Zevenbergen, R. (2006). Teacher actions to maximize mathematics learning opportunities in heterogeneous classrooms. International Journal of Science and Mathematics Education4(1), 117-143.

Tytler, R. (2019). The challenge of STEM. Education Matters, March 20.

Tytler, R., & Aranda, G. (2015). Expert teachers’ discursive moves in science classroom interactive talk. International Journal of Science and Mathematics Education. 13(2), 425-446. DOI 10.1007/s10763-015-9617-6

Tytler, R., Murcia, K., Hsiung, C-T., & Ramseger, J. (2017). Reasoning through representations. In M. Hackling, J. Ramseger, & H-L S. Chen (Eds), Quality Teaching in Primary Science Education: Cross-cultural perspectives (pp. 149-179). Dordrecht, Netherlands: Springer. DOI: 10.1007/978-3-319-44383-6_5

Tytler, R., Prain, V., & Hobbs, L. (2019). Re-conceptualising interdisciplinarity in STEM through a temporal model. Research in Science Education.

Tytler, R., Prain, V., Hubber, P., & Waldrip, B. (Eds.). (2013). Constructing representations to learn in science. Rotterdam, The Netherlands: Sense Publishers.

Tytler, R., Williams, G., Hobbs, L., & Anderson, J. (2019). Challenges and opportunities for a STEM interdisciplinary agenda. In B. Doig, J. Williams, D. Swanson, R. Borromeo Ferri, P. Drake (Eds) Interdisciplinary Mathematics Education: The State of the Art and Beyond (pp. 51-81). Springer ICME series.

Warshauer, H. K. (2015). Productive struggle in middle school mathematics classrooms. Journal of Mathematics Teacher Education18(4), 375-400.


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Peter Burrows

Russell, you make a compelling argument for guided inquiry and differentiate this from generic and poorly formulated ideas about ‘inquiry’, I wonder if this should be reflected in the title of the blog post?