By Russ Fox
Posted Tue 7 May, 2024

As an early career researcher, I have relatively recently made the transition to academia and am getting used to the rhythms, expectations, challenges, and pleasures of academic life. However, one familiar and happy place for me is the classroom. I have had the advantage of forming an identity as a teacher and developing my classroom practice with primary school, secondary school, and adult learners. A critical challenge I have wrestled with over the journey has been, “how much should I explicitly teach and how much should I guide and facilitate students to engage in their own learning?” This is a relevant question for the university context. How much teaching is too much for our adult learners?

Different approaches

Educators have long debated the merits of different instructional approaches. More active approaches – such as project-based – focus on creating opportunities for learners to engage with key concepts or skills independently or in small groups with minimal teacher guidance in the first instance, with the goal of fostering autonomy and deep engagement. These might include more open-ended or project-based tasks that require students to apply content knowledge or skills described in readings, textbooks, or other resources. Such approaches are commonly presented as the antithesis of teacher-led (e.g. lecture-based) classes and have been found to positively impact student learning (see Freeman et al., 2014).

In contrast, explicit instructional approaches involve directly teaching necessary terms, concepts, or skills to students as a starting point. Following this, the teacher models how to apply the relevant concepts or skills before providing students with structured opportunities to practise their learning and receive feedback. Explicit instructional approaches differ from traditional forms of didactic lecturing as they require learners to actively respond to the material being taught and modelling phases of instruction (e.g., class-wide multiple-choice questions, think-pair-share activities, short written responses to prompts, or brief technical demonstrations of skills).

Which is best for my students?

Well, both. In their recent study, Martella et al. (2024) tested the impact of different combinations of lecture-style and active learning (i.e., more student led or project-style) approaches on novice tertiary student learning. When comparing a 100% lecture condition with a 100% active learning condition, Martella and colleagues found the lecture-based approach was more effective than active learning. However, this experiment does not reflect how university teachers teach, using a mix of both. Martella et al. (2024) then conducted a second experiment comprised of three conditions, one exclusively lectures, another where lectures were interspersed with active student-led learning, and a third that used blocks of lecturing followed by blocks of active learning. The interspersed condition had the greatest effect on student learning, with no statistically significant difference lecture only and blocked approach. This makes intuitive sense to me. We need approaches that are fit for purpose. 

So, when is too much teaching too much?

Knowing when to instruct explicitly and when to provide more independent, open-ended, and complex project-based tasks is critical to ensuring we match our instructional approach to our learners’ needs. The following ideas may be helpful in deciding when to teach more explicitly, and when to create more active, open-ended opportunities for students to independently lead their own learning.

Knowing when to instruct explicitly and when to provide more independent, open-ended, and complex project-based tasks is critical to ensuring we match our instructional approach to our learners’ needs.

Teach when things are new and learners are novices

If the learning material is new, novel, complex, has multiple steps, or unfamiliar components, this can create significant cognitive load for an individual. Cognitive load refers to the cumulative impact of components of a specific learning task on an individual’s working memory (Sweller et al., 2019). Working memory can be thought of like the ‘workbench’ humans use to ‘hold’ stimuli –information about the task, terminology, specific skill components, concepts, as well as the context itself– so it can be manipulated and applied to the task at hand. While variation in working memory capacity across individuals exists, we all reach a cognitive load limit. Subjectively, learners may feel overwhelmed, frustrated, or disengaged. As noted by Kalyuga (2007), cognitive load and working memory processing are a major factor influencing the overall effectiveness of instruction.

Problem-solving, inquiry, and projects all require high levels of knowledge and skill for an individual to be able to understand what the task involves, where to begin, and what information may be relevant or irrelevant. As a result, such approaches can increase the cognitive load for novice learners – potentially explaining the benefits of 100% lectures over 100% active learning in Martella et al.’s (2024) study. By contrast, long-term memory has seemingly endless capacity and once skills and knowledge have been acquired, a learner can connect, relate, and readily problem-solve with reduced load. Explicit instructional approaches work to reduce the risk of cognitive overload, increasing the likelihood of novice students retaining the desired knowledge.

Increase independence and challenge as expertise grows

Once learners are fluent (i.e., can respond correctly and relatively quickly) with their new knowledge and skill, then increased complexity and independence become necessary to maximise learner engagement and progress. The expertise reversal effect describes the phenomena where supports that work to reduce cognitive load and enhance learning outcomes for novice learners become detrimental to learning for students once they have developed expertise (Kalyuga, 2007). At this stage, requiring learners to discern what a task involves, where to begin, and what information may be relevant or irrelevant becomes optimally challenging, rather than cognitively overloading.

Expert learners need to be challenged, extended, and their skills and conceptual knowledge independently applied in creative and open-ended ways (see Castro-Alonso et al., 2021 for suggestions on instructor-managed and learner-managed supports to optimise cognitive load). For example, once learners in an undergraduate education course have demonstrated sufficient understanding and expertise in the theory and practice of different classroom management approaches, they are likely to benefit from the challenge of identifying specific models of behaviour support to apply to the real-world context of their placement school or to address the needs of a specific case-study student. Here, more teaching may be too much teaching.

While I am in a happy place in the classroom – online or on campus – finding ways to check-in with students to see whether they need more support or more independent challenge is still a practice I am developing. 

Please feel free to share ways you check-in with your students to assess their progress in real-time.

References

Castro-Alonso, J. C., de Koning, B. B., Fiorella, L., & Paas, F. (2021). Five Strategies for Optimizing Instructional Materials: Instructor- and Learner-Managed Cognitive Load. Educational Psychology Review, 33(4), 1379–1407. https://doi.org/10.1007/s10648-021-09606-9

Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., & Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering, and mathematics. Proceedings of the National Academy of Sciences, 111(23), 8410–8415. https://doi.org/10.1073/pnas.1319030111

Kalyuga, S. (2007). Expertise Reversal Effect and Its Implications for Learner-Tailored Instruction. Educational Psychology Review, 19(4), 509–539. https://doi.org/10.1007/s10648-007-9054-3

Martella, A. M., Schneider, D. W., O’Day, G. M., & Karpicke, J. D. (2024). Investigating the intensity and integration of active learning and lecture. Journal of Applied Research in Memory and Cognition. https://doi.org/10.1037/mac0000160

Sweller, J., van Merriënboer, J. J. G., & Paas, F. (2019). Cognitive Architecture and Instructional Design: 20 Years Later. Educational Psychology Review, 31(2), 261–292. https://doi.org/10.1007/s10648-019-09465-5