Evidence-based principles for learning and teaching STEM—part two

More of the best-established principles from learning research that every STEM teacher should know about.

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By Tina Overton, Monash University, and Liz Johnson, Deakin University

This article is the second describing the best-established principles derived from learning research that should inform the design of STEM courses. Read part one here.

5. Embrace flipping

The Challenge

Learners have limited capacity to absorb and use new information

The Research

Studies on the use of the pre-lecture sound very much like the forerunners of the flipped lecture, where students prepare before attending an interactive lecture. The pre-activity in the flipped format can vary and may be in the form of reading or carrying out research but often is in the form of watching a video. The ready availability of technology to capture lectures and produce screencasts has undoubtedly lead to the rise in its popularity. The benefits of the flipped classroom model are not up for debate. Studies such as that recently published by Weaver (2015) demonstrated convincingly that grades improved for students studying via a flipped mode. Notably interactive sessions give students a sound reason to turn up in the face of declining lecture attendance. Of course the value of the flipped model is twofold; the pre-lecture preparation that prepares the student and the switch from a didactic lecture to an active, student-centred face-to-face session.

Applying the research

Flip lectures to make best use of the class time:

•          create a learning program that requires and rewards preparation

•          create a lecture environment that builds on and applies the preparation

6. Ensure active learning

The Challenge

Learning requires active engagement

The Research

Active learning has been discussed in the literature for decades; its benefits to learning and motivation are very well documented. The definitive study by Freeman et.al. (2014) was a meta-analysis of 225 studies that reported data on examination scores or failure rates for STEM undergraduates studying through traditional lecturing or active learning. The results showed that average examination scores improved by about 6% when active learning was employed and that students taught by traditional lecturing were 1.5 times more likely to fail than students taught through active learning. Concept inventories are designed to measure deep understanding of foundational principles in a discipline. Active learning had an even greater effect on student performance on concept inventories than the gain seen in more conventional examinations. This implies that active learning is even more important for core disciplinary understanding than for discrete tasks.

The benefits of active learning are so impressive and so well reported that some have suggested that it is immoral to continue to teach using traditional didactic lectures (Waldrop, 2015). So the success of the flipped model should be no surprise, combining as it does two approaches that have already been demonstrated to be effective for student learning. Yet across Australian universities, students still sit in lecture theatres, enduring interminable PowerPoint presentations of one-way delivery of information. Is there any wonder students vote with their feet and choose not to attend? Ironically, working through the material for themselves is a more active way of learning than the lecture itself and thus probably more effective for their learning.

Applying the research

Design learning experiences that require the student to actively work with the material:

  • ask students to construct their own interpretation of core concepts
  • pose problems and challenges that require students to review their own understanding through application
  • use peer learning to encourage students to test their understanding and explore different viewpoints
  • include multiple modes of learning and assessment that require students to work with material in multiple forms and apply in different ways.
  • include problem-based or case-based learning activities
  • manage complexity of real-world problems with careful scaffolding of material and/or structured group learning
  • check the relevance of problems is clear to your students.

7. Make it authentic

The Challenge

Learner engagement and relevance of the material affects learning outcomes

The Research

Authentic, real life contexts and relevance are known to motivate students (Hmelo-Silver, 2004). Students develop synthesis and judgement skills as they grapple with counter-balancing ideas and facts, and often, an absence of definitive evidence (Lombardi, 2007). The pedagogy that brings together active learning with authentic contexts is problem-based learning (PBL) and related variants. In PBL, students work on real problem scenarios in groups and the tutor takes on the role of facilitator rather than source of knowledge. PBL differs from problem-solving in that students are presented with the problem before they have acquired the relevant knowledge. They define for themselves what they need to know, source information and share it and tackle the problem. PBL is widely used in medicine and other professional disciplines and is making some appearances in STEM education. Variants include structured group learning (Eberlein et al, 2008), and case-based learning (National Centre for Case Study Teaching in Science, 2016). The research shows quite clearly that student learning through PBL have enhanced transferable skills, are better motivated, make better postgraduate students and have better retention of knowledge (Boud & Feletti, 1991).

Problem and inquiry-based pedagogies do have their critics. The 2006 paper by Kirschner, Sweller and Clarke caused quite a stir when it was published as it claims that problem and inquiry-based approaches place too much load on working memory to be effective, leading to cognitive overload. It is important to keep cognitive load in mind when designing learning activities and the inclusion of authentic or real life contexts does increase cognitive load. However, the authors’ model of problem and inquiry-based approaches is based on very unstructured activities and, in practice, most models use heavily scaffolded activities, so reducing potential cognitive overload. 

Applying the research

Build authentic/real-world applications into learning:

8. Consider the implications of technology  

The Challenge

New technologies are changing the way students engage with learning activities and provide opportunities to improve practice

The Research

Technology inevitably influences how we teach in the classroom and beyond, with many teachers assuming that the use of technology always enhances learning. It is common to see lecture theatres of students with laptops open, using them to make notes or annotate slides rather than using paper and pen. Research into the use of technology in the learning environment is running behind its implementation. One interesting study has compared the practice of taking notes on a laptop with taking notes using paper and pen. In 2014, Mueller and Oppenheimer reported that students who took notes in lectures using a laptop did so verbatim, whereas those who made notes using pen and paper made fewer notes, but processed the information and reframed it in their own words, which was beneficial to learning. The students who made paper and pen notes performed better on tests of conceptual understanding thus demonstrating better understanding. Tutors should be aware of such research and share it with their students to ensure that all are aware of the optimal learning environment. 

New technologies also introduce the capacity to learn about our students in more rigorous ways. Online learning creates a digital learner footprint that can illustrate how learners use learning resources and interact with universities. This is precious information for teaching teams that can be used to evaluate the efficacy of materials in real-time and to adjust learning and assessment to better fit the students. It is also proving crucial for universities to better support student’s experience of higher education and manage student attrition from courses. Current research investigates how teachers use data from learning and how students can use data to monitor their own learning (Colvin et al, 2015). The field of learning analytics is accelerating as universities move to the minimum of a blend of online and face-to-face teaching and will require teaching teams to develop their own expertise to effectively manage and interpret the large volumes of data.


Extract from report prepared for the Australian Council of Deans of Science.

Tina Overton

Professor, Monash University