What economics can tell us about teaching in higher education

This is the second post in a series which looks at higher education learning and teaching through a disciplinary lens. What can the knowledges, theories, methods and practices of particular disciplines tell us about learning and teaching at a university level? In each post, I will be speaking to disciplinary experts from my university and seeking their insights to inform the teaching practices of colleagues in other disciplines. Cross-posted at Teche.

You can read the first post in the series What psychology can tell us about teaching in higher education here.

Today’s post comes from Behavioural Economics, which offers insights into why people do – or don’t do – certain things in the economic sphere.

I spoke with discipline expert Wylie Bradford. Wylie is an Associate Professor of Economics and a Teaching & Leadership academic with significant experience in University governance and policy work.

He is also Macquarie University’s longest-serving Indigenous staff member having been at the university for 26 years. He currently teaches history of economic thought, behavioural economics and environmental economics.

Our conversation taught me some fascinating concepts, such as choice architecture, gain-loss framing and hyperbolic discounting. Wylie uses these ideas to design learning activities and assessment tasks that engage students.

What is behavioural economics?

Simply put, economics analyses the choices that people make and the consequences of choices, especially things like consumption, saving and investment. Traditional models and theories to explain economic choices make assumptions that people are consistent, well-informed, rational, and make decisions based on their best interests.

Unfortunately this is not the case! Behavioural economics takes what we know from social psychology to challenge these assumptions.

The reality is that humans do not make choices by taking into account all available information, evaluating the costs and benefits, and deciding on the best outcome. Humans are inconsistent. We are subject to various heuristics and biases which mean that we don’t behave in textbook ways.

What does behavioural economics tell us about making choices?

We tend to understand making a choice as a change – a movement from one point to another – and we ask ourselves: ‘where do I go from here?’ ‘Here’ is a reference point for evaluating our options and making a choice. The reference point is subjective and varies from person to person.

We know that choice architecture matters. That’s a fancy way of saying that how a choice is presented to someone has an impact on their decision-making. That’s probably the ultimate message of behavioural economics – choice architecture matters because humans make decisions in context. They are not context-free. We make choices that are inconsistent, subjective, and influenced by multiple factors.

What insights can behavioural economics offer about student behaviour?

A key concept is framing, and loss aversion in particular. Loss aversion is the idea that humans put more weight on negative outcomes than they do on positive outcomes. That is, we would be prepared to do more to avoid a given loss than we would to get the equivalent gain. That’s where the reference point comes in. It really matters whether or not people see things as a loss frame or whether they see them as a gain.

Where people see a situation as a loss – so they’ve set a reference point and the see the outcome as being a loss from that – they tend to behave in a more risky fashion. In a gain frame – where the reference point is lower and the outcome is an improvement – then people tend to play it safe.

Wylie describes loss aversion using the analogy of the half-full or half-empty glass in this one minute audio excerpt:

For university students, loss aversion can offer insights into the decision about whether or not to come to campus for a lecture. Images of empty lecture theatres have been doing the rounds on social media. With the option of listening to or watching lectures online, being in the room at university doesn’t hold value for accessing learning materials. If a student applies a loss frame, they a more likely to take the risk of not engaging with the lecture on campus.

In this 45 second audio excerpt, Wylie suggests that coming to campus to attend a lecture is like a half-empty glass:

From a behavioural economics perspective, studying at university is challenging. A student has to decide to spend time doing something now that will pay off at some point in the future. In deciding that is worth doing, they need to consider how they value the future relative to the present. This is where they idea of discounting is relevant.

What is hyperbolic discounting and how does it relate to procrastination?

Hyperbolic discounting is that idea that humans do not evaluate the future in a consistent way.

Wylie explains the concept of hyperbolic discounting in this two minute audio excerpt:

Procrastination is a kind of time inconsistency.

Think about it: imagine you are a student with an assignment due next week on Friday. You plan to work on it on Monday. You make a judgement that this will be enough time. On Monday, you don’t want to start work on the assessment so you tell yourself you will do it on Wednesday.

In other words, the way you envisaged how much it was worth doing the assignment last week no longer applies. You are applying a higher discount rate. The closer you get, the more painful it is to give up your time and the greater the risk you are willing to take. If an assessment task is due at midnight on Friday, teachers will see lots of submissions coming in at 11.59pm.

That’s procrastination. We all do it. Humans are not good at planning over time. We don’t use a consistent discount rate. We are always using a reference point of where we are now compared with a future point. Remember you only ever make decisions in the present, and the reference point for evaluating those decisions is constantly changing.

So hyperbolic discounting is that idea that humans do not evaluate the future in a consistent way. Their evaluation changes the closer they get to a given event in the future. This makes holding on to a plan difficult. This is not a character failing. It is a consequence of being a human moving through time.

How can teachers design assessment with these behaviours in mind?

The way in which assessment is set up will affect the way in which students allocate effort. Assessment should not push students into the path of behaviour that is not going to be in their best interests.

Progressive assessment helps cut across hyperbolic discounting, as does minimising high stakes exams at the end of a unit. Students are not left to make big decisions about how to allocate their time over long stretches of time.

Wylie includes a weekly blog activity in his Behavioural Economics unit. Following an interactive class discussion, students write a reflection on what they think is the most important idea and why. In evaluations of the unit, students say that the weekly blogs are beneficial as a type of assessment for learning. They agree that the progressive approach cuts through the time inconsistency problems they would otherwise face.

This post is just a snapshot of our conversation. Wylie experiments with assessment design based on principles of behavioural economics, such as starting students with a mark of 100% to trigger loss aversion with each assessment task. Many of Wylie’s suggestions run counter to common higher education teaching practice – the problems with practice exam papers, why students don’t turn up for final exams or complete MOOCs, and why exam results should be released before final grades.

Listen to the full 48 minute conversation:

Download a pdf transcript of the full conversation.

Further reading

Arkes, H.R. and Blumer, C. (1985) “The psychology of sunk cost”, Organisational Behavior and Human Decision Processes, 35, 124-140.

Fryer, R,G. et.al. (2012) “Enhancing the Efficacy of Teacher Incentives through Loss Aversion: A Field Experiment”, NBER Working Paper 18237 (http://www.nber.org/papers/w18237)

Hsee, C.K. et.al. (2003) “Medium Maximisation”, Journal of Consumer Research, 30, 1-14.

Kahneman, D. (2011) Thinking Fast and Slow. Farrar, Straus and Giroux.

Kahneman, D. and Tversky, A. (1979) “Prospect Theory: An Analysis of Decision under Risk”, Econometrica, 47, 263-291.

Lowenstein, G. and Thaler, R.H. (1989) “Anomalies: Intertemporal Choice”, Journal of Economic Perspectives, 3, 181-193.

Thaler, R.H. (1999) “Mental Accounting Matters”, Journal of Behavioral Decision Making, 12, 183-206.

Image sources: Hyperbolic discounting. Banner image by Shutterstock.

What psychology can tell us about teaching in higher education

Welcome to the first post in a new series in which we look at higher education learning and teaching through a disciplinary lens. What can the knowledges, theories, methods and practices of particular disciplines tell us about learning and teaching at a university level? In each post, I will be speaking to disciplinary experts from my university and seeking their insights to inform the teaching practices of colleagues in other disciplines. Cross-posted at Teche.

Today’s post comes from Psychology, and I spoke with award winning teachers and discipline experts Penny van Bergen and Alissa Beath. You can listen to audio excerpts of our conversation throughout this post, and listen to the full (29 minute) conversation or download a transcript from the link at the end of the post.

Alissa is a Senior Lecturer and Psychology Undergraduate Course Director in the School of Psychological Sciences. Her research lies in Health Psychology and Educational Psychology, looking at the role of psychological processes such as self-efficacy, emotion regulation, and resilience, in health, stress, and wellbeing. Teaching research methods and statistics to undergraduate students of all year levels, Alissa is keenly aware of the need to teach in the right way, and for students to learn in the right way. In her Course Director role, Alissa draws upon science of learning and educational psychology, especially in the intersection of the way teachers teach, the way students learn, and how institutions can be set up to best support both those things.

Penny left Macquarie this year (but remains connected as an honorary associate and supervisor) to take up the role of Professor of Educational Psychology and Head of School of Education at the University of Wollongong. With a background in developmental psychology, she applies her understanding of memory, emotion, and learning to the field of education, focusing on emotional development, cognitive development, and student-teacher relationships. She is passionate about ensuring that students of all ages have opportunities for belonging, engagement, and transformational learning.

Educational and developmental psychology offer insights into the fundamental question of what it means to learn and how learning happens. When we talk about learning from a psychological perspective, we are fundamentally interested in changes in understanding, knowledge or skills.

My conversation with Alissa and Penny highlights concepts such as memory, motivation and self-efficacy, and raises obvious — but challenging — questions.

What is learning?

In this 42-second audio excerpt, Penny describes the brain’s limited capacity for information, the magic number seven for working memory and designing teaching activities so learners are not overwhelmed:

What is memory?

Psychology understands our memory as our capacity for encountering, managing, processing and storing new knowledge and skills, including conceptual knowledge. As Penny puts it: “Everything we know, everything we know how to do, everything we know about the world, everything we know about ourselves is held within memory.” Understanding how it works is really important for teachers and students. Below is a simplified model of how the brain learns that Penny shows undergraduate students:

Learning means putting knowledge into long-term memory so that it can be consciously retrieved as needed.

We use working memory to think about information we receive from our senses, and to retrieve what we already know from long term memory. Anything you are thinking about right now is your working memory. That means any cognitive activity — including problem solving and decision-making — happens in working memory, making it critical for university study.

In this 90-second excerpt, Penny and Alissa describe information processing and encoding in long term memory and the role of teachers in engaging learning:

Why is exam cramming ineffective?

Talking about how memory functions busts a common learning myth. A classic strategy students employ for exam preparation — rereading class notes — is ineffective for learning, especially for complex problem solving. (Listen to the full conversation to hear Penny and Alissa debunk the myth of learning styles).

In this 40-second audio excerpt, Penny describes elaborativeness and distinctiveness to talk about making connections and difficult decisions:

In this 64-second excerpt, Alissa and Penny describe active learning and why it works:

What can teachers do?

Strategies that teachers can use to promote learning include:

  • Designing learning with an understanding that working memory has a limited capacity (the magic number 7). For example, review your resources with this in mind, consider timing of complex information, and share key take-aways for students.
  • Enabling connections with existing prior knowledge. For example, explicitly link new material with what has been covered in prior classes, or ask students to think how a topic might apply to their lives.
  • Designing activities that require deep thought. For example, provide students with contradictory statements and ask them to consider them. Or present a real-life problem/issue and ask students to reflect on it.
  • Encouraging students to come up with their own examples, explanations, and questions to test their ability to apply the material to novel scenarios or new contexts.

Having talked about the learning process, how does Psychology understand learners themselves?

This is where motivation and self-efficacy come in.

Colloquially speaking, motivation is the push or pull away from a task. In a study context, we are interested in the reasons a student will try to succeed. Note that students’ motivations vary considerably, as Penny explains in this 36-second audio excerpt:

Motivation is complex and being motivated to complete a degree does not necessarily mean a student is motivated to complete an assessment task or attend a lecture.

Teachers can help students increase their motivation for study — and manage the competing motivations of paid work and social demands — by reminding students that achieving the smaller things leads to the desired outcome of a qualification or a career.

It’s not enough for students to want to do well, they have to believe they can succeed. Self-efficacy refers to students’ own beliefs about their capacities and their competence in a specific area. As Alissa explains in this 28-second excerpt, higher self-efficacy intersects with motivation to promote effective learning behaviours:

Teachers can enable mastery opportunities, and balance independent learning skills and learning support, by scaffolding learning and breaking down tasks into smaller chunks, defining the parameters for learning with opportunities for cognitive growth, and encouraging students by sharing strategies for success.

Towards the end of our conversation, Penny and Alissa discussed students’ mental health and the impacts it can have on motivation and self-efficacy. They emphasise the importance of referring students to Wellbeing services for high level expertise, providing evidence-based reasonable adjustments, and promoting safe and supportive environments for students across the institution.

Listen to the full 29-minute conversation and/or download a transcript:

Further reading 

Butler, A.C., Marsh, E.J., Slavinsky, J.P. & Baranuik, R. G. (2014). Integrating Cognitive Science and Technology Improves Learning in a STEM Classroom. Educational Psychology Review, 26, 331–340. DOI: https://doi.org/10.1007/s10648-014-9256-4

Glass, A. L. & Kang, M. (2019) Dividing attention in the classroom reduces exam performance. Educational Psychology, 39(3), 395-408. DOI: 10.1080/01443410.2018.1489046

Honicke, T. & Broadbent, J. (2016). The influence of academic self-efficacy on academic performance: A systematic review. Educational Research Review, 17, 63-84. DOI: https://doi.org/10.1016/j.edurev.2015.11.002

Mayer, R. E. (2001) What Good is Educational Psychology? The Case of Cognition and Instruction. Educational Psychologist, 36(2), 83-88. DOI: 10.1207/S15326985EP3602_3

Munro, J. (2020, March 10). You can do it! A ‘growth mindset’ helps us learn. The Conversation. https://theconversation.com/you-can-do-it-a-growth-mindset-helps-us-learn-127710

Thank you to Alissa and Penny for the conversation, slides and recommended reading. Thank you to Alison Hayward and Kylie Coaldrake for technical support with the audio recording.

ABCs of pedagogy: B is for blended or hybrid teaching

Welcome to a new series, the ABCs of Pedagogy, cross-posted at the university blog Teche. It is learning and teaching award season at my university and one of the aims of this series is to provide applicants with the scholarly language to describe their teaching and learning practice. This skill goes beyond award applications and may also be useful for the purposes of reflection, conversations about teaching and learning, scholarly activities, and career progression.

Blended synchronous or hybrid flexible teaching (also referred to as ‘hyflex teaching’) is when you simultaneously teach some students in person and others online. For many of us, it is a relatively new phenomenon in the context of COVID-19. This mode of teaching is certainly challenging for both teachers and students! To support the practice of ‘blendsync’, my university blog has published posts and shared resources (including slides from a recent workshop by Mathew Hillier with a shout out to Matt Bower’s pre-pandemic research).

Perhaps you have heard the aphorism “pedagogy before technology” but the rapid shift to online and blended teaching may mean some catching up is required on the pedagogical front. If you are preparing an application for a teaching award this year, it’s likely you will mention the impacts of the pandemic on your teaching and your students’ learning. Luckily, the pedagogical language and conceptual models for blended synchronous teaching are well established.

George Siemens (2005) proposed connectivism as the learning theory for the digital age. It is an extension of constructivism, one of the most influential learning theories in formal education around the world, where learning is understood to happen through social interaction and experience (more on that in the next post in the series C is for Constructivism). In connectivism, students learn in and across networks and work collaboratively to create knowledge in digital formats.

Connectivism emphasises the ability to connect and organise information and adapt to rapidly changing systems. Learning is viewed as ‘actionable knowledge’ (Siemens, 2005) and exists beyond people to reside in technological forms and structures. If your teaching involves teams of learners contributing to shared documents and creating new learning artefacts, then connectivism may be aligned with your practice.

To describe your blended synchronous teaching, there are several scholarly frameworks for thinking about the relationship between pedagogy and technology.

Perhaps the most well-known is Mishra and Koehler’s (2006) TPACK (technological pedagogical and content knowledge) framework.

Image source.

TPACK highlights that effective digital learning requires teachers to understand technology, pedagogy, and disciplinary knowledges. For example, if a teacher only addresses technological and content knowledge (TCK) domains, this could mean asking students to generate a wiki entry to explain a difficult concept. If Pedagogical Knowledge (PK) is not considered, and the task is not scaffolded, students may struggle.

For more information, seeTPACK Explained

Building on TPACK, another model for thinking about your blended synchronous teaching pedagogy is Puentedura’s (2010) SAMR (substitution augmentation modification redefinition) framework, which offers four tiers for teaching with technology. SAMR shifts from the use of technology to enhance teaching (or make it possible during a pandemic) to the use of technology to transform teaching and learning.

Image source.

Think about these levels in relation to your teaching. At the Substitution or Augmentation level, you might be replicating f2f activities for online students by recording or streaming lectures, or using online activities to prompt learning. I expect that as you continued teaching online, and started to teach online and face-to-face simultaneously, you moved into the Modification and Redefinition levels. For example, you might have designed learning activities to combine f2f teaching with features such as online chat, annotations, collaborative documents, polls, simulations and more. Modification changes the nature of a learning or assessment task given the capabilities of technology, and Redefinition uses the affordances of technology for tasks that could be not be undertaken without it.

Read more about SAMR and Bloom’s taxonomy.  

Smyth’s (2011) 3E – Enhance, Extend, Empower framework offers an alternative for describing your technology-enabled teaching practice. If the ideas of student agency and co-creation appeal to you, this may offer a way to describe your practice and philosophy of teaching.

Image source: https://staff.napier.ac.uk/services/vice-principal-academic/academic/TEL/TechBenchmark/Pages/overview.aspx

You can find detailed examples of the 3E framework on the Edinburgh Napier University website.

When reflecting on your teaching, questions to consider include:

  • How did your teaching practice change as a result of moving online during the pandemic?
  • What strategies for teaching will you continue to use now that students are face-to-face as well as online?
  • What have you done to build relationships with students and between students?
  • How do you create shared learning spaces for face-to-face and online students?
  • Are you scaffolding networked learning? How are your students using technology to leverage their collective creativity?

Acknowledgement: In developing this series on the ABCs of Pedagogy, I would like to acknowledge the teaching and scholarship of current and former Macquarie University staff members including Vanessa Fredericks, Marina Harvey, Mathew Hillier, Olga Kozar, Danny Liu, Karina Luzia, Margot McNeil, Anna Rowe, Cathy Rytmeister, Theresa Winchester-Seeto and others.

Mishra, P., & Koehler, M. J. (2006). Technological Pedagogical Content Knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017-1054.

Puentedura, R. (2010). SAMR and TPCK: Intro to advanced practice. Retreived from

Siemens, G. (2005). Connectivism: A learning theory for the digital age. International Journal of Instructional Technology and Distance Learning, 2(1), 3-10.

All images of theoretical models in this post are shared under a Creative Commons Attribution Share-Alike license.