By Tine Hoof, Tim Surma, Paul A. Kirschner & Mirjam Neelen
This blog is the seventh in a series of eight blogs, originally written by Tine Hoof, Tim Surma & Paul Kirschner, and published on excel.thomasmore.be.
In 2015, Richard Mayer and Logan Fiorella published their book ‘Learning as a Generative Activity’ describing eight generative learning strategies. They’re called generative (also productive) because they allow/force learners to ‘remould’ the subject matter and based on that, create their own output, such as a summary or a drawing. In other words, as a learner, you generate/produce something yourself based on and that goes further than what you’ve learned. In addition to imagining, Mayer and Fiorella also discuss summarising, drawing, mapping, self-testing, self-explaining, teaching, and enacting.
Each strategy prompts learners to apply Mayer’s Selection, Organising, and Integrating (SOI) memory model. These strategies ensure that the learner engages with the new subject matter in a ‘cognitively active’ manner. In the first blog (on summarising) you can read more about why this is important when studying.
What is imagining?
Imagining as a productive learning strategy means that while studying/learning you’re intentionally creating a mental image of what you’re learning. Think of learners who read a story and try to imagine what a certain scene would look like. Or think of learners who try to imagine how food is broken down into smaller components and absorbed, after listening to their biology teacher explaining the digestive system. Imagining something (seeing something ‘in your mind’s eye’) implies converting verbal or textual information from the original source into a mental image that the learning generates. In that way, this learning strategy is closely related to drawing as both strategies stimulate learners to convert verbal information into visual information. The only real difference is that one is also a physical activity while the other exclusively a mental activity.
Why does imagining work?
As with other productive learning strategies, learners who use imagining as a study or learning strategy go through the SOI model (select, organise, integrate). They generate a new product (in this case, a mental image) based on the subject matter, by selecting the most important ideas from the information source (e.g., a lesson, video, podcast, book). They then have to think about how to organise those core ideas into a coherent image and link that image to their prior knowledge in order to integrate it into their long-term memory.
In comparison to generative learning strategies like mapping or drawing, the danger of distraction caused by the mechanics of the writing or drawing is limited. The learner also isn’t seduced into doing irrelevant things like pimping the map or drawing to make it ‘look nice’. However, if the learner is confused about what to exactly imagine, then the act of imagining itself might create additional extraneous cognitive load, but this isn’t really different from drawing. Moreover, the mental image the learner creates needs to be constructed and held in working memory while thinking about how it relates to the learner’s prior knowledge, which might be too cognitively demanding for learners with low prior knowledge. When drawing or mapping, a learner ‘cognitively offloads’ the information, thus creating room in working memory. “Cognitive offloading refers to the act of reducing the mental processing requirements of a task through physical actions like writing down information or storing information on a cell phone or computer” (Morrison & Richmond, 2020).
How does imagining work?
Experiments like the one conducted by Leopold and Mayer (2015) demonstrate the potential effect of prompting learners to create mental images when reading a scientific text. In their experiment learners studied a nine-paragraph, computer-based scientific explanative text on the human respiratory system. The first group read each of the nine paragraphs without further instructions (control group). The second group was asked to form a mental image corresponding to each paragraph while reading (imagery group). After reading a paragraph on the structure of the nervous system for example, learners were prompted to imagine the steps in the nervous system process of the brain sending a signal to the diaphragm and rib muscles. A third and fourth group of learners were asked to create images while reading, but were also shown an onscreen drawing before reading each paragraph (picture-before-imagery group) or after reading each paragraph (imagery-before-reading group).
All learners took an immediate test and a delayed test, both of which had retention and transfer questions. On both tests the imagery group outperformed the control group on both question types. The added pictures, however, had no additional effect beyond imagining. A possible explanation might be that the learners in both imagery-and-picture groups relied on the added picture and therefore invested less mental effort in creating images themselves; they only had to remember the image. Prompting learners to convert learning content into mental images can lead to deeper learning. It is worth noting, however, that it’s difficult to determine which aspects caused this improvement in learning as learners from the imagery group were re-exposed to key concepts from the text (nervous system, diaphragm …) that re-appeared in the prompts.
Another experiment by Leopold and colleagues (2019) also highlighted the importance of the prompts used to incite learners to create mental images. In this experiment learners studied a scientific text on how the human circulatory system works and were prompted to either imagine a mental imagine from a first-person perspective (“Please imagine how your heart, arteries, capillaries, and veins are connected to each other”) or a third-person perspective (“Please imagine how the heart, arteries, capillaries, and veins are connected to each other”). Learners who imagined from a first-person perspective outperformed learners who imagined from a third-person perspective and learners from the control group who were given no instructions to imagine.
It seems, in other words, that the wording of the prompts used to stimulate learners to create mental images matters. Other experiments also highlighted the need for explicit instruction on how to implement this strategy and what concepts to include in the mental image learners try to create.
Fiorella and Mayer’s 2015 publication on generative learning strategies includes a few limitations. First of all, to be able to form an appropriate and correct mental image of the learning content, learners need some prior knowledge, which makes this learning strategy less effective for learners with little domain-specific prior knowledge. For them, this strategy might be too cognitively demanding or cause them to create incorrect mental images. Other generative learning strategies like elaborating (i.e., thinking more deeply about the content, asking yourself questions) or self-explaining (i.e., explaining the content to yourself) might be more suitable for such learners to process the learning content (Dunlosky et al, 2013). Moreover, whether learners actually form correct mental images about the learning content, is hard to verify. Also, some learners might use this learning strategy spontaneously, without being aware of it or without receiving the instruction to do so. And vice versa, even if learners are asked to use imagery, they may not (Smallwood & Schooler, 2015). Secondly, explicit instruction (including modelling) and sufficient practice are necessary with respect to how to use imagining as a generative learning strategy and which components should be included in the mental image learners create. Prompts should be used to support learners implementing this strategy.
Thirdly, studies on imagining have focused mainly on learning procedures or studying imagery-friendly, often scientific texts. Imagining is less useful as a learning strategy to learn how to solve mathematical equations or study abstract concepts, though it is possible when an equation can be graphed (i.e., imagining how a curve or a line produced by a linear or quadratic equation would look). Finally, the long-term benefits of this learning strategy are yet to be investigated, meaning that we should be cautious as to when and how we implement this strategy.
Fiorella and Mayer (2015) refer to 22 studies that investigate the impact of imagining as a generative learning strategy. In 16 of these studies it had a positive impact on learners’ learning outcomes. Dunlosky and colleagues (2013) rate this strategy as a low utility strategy, mainly because of the limitations mentioned above. They highlight the need for more research into the use of this strategy.
In conclusion, we advise using imagining as a generative learning strategy in a very deliberate way. Prompting learners to imagine something (“Try to imagine what this would look like”) might help learners process the content, but don’t expect any miracles from this limited-in-use strategy.
Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving learners’ learning with effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14(1), 4-58.
Enser, Z. & Enser, M. (2020). Fiorella & Mayer’s generative learning in action. John Catt Educational Ltd.
Fiorella, L., & Mayer, R. E. (2015). Learning as a generative activity: Eight learning strategies that promote understanding. Cambridge University Press.
Morrison, A. B., & Richmond, L. L. (2020). Offloading items from memory: individual differences in cognitive offloading in a short-term memory task. Cognitive research: principles and implications, 5(1), 1-13.
Leopold, C., & Mayer, R. E. (2015). An imagination effect in learning from scientific text. Journal of Educational Psychology, 107(1), 47–63.
Leopold, C., Mayer, R. E., & Dutke, S. (2019). The power of imagination and perspective in learning from science text. Journal of Educational Psychology, 111(5), 793–808.
Leahy, W., & Sweller, J. (2004). Cognitive load and the imagination effect. Applied Cognitive Psychology: The Official Journal of the Society for Applied Research in Memory and Cognition, 18(7), 857-875.
Smallwood, J., & Schooler, J. W. (2015). The science of mind wandering: empirically navigating the stream of consciousness. Annual Review of Psychology, 66, 487-518