What to learn about learning?

Table of contents

What to learn about learning?

Conclusion

Works cited

What to learn about learning?

Learning is an important human capacity that allows us to acquire deeper levels of understanding of the world, which represents the foundational basis for innovation and knowledge development. Although learning as a specific field was neglected for lots of years in which it was just considered as a passive activity wherein the information was merely transferred from one generation to another, recently, psychologists, educators, and neuroscientists have started to conceive learning as a complex process itself that can be analyzed and theorized, so that we can better exploit our learning capabilities. These different theories have been re-evaluated over the years, leaving several useful and beneficial techniques for the learning process but that vary widely in their effectiveness. While it is true that different techniques offer different advantages to learn effectively depending upon personal traits, recalling has proved to be one of the most global and effective strategies to improve the learning of intricate concepts, and it appears to outdo generally used techniques such as concept mapping and rote rehearsal. Additionally, combining recalling with different monitoring strategies during learning might help not only consolidate memory but also reduce negative feelings during learning such as anxiety and apprehension.

Nowadays, learning can be defined as a process in which the brain makes a conscious effort to acquire new abilities or information with a specific purpose. However, more than one kind of learning exists, namely rote learning and meaningful learning. In the rote learning, the brain is not required to associate the novel information with relevant knowledge elements already present in the learner’s mind. In contrast, in the meaningful learning, the brain ingrains the novel information in the learner’s mind by using relevant knowledge elements previously established (Novak). From these definitions, it is evident that only meaningful learning can lead to the development of a well-connected knowledge network in which every new entry of information is able to modify the cognitive space in one’s mind, thus leading to the refining of existing concepts and propositions (relationships between concepts). This continuous modification of concepts is key for critical skills such as problem solving and creativity. Consequently, people who learn mainly by rote normally struggle to solve novel problems. The development of meaningful learning is not simple, and it usually requires a high integration of several aspects. Beyond the necessity of some existing well-structured knowledge in the mind, to which the new information can be associated with, a high emotional commitment is mandatory. In other words, without a determined attitude and conscious effort to learn, no meaningful learning can occur. Notwithstanding, several strategies are available that can nurture and facilitate this powerful type of learning.

Most of the strategies that encourage meaningful learning are considered as elaborative studying techniques, which means they elaborate concepts to establish an understanding not only of the meaning but also of the relationships of the information to be learned. In this category, we find concept mapping, which according to its creators Joseph Novak and Bob Gowin “is a schematic device for representing a set of concept meanings embedded in a framework of propositions” (15). In other words, concept maps claim to clarify the connection between the information that is presented. In this technique, the material is organized in a hierarchical way, showing inclusive concepts at the top of the map, and progressing to more detailed or specific concepts as we move down. This relative simplicity and easy applicability to a variety of knowledge fields make concept mapping appear regularly in the classroom environment and textbooks.

There are different significant characteristics that make concept mapping a powerful learning technique. For instance, when constructing the concept maps, students and teachers have recognized they can identify new meanings they were not aware of before constructing the concept maps. Then, this technique can stimulate creativity and discovery. Furthermore, concept mapping can be useful to show misconceptions within students by the proposition of wrong relationships or the absence of critical connections. In addition, concept mapping can positively influence the retrieval process because not only does it stimulate rote recall of knowledge but also other learning domains such as analysis and synthesis, thus being able to encompass 3 out of the 6 recognized learning domains – namely, evaluation, synthesis, analysis, application, comprehension, knowledge (Conklin 80)-. Finally, one important benefit in favor of concept mapping, also mentioned by its creators, was that in general terms, humans possess a remarkably poor memory for specific details but have instead a privileged memory for visual concepts. In that sense, the graphical representation of the map can stimulate better connections in the mind that might consolidate easily in the long-term memory. Novak and Gowin also comment that the simplicity of concept maps represents an advantage for revision tasks cherished by students because they prefer this tool over rewriting of reports. Additionally, during the redrawing of concept maps, students can reduce the clutter and crowding generated by the study of complex ideas. In that sense, clarity can be strongly boosted using this technique.

However, while concept mapping can constitute an effective way of presenting, synthesizing, and evaluating knowledge, apparently it is not actually the best way for learning when studying individually, as some researchers have found. Jeffrey D. Karpicke and Janell R. Blunt, recognized researchers in psychological sciences at Purdue University, have been actively working in the study of recalling, also known as retrieval, as an effective learning tool for 6 years now. In their study “Retrieval practice produces more learning than elaborative studying with concept mapping” (772–75), they found that free-retrieval produces better results than concept mapping and re-reading for long-term learning. To start, retrieval refers to the active process of reconstructing knowledge in the mind. While retrieval is regarded as a way of measuring knowledge because it represents an act of access to the stored knowledge in the mind, it has received little attention as a productive learning process. This is mainly a consequence of the bad comparison with the measurement of a physical object, where it is assumed that the act of measuring that object cannot change any of its properties. However, given that the act of retrieval itself can affect memory and turn on new neural networks, this act should be considered as a learning strategy too. In their research, Karpicke and Blunt evaluated a group of more than 100 students, in which they were asked to use each technique to learn information that was presented in two different structures usually found in science education, namely enumeration sequence (i.e. text describing different body parts and their properties) and continuous sequence (i.e. texts describing ordered events as when describing biological processes such as respiration). Also, the tests to assess the material learned included verbatim and inference questions, which can evaluate different degrees of knowledge. In this way, the authors guarantee that the validity of their conclusions does not depend on the structure of the material studied, or the depth of the knowledge acquired.

Karpicke and Blunt’s results show that both retrieval and concept mapping, which are active learning strategies – approaches that require students to do things while thinking about why and how they are doing them – produced better performance than re-reading, which is regarded as a passive learning strategy – approaches in which students only receive and internalize the information given by a particular source such as a professor or a book. When comparing the results of retrieval and concept mapping, surprisingly the authors found that retrieval almost doubles the results obtained by concept-mapping, and that retrieval was still better even when the students were asked to produce concept maps in the tests. The major explanation for this result was that apparently, students tend to overload the concept maps when creating them with open books. In that sense, the concept maps can be more difficult to attach to the memory. On the contrary, remembering tends to produce simpler representations in the memory that are in turn easier to recall. In other words, representations with less cognitive load favor the learning process. Furthermore, the authors highlight that the advantage related to the retrieval process may lie in the deliberate effort to actively discriminate between concepts, which may promote a deeper learning. On the other hand, elaboration with concept mapping increases the number of encoded features (cognitive load) but not necessarily discrimination. The overload of details, in that case, may transform the learning process into a frustrating experience. In favor of this cognitive load effect, another study conducted by Detlev Leutner et al (284–89) at Duisburg-Essen University in Germany evaluated the effects of drawing versus mental imagery formation against cognitive load and comprehension. The authors concluded that the building of mental images tends to decrease the cognitive load and reduce the split-attention effect – distraction caused when paying attention to unintegrated verbal and visual material – in turn, leading to an increased comprehension of the information.

Interestingly, one of the key factors for an effective learning is that only the student can choose how to learn, and his success in this process is determined to a high extent by his own knowledge of the existing cognitive strategies. This is also known as metacognition, which means “the cognition about cognition”. A lack of knowledge about the different learning strategies available (poor metacognition) can generate anxiety, which in turn can lead to procrastination (Paechter et al. 1–13). Aside from the poor metacognition, other specific factors that also influence the development of anxiety related to learning are the field of study, societal myths, gender, ethnicity and previous bad experiences in similar subjects. For instance, several studies have found that female students tend to show higher levels of anxiety when learning mathematics. Also, a previous mathematics anxiety can be translocated into statistics and physics anxiety in the future, and even social stereotypes about mathematical giftedness can induce anxiety when learning mathematics too (Paechter et al. 1–13). All the apprehension felt during this anxiety phase can induce students to sacrifice accuracy and mastering of the material for speed to terminate the anxiety-evoking situation. Some studies have found that this anxiety induced procrastination is highly related to temporal discounting (Howell and Watson), which privileges rewards of the present at the expense of the rewards of tomorrow. To address this problem, the development of metacognitive strategies such as planning, monitoring, and short-term rewards for diligent work is crucial. The benefits can be translated in a continuous, staggered, and strong knowledge progress that can also help to identify and fill knowledge gaps early when studying for tests. However, no matter how well organized a learning process is, if there’s no awareness of the several existent learning techniques and their relative effectiveness, this process can become nothing but slow and frustrating. This frustration, again, can develop into anxiety and lead to procrastination, which can ultimately not only delay the learning but also impact its quality due to the relative low deep processing of information versus high surface processing. (Howell and Watson 167–78). In other words, acquiring information at last minute before some examination can be effective to retain information in the working or short-term memory, but it is unlikely to result in any meaningful integration of the information in the long-term memory .

Some experts have stated that the key to defeating anxiety and procrastination problems might be repeated testing (Keresztes et al. 3025–35). This monitoring strategy can be considered as a way of retrieval given the effort needed to reconstruct knowledge to answer the question in the test. Yet, the benefit of testing is not due to the test itself, which might even promote some anxiety and negative feelings, but rather to the changes induced in the mind by the knowledge reconstruction process (Karpicke and Blunt 37–41). Several types of retrieval can be applied when using this technique such as prompt retrieval, cued recalling, visual recalling, and multiple-choice test retrieval. During prompt retrieval, students are asked to explain concepts and give specific details about the material. This can benefit successful learning because students are directed to remember details that are considered essential by the instructor. In the cued recalling, beyond explanations, the students are presented with cue words instead of questions to help remember concepts. In that way, learners are not necessarily analyzing information to answer a question but rather triggering the recalling of the rest of the information that is related to one specific concept. Visual recalling is a technique that has proved that recalling is not only limited to the verbal material. In their research, Carpenter and Pashler (474–78) focused on recalling to enhance the learning of maps using covert pictures, but for principle, this idea might be extended to other learning tasks that involve visuals such as biological or physical cycles. With respect to multiple-choice test retrieval, some studies have shown that when the questions are well designed and stimulate analytical capabilities to choose between the options available, the test can stimulate not only the recalling of the right answers but also information related to the incorrect alternatives (Little et al. 1337–44). Notoriously, even though some differences in the learning process are expected to be triggered with each guided retrieval technique, as yet no statistical differences have been reported among the different approaches (Smith and Karpicke 784–802; Smith, M. A., Blunt, J. R., Whiffen, J. W., Karpicke 544–53). These latter results open the gate to a variety of options from which students can pick to boost their learning outcomes to the highest level.

One additional benefit frequently overlooked about the use of metacognitive strategies is that the effective time management related to their use can, in turn, avoid last-minute overnight study sessions, which can potentially prevent issues related to sleeping and memory. It is well known that sleeping has a paramount importance in processes intended to consolidate memory. Some of the first interpretations suggested that sleeping had a passive role in oblivion because it prevented new memories from intruding or interfering with the previous memories acquired before sleep (Peigneux et al. 165–84). However, subsequent neuroscientific studies deepened in the role of sleeping and found that there is a burst of cortical activity during sleep that mediates a transfer of neural patterns from the hippocampus to the cerebral cortex (Peigneux et al. 165–84; Keresztes et al. 3025–35). In other words, there is a consolidation of memories from working memory to long-term memory. In that sense, sleep deprivation is considered harmful for memory consolidation. Even though some things can be recalled from working memory. This may explain why a student can still reach a high grade in a test just studying the night before. The drawback is that this student will certainly forget that information faster than a student who has studied consistently for a longer period and has allowed time and sleep to memory consolidation.

After all this analysis, it is clear that retrieval can be used as a learning technique and bring enormous benefits to the learning process. Considering that the brain works mainly as a visual processor instead of a word processor, recalling with the deliberate use of images even for non-visual concepts might represent an additional enhancement to the use of this technique that is worth exploring further. Also, one of the main surprising facts usually found within students is their lack of knowledge about all the theory behind the learning process. In that sense, with a consolidated and well-documented strategy such as retrieval, more efforts should be done to spread this knowledge to young students. The implementation of required classes devoted to learning how to learn might bring invaluable advantages for new generations. Not only will it boost their cognitive abilities to their highest level, but also it will promote more effective time management when studying, and ultimately a healthier life style. The knowledge and use of metacognitive strategies might allow the release of time used in senseless learning techniques to life-enriching activities.

Conclusion

In conclusion, learning is a very complex activity influenced by several factors that should be studied and comprehended by all who intend to obtain the most of this process. Different metacognitive strategies are available to maximize the long-term retention of the information to be learned, but students need to be conscious of those strategies first to harness them. In recent years, retrieval or the simple act of accessing stored knowledge in one’s mind has been elevated from a trivial way of measuring knowledge to maybe the most effective way of studying. Several strategies can be interchangeably applied with this technique such as free-retrieval, prompt retrieval, cued recall, visual recalling, and multiple-choice test retrieval. The knowledge and application of these strategies, concomitantly with some regular monitoring of the content studied can help to plan ahead in the learning process, avoid potential anxiety, derived procrastination, and sleep disorder problems, and ultimately help consolidate the material learned in the long-term memory, which is the definitive goal when we decide to learn something new.

Works cited

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Conklin, Wendy. Applying Differenciation Strategies: Teacher’s Handbook for Grades 3-5. Shell Education, 2007.

Howell, Andrew J., and David C. Watson. “Procrastination: Associations with Achievement Goal Orientation and Learning Strategies.” Personality and Individual Differences, vol. 43, no. 1, 2007, pp. 167–78, doi:10.1016/j.paid.2006.11.017.

Karpicke, Jeffrey D., and Janell R. Blunt. “Retrieval Practice Produces More Learning than Elaborative Studying with Concept Mapping.” Science, vol. 139, no. February, 2011, pp. 772–75.

Keresztes, Attila, et al. “Testing Promotes Long-Term Learning via Stabilizing Activation Patterns in a Large Network of Brain Areas.” Cerebral Cortex, 2014, pp. 3025–35, doi:10.1093/cercor/bht158.

Leutner, Detlev, et al. “Cognitive Load and Science Text Comprehension: Effects of Drawing and Mentally Imagining Text Content.” Computers in Human Behavior, vol. 25, no. 2, Elsevier Ltd, 2009, pp. 284–89, doi:10.1016/j.chb.2008.12.010.

Little, Jeri L., et al. “Multiple-Choice Tests Exonerated, at Least of Some Charges: Fostering Test-Induced Learning and Avoiding Test-Induced Forgetting.” Psychological Science, vol. 23, no. 11, 2012, pp. 1337–44.

Novak, Joseph D. “Ausubelian Theory of Learning.” Encyclopedia of Science Education, 2013, pp. 1–8, doi:10.1007/978-94-007-6165-0.

Novak, Joseph D., and D.Bob Gowin. Learning How To Learn. Cambridge University Press, 1984.

Paechter, Manuela, et al. Mathematics Anxiety and Statistics Anxiety . Shared but Also Unshared Components and Antagonistic Contributions to Performance in Statistics. Vol. 8, no. July, 2017, pp. 1–13, doi:10.3389/fpsyg.2017.01196.

Peigneux, Philippe, et al. “Sleep and Forgetting.” Forgetting, edited by Sergio Della Salla, Psychology Press, 2010.

Smith, M. A., Blunt, J. R., Whiffen, J. W., Karpicke, J. D. “Does Providing Prompts during Retrieval Practice Improve Learning?” Applied Cognitive Psychology, vol. 30, 2016, pp. 544–53.

Smith, M. A., and J. D. Karpicke. “Retrieval Practice with Short-Answer, Multiple-Choice, and Hybrid Tests.” Memory, vol. 22, no. 7, 2014, pp. 784–802.