Based on my own observations in Fulbright , note-taking is a common practice among students due to its potential usefulness for learning. However, I've noticed that students often lack a systematic understanding of different strategies to use when taking notes, as well as strategies for how they learn and processing information. Additionally, note-taking is a complex cognitive process. Therefore, the value of a product that explains and synthesizes the scientific knowledge about learning and information processing can assist students in selecting appropriate note-taking strategies and, perhaps, in understanding how to effectively utilize artificial intelligence tools such as LLMs (Chat GPT).
This article will focus on the cognitive explanation of note-taking and note-taking strategies, helping lay the groundwork for information processing strategies that student can use for learning.
Two primary benefits of note-taking for learning are encoding (helping individuals to think) and storing (helping individuals to remember) (Slavina, 2018; Kiewra, 1989; Di Vesta and Gray, 1972). These two functions will be explained in detail below.
Note-taking practice aids in encoding information by engaging students mentally with the material, thus enhancing learning effectiveness through the encoding hypothesis (Kiewra, 1989). This theory finds support in studies showing positive effects of note-taking, without review. Einstein's study (1985) demonstrated that individuals who took notes could recall important propositions better than unimportant ones. Conversely, those who did not take notes recalled both important and unimportant propositions similarly. This note-taking effect aligns with the depth of processing theory proposed by Craik and Lockhart (1972), more deeply information is processed during encoding, the better it is remembered later on. In their experiments, participants remembered words better if they asked questions about the meaning of the word rather than just focusing on the word's visual aspects.
Different note-taking strategies might create different effects on encoding and the depth of information processing. For example, Bretzing and Kulhavy (1979) conducted a study comparing different note-taking strategies. They suggested that paraphrasing and summarizing can encourage deeper semantic processing compared to simply transcribing directly.
To explore the impact of encoding through note-taking more deeply, I will analyze various note-taking strategies and their influence on information processing. Here is an overview of different note-taking strategies outlined by McPherson (2012), along with my explanation of their cognitive effects in learning. Note-taking strategies for processing and encoding information can be categorized into two main groups, based on McPherson's classification (2012), including selective practice and connection practice. The selective strategy includes (1) Highlighting, (2) Using Headings, and (3) Summarizing & Visual Summarizing. Connection practice involves (4) Concept notes, (5) Concept maps and mind maps, and (6) Active recall and self-explanation.
Below is a description of the various note-taking practices and my explanation of their cognitive roles in learning.
The highlighting strategy helps readers become more active in determining what information is important to highlight while reading and thinking (Ponce & Mayer, 2014). Winchell (2020) studied the choice of information that students highlight, which can reveal the level of understanding, how they grasp key ideas, and their reading goals. Highlighted information stands out more and is easier to remember compared to information that is not highlighted, based on the isolation effect (Von Restorff effect) (Parker, 1998). In a study by Ponce & Mayer (2014), participants spent more time looking at highlighted phrases. Additionally, highlighting might aid retention. In 1980, Harley conducted a study comparing two groups of sixth-grade children, with one group reading a passage with highlighted text while the other group read plain text. The group that read the highlighted passage scored higher on the fill-in-the-blank test assessing memory after reading.
Summarizing and Visual Summarizing: Summarizing helps users filter and synthesize important information.
Summarizing helps users filter out important information from the text, then synthesizes it into a concise paragraph (McPherson, 2012). Meanwhile, visual summarizing allows for flexible summarization and organization of information without being limited by the linear format of text. It also enables the encoding of information through dual-encoding (using both words and images). This is another way to expand the function of working memory because verbal and non-verbal information can be encoded separately and together within working memory, according to the dual-encoding theory (Paivio, 1981).
Heading: group information into meaningful chunks.
By looking at headings, users can get an overall idea of the text. According to McPherson (2012), headings help highlight the structure of information. Studies have shown that the presence of headings in a text helps learners summarize better (Brooks, 1983), write better outlines (Dee-Lucas, 1980), and remember main ideas better (Hartley, 1980). Headings, along with titles and tables of contents, are classified by McPherson (2012) as organizational signals in a text as they help to organize information in a meaningful way.
Self-explanation help users to explain learning content in their own way.
Explaining is about identifying the relationships between components in the system—it answers the questions "How" and "Why" events happen (Granott, 2002). Studies provide further evidence of the effect of self-explanation in learning. Chi (1994) demonstrated that creating explanations helps students learn better compared to spending the same amount of time rereading the material.
Stigler (1999) compared math education in the United States and Japan, showing that Japan scored higher because it focused more on explaining why mathematical formulas work, while in the U.S., teachers only provided introductions and exercises. The effect of self-explanation can be explained by Ausubel's Meaningful Learning Theory. Ausubel hypothesized that learning occurs by connecting new concepts to what the learner already knows (Ausubel, 1962) (Novak, 2008).
Concept Note - a practice that helps self-explain key concepts learned.
This note-taking strategy is one I've developed based on my understanding of the value of concepts and the act of self-explanation.
Concepts are how we understand the world through the process of abstraction. Humans develop this ability from around the age of 3 when they recognize patterns in the world and begin to identify language labels for those patterns (Macnamara, 1982). Humans don't just process individual pieces of information; we also form larger ideas - concepts - to connect and find commonalities among information (Medwell, 2020). Concepts are also theorized as part of semantic memory - the way long-term memory stores knowledge about the world. We build an understanding of the world through concepts and the logical connections between them (Collins & Quillian, 1967; Jones, 2015).
Alongside the value of concept is the role of self-explanation in verifying one's understanding (Granott, 2002). Because people tend to believe that they understand the world more than they actually do, self-explanation is crucial. People often mistake observing (or reading) about a phenomenon/object for truly understanding its mechanisms (Rozenblit, 2002). It makes sense for learners to self-assess their understanding of key concepts after learning by writing in their notes what they understand about those concepts.
The concept note serves as a strategy for connecting information across various disciplines and courses. For instance, I encounter the Framing theory in linguistics, visual studies, and architectural history classes. Over time, through practicing concept notes—explaining my understanding in notes themselves—those notes become the place where I gradually build my knowledge of the Framing theory in different contexts and fields.
Additionally, concepts form the foundation of the knowledge structure (Erickson, 1995). According to Erickson's model of knowledge structure (1995), concepts act as the fundamental units for constructing principles or theories within a chosen field. By gradually developing an understanding of the key concepts in a field of study, students can incrementally build their expertise. The knowledge structure (concepts and the logical relationships between them) of experts is clearer and more systematic when compared to novices. Novices' knowledge is often disorganized and incomplete. They lack a full understanding of the relationships between concept and the scope of the knowledge domain (Day, 2001).
Therefore, I see the concept note as a fundamental tool for understanding, synthesizing knowledge, connecting, managing, and constructing knowledge for learners, as it helps learners identify, explain, and gradually build their understanding over time.
Mind maps and concept maps help identify key concepts and the relationships between those concepts.
Concept maps, along with mind maps, are graphical tools for organizing and representing knowledge, used to visualize the connections between semantic units (units of meaning) (Novak, 2006). Therefore, students can use concept maps and mind maps to identify the main concepts of the topic they are studying and draw logical connections between those concepts. Both practices are grounded in cognitive theory based on the structure of semantic memory, which includes concepts and the relationships between them (Jones, 2015). Semantic memory is a part of long-term memory and is where knowledge about the world is stored (Tulving, 1972).
Therefore, concept maps and mind maps can be used to visualize the internal knowledge structure of students. This practice has the potential to make learning meaningful for learners because meaningful learning involves finding connections between new knowledge and what is already known, according to Ausubel’s meaningful learning theory (Ausubel, 1962).
Concept maps have been used to visualize changes in students' understanding. Novak's longitudinal study (1991) tracked the development of students' knowledge in science. Novak interviewed students initially in grade 2 and then after 10 years, in grade 12. He interviewed students about their subject knowledge, transcribed their responses, and drew concept maps to visualize and track the development of the knowledge structure in students.
The difference between mind maps and concept maps lies in their structure. A mind map starts with a central topic and then branches out around it; therefore, the structure tends to be hierarchical, including smaller sub-concepts. On the other hand, a concept map allows for more flexible connections; concepts can be connected in various ways, reflecting the multidimensional connections in human semantic memory more accurately.
Mindmap example
Concept map example