Thinking Well and Learning Well: The Research Behind the ThinkWell-LearnWell ™Diagram
Within 48 hours of posting Why “Good” Students Do “Bad” in College, the article received thousands of views! Hundreds of requests for the ThinkWell-LearnWell ™Diagram poured in from all types of colleges and universities across the United States and around the world. Now that the diagram is being more widely distributed, I feel the need to shed some insight on the research on which it was built and offer some useful applications.
This is the first of two posts. It provides a brief background of the research that has gone into creating the diagram. The ensuing post will focus on some of its applications.
The purpose of the diagram is to help students distinguish poor thinking and learning from thinking and learning well. It aspires to enable them to make such distinctions in real-time, in-the-moment studying and learning situations.
The diagram brings together three crucial areas of research into a concise, one-page document. These areas include the following:
- Students’ approaches to learning
- Students’ metacognitive activity
- Students’ thinking skills, according to Bloom’s Taxonomy
Each of these areas has been effective at improving students’ learning and academic success.
Approaches to Learning
Surface vs. Deep
By the time students enter college, they already have developed learning strategies, methods that were inculcated formally or informally. Their approaches to learning involve “previously constructed ideas, knowledge and beliefs that help make sense of new information” (Tait, 2009, p. 1). They are considered to be a primary determinant of students’ learning outcomes (Tait, Triggwell &Prosser, 1991). Researchers have categorized students’ approaches to learning into two groups: surface approaches and deep approaches (Eklund-Myrskog, 1997, McCune & Entwistle, 2000, Triggwell & Prosser). Surface approaches have been defined as those rather useless learning processes that lead to the accumulation of unrelated details that have little meaning to the learner (McCune & Entwistle, Tait). Surface knowledge has been described as a mile wide and an inch deep. Surface approaches, by definition, lead to surface outcomes. Therefore, it is not surprising that students who employ a surface approach to learning likely will experience academic difficulty in courses that require them to reach deep learning outcomes such as application, analysis, and evaluation of information.
Deep approaches to learning are those processes that connect information in a meaningful and lasting manner (Laird, 2008, McCune & Entwistle, Tait). Students who adopt deep approaches view understanding as a chief learning goal (Triggwell & Prosser); as a result, they often comprehend the fundamental principles of the subject of study (Eklund-Myrskog). A deep learning approach actively engages students in their learning and leads them to search for relationships between the text and the surrounding world (Eklund-Myrskog); unsurprisingly, these students are more actively engaged and interested in their studies. Research has consistently demonstrated a strong correlation between deep approaches to learning and deep learning outcomes (Eklund-Myrskog, Triggwell, et al, 1999). Such approaches equip students to master rigorous academic coursework.
The Relationship Between Thinking and Learning
One of the key transitional challenges students face as they enter college is the degree to which they are required to think about the material they are learning. This increased time is paramount to converting their cognitive activity into sufficient learning outcomes. Researchers Paul and Eller (2010) describe the inseparable bond of thinking and learning: “If we think well while learning, we learn well. If we think poorly while learning, we learn poorly” (Paul, 2010). How students think about the material they are studying is perhaps the primary determinant of the types of learning outcomes that they will realize. Students who think poorly will learn poorly; students who think well will learn well. (Hence the name of my company: The LearnWell Projects and the ThinkWell-LearnWell Diagram.)
A recursive relationship exists between approaches to learning and thinking skills. Surface-based thinking is classified as poor thinking because it leads students only to surface outcomes, which are insufficient products for rigorous coursework. Surface learning primarily engages the memory (Triggwell & Prosser). Memorization is the lowest thinking skill, based on Bloom’s Taxonomy of higher-order thinking skills (Overbaugh & Schulz, 2010).
Conversely, deep-based thinking is considered thinking well because it leads to outcomes that are sufficient for coursework that demands deep learning. Deep learning leads to understanding and is a catalyst for application, analysis (McCune & Entwistle, Triggwell & Prosser), and evaluation, all of which occur at higher stages on Bloom’s Taxonomy. As students employ surface approaches to learning, they will use lower level thinking skills. As students apply deep approaches to learning they will exercise higher level thinking skills.
The relationship between what and how students think when studying and the quality of their learning has received much attention from researchers such as Brown (1987), Coutinho (2006 and 2008), Flavell (1979), Hacker (1998), Paul (2010), and McGuire (2011). Specifically, metacognition, or the silent thinking that occurs between, beyond, and around the lines of our conscious thought, has been well established by these researchers’ findings. Taylor (1999) defines metacognition as
an appreciation of what one already knows, together with a correct apprehension of the learning task and what knowledge and skills it requires, combined with the agility to make correct inferences about how to apply one’s strategic knowledge to a particular situation, and to do so efficiently and reliably.
Research has shown that students who are not metacognitively aware will struggle in college (Caverly D.C., 2009).
The ThinkWell-LearnWell Diagram is squarely based on these areas of research. It is a metacognitive tool that enables students to think critically and learn deeply to produce sufficient learning outcomes for demanding academic courses. It helps students efficiently navigate their way through the thinking process and to convert their cognitive activity into measurable learning outcomes that meet the demands for whatever level of rigor their courses require. The diagram has been successful at increasing students’ learning and academic performance by improving their general studying outcomes, textbook comprehension, math and writing. Applying the diagram to these areas will be the focus of part two of this two-part post.
The follow-up article: the application of the diagram will be forthcoming soon.
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Caverly D.C., F. R. (2009). Handbook of College Reading and Study Strategy Research, 2nd Edition. New York: Routledge.
Coutinho, S. a. (2008, May 6). A model of metacognition, achievement goal orientation,learning style and self-efficacy. Dekalb, Illinois, USA: Springer Science+Business Media B.V.
Eklund-Myrskog, G. (1997). The influence of the educational context on student nurses’ conceptions of learning and approaches to learning. British Journal of Educational Psychology , 371-381.
Flavell, J. (1979). Metacognition and cognitive monitoring: A new area of cognitive-developmental inquiry. American Psychologist , 34, 906,911.
Hacker, D. (1998). Metacognition in educational theory and practice. Mahwah: Erlbaum.
Paul, L. E. (2010, Winter). Critical Thinking: Competency Standards Essential for the Cultivation of Intellectual Skills, Part 1. Journal of Developmental Education , p. 2.
Tait, K. (2009). Understanding Tertiary Student Learning: Are They Independent Thinkers or Simply Consumers and Reactors. International Journal of Teaching and Learning in Higher Education , 97-107.
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