A Conversation (with Students) About a Deep Learning Experience
If students are to excel in rigorous courses, they must learn deeply. Furthermore, they must learn in ways that enable them to efficiently retrieve their learning products and transfer them to their respective learning tasks.
For the past decade, I have been conducting Transforming Good Students into Great Learners projects. These 4-part sessions routinely help students significantly deepen their learning outcomes, and typically results in an average 20+ point increase in test scores in participants most rigorous courses.
The video segment below features an interview with students who participated in a Fall 2012 project.
I hope you enjoy the conversation!
There are a few more slots available for the Spring 2013 Webinar! Click on the following link if you are interested in participating in the Spring 2013 Transforming Good Students into Great Learners webinar.
For related post, check out the “Archive” section on the right side bar of the page.
Data-Informed Learning: Using Students’ Cognition to Deepen Learning and Improve Test Performance
Students’ studying experiences are driven largely by intuition. Learners rely on gut feelings to determine which content they need to learn. Their sense of “I-got-it-ness,” which serves as the guiding force of their studying, is generated by instinctive cues based on precollege success measures.
But what happens when these students transition to college and their learning instincts no longer generate the same type of performance?
Well, most students find themselves entrapped by what I call the failure-frustration cycle. Students devote increasing amounts of time and effort to studying, but don’t achieve a significant return on their investment. As they increase their effort and attention in preparation for tests, their expectation of improved performance rises proportionately. However, when their test grades (their performance measures) don’t improve, their level of frustration increases. As students repeatedly experience the failure-frustration cycle in various courses, deflation replaces frustration. Eventually, students begin to question their academic abilities. Unfortunately, this scenario describes the experience of far too many college students.
The cause: bad data!
Students generate significant quantities of cognitive data while studying. Yet they, and often those who seek to help them, don’t recognize this data. As a result, learners are unable to make the proper changes that lead to deeper learning and improved performance.
There is an old saying in business: You can’t manage what you can’t measure. Businesses use data to create measurements that are then used to inform decision-making. This process can be applied to students. Studying is a continuous act of decision-making. While students may be aware that they are making a variety of decisions during their studying experiences, such as those related to content relevance, time apportionment, and learning sufficiency, they don’t analyze their decisions. More importantly, they don’t evaluate the metacognitive activity that lead to their decisions. If they did, they would recognize consistent data trends that can be used to sharpen their intuition and improve performance.
Data Mining Students’ Minds
My approach to helping students combines two seemingly divergent fields: business and counseling. Through my business mind, I am interested in incentives, metrics, and performance outcomes. As a trained therapist, I am intrigued by students’ cognitive processes. When working with students, I devote most of my attention to listening. I don’t mean I sit in silence; I employ active listening skills to ensure that I hear precisely what students are communicating (verbally and non-verbally) and to make certain that I accurately reflect what I’ve heard.
I have been specifically drawn to the following set of questions: What are students attempting to learn when studying? How do they confirm each distinct learning outcome? When does this confirmation occur? What triggers this confirmation? What information product have they produced at the very moment of confirmation? Are there identifiable cues within the information that make students more likely to attribute relevance to one type of information over another? If so, why are they deemed relevant?
I listen for answers to these questions during every conversation I have with students. I search for evidence for these questions in students’ studying notes. In fact, I have done this so frequently on my campus that I can predict how students will perform on their exams just by listening to them discuss the material for a few moments or by surveying their notes. In fact, students often ask me to observe them as they study for a particular exam, then forecast how they will perform. While I can’t predict exact scores, I can usually tell students the letter grades to expect.
Horizontal Mobility vs. Vertical Mobility
There are two cognitive data trends that I’ve observed among students: horizontal mobility and vertical mobility. Horizontal mobility occurs when students learn material at the same depth regardless of how long or attentively they study. The term mobility in this context refers to the direction of students’ interaction with the material they are studying. When students engage in horizontal mobility, they think along the same shallow level throughout their interactions with the content. The result is a one-dimensional learning experience that produces insufficient learning outcomes for rigorous coursework.
Horizontal mobility is highly deceptive because the accumulation of low-level knowledge generates a sense of fulfillment, but it does not produce the deep learning needed to excel in rigorous courses. The plot chart below depicts this phenomenon.
Horizontal Mobility
Along the “x” axis at the bottom of the illustration, the “Types of Evidences” are simply the various methods by which the students record their learning outcomes. Listed on the “y” axis along the left side of the graph are the various levels of thinking skills used (according to Bloom’s Taxonomy of Higher Order Thinking, Revised version). Each of the thinking levels represents a different depth of cognitive interaction from top to bottom, with the shallowest form of learning at the top and the deepest form of learning at the bottom. (See the ThinkWell-LearnWell ™Diagram to better comprehend this relationship.) The red data points represent the depth of participants’ learning outcomes prior to the Transforming Good Students into Great Learners workshop series, while the green points represent their outcomes at the midpoint of the experience.
This chart was created to illustrate the radically different learning experiences of students who participated in the Transforming Good Students into Great Learners program and those who did not.
The students reflected in the graph above did not participate in the workshop. As you can see, the depths of their learning outcomes remained relatively the same through the midpoint interval. Rather than reaching deeper learning, these students continued to employ lower-level thinking skills that did not lead to more meaningful interactions with the content they were studying. This cohort did not experience a significant increase in academic performance.
Conversely, the graph below includes students who did participate in the program. As you can see, these students experienced significant changes in their interaction with the material during the workshop series.
Vertical Mobility
In this graph, the deepening, or downward movement, of participants’ learning over the two-week period is evident. These students interacted with the material at much deeper levels. Their test scores increased by an average of 20 points in a variety of disciplines!
In addition to students being able to sense that they were learning at a much deeper level, and receiving confirmation in the form of much higher test grades, this plot chart enabled them to visually confirm the deepening of their learning. This was a transformative experience for these students. In fact, in a follow-up interview, many of the participants reported being able to significantly reduce their study time and maintain high grades in their courses. Results such as these are common as students sharpen their intuition and use better cognitive data to both guide and gauge their learning.
Trisha Travis, Learning Center Director at Yavapai College’s Verde Valley Campus, Clarksdale, AZ, replicated the Transforming Good Students into Great Learners program on her campus. The plot chart below shows the change that occurred during her sessions.
Yavapai College’s (Clarksdale, AZ) Plot Chart
Below is a brief reflection of Trisha’s experience:
Prior to the conclusion of study, some participants were earning higher scores on quizzes and tests, and were noticing a marked difference in how they were interacting with the content of their courses. By their own reporting, being able to formulate meaningful metacognitive learning goals at deeper levels of thinking enabled them to get a firmer grasp on the material, be able to make meaningful associations, and get a bigger picture view of the subject.
Although the approach to transforming students’ learning outcomes is a reasonably simple process, many students find modifying their end goals makes a big difference in how they learn. Utilizing the ThinkWell-LearnWell approach leads them to discover what they can do with newly learned concepts, rather than just remembering or understanding the new information. And this is what makes all the difference in being successful in rigorous college courses.
(Plot charts and responses from other participating institutions were not available at this time, as their programs are still ongoing. However, preliminary discussions suggest similar outcomes.)
Note: This data in the plot charts was collected during program assessments rather than a formal study.
If you are interested in participating in the Spring 2013 Transforming Good Students into Great Learners webinar training on your campus and/or possibly partnering in a formalized study in the Fall 2013-2014 academic year, please see the following link: Information Here.
Playing to the Middle: Transforming the Academic Culture from the Center Outward
In October 2011, The Ohio State University Fisher College of Business and GE Capital teamed up to hold the nation’s first Middle Market Summit, Leading from the Middle. I came across an online report about the summit and was fascinated by the title. I’d just presented Playing to the Middle: Building Academic Success from the Center Outward at the National College Learning Center Association’s annual conference. The idea of an unknown, valuable market rising to the forefront in the business sector intrigued me. As I read the summit’s report, I was absolutely beside myself: The introduction mirrored that of my presentation. Here is an excerpt from that introduction:
Virtually ignored by the media, one of the most important drivers of America’s economy flies largely under the radar. It accounts for a third of private sector GDP and jobs, and has been growing even over the past four difficult years, yet it gets little attention from policy-makers or the public. This overlooked, perhaps surprising, force in U.S. business? The Middle Market segment.
Small businesses (less than $10 million in revenue) bask in media attention as the leading indicator of the nation’s entrepreneurial drive, with the Small Business Administration playing a key role in its development. Large multinational corporations (greater than $1 billion) operate on the other end of the spectrum and are the headliners of American business. They are unrivaled in terms of leveraging their size to influence favorable policy development and economic development.
Between the small and the large lies the Middle Market, with an influence on the national economy just as large — and just as significant — as the other two segments. Indeed, its impact is staggering. If the Middle Market were a country, its GDP would rank it as the fourth largest economy in the world, just behind Japan. Clearly then, there is a need to better understand this important market sector and provide it with the level of support, attention, and advocacy it merits.
Click here for the Middle Market website.
These business leaders and I were unearthing similar hidden gems in different industries. A week after I presented in Indianapolis on a “middle market” in higher education, the Middle Market Summit revealed groundbreaking research one state over in Ohio. These leaders have realized that the assumptions that formulate the entire paradigm by which the nation views the business economy have precluded us from seeing this critical market.
Analyses of the business climate by the media, the business community, and policy-makers have been based on grouping businesses into categories with easily identifiable characteristics; therefore, we have the agriculture sector, financial services, manufacturing, retail, etc. This practice, and more importantly the set of assumptions on which the practice has been based, prevented analyzers from seeing the phenomenon of the Middle Market. Now that this market has been identified, proper attention and resources can be allocated to maximize its potential. The summit concluded with unbridled optimism as the organizers expressed confidence that investing in the Middle Market will play a key role in America’s future prosperity.
I recognized many years ago that higher education has a similar under-tapped “middle market.” While assisting students who were on academic probation, I realized that two prevailing modes of thinking were used to explain why students performed poorly in college. The first was that they did not belong in college (because they were not “college material”). The second was that perhaps the students belonged, but their poor performance was a result of goofing off. These two faulty assumptions produced rather straightforward solutions: Stop admitting students who do not belong and make the others work harder. There were no other explanations for why students ended up on academic probation.
After working with this cohort, I soon realized that there were indeed a few students who perhaps were not college material. There was a slightly larger population who could be solid students if they were more studious. But these students were in the minority. It became apparent rather quickly that there was a largely unidentified group of students who were capable, serious-minded, and very hard-working. In fact, they were students whose backgrounds suggested they would excel in college. They had secured successful pre-college academic backgrounds in solid courses. Many of them scored well on AP exams. Some were even high school valedictorians. Yet, they were failing in college.
My experiences with these students prompted me to write the article “Why Good Students Do ‘Bad’ in College” and forever changed the way I categorize students. These students are higher education’s “middle market.” They offer the same opportunity and promise to colleges and universities that middle market businesses offer the business sector. If we begin to understand this cohort of learners and mobilize resources to address their needs, the enrollment problems that plague most campuses may be a thing of the past.
Who Is Higher Education’s Middle Market?
Higher education, like the business community, categorizes students according to easily observable characteristics. We develop learning communities to segment students by academic interest. We design residence halls to organize students around living interests. We describe students by age: traditional or non-traditional; by whether they drive to campus or not: residential or commuter. This does not include the endless list of codings such as those for student-athletes, racial and ethnic minorities, LBGTQ, veterans, first-generation, and so on. The never-ending micro-categorization stems from a belief that students have different needs and if we meet those needs, the students will be more likely to succeed. So we segment students and organize resources around their particular characteristics. This type of subdividing has its merits, but it also has prevented us from viewing students through the proper academic lens.
Three Types of Students
When you consider that higher education’s core business is academically educating students, I believe there are three types of college students: poor students, good students, and great learners.
Great learners constitute the small percentage of students who excel from the minute they begin college and experience no academic problems throughout their collegiate careers. They make up only a tiny fraction of students. These students are awarded most of the scholarships and fellowships. Great learners provide significant individual returns on the investments they receive. The small size of this cohort, though, coupled with the isolated manner in which they are “herded” along throughout their collegiate careers, limits their impact on the overall institutional culture.
Poor students are at the other end of the spectrum. They are the students who are not studious. They often have obvious deficiencies in their preparation. They frequently are unmotivated to learn and are not serious about college. They get an enormous amount of attention, but, like the group of great learners, they constitute only a small percentage of students. Poor students require significant investments of time, personnel, and money, but they often are not in a position to capitalize on the investments. Consequently, they provide a very low return on investment (ROI).
Good students make up higher education’s “middle market.” They consist of capable, hard-working students whose grades lag behind their ability and efforts. Numerically, this group accounts for more than 80% of students. The good students are equivalent to businesses in the Middle Market. They have been a sustaining force even without the army of resources that poor students receive or the financial incentives that great learners enjoy. Just as the summit report forecasted about the Middle Market, I am convinced that investing in the middle – the good students — must be a key strategy in higher education planning going forward. In addition to my personal conviction, the need for educational institutions to improve the academic performance of students in the middle was highlighted at the 2011 National Governors Association Meeting. Plenary Speaker, and New York Times Columnist and author of the international bestselling The World is Flat, Thomas Friedman exhorted the nation’s governors to ensure that their educational institution’s “bring our average so much higher.” (You can view his exhortation at the follow C-SPAN hyperlink: CLICK HERE. View the time segment from 32:18-33:30 for the content most applicable to this article.)
Colleges and universities must appreciate the impact that addressing the needs of good students can have on their institutions. The business community is realizing that the Middle Market has been a silent force within the larger US economy and that it is critical to America’s competitiveness and future. Likewise, good students hold the key to healthy enrollment for higher ed institutions. To experience the rich benefits that flow from this student market, we must stop playing to the extremes and begin playing to the middle.
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What “Good” Students Need to Succeed: Five Key Insights from the Field
In the article Why “Good” Students Do Bad in College, I shared insights about why capable, hardworking students struggle in college. (Click here to view Why “Good” Students Do Bad in College.) In this post, I identify five things good students need in order to succeed.
I must be upfront: My view of success reaches far beyond merely passing exams. When good students are successful learners, they are able to do the following:
- Accurately interpret the general course learning outcomes and specific content learning outcomes that are required for their classes
- Translate the course and content outcomes into metacognitive learning goals that form the foundation for their studying
- Manage their interaction with the various forms of information, while they are in the act of studying, to produce measurable learning outcomes before their tests
This view of success involves students’ awareness of the process of learning and their ability to deliberately produce sufficient products as a result of their process. When students can accomplish this, they are more likely to find studying and learning rewarding and consequently make many more “A’s” on their exams.
I can already hear the bewilderment: “Yeah, but how many students can actually do this?” Based on more than a decade of helping college students excel in their courses, I would argue that 80%-90% of incoming college freshmen enroll with the abilities embedded within them. In fact, I frequently say in faculty workshops that students are very adept at reaching learning outcomes. Unfortunately, they are not so skilled at meeting those that are required for their courses. This means that the process of reaching learning outcomes is ingrained; however, it is unrecognized and uncultivated. If colleges and universities can help students access this process and calibrate it to meet the learning demands of the collegiate environment, students can enjoy quicker and lasting success.
Good students have the will and means to learn, but need some assistance in finding the way. Listed below are five need-to-know factors that will produce lasting success:
- They must know the 80/20; 20/80 Rule. This is perhaps the most important lesson that students have got to learn in college. They must not only learn it; they must also understand its implications in their approach to learning. The Rule symbolizes the difference in responsibility between students’ pre-college and college learning environments. Prior to college, students were responsible only for a small percentage of learning (20%), while their teachers prepared them for success (80%). In college, professors will only account only for a small percentage of students’ preparation for exams (20%), while students will be responsible for about 80% of their preparation. (You can read more about the 80/20; 20/80 Rule in Why “Good” Students Do Bad in College.)
- They need transparent learning outcomes. Students seek cues that inform them about the types of learning that are required. A simple, well-crafted syllabus provides students with the signals needed to interpret the various learning outcomes necessary for success.
- They need to know that there are degrees of learning. Good students are aware that they have learned something when they reach the conclusion of their studying. However, they don’t know how to determine the degree(s) of learning they have attained. One of the most powerful exercises I do with students is to help them reach different learning outcomes with the same content. When students realize that there are different learning outcome possibilities and that they can actually control the types of outcomes they produce, learning becomes a more rewarding experience.
- They need to become aware of their learning goals. All students have learning goals. Research shows that setting metacognitive learning goals is perhaps the most important step in the studying sequence (1). There is also evidence that students often skip this step. Students must learn how to recognize the learning goals that formulate the basis of inquiry that guide and gauge their learning.
- They need to come to the realization that time apportionment is a function of the perceived learning outcome(s). I have developed a rather unconventional way of talking with students about time management. Rather than telling students how long they need to study, I help them understand the difference among the various learning outcomes. Once students understand the essence of different learning outcomes, they automatically change how they apportion time. During my sessions, students often come to the realization that studying earlier or continuously will perhaps benefit them more than simply studying more. These personal “ah-ah” moments are key to producing transformative, lasting change.
When these five needs are met, good students will excel in college. The ThinkWell-LearnWell ™ Diagram makes these abstract insights concrete. When students learn how to use the TWLW diagram to put these ideas into everyday practice, they become much stronger learners. The result is a better teaching experience for professors and a superior learning experience for students. (Click here to request a free PDF version of the TWLW Diagram.)
1 Hacker, D. (1998). Metacognition in educational theory and practice. Mahwah: Erlbaum.
3-Part Webinar Series: Transforming “Good” Students into Great Learners
Webinar Hosted by The LearnWell Projects
Event Dates:
Tuesday, July 10, 17 & 24
All times are from 2:00 pm to 3:30 pm, EST
Register Now at: This event has already occurred.
Only 31% of students at four-year public colleges and universities graduate in six years, and only 53% at private institutions. Recent data shows that while institutions are structured and resourced to address the needs of students at the bottom of the academic continuum, they are increasingly losing their good students in the middle.
Like it or not, we are in the value-added era of higher education. Federal and state funds are being increasingly tied to graduation rates. Accrediting bodies are emphasizing quality enhancement. Parents, students and the business sector are openly questioning the value of higher education.
Institutions that thrive in this new reality, must move beyond the current preoccupation with keeping the minority of students at the bottom enrolled to moving the majority who are stuck in the middle toward the top (National Governors Association Meeting, Summer 2011). It is by moving the middle that institutions improve overall retention and graduation rates, and enhance the learning culture.
Did you know that the methods used to assist students at the bottom are very different from those needed to boost the performance of those in the middle? In this webinar, participants will explore the profile of “good” students, how to access these students and, most importantly, how to make them great learners.
Click here to view clips from a previously conducted study: http://wp.me/p26hnd-64
Webinar Objectives
Participants will be able to:
- Help students adjust their information valuation system. Students study to produce information products. Professors then ascribe value to these products in the form of grades. However, the two parties have very different information valuation systems. At the end of this webinar series, participants will know how to translate this valuation system to students in ways that produce measurable increases in learning and higher test performance.
- Help students set learning goals that inform, guide and gauge learning. Participants will learn out to use the ThinkWell-LearnWell TM Diagram — a metacognitive tool that enables students to think critically, learn deeply and produce learning outcomes that stand up to the demands of rigorous academic courses. The diagram is currently used by more than 500 colleges and universities around the world. Click here for a free PDF version of the diagram or more information on the diagram.
- Help students ascertain the salient information from textbooks. Thankfully, most college students can read. Many however are unable to sufficiently comprehend college textbooks. One key reason for this is that textbooks are one of only resources that require readers to continuously toggle between thinking skills. The Textbook Mapping reading comprehension technique will enable participants to help students efficiently gather the most important concepts from their textbooks and apply them to the overall course content.
Webinar Speaker
Leonard Geddes, creator of The LearnWell Projects and Associate Dean of Co-Curricular Programs at Lenoir-Rhyne University, NC.
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This event has already occurred.
Once registered you will receive an email confirming your registration with information you need to join the Webinar.
Can’t make one of more of the dates? Participants who are unable to attend the live session will receive access to the actual recorded webinars.
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Please direct all questions to: learning@thelearnwellprojects.com.
System Requirements
PC-based attendees
Required: Windows® 7, Vista, XP or 2003 Server Macintosh®-based attendees
Required: Mac OS® X 10.5 or newer
Institutions participating in the From Good to Great 4-Week Study will also receive a From Good to Great study kit in the mail. This kit will equip study conductors with the tools they need to execute the study sessions. This packet will include a sample informed consent document and IRB documents as well.
From Good to Great Learning: 4-Week Academic Study
Are you tired of seeing good, hard-working students under-perform in college? Do you believe there are a different set of factors underlying students’ academic problems than the usual pejoratives: “they’re lazy”, “high school didn’t teach them anything”, or “they don’t care about their learning.”
Are you seeking interventions that can boost students’ learning and test performance across all academic contexts? Is this even possible?
Well, I am not sure if the last question can be fully answered, but the From Good to Great Learning 4-Week Study gives it a darn good shot!
Let’s start with the end in mind. We have concluded this year’s 4-Week Study. Below are the amazing results:
Results:
- 20+ point increase in aggregate test scores! The increase in test performance occurred within the first two weeks of the study, as most professors administered exams before the Easter break. Subsequent exam and/or quiz grades suggest that the gains are being sustained and/or increased.
- All test grades have been confirmed with professors, who had no knowledge that the students were participating a study.
- Peers in the same courses did not experience similar jumps in their academic performance.
- Many of the students recorded their first “A” ever in their most rigorous courses.
For the past ten years, I’ve been researching the factors that distinguish good students from great learners. I’ve conducted several studies over the years, but this is the first time I’ve actually video taped it.
The Video:
- The abridged version is featured on this page (approx. 30 minutes)
- The unabridged videos are located at the bottom of this page.
- Some participants were not available for pictures – you will understand after you watch it.
- Make sure you watch the entire video, the finale is AWESOME!
The following questions were the impetus for this study:
- Can students significantly boost their learning and test scores in a few weeks?
- Can students’ understanding of what it means to study and their ability to control their learning be measurably improved within a couple of weeks?
- Can one intervention impact students learning across a range of academic contexts, without addressing the course content?
Learning Captured
This graph shows the progression in learning from before the study to the mid-point of the study.
The graph above shows the significant improvement in higher-order thinking and the deepening of learning outcomes that were captured. (The comparison is between students’ before-study “evidences of learning” and the mid-point evidences because the final evidences had not been collected at the time of this post.)
The graph shows the following noteworthy improvements in learning:
- Visually, it is quite obvious that the bottom half of the diagram has many more green dots (mid-point outcomes), than red dots (before outcomes); this shows that the participants’ were engaging in much higher levels of thinking and generating much deeper learning outcomes at the mid-point of the Study than before the Study.
- The strategies students’ employed were less important; their level of interaction was most important. Participants experienced deeper learning outcomes with every type of learning tactic they used.
- There was an increase in the quantity of outcomes, but also a broader range of outcomes, which included many deeper learning outcomes.
About the Study:
- The study consisted of four 50-minute sessions.
- Participants took a pre and post Learning Assistance and Study Skills Inventory (LASSI) and the Metacognitive Awareness Inventory (MAI)
- No course content was addressed during the study. Participants simply learned how to use the ThinkWell-LearnWell Diagram and Textbook Mapping, a textbook reading comprehension technique that is based upon the diagram. They determined the courses in which to apply the new way of learning.
- Participants applied the Diagram to more than 18 different courses from a variety of disciplines.
- The participants were self-identified “good” students. They responded to an open invitation to join a 4-week study session designed to transform “good” students into great learners.
- The group consisted of freshmen to seniors, traditional-age students and adult learners.
- They represented a broad array of academic disciplines.
Adjusting to Rigor: Changing Students’ Default Settings
Every technology product we purchase comes with default settings. These settings are basic operational parameters that are preset by the manufacturer. The same presets exist in every device. So even though millions of us hold individual cell phones, we share the same default operating system. Our defaults are automatic and operate without our knowledge.
For example, based on presets, our cell phones roam to find the nearest cell phone tower. The manufacturer has embedded cues within the devices that enable our phones to work continuously. As we go about our lives, our devices use these pre-installed signals to maximize performance.
Most of us have never changed our devices from their default settings, and many of us never will. When is the last time you changed your computer, television, or cell phone’s default settings? We probably wouldn’t know how to access these settings if we were interested in changing them. However, if we were traveling abroad, we might need to change our cell phone settings to an operating mode that is more conducive to our new environment.
Students enter college with default settings as well. They have preset metacognitive learning goals. Much like our technology devices, these defaults operate rather automatically. Metacognition research affirms that students are unaware of these built-in settings, nor do they know how to adjust them or under which conditions they may need adjusting.
Students’ default metacognitive learning goals are rooted in their pre-college experience. These presets determine the parameters of their learning. They function as embedded cues on which students rely to guide, gauge, and confirm their learning. However, these goals don’t translate well to the college experience. Unfortunately, students’ default settings don’t come with roaming capabilities that automatically adjust to their new environment. They must manually customize their settings to fit each course.
If students do not adjust their metacognitive learning goals, their studying activities will be futile. Their outcomes will be as outdated and unusable as a rotary phone in today’s mobile world.
All students set learning goals each time they study. Setting appropriate metacognitive learning goals is the most critical step in students’ study sequence, yet research shows that it is the most overlooked step as well. Students’ entire learning structure is predicated upon these goals. If they set inappropriate goals, they will not reach sufficient learning outcomes.
The left column of the ThinkWell-LearnWell ™ Diagram (TWLW Diagram) offers various metacognitive learning goals for each respective level of thinking. These goals define the parameters of what students seek to accomplish during their study activity. I often compare them to the foundation of a house under construction. The foundation is the first step in the building process. Although this stage occurs several months before the house is complete – and countless other stages occur in-between – the foundation determines the perimeter of the eventual structure. If the foundation is laid for a 1200 square feet, the final product will be 1200 square feet. This reality remains regardless of how much time the builders invest in the project. Likewise, students’ initial learning goal will determine the type of learning they will construct.
Example of a Default Metacognitive Learning Goal
Metacognitive learning goals are typically unspoken statements or questions that students seek to satisfy when studying. They usually are very simple and can be formulated as questions or statements. Here’s an example of a learning goal expressed as a statement: “At the end of reading this section on fungi, I will know all the types of fungi.” A learning goal expressed as a question might be, “How do the various fungi differ from one another?”
Students’ default settings are calibrated to memorize the information they are studying. An example of a typical default learning goal would go as follows:
Jeremy, a physics student, is studying for an upcoming exam in which he expects at least one of the test items to be on the laws of thermodynamics. Jeremy more than likely will have never consciously thought, verbally express(ed), or even been aware of his goal. However, a brief analysis of his learning “evidence” – flashcards, highlighted segment(s) of his book, study notes, or a verbal articulation of knowledge – will reveal that Jeremy’s goal is to remember the different laws of thermodynamics. Therefore, if expressed in written form, his learning goal would sound something like this: “I will be able to define each of the laws of thermodynamics.”
Jeremy may be more intelligent and more diligent than all of his peers, but he will never excel on that part of his physics exam if the questions about thermodynamics require him to express an answer that goes beyond merely defining the laws to explaining why the laws are important or analyzing the laws.
If Jeremy was designing learning goals for these types of questions, his flashcards, notes or other sources of learning evidence would show that he had captured the underlying principles of the laws or that he can compare and contrast the laws. Furthermore, his adjusted metacognitive learning goals would have been expressed as follows: “At the end of reading this section of text (the same section he read before), I need to know why the laws are important to physics and how the laws relate to each other.” By simply setting metacognitive learning goals that resemble these, he would have built a structure that could support the types of outcomes he needs to reach for his exams.
Click here to obtain your free, color version of the TWLW Diagram.
This article is a continuation of: What Is Academic Rigor to Students? A View From the Other Side
What is Academic Rigor to Students? A View From the Other Side
Did you know that students bring more than 16,000 hours of learning with them to college? (And this does not include out-of-class studying.) According to Malcolm Gladwell’s 10,000 Hour Rule, which asserts that it takes about 10,000 hours of practice before one reaches expert level, students should be expert learners by the time they reach college. However, we know this is not the case!
In Gladwell’s bestselling Outliers, he lists a wide variety of fields and industries in which the 10,000 Hour Rule is affirmed. However, this rule does not seem to apply to students.
So why are students not experiencing the benefits of the 10,000 Hour Rule? Why aren’t students able to learn effectively, given the amount of time they invest in it the process?
In this era in which K-12, colleges, and universities are pledging to ramp up their levels of rigor, I believe it’s important to consider how students experience rigor. If we understand rigor from their perspective, then we can more effectively help them thrive in this increasingly demanding period.
There are a variety of elaborate definitions of rigor in academia. However to students, rigor is very simple: “it” is the gap between the learning outcomes they are accustomed to reaching and those that are required for their college and university courses. The greater the disparity, the more rigorous the course.
I’ve had the privilege of obtaining views from a wide array of students from a variety of institutions over the years. Through workshops, in-depth personal interviews, document analysis, learning assistance sessions, and perhaps most importantly, informal chats, I have learned one key thing: Students are quite adept at reaching learning outcomes; they simply don’t know how to attain the kinds of outcomes their professors’ expect.
Students’ Evolving Views on Rigor
Prior to college, students identify course rigor by the quantity of required tasks. The more rigorous courses require the most papers, have the most tests and quizzes than, and demand the most homework. When high school students discuss class difficulty, they make comments such as, “Mr. Jones assigns a lot of homework”, or “We have to write a lot of papers.” Or as one graduate a prestigious private school told me, “In high school we didn’t learn how to learn; we learned how to never be outworked by anyone else.” Such students believe that handling the workload is the chief goal of learning, and their success is affirmation that they are capable students.
However, these same students are often pacified in their early college years. As they are assigned less homework and have fewer quizzes and exams, they are lulled into believing that their courses aren’t as rigorous as they originally had imagined. This “truth” was captured during the compilation of the National Survey of Student Engagement (NSSE) data, which shows that students’ perceptions of college difficulty are greater prior to entering college than they are after a year of college. These beliefs persist despite the jarring reality that they perform less than expected after the first year of college than they anticipated prior to starting college. What’s going on here?
A change in rigor metrics is under way. Students are encountering a shift in the way rigor is measured. They are still operating according to their pre-college rigor metric system, which was solely based on the quantity of tasks. Therefore they conclude, “I am not doing as many things as I did prior to college and certainly not as much as I imagined. College is not as hard as I assumed.” Consequently, they don’t work as hard. They don’t realize that while the quantity of tasks drops considerably, the quality of learning that they’re expected to achieve while doing those tasks significantly increases. This explains why promising students do badly early in college. Their signals are all crossed. Their former metrics no longer apply, and they aren’t even aware that rigor is measured differently in their new environment.
Upperclassmen often attempt to “help” new students understand how course difficulty is measured in college. Recognizing that course rigor is largely a function of the professor teaching the course rather than the course itself, the upperclassmen tell underclassmen students which professors they should take for their courses. Unfortunately, many of these seasoned students will say things such as Dr. Jones’s course is hard; don’t take her”, or “Take Dr. Foster; he is so easy.” Delightfully, the more serious-minded upperclassmen will encourage students: “Take Dr. Fletcher. Her course is hard, but you will learn a lot.” This is invaluable information to new students because, whether these upperclassmen know it or not, they are conveying a new rigor metrics system.
When viewed according to the pre-college metrics paradigm, most college courses appear to have comparable levels of rigor because they have similar quantities of tasks (e.g. numbers of tests, papers, etc). However, the wise upperclassmen are unknowingly introducing students to the true rigor measurement in college: the quality of required learning outcomes for the course.
So these students underclassmen learn have learned two useful lessons:
1) Their former rigor metric system is no longer applicable (realized through trial and error)
2) There is a qualitative difference between courses (articulated by upperclassmen)
Now that these students are using the proper metrics, they need a model that enables them to navigate this new system. The ThinkWell-LearnWell Diagram™ (TWLW Diagram) was created for this purpose. It is a metacognitive tool that helps students adjust their thinking skills and learning outcomes to match those required to excel in their courses. Students report that using the diagram deepens their learning and boosts their test scores. (See comments section in Why Good Students Do Bad in College.) In other words, they are able to adjust their learning according to the rigor of their courses.
So how can institutions expedite students’ adjustment to more rigorous environments?
1) Institutions must make the process explicit. We must make students aware, in plain language, of the qualitative change that is required to excel in college, along with the implications of the change. We cannot continue our current practice of hoping students learn how to navigate this change through osmosis.
2) We must describe the implications of the change. Simply including Blooms Taxonomy of Higher Order Thinking Skills in a syllabus or making students aware of the different thinking levels is insufficient. They need to know how to manage their learning from the creation of appropriate goals to assessing learning outcomes. The ThinkWell-LearnWell ™ Diagram is useful in achieving this goal. It helps students set goals and convert their study activity into usable learning outcomes. (Click here to obtain a free pdf. version of the TWLW Diagram.)
I’ve shared some observations I’ve gathered from students. Please post your thoughts on whether you are seeing this experience at your institution. Feel free to share this post with your students and encourage them to comment as well.
Click here for Part II: Adjusting to Rigor: Changing Students’ Default Settings
Pointers vs. Painters: What Are We Really Capturing in Writing Scores?
Do you remember the fun you had playing with LEGOs as a child? The multicolored plastic bricks are timeless toys enjoyed generation after generation. But, have you ever closely watched a child building with LEGOs? The process unfolds in one of two ways:
- The child thoughtfully selects and places each piece as if following a model that exists within the child’s mind.
- The child dumps all the pieces onto the floor and builds a structure in the moment.
I tested this theory by observing neighborhood kids as they collectively decided what to build, such as a fort or a house, and then worked individually to construct the object. At other times, I suggested an object for them to build. Whether they generated the idea on their own or create an object based on my input, there were those children who preferred dumping all of the pieces onto the floor and those who plucked individual pieces from the bag of LEGOs as they were needed.
Dr. David Ludwig is a marriage and family therapist and founding director of The Power of WE: Center for Family and Community Relations at Lenoir-Rhyne University in Hickory, North Carolina (www.thinkwe.com). Dr. Ludwig developed a relational typology whereby he classifies communicators as pointers or painters. When pointers communicate, the first thing out of their mouth is typically the most important, with follow-up statements serving as support for the main idea. He advises families to minimize miscommunication by listening to the first thing the pointer says, focus on that one idea, and ask for clarification or further details. Pointers are like the kids who place each LEGO piece as it is needed. They methodically communicate their point and support it with each statement.
Painters, on the other hand, paint a picture with their speech. Their first words are just the first brush strokes onto the canvas of the conversation, not the main point. They typically will paint a colorful picture with their words and then put forward their main point at the end of their speech. Dr. Ludwig counsels families to invite the painter to paint the whole picture. He suggests that families listen with interest as their painters express themselves. Painters resemble the children who dump out all the pieces as if the act of dumping is a cathartic experience in itself. They eventually may achieve the same goal as the pointers, but do so differently. Dr. Ludwig’s advice has helped thousands of couples and families avoid conflicts due to simple differences in communication styles.
I offer a presentation, Professors Are From Mars, Students Are from Venus: Learning Occurs on Earth, in which I assert that the faculty/student(s) relationship is the most important and powerful force in the learning environment. However, the relationship is hindered by various forms of dysfunction that stem from each party’s very different world. I wondered whether the pointer and painter typology was applicable to student writing. After all, writing is a form of communication; it involves a process of laying out thoughts similar to children placing LEGOs. More importantly, I considered the miscommunication that could occur between students and their professors. I questioned if students’ perceived abilities, at least in part were determined by whether they operated from a pointer or painter disposition. The manner by which students structure their writing has significant consequences, both immediate in terms of grades and lasting in terms of students’ confidence in their writing abilities.
I don’t believe it is a large leap to say that most professors prefer the pointer’s way of communication: making a point and supporting it with statements. This aligns well with the traditional writing format. But what about the painters? They may be communicating the same ideas, just in different ways. They may be painting the picture with their writing and summarizing, or putting the main point, at the end.
Following are two excerpts that address the same topic. One excerpt is the product of a painter’s style of communicating; the other, a pointer’s. Should they be valued differently?
|
Painter |
Pointer |
| 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, which is categorized as a lower-level thinking skill, based on Bloom’s Taxonomy of higher-order thinking skills.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, and evaluation, all of which occur at higher stages on Bloom’s Taxonomy. Therefore, a recursive relationship exists between approaches to learning and thinking skills. As students employ surface approaches to learning, they will use lower level thinking skills. As they apply deep approaches to learning they will exercise high-level thinking skills.
[Notice that this excerpt first explains, or paints a picture, and then expresses the main point (in bold) near the end.] Click here to view the article from which this excerpt was taken. |
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, which is categorized as a lower-level thinking skill, based on Bloom’s Taxonomy of higher-order thinking skills.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 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.
[In this excerpt, notice that the main point (in bold) is at the beginning.] Click here to view the article from which this excerpt was taken. |
Current tally:
Faculty/Staff — Painters – 41%; Pointer – 8%
Students — Painters – 21%; Pointers – 30%
Since professors typically seek the main point at the beginning of a paper, they may react prematurely to a painter’s work, making judgments before they have finished reading the composition. In essence, they draw conclusions about the student’s writing before considering the entire picture. Is this okay? If so, should we be teaching children that there is only one way to build with LEGOs?
(Please add your response in the comments’ section. If it is not listed at the bottom of this page, then click on “comments” tab next to the date, near the top of the page.)
Applications of the ThinkWell-LearnWell™ Diagram
Try this experiment:
Ask one of your colleagues a basic question such as, What are your two favorite foods? Jot down the answer and then ask, Why do you like those particular foods? Record that answer and conclude with the following question: What about the foods do you like and don’t like? Record this answer as well.
Now consider your colleague’s responses. You likely will notice the following:
- The answers got progressively longer with each question.
- Each question caused your colleague to think a little more to generate a sufficient response.
- Each question evoked a response from a different thinking level: the first query triggered a basic recall level of thinking, the second bumped the thinking level up one notch to understanding, and the third ramped the thinking up to analysis, the fourth level of thinking, according to Bloom’s Taxonomy. (See the ThinkWell-LearnWell Diagram for a visual depiction.)
Also, note the effect your questions had on the verbal exchange between you and your co-worker:
- Your questions dictated the type of information you obtained from your co-worker.
- Your questions forced your colleague to engage in higher levels of thinking.
- Each question had an embedded metacognitive goal (meta-goal).
This simple exercise demonstrates the power of interaction. Interaction is a two-way process that affects both parties. In the exercise above, your questions dictated the terms of interaction. When your colleague answered, the information that you obtained satisfied a meta-goal. And, her response was a learning outcome, evidenced by the fact that you acquired new information about your colleague as a result of the verbal exchange.
Another way to view the interaction is to consider it a transaction between you and your colleague: You traded questions for answers. This type of personal interaction illustrates the abstract interactions that occur between students and the material they study. Louise Rosenblatt, promoter of Transactional Theory, maintains that the act of reading is a dynamic exchange between the reader and the text. Much of the reading in which college students engage is efferent reading, meaning the students’ primary concern is what they must take away from the text. As in the exchange about favorite foods, the questions posed by students as they study dictate the level of interaction they have with the text, and that interaction determines their learning outcomes.
After comparing the information products of good students and great learners, I am convinced that great learners interact more deliberately and more deeply than their less successful peers. This difference in interaction is the root cause of the disparity in academic performance between good and great learners. When used properly, the ThinkWell-LearnWell Diagram enables good students to build a staircase to higher levels of thinking, interacting, and learning. This structure allows them to reach outcomes that meet the demands of all courses, regardless of the requirements.
The previous article, “Thinking Well and Learning Well: The Research Behind the ThinkWell-LearnWell Diagram,” presented some of the research that went into the development of the ThinkWell-LearnWell Diagram. This article focuses on some of the ways that the diagram can be useful to students. The diagram promotes general critical thinking competencies in that it is applicable to all thinking within all domains, subjects and professions. It enables students to set the terms of interaction as they tackle their coursework.
Below are four areas in which students benefit by using the ThinkWell-LearnWell Diagram:
- Textbook comprehension
- General studying and learning
- Writing
- Math
Textbook Comprehension
One of the most difficult things for students to do is ascertain salient information from textbooks. Even students who successfully determine the key information from other sources are unable to do the same with course books. One reason is that a textbook requires readers to travel among the various thinking levels in order to successfully process and use the information. I have found that students tend to remain on one thinking level without considering the skills needed to effectively learn the text.
Yes, textbooks contain dry, complex material. The real challenge for students, however, is to continually take into account all thinking levels and to appropriately employ those which lead to optimal comprehension. Higher levels of thinking facilitate mastery of material. Remaining stuck in the rut of low thinking levels means far less comprehension. Even a student who invests great chunks of time into studying won’t reap academic rewards if she allows her mind to remain on the lowest rungs of the thinking ladder.
Click on image to enlarge.
Students likely will comprehend the low-thinking material (in the red area), but will not grasp the information that requires higher thinking levels (in the white section). As you can see, much of the information requires high-level thinking. This illustrates why students comprehend so little of their textbook information.
While students do have trouble adjusting their thinking while reading, it is important to note that college students possess the ability to think on all thinking levels. It is equally important to be aware that they actually do think on all thinking levels in practically every area outside of their academic lives. For example, I have used the ThinkWell-LearnWell Diagram with coaches and their teams to chart the various thinking levels that they use in their sport. Each time, coaches and players are surprised to realize that they are actively employing every thinking level. I have done the same with video games, musicians, cooking, and a variety of everyday activities.
Using the ThinkWell-LearnWell Diagram improves students’ comprehension because they can use it as they apply their learning goals to the text, evoking the appropriate thinking skills for respective sections of content. In Textbook Mapping, a textbook reading comprehension technique that I created, I demonstrate the benefits of this approach. This techniques calls students’ attention to the learning goals embedded within their textbook, shows them how to use these goals to evoke appropriate thinking skills, and finally to assess their levels of comprehension. After using the technique, students consistently report being able to read faster and get more out of what they read.
General Studying and Learning
It seems that study skills and learning strategies are used most commonly to improve students’ study behavior. This observation was affirmed during the 2011 National College Learning Center Association conference when I asked learning center directors and coordinators to provide working definitions and examples of study skills and learning strategies. Their responses included equipping students with good habits, such as time management and regular class attendance. Good students typically display these behaviors. And, poor students often are able to elevate themselves to good-student status by incorporating such habits, but they are improper remedies for transforming good students into great learners.
Students tend to default to lower-level thinking skills throughout their studies, regardless of the strategies they employ. Of course, students need strategies and tactics when studying, as they constitute the activity of studying that leads to learning. However, strategies rarely change the way students interact with material and, therefore, do not advance their thinking. For example, students will think the same way about the material they’re studying whether using a tactic as simple as flashcards or something as complex as Cornell Notes.
The ThinkWell-LearnWell Diagram enables students to both guide and gauge their thinking in real-time, in-the-moment learning situations. Students who can set proper learning goals and successfully navigate their thinking will reach sufficient learning outcomes for whatever courses they are taking.
Writing
Here is a common scenario:
A professor instructs a class to read a segment of text and then respond in writing to the passage. The professor explains that the students are to support their thoughts, analyze and evaluate the text, and summarize the information in their own words. The students return to class a few days later and hand in their written products, which are, essentially, narratives.
If left to their own devices, students will produce narratives, basic written reports of what they’ve read. Narratives require only low-level thinking skills as students simply “chew up” the text a bit and then regurgitate it on paper. The ThinkWell-LearnWell Diagram provides a model whereby students can deliberately contemplate their writing differently, enabling them to set higher-level writing goals, think on higher levels, and produce writing samples that meet their professors’ expectations. Using the diagram, students are more likely to interact with the assigned content and think in ways that will help them produce exemplary expository, persuasive, analytic, and imaginative writing.
Mathematics
Most students enroll in college with the belief that excelling in math requires a great memory for formulas. Those who perform poorly in math classes often blame their lack of success on an inadequate memory, and those who do well often wrongly attribute their success to their memorization skills. In truth, those who excel in math don’t rely on their memory; instead, they seek to understand the principles that govern the formulas. These students get the “hows” and “whys” by analyzing and evaluating the logic within the computations and problems. Essentially, they apply higher level thinking skills to numbers and numerical situations the same way other great learners ascertain information in non-math domains.
The ThinkWell-LearnWell Diagram can be used as a model for math students as they determine which thinking levels they need to access in order to realize their learning goals. The deliberate use of high-level thinking skills produces deep learning outcomes. When students deepen their thinking, they go beyond formula memorization to successfully analyze and explain the logic upon which the formulas were built.
Make no mistake: The ThinkWell-LearnWell Diagram is not a panacea. However, because it addresses the core of learning problems — the ways learners interact with the material they are studying — it can produce sweeping results that span all disciplines, domains, and content areas.
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