7.5 Learning in the Classroom

In this chapter we’ve considered several different types of learning from behavioral, cognitive, evolutionary, and neural perspectives. Yet it may seem strange to you that we haven’t discussed the kind of learning to which you are currently devoting much of your life: learning in educational settings such as the classroom. Way back in the first chapter of this book (Psychology: Evolution of a Science), we reviewed some techniques that we think are useful for studying the material in this course and others. But, we didn’t say much about the actual research that supports these suggestions. During the past several years, psychologists have published a great deal of work specifically focused on enhancing learning in educational settings. Let’s consider what some of this research says about learning techniques, and then turn to the equally important topic of exerting control over learning processes.

Techniques for Learning

Technique Description Utility
Elaborative interrogation Generating an explanation for why an explicitly stated fact or concept is true Moderate
Self-explanation Explaining how new information is related to known information, or explaining steps taken during problem solving Moderate
Summarization Writing summaries (of various lengths) of to-be-learned texts Low
Highlighting/ underlining Marking potentially important portions of to-be-learned material while reading Low
Keyword mnemonic Using keywords and mental images of text materials while reading or listening Low
Imagery for text Attempting to form mental images of text materials while reading or listening Low
Rereading Restudying text material again after an initial reading Low
Practice testing Self-testing or taking practice tests over to-be-learned material High
Distributed practice Implementing a schedule of practice that spreads out study activities over time High
Interleaved practice Implementing a schedule of practice that mixes different kinds of problems, or a schedule of study that mixes different kinds of material, within a single study session Moderate
Table 7.2: Rating the Effectiveness of Study Techniques

Students use a wide variety of study techniques in attempts to increase learning. Popular techniques–ones that you might use yourself–include highlighting and underlining, rereading, summarizing, and visual imagery mnemonics (Annis & Annis, 1982; Wade, Trathen, & Schraw, 1990). How effective are these and other techniques? A team of psychologists that specialize in learning recently published a comprehensive analysis of research concerning 10 learning techniques that are used to by students (Dunlosky et al., 2013). They considered the usefulness of each technique across four main variables: learning conditions (e.g., how often and in what context the technique is used), to-be-learned materials (e.g., texts, math problems, concepts), student characteristics (e.g., age and ability level), and outcome measures (e.g., rote retention, comprehension, problem solving). Based on the picture that emerged across these four variables, Dunlosky et al. evaluated the overall usefulness of each technique and classified it as high, moderate, or low utility. TABLE 7.2 provides a brief description of each of the 10 techniques and the overall utility assessment for each one.

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Despite their popularity, highlighting, rereading, summarizing, and visual imagery mnemonics all received a low utility assessment. That doesn’t mean that these techniques have no value whatsoever for improving learning, but it does indicate that each one has significant limitations and that time could be better spent using other approaches–a reason why none of these techniques appeared in the Improving Study Skills box. The Improving Study Skills box did review strategies that roughly correspond to two of the techniques in Table 7.2 that received a moderate utility assessment–elaboration interrogation and self-explanation–and we also discussed some material related to these techniques in the Memory chapter. Furthermore, the Improving Study Skills box highlighted both of the techniques that received high utility assessments: distributed practice and practice testing. Let’s take a deeper look at some of the research that supports the beneficial effects of these two effective techniques, which have been intensively investigated during the past few years.

Distributed Practice

Cramming for exams (neglecting to study for an extended period of time and then studying intensively just before an exam; Vacha & McBride, 1993) is a common occurrence in educational life. Surveys of undergraduates across a range of colleges and universities indicate that anywhere from about 25% to as many as 50% of students report relying on cramming (McIntyre & Munson, 2008). Though cramming is better than not studying at all, when students cram for an exam, they repeatedly study the to-be-learned information with little or no time between repetitions, a procedure known as massed practice. Such students are thus denying themselves the benefits of distributed practice, which involves spreading out study activities so that more time intervenes between repetitions of the to-be-learned information (and students who rely on cramming are also inviting some of the health and performance problems associated with procrastination that we outlined in The Real World box on p. 270).

Studying well in advance of an exam, so that you can take breaks and distribute study time, will generally produce a better outcome than cramming at the last minute.
AGEFOTO STOCK/SUPERSTOCK

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The benefits of distributed practice relative to massed practice have been known for a long time; in fact, they were first reported in the classic studies of Ebbinghaus (1885/1964) concerning retention of nonsense syllables (see the Memory chapter). What’s most impressive is just how widespread the benefits of distributed practice are: They have been observed for numerous different kinds of materials, including foreign vocabulary, definitions, and face–name pairs, and have been demonstrated not only in undergraduates, but also in children, older adults, and individuals with memory problems due to brain damage (Dunlosky et al., 2013). A review of 254 separate studies involving more than 14,000 participants concluded that, on average, participants retained 47% of studied information after distributed practice compared with 37% after massed practice (Cepeda et al., 2006).

Despite all the evidence indicating that distributed practice is an effective learning strategy, we still don’t fully understand why that is so. One promising idea is that when engaging in massed practice, retrieving recently studied information is relatively easy, whereas during distributed practice, it is more difficult to retrieve information that was studied less recently. More difficult retrievals benefit subsequent learning more than easy retrievals, in line with idea of “desirable difficulties” (Bjork & Bjork, 2011) introduced in the Improving Study Skills box. Whatever the explanation for the effects of distributed practice, there is no denying its benefits for students.

Practice Testing

Why does a difficult practice test have the greatest benefit?

Practice testing, like distributed practice, has proven useful across a wide range of materials, including learning of stories, facts, vocabulary, and lectures (Dunlosky et al., 2013; Karpicke, 2012; see also the LearningCurve system associated with this text, which uses practice testing). As you learned in the Memory chapter, practice testing is effective, in part, because actively retrieving an item from memory on a test improves subsequent retention of that item more than simply studying it again (Roediger & Karpicke, 2006). Yet when asked about their preferred study strategies, students indicated by a wide margin that they prefer rereading materials to testing themselves (Karpicke, 2012). The benefits of testing tend to be greatest when the test is difficult and requires considerable retrieval effort (Pyc & Rawson, 2009), also consistent with the desirable difficulties hypothesis (Bjork & Bjork, 2011). Not only does testing increase verbatim learning of the exact material that is tested, it also enhances the transfer of learning from one situation to another (Carpenter, 2012). For example, if you are given practice tests with short-answer questions, such testing improves later performance on both short-answer and multiple-choice questions more than restudying (Kang, McDermott, & Roediger, 2007). Testing also improves the ability to draw conclusions from the studied material, which is an important part of learning and often critical to performing well in the classroom (Karpicke & Blunt, 2011).

Testing Aids Attention

Recent research conducted in the laboratory of one of your textbook authors highlights yet another benefit of testing: including brief tests during a lecture can improve learning by reducing the tendency to mind wander (Szpunar, Khan, & Schacter, 2013). How often have you found your mind wandering–thinking about your evening plans, recalling a scene from a movie, or texting a friend–in the midst of a lecture that you know that you ought to be attending to carefully? It’s probably happened more than once. Research indicates that students’ minds wander frequently during classroom lectures (Bunce, Flens, & Neiles, 2011; Lindquist & McLean, 2011; Wilson & Korn, 2007). Critically, such mind wandering impairs learning of the lecture material (Risko et al., 2012). In the study by Szpunar et al. (2013), participants watched a videotaped statistics lecture that was divided into four segments. All of the participants were told that they might or might not be tested after each segment; they were also encouraged to take notes during the lectures.

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How does taking practice tests help focus a wandering mind?

At random times during the lectures, participants in all groups were probed about whether they were paying attention to the lecture or mind wandering off to other topics. Participants in the nontested and re-study groups indicated that they were mind wandering in response to about 40% of the probes, but the incidence of mind wandering was cut in to half, to about 20%, in the tested group. Participants in the tested group took significantly more notes during the lectures, and retained significantly more information from the lecture on a final test than did than participants in the other two groups, who performed similarly. Participants in the tested group were also less anxious about the final test than those in the other groups. These results indicate that part of the value of testing comes from encouraging people to sustain attention to a lecture in a way that discourages task-irrelevant activities such as mind wandering and encourages task-relevant activities such as note taking. Because these benefits of testing were observed in response to a videotaped lecture, they apply most directly to online learning, where taped lectures are the norm (see Other Voices: Online Learning), but there is every reason to believe that the results would apply in live classroom settings as well.

Control of Learning

It’s the night before the final exam in your introductory psychology course. You’ve put in a lot of time reviewing your course notes and the material in this textbook, and you feel that you have learned most of it pretty well. You are coming down the home stretch with little time left, and you’ve got to decide whether to devote those precious remaining minutes to studying psychological disorders or social psychology. How do you make that decision? What are its potential consequences? An important part of learning involves assessing how well we know something and how much more time we need to devote to studying it.

Recent research has shown that people’s judgments about what they have learned play a critical role in guiding further study and learning (Dunlosky & Thiede, 2013; Metcalfe, 2009). Experimental evidence reveals that these subjective assessments, which psychologists refer to as judgments of learning (JOLs), have a causal influence on learning: People typically devote more time to studying items that they judge they have not learned well (Metcalfe & Finn, 2008; Son & Metcalfe, 2000).

The finding that JOLs are causally related to decisions about how much to study a particular item is important because JOLs are sometimes inaccurate (Castel, McCabe, & Roediger, 2007). For example, after reading and rereading a chapter or article in preparation for a test, the material will likely feel quite familiar, and that feeling may convince you that you’ve learned the material well enough that you don’t need to study it further. However, the feeling of familiarity can be misleading: It may be the result of a low-level process such as perceptual priming (see the Memory chapter) and not the kind of learning that will be required to perform well on an exam (Bjork & Bjork, 2011). Similarly, recent research has shown that students are sometimes overconfident in judging how well they have learned definitions of new terms, and fail to study them effectively (Dunlosky & Rawson, 2012). One way to avoid being fooled by such misleading subjective impressions is to test yourself from time to time when studying for an exam under exam-like conditions, and in the case of learning definitions, carefully compare your answers to the actual definitions.

In what ways can JOLs be misleading?

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So, if you are preparing for the final exam in this course and need to decide whether to devote more time to studying psychological disorders or social psychology, try to exert control over learning by testing yourself on material from the two chapters; you can use the results of those tests to help you decide which chapter requires further work. Heed the conclusion from researchers (Bjork, Dunlosky, and Kornell, 2013) that becoming a more sophisticated and effective learner requires understanding: (a) key features of learning and memory; (b) effective learning techniques; (c) how to monitor and control one’s own learning; and (d) biases that can undermine judgments of learning.

OTHER VOICES: Online Learning

Daphne Koller is a professor of computer science at Stanford University.
PHOTO BY HECTOR GARCIAMOLINA

Online learning has become a hot topic recently as a result of new online initiatives from a number of leading brick-and-mortar colleges and universities. Daphne Koller, a professor of computer science at Stanford University, is one of the founders of the popular online learning platform, Coursera. She wrote the following article several months before the launch of Coursera in April 2012.

Our education system is in a state of crisis. Among developed countries, the United States is 55th in quality rankings of elementary math and science education, 20th in high school completion rate and 27th in the fraction of college students receiving undergraduate degrees in science or engineering.

As a society, we can and should invest more money in education. But that is only part of the solution. The high costs of high-quality education put it off limits to large parts of the population, both in the United States and abroad, and threaten the school’s place in society as a whole. We need to significantly reduce those costs while at the same time improving quality.

If these goals seem contradictory, let’s consider an example from history. In the 19th century, 60 percent of the American work force was in agriculture, and there were frequent food shortages. Today, agriculture accounts for less than 2 percent of the work force, and there are food surpluses.

The key to this transition was the use of technology–from crop rotation strategies to GPS-guided farm machinery–which greatly increased productivity. By contrast, our approach to education has remained largely unchanged since the Renaissance: From middle school through college, most teaching is done by an instructor lecturing to a room full of students, only some of them paying attention.

How can we improve performance in education, while cutting costs at the same time? In 1984, Benjamin Bloom showed that individual tutoring had a huge advantage over standard lecture environments: The average tutored student performed better than 98 percent of the students in the standard class.

Until now, it has been hard to see how to make individualized education affordable. But I argue that technology may provide a path to this goal.

Consider the success of the Khan Academy, which began when Salman Khan tried to teach math remotely to his young cousins. He recorded short videos with explanations and placed them on the Web, augmenting them with automatically graded exercises. This simple approach was so compelling that by now, more than 700 million videos have been watched by millions of viewers.

At Stanford, we recently placed three computer science courses online, using a similar format. Remarkably, in the first four weeks, 300,000 students registered for these courses, with millions of video views and hundreds of thousands of submitted assignments.

What can we learn from these successes? First, we see that video content is engaging to students–many of whom grew up on YouTube–and easy for instructors to produce.

Second, presenting content in short, bite-size chunks, rather than monolithic hour-long lectures, is better suited to students’ attention spans, and provides the flexibility to tailor instruction to individual students. Those with less preparation can dwell longer on background material without feeling uncomfortable about how they might be perceived by classmates or the instructor.

Conversely, students with an aptitude for the topic can move ahead rapidly, avoiding boredom and disengagement. In short, everyone has access to a personalized experience that resembles individual tutoring.

Watching passively is not enough. Engagement through exercises and assessments is a critical component of learning. These exercises are designed not just to evaluate the student’s learning, but also, more important, to enhance understanding by prompting recall and placing ideas in context.

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Moreover, testing allows students to move ahead when they master a concept, rather than when they have spent a stipulated amount of time staring at the teacher who is explaining it.

For many types of questions, we now have methods to automatically assess students’ work, allowing them to practice while receiving instant feedback about their performance. With some effort in technology development, our ability to check answers for many types of questions will get closer and closer to that of human graders.

Of course, these student–computer interactions can leave many gaps. Students need to be able to ask questions and discuss the material. How do we scale the human interaction to tens of thousands of students?

Our Stanford courses provide a forum in which students can vote on questions and answers, allowing the most important questions to be answered quickly–often by another student. In the future, we can adapt Web technology to support even more interactive formats, like real-time group discussions, affordably and at large scale.

More broadly, the online format gives us the ability to identify what works. Until now, many education studies have been based on populations of a few dozen students. Online technology can capture every click: what students watched more than once, where they paused, what mistakes they made. This mass of data is an invaluable resource for understanding the learning process and figuring out which strategies really serve students best.

Some argue that online education can’t teach creative problem-solving and critical-thinking skills. But to practice problem-solving, a student must first master certain concepts. By providing a cost-effective solution for this first step, we can focus precious classroom time on more interactive problem-solving activities that achieve deeper understanding–and foster creativity.

In this format, which we call the flipped classroom, teachers have time to interact with students, motivate them and challenge them. Though attendance in my Stanford class is optional, it is considerably higher than in many standard lecture-based classes. And after the Los Altos school district in Northern California adopted this blended approach, using the Khan Academy, seventh graders in a remedial math class sharply improved their performance, with 41 percent reaching advanced or proficient levels, up from 23 percent.

A 2010 analysis from the Department of Education, based on 45 studies, showed that online learning is as effective as face-to-face learning, and that blended learning is considerably more effective than either.

Online education, then, can serve two goals. For students lucky enough to have access to great teachers, blended learning can mean even better outcomes at the same or lower cost. And for the millions here and abroad who lack access to good, in-person education, online learning can open doors that would otherwise remain closed.

Nelson Mandela said, “Education is the most powerful weapon which you can use to change the world.” By using technology in the service of education, we can change the world in our lifetime.

Koller makes a strong positive case for online learning, and the rapid spread of online courses since the publication of this article indicates that others agree with her. Furthermore, Koller’s comments about the delivery of information in “bite-sized chunks” and the use of testing are generally consistent with the recent findings of Szpunar et al. (2013) discussed in the main text showing that intermittent testing can reduce mind wandering during online lectures. But online learning is not without its critics. For example, in a New York Times op-ed article written some 6 months after Koller’s column, when Harvard and MIT announced their own online plans, David Brooks (2012a) raised some important questions: “If a few star professors can lecture to millions, what happens to the rest of the faculty? Will academic standards be as rigorous? What happens to the students who don’t have enough intrinsic motivation to stay glued to their laptop hour after hour? How much communication is lost–gesture, mood, eye contact–when you are not actually in a room with a passionate teacher and students?”

What do you see as the major challenges for online learning? How important is face-to-face interaction in your own educational experience? What kind of research would you like to see done to further the effectiveness of online learning?

From the New York Times, December 5, 2011 © 2011 The New York Times. All rights reserved. Used by permission and protected by the Copyright Laws of the United States. The printing, copying, redistribution, or retransmission of this Content without express written permission is prohibited. http://www.nytimes.com/2011/12/06/science/daphne-koner-technology-as-a-passport-to-personalized-education.html

  • Research on learning techniques indicates that some popular study methods such as highlighting, underlining, and rereading have low utility, whereas other techniques such as practice testing and distributed practice have high utility.
  • Practice testing improves retention and transfer of learning and can also enhance learning and reduce mind wandering during lectures.
  • Judgments of learning play a causal role in determining what material to study, but they can be misleading.

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