11

Our Learners and How They Learn

GENERATIONS ONLINE

For the first time in history, students from three generations could conceivably be found taking classes in college. These generations are the baby boomers, Gen-Xers, and millennials. Much has been written about the Gen-Xers and millennials with regard to personality traits, expectations of life, how they learn, and other dimensions on how they differ from previous college students. I have been tempted to reiterate the information. However, other, more relevant forces are at work in higher education, such as moving education from the classroom to the online environment, a change that many faculty are ill-prepared for from a theoretical and practical perspective; recent findings about how the brain works with relation to learning; the use of handheld technology as peripheral cognitive storage; and the not-so-recent understandings from the field of cognitive psychology that are being translated into practice in higher education. Thus, I will resist the urge to summarize what has been written about these groups as the information seems to be a moving target. Instead, let me place these generations in perspective chronologically.

Before providing a brief overview of the three generations, sans characteristics, understanding what the terms traditional and nontraditional learners mean is in order. Not specifically defined, but almost universally understood without using the term “traditional,” these students enrolled full time in college immediately after graduation from high school and were financially dependent upon others, typically their parents. Conversely, the concept of the nontraditional student has been the focus of research on persistence and risk of attrition, although a consensus for a definition of the “nontraditional” student has not been reached (Chung, Turnbull, & Chur-Hansen, 2014). Studies completed for the National Center for Education Statistics (NCES; Radford, Cominole, & Skomsvold, 2015) used the following characteristics to identify undergraduate nontraditional learners:

Findings from five separate NCES studies from 1995 to 2012 on the nontraditional learner have been consistent over time and indicate that 74% of college students can be defined as nontraditional.

The distinction between traditional and nontraditional students may have greater implications for teaching and learning than generational differences. Most online nursing programs involve either RN to bachelor of science in nursing (BSN) or graduate students. These students will, most likely, fit the definition of the nontraditional learner because they work more than 35 hours each week and are financially independent. They may also be single parents. This characterization has implications for the time they can devote to studying, which encourages faculty to choose teaching strategies and assessments strategically, as well as to design the learning management system (LMS) for intuitive navigation.

Baby Boomers

The baby boomers were born between 1945 and 1964, which means the youngest members of this group turned 50 in 2014. Some of these students may very well return to college for a second career or graduate study. Most likely, they are traditional learners who were taught in the classroom, where lecture was the main educational strategy used.

Many nursing faculty belong to this generation. Recent national statistics indicate that the average age of doctorally prepared nursing faculty, regardless of rank, and the average age of full professors at 61.6 years old (American Association of Colleges of Nursing [AACN], 2014). In addition, 50% of RNs—and therefore potential students—are older than 50 years of age, according to a survey by the National Council of the State Boards of Nursing (2013).

Gen-X

Gen-Xers, the children of the baby boomers, were so named because some authors felt, as a group, they lacked a generation-defining event (Wilson, 2002). Sandwiched in-between the boomers and millennials, they are 3considered traditional learners even though they grew up with technology. Although authors differ on exact dates, the Gen-Xers were born from the mid-1960s to the early 1980s. The oldest members of this group turned 50 in 2015.

Millennials

The millennials were born between the early 1980s and 2004, although some authors are less solid on the dates. Technology has been with this group their entire lives, with many using computers from a very early age. The oldest members of this group are in their early 30s, the youngest in middle school.

A plethora of writing has been published on the Net Generation (Gen-Xers and millennials), much of it in disagreement, leaving the educator with few solid strategies to advise teaching. Instead of attempting to customize our teaching to meet disparate characteristics of our learners, our focus should be on applying effective learning theories, models, and concepts, regardless of how long they have been around; using teaching strategies that support how the mind learns, regardless of how old or what generation that mind belongs to; and using technology effectively and efficiently to support all of this. Thus, the focus of this chapter is on the learners and how they learn, introducing concepts that have been around for a while, but perhaps may be less familiar to nurse educators. In addition, I discuss perhaps even less familiar concepts to promote learning from cognitive science research.

The Net Generation

Another means of identifying traditional and nontraditional learners is how they learn, which for the Gen-Xers and millennials is technology based, leading many to prefer the more descriptive term of Net Generation for these two generational groups. Although not true for all members of the Net Generation, they have come to rely on technology in all aspects of their lives, including learning, which led Rosen (2011) to define a subgroup of the Net Generation born in the 1990s that he calls the iGeneration. For this group, technology is not something special to be used under specific circumstances. Instead, all forms of technology—laptops, tablets, smartphones, e-readers, and so forth—are extensions of who they are; a very different perspective from how the telephone was thought of by the baby boomers. In Rosen’s (2011) view, members of the iGeneration “don’t question the existence of technology and media. They expect technology to be there, and they expect it to do whatever they want it to do. Their WWW doesn’t stand for World Wide Web; it stands for Whatever, Whenever, Wherever” (para. 7).

4This perspective has the potential to forever alter how we teach and the definition of learning in general. Having the answer to almost any question a few clicks away by using a handheld device of some sort, learners have essentially added external brain capacity. This may alleviate the need to teach many facts and concepts, instead shifting the focus of education to critical thinking, critical appraisal, and the ability to distinguish reliable resources from those that are not. With this somewhat radical thought in mind, a review of what is currently known about how we learn is in order.

HOW WE LEARN

Learning occurs because of the interaction among attention, thinking, and memory. One cannot learn for the long term without attending to the lessons, engaging cognitive and metacognitive processes, and encoding and storing whatever was attended to in long-term memory (LTM). Our understanding of how learning occurs has shifted from what Miller (2014) refers to as the three-box theory of memory, specifically working memory, short-term memory (STM), and LTM, to that of the relationship of attention to memory.

The Three-Box Theory

Research on memory is in a bit of a flux, with the three-box theory falling out of favor and an explanation understandable to educators yet to emerge from cognitive research (Miller, 2014). The process originally introduced by Atkinson and Shiffrin (1968), which Miller (2014) refers to as the three-box theory, was composed of three subsystems, “sensory register, short-term store, and the long-term store” (p. 16), now known as working memory, STM, and LTM. Although gaps in our understanding exist, which explain how observations from our environment become mental representations that are then stored in memory, the current understanding is that “the brain converts your perceptions into chemical and electrical changes that form a mental representation of the patterns you’ve observed” (Brown, Roediger, & McDaniel, 2014, p. 72). How these mental representations became retrievable is illusive, but the process has been referred to as encoding since the early research of Tulving and Thomson (1973), and the representations are called memory traces. Through a process called consolidation, these memory traces are organized and linked to prior knowledge that helps make sense out of the incoming information. Consolidation may take hours to days to occur and is an unconscious phenomenon, resulting in storage in LTM as a schema or mental model. What strengthens the consolidation process 5is time away from actively thinking about the information, with sleep actually promoting the process.

Retrieval, recalling, or remembering the information is necessary to use the information. Retrieving information from LTM and moving it into working memory “can both strengthen the memory traces and at the same time make them modifiable again, enabling them, for example, to connect to more recent learning. This process is called reconsolidation. This is how retrieval practice modifies and strengthens learning” (Brown et al., 2014, p. 74). Cues, or aspects of the information (content and context), employed to store memories are important for retrieval. These cues are strengthened and new ones added through mental rehearsal, a means of recall or retrieval. Without periodic rehearsal or retrieval, over time the cues are forgotten. The memory remains, but it cannot be accessed and therefore is not retrieved without a cue to bring it forward. Remembering information within a context, however, provides a richer selection of cues that makes information easier to recall. Thus, learning requires encoding into LTM, making associations with multiple cues, and practicing retrieval so that the cues remain active (Brown et al., 2014).

Mental Models

Mental models can range from a single piece of data to a bundle of related knowledge (know that), skills (know how), and a complex set of connections that are difficult to extract, but have to do with applying the information, or knowing when. For example, as a child you might have a schema or mental model for a specific grocery store because your mother takes you to the same store shopping each week. As your experience increases, the concept of grocery store takes on a variety of meanings from a corner convenience store where a small selection of groceries can be purchased to a Walmart Supercenter that has just about everything. Yet, your mental model stored in LTM is that of a grocery store in general that contains multiple links or traces to various types of grocery stores. Mental models or schemas provide bundled storage in LTM, so as not to tax the capacity of working memory or STM. When the data is needed, we can retrieve it via the traces; bringing it back into consciousness for use. If we encounter a new piece of information, such as that grocery stores in Colorado do not sell alcohol, our mental model for grocery stores has just been modified.

Developing mental models takes practice and occurs over time, so it is not surprising that experts have more mental models than novices, which promote the fluid and intuitive performance of the expert. The news is not all good here, as experts often have difficulty deconstructing their mental models because the individual elements are so embedded in complex 6cognitive structures. Novices, after all, are rule-guided when applying what they have learned, which requires that they learn it in a step-wise fashion (Benner, 1984/2001; Brown et al., 2014).

Cognitive Load

The concept of cognitive load is built on the known limited capacity of working memory. Sweller, Van Merrienboer, and Paas (1998) explained that:

Here the authors make a distinction between holding information and actually processing it, which involves, among other activities, that of schema creation or modification. Three types of cognitive load have been identified as intrinsic, extraneous, and germane (Young, Van Merrienboer, Durning, & Ten Cate, 2014).

Intrinsic cognitive load is that imposed by course content itself. For example, if the course content is completely new to students, meaning they have no mental models or prior knowledge to fall back on, and contains multiple interrelated elements, then intrinsic load can be high. Faculty can do little to control for this other than assuring that assigned readings are consistent with the student’s educational level, breaking complex content into smaller more understandable chunks, and choosing reading and assignments strategically.

Extraneous cognitive load is that imposed by the design and organization of learning materials and the online LMS (i.e., Moodle or Blackboard) that faculty can control. The extraneous cognitive load has to do with how the computer–user interface is designed and is discussed in Chapter 12. If the LMS is not well designed, students spend an inordinate amount of time trying to locate information. Also, if the syllabus and organization of the LMS are not parallel, additional extraneous cognitive load is imposed, a topic discussed in Chapter 12.

Two types of extrinsic cognitive load have been identified—split attention and redundancy—which have implications for choosing instructional resources for students. Split attention refers to providing multiple resources for the student to consider. If students’ time is limited, which it often is for nontraditional students, choosing which resource to use, because they do not have time to read or review them all, adds extra cognitive load. 7Consequently, students’ attention is split among these resources, which may result in students feeling overwhelmed and not attending to any of them. Redundancy refers to providing repetitious resources. This is especially frustrating for students who prefer to make hard copies of references, resulting in wasted paper and printer ink.

Adaptive Memory Framework

Nairne, Thompson, and Pandeirada (2007) formulated a more recent theory of memory termed the adaptive memory framework, which posits that memory is evolutionary and adapts to remember what is most crucial to solving recurring problems related to survival and reproduction. The foundation of their theory is based on how the brain has adapted over time to ensure the survival of the species in a changing environment. Thus, its primary function has been that of remembering important information in order to solve problems.

How does this relate to teaching and learning? Nairne et al. (2007) views memory from a functional perspective as opposed to the structural view of the three-box theory. Their theory posits that we are most attuned to what we care about. This can be translated into our teaching practices by taking the time to determine what information students must know, what they believe is nice to know, and what is really irrelevant to their future goals. Miller (2014) suggests posing these questions to help you make a distinction among these three areas: “Why should students remember the information I’m giving them? Does it relate to their goals? . . . If not, they are likely to forget it—a case of the brain just doing its job the way evolution shaped it to do” (p. 98).

COGNITION, METACOGNITION, AND REFLECTION

Flavell (1979) first described the term metacognition as “cognition about cognitive phenomena” (p. 906). As cognition refers to thinking, metacognition is really thinking about thinking. Metacognition can be thought of as that internal voice that guides and monitors thinking and learning. I am sure you know what I mean—that little voice in your head that gets your attention to tell you it did not understand what you just read, for example.

Metacognition

Flavel (1979) identified three types of metacognition: knowledge about the self, knowledge about cognitive tasks, and strategic knowledge. 8Self-knowledge requires knowing one’s strengths and weaknesses to prepare for learning appropriately, being aware of the depth and breadth of one’s knowledge, and understanding what strategies work best for specific learning tasks. Self-knowledge is related to motivation and self-efficacy, which also affect how students approach learning. It is this self-knowledge that leads to the concept of assessment driving learning, for students choose the appropriate study strategy depending on the perceived demands of how the material will be assessed, such as the type of test.

Knowledge about cognitive tasks encompasses the ability to recognize the complexity of a task. This includes matching that task with the appropriate learning strategy and understanding when and why particular strategies are appropriate.

Strategic knowledge is the most applicable in this context as it includes the specific strategies employed for learning and problem solving. Weinstein and Mayer (1983) have grouped these various strategies into five categories: rehearsal, elaboration, organizational, comprehension monitoring, and affective.

Rehearsal is an active, yet not particularly effective, form of learning in which the learner repeats information over and over in an attempt to memorize it. Rehearsal also involves highlighting content in the text or copying important information in notes. Highlighting information in a text to improve learning has been researched by cognitive scientists and found not to be particularly strategic for learning (Roediger, 2013).

Elaboration involves “paraphrasing, summarizing, or describing how new information relates to existing knowledge” (Weinstein & Mayer, 1983, para. 8) and serves to bring forth prior knowledge into working memory to assimilate it with the new information. Elaboration strategies are more effective than rehearsal strategies. Answering self-generated questions or completing those provided in the text is one of the elaboration strategies requiring retrieval from LTM that has been found to be effective for long-term learning and transfer (Brown et al., 2014).

Organizational strategies involve outlining a chapter, concept mapping, or diagraming. These activities serve to bring forth the relationships among and between elements of content (Weinstein & Mayer, 1983).

Comprehension-monitoring activities include those that check for understanding such as reviewing questions in a text prior to reading in order to focus the learner on important content and activate prior knowledge. This type of self-monitoring activity requires that the student set goals, monitor progress in meeting those goals, and modify strategies accordingly (Weinstein & Mayer, 1983).

Affective strategies involve monitoring anxiety levels or negative self-talk of failure to maintain focus on the task at hand and taking active steps to remain alert. Another affective strategy involves studying in a quiet place (Weinstein & Mayer, 1983).

9Reflection

Nursing educators seem to focus on the term reflection, which is often equated with metacognition. Reflective journals and other reflective assignments are common in nursing and do serve as retrieval practice (Brown et al., 2014). The desired outcome of reflection is to improve practice based on a mental review of related knowledge and experience regarding a specific performance. A variety of models exist that include different language, but seem to agree that the purpose of reflection is to identify learning needs; integrate personal beliefs, attitudes, and values with knowledge and experience; and link what is known to new knowledge and experience (Mann, Gordon, & MacLeod, 2009).

Schön (1987), who first described the reflective practitioner, is also credited with separating the construct into reflection-in-action and reflection-on-action. Reflection-in-action is activated when the individual lacks adequate experience performing the task or the task is complex. This form of reflection may be considered parallel to metacognition for it involves thinking about thinking during the performance task to guide thoughts and actions. Reflection-in-action may result in modification of performance based on knowledge and prior experience combined with real-time environmental cues such as a patient’s changing condition. This is difficult for the educator to assess while the performance is occurring, but afterward, the student can verbally walk faculty through what he or she was thinking while performing the task. Conducting research on this construct is equally challenging because what is occurring in the student’s mind cannot be assessed as it is occurring (Mann et al., 2009).

Reflection-on-action is commonly used as an assignment in education as a means to encourage learning from experience. I do think that when the term reflection is used in this context it is this construct of reflection-on-action that is meant. Reflection in this regard occurs after the performance has been completed and requires critical thinking and analysis (Mann et al., 2009). This type of reflection includes revisiting the experience without constraints of time; experiencing the emotions felt during the event or when thinking about the event; and evaluating the experience in terms of how it fits with existing knowledge and experience. The outcome of reflection is to validate, reshape, and/or completely revise future performance (Boud, 2001).

Boud (2001) adds another dimension to reflection-in-action or reflection-on-action and that is reflection-before-action, or preparing oneself for what is to come. He specifies three aspects to this practice: focusing on the learner, the context, and potential learning to be gained. This pre-experience type of reflection brings into conscious awareness what the learner should consider and tune into to gain the most from the learning experience. This 10strategy is often employed during clinicals when a preceptor takes the student aside prior to performing a new skill to review the procedure, which results in both student and instructor feeling assured that the student is prepared for the task.

Taken together, the work of Schön and Boud was combined into a model of reflective practice by Abrami et al. (2009, as cited in Johnson, 2013) that considers reflection occurring in three stages:

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