introduction
Stress impacts both quality and length of life (Bowman, 2005; Sapolsky, 1998), but the stress of learning is yet to be understood. Recent researchers attempt to explain how stress can both increase and hamper learning, but no studies were found that linked learning stress to life long stress. Until recently no technologies could measure the biophysical variables in normal activities of life. Invasive technologies made it difficult to study people in vivo.
The Allostatic Load Theory provides a foundation for the study as learning begins at the earliest stages of life and continues until old age (Alfarez, Wiegert, & Krugers, 2006; McEwen, 1998). Research indicates stress over long periods induces a variety of chronic diseases (Kiecolt-Glaser, McGuire, Robles, & Glaser, 2002; Blair, Granger, & Raza, 2005). Weight gain, hypertension, osteoporosis, immunosuppression, insulin resistance, atherosclerosis, and cardiovascular disease are a few complications of long term stress (Karlamangla, Singer, McEwen, Rowe, Seeman, 2002). The ultimate result is death. Stress may be the largest public health issue for the new century.
Since learning stress is known to reduce memory transfer (Shors, 2006), the reduction of stress becomes an instructional design issue (Molinari, Dupler, & Lungstrom, 2005) Stress prevents learning by limiting perceptions, impairing thinking, and hampering transfer of capabilities during performance (Wu, Song, Tian-Bao, Li, He, Ge, Wang, 2007; McGaugh, 2004; Kuhlmann, Piel & Wolf, 2005). The problems later trigger more stressful performance events (Sapolsky, 1998).
background
The inability to think or remember concepts, procedures, and methods can threaten lives when demonstrated by service professionals like pilots, air controllers, nurses, doctors, police, firemen, and armed forces. The outcomes of a particularly stressful situation can be the failure to process information properly (Kuhlmann, Piel & Wolf, 2005). Stress management is vital to saving lives. Instructors should no longer view stress as a normal and uncontrollable side effect of the academic process. The stress related disease epidemic begins in childhood (Marano, 1999; diFabio & Prosch, 2003; Rosenzweig, Breedlove, & Watson, 2004; Isgor, Kabbaj, Akil, & Watson, 2004) and the demand for life long learning, means stress management is a life long issue.
Stress reduces immune function creating vulnerability to acute illness (Kiecolt-Glaser, McGuire, Robles, & Glaser, 2002). Reducing stress could minimize colds, flu, and mild depressive symptoms that complicate student achievements and relationships. Stress hormone levels can predict future relationship problems according to Glaser and associates (Glaser, Robles, Malarkey, Sheridan, & Kiecolt-Glaser, 2004).
allostatic load
Allostasis was first described by Sterling and Eyer (1988) to explain the constant biophysical change occurring to meet perceived and anticipated challenges. McEwen and Stellar (1993) developed a model describing how stress reactions may be both adaptive and life-threatening. The model describes the results of repeated stress reactions. The long term effect of continuous hormone release produces homeostasis in the immediate situation but can wear down the body.
The allostatic load model links adaptation and survival to disease process through persistent acute responses to stress. With each perception neurochemicals are released to activate or restrain bodily functions. This triggers psychological reactions that create further neurochemical responses. When a response to a perceived demand occurs, the body is successful, and similar responses are often chosen in future situations. Repeated occurrences that are beneficial in the short run have deleterious effects over time (Mirescu, Peters, & Gould, 2004; McEwen, 2002).
Reducing learning stress theoretically enables more learning, but studies are needed to define how this occurs. What elements of instructional design make a difference? Are there alternative methods of reducing test anxiety besides those commonly used? For instance, do popsicles, massage, acupressure, or music help? Which is less upsetting, performance testing in isolation with a video camera, using a peer group or with just an evaluator? How does simulation work in stress reduction? The science is very young.
Stress Indicators
Learning is biological. There are many neurochemicals involved .A briefglimpse ofbrain chemicals explains the impact on learning and why learning allostatis model. Cortisol is a glucocorticoid key to acute adaptations to stress (Stewart, 2000; Hughes, Romick, Sandor, Phillips, Glaister, Levy, Rock, 2003). Cortisol is easily measured in the lived experience and its impact on learning needs study. Glucocorticoids enhance amygdala activity. The amygdala is a small area of the central brain that facilitates reactions to fear and other strong emotions. Emotion-related memory is centered here (Charney, 2004; Kilpatrick, & Cahill, 2003). Research indicates information processing begins in the amydala. Cortisol mobilizes and replenishes energy stores. By impacting the amydala the hormone increases arousal, vigilance, focused attention, and memory formation.
Continual and sustained cortisol produces negative effects. Long term effects include: weight gain, hypertension, osteoporosis, immunosuppression, insulin resistance, atherosclerosis, and cardiovascular disease (Romeo, Bellani, Karatsoreos, Chhua, Vernov, Conrad, McEwen, 2006; Listen, Miller, Goldwater, Radley, Rocher, Hof, Morrison, McEwen, 2006; Karlamangla, Singer, McEwen, Rowe, Seeman, 2002). For each reaction in the body, another negative feedback system exists to turn off the reaction. Cortisol is turned off through a complicated system involving other glucocorticoid and mineral corticoid receptors. Measurement of hormones like Dehydroepiandrosterone, Corticotropin-releasing hormone might also impact learning stress research in the future.
One can measure other variables. The cardiopulmonary systems react immediately to stressors. Norepinephrine and Neuropeptide Y impact the body by influencing the cardiovascular system and feelings of anxiety. Epinephrine modulates memory consolidation (Cahill & Alkire, 2003). Overtime stress can cause cardiovascular problems. Are there differences in reactivity at different ages? If so, how should stress be defined and measured?
Students report psychological stress from preschool through adulthood and studies now find that prenatal stress can have impacts on learning and stress management (Priebe, Brake, Romeo, Sisti, Mueller, McEwen, & Francis, 2006). Higher education students experience stress related ailments like ulcers, and autoimmune disease (Heath, Macera, & Nieman, 1992; Reid, Mackinnon & Drummond, 2001) due to the learning environment (Hughes, et al., 2003). K-12 students also experience stress related symptoms like stomach aches and headaches. What variables stress people with what learning styles? There is a lot to study and learn.
Main Focus: Allostatic LEARNING model
The Allostatic Learning Model (see figure 1), attempts to explain the complex relationships among genetic, environmental and physical learning variables as they relate to stress and achievement. Previously researchers studied variables separately making it impossible to see how factors are interrelated. There are many important seminal works on individual factors, but few studies incorporate many factors into the same study. The al-lostatic learning model permits study of a variety of factors simultaneously.
Measuring stress processes under everyday conditions challenged educational researchers until recently. Self-report methods are considered unreliable due to the filtering that occurs between experience and report (Dinges, 2003; Razavi, 2001). Researchers state biophysical measures are the most reliable reflection of lived experience. Despite this understanding, the ability to collect physiological data was limited to the laboratory.
Measurement of cortisol and cardiopulmonary variables provides a picture of stress as it occurs. Increased glucocorticoid levels impair memory function, problem solving, and spatial recognition memory (Gulpinar & Yegen, 2004:Rozzendaal, 2001; McEwen & Seeman, 2003). Cortisol, a glucocorticoid, is regulated by the adrenocorticotrophic hormone (ACTH) (Carrasco, & VandeKar, 2003) and plays a major role in the stress of learning (Charney, 2004), and in memory processes underlying behavior adaptation ((Bremner, Vythilingam, Vermetten, Anderson, Newcomer, & Charney, 2004; Gesing et Al, 2001). Salivary cortisol reacts within 10-20 minutes of a stressor (MacArthur & MacArthur, 2002).
Cortisol rises when people perceive stress. The rise can be measured immediately through blood draws, or over a 24 hr period with urine collection. Blood draws, urine samples, and connection to machines during rest periods prevented measurement of normally lived experience. The development of salivary sampling enabled field study collection of cortisol. Salivary samples are reliable, inexpensive, and possible during in vivo study. The invention of wearable computers facilitated continuous cardiopulmonary tracking. A drawback to in vivo studies is that several physical and experiential conditions impact levels and need control (Miller, Chen & Zhou, 2007).
The cardiac and respiratory systems instantaneously respond to perceptions (Sapolsky, 1998). Until recently educational heart and respiratory variables could only be measured periodically, providing a hit and miss snapshot of physiological fluctuations that often miss the peaks and valleys of stress reactions (Grossman, 2003). Since the heart and lungs are instantaneously responsive to aversive stimuli, continuous measurement can provide a “moving” picture of experience. The invention of ambulatory measurement devices permits noninvasive continuous cardiopulmonary measurement. Ambulatory measurement vests are light weight, washable garments. The LifeShirt® device collects objective physiologic data through various sensors including RIP bands that measure pulmonary function (tidal volume, respiratory rate, etc) and electrical activity of the myocardium via a 3-lead electrocardiogram, and activity/posture via a tri-axial accelerometer. Data is stored in a personal digital assistant (PDA) sized computer. The PDA also permits gathering subjective participant data in a digital diary. The small computer is slipped into a pocket, worn on a belt or hung over a shoulder. The vest measures 30 cardiopulmonary variables and can be used as a platform for other measurements such as electroencephalograms. The descriptive statistical software accompanying the vest allows researchers to diagnose problems, observe trends, view findings in graphic or numeric formats, and gather descriptive statistics from a few seconds to 14 hours.
Figure 1
LifeShirt® monitoring and salivary cortisol sampling were the primary measurements modalities utilized in a recent study of online learning. The goal was to describe student stress under “normal” learning conditions. The pilot feasibility study asked, can technology detect differences in learning stress of online learners in two settings?
Thirty-six students studying “how to author a database” completed an online tutorial adapted from Microsoft. Junior year-first semester nursing students were randomly assigned to one of two sections. Students in the isolated section completed the module alone in a room with an Internet-connected computer. Students in the classroom section completed the module in a computer lab with more than 2 companions and an instructor who answered questions. All participants wore the ambulatory monitoring device throughout the experience and provided three salivary cortisol samples.
All physiological measures were taken while students sat at their computers. Five minute means of the continuous variables provided the comparison data.
Heart rate and pulmonary function were sampled “pre,” “post,” and at the one hour “peak” periods. Statistics for maximum and minimum means as well as an overall mean for each period were compared. SPSS was used to compare individual and group results over time and then between groups.
salivary cortisol Results
All students experienced a salivary cortisol rise during the study indicating a stress increase. Since the diurnal expectation posits a steady decrease in cortisol levels throughout the day, any rise is perceived as an indication of stress. Significant differences for the amount of change from times “pre” to “peak” and again from “peak” to “post” were t-2.66, p-.01 indicating a rise and then a fall in cortisol levels for the whole class. No significant between group differences were observed.
cardiopulmonary Results
A comparison of group means using the t test noted no difference between isolation and classroom groups for the pre study heart rate mean indicating students in both groups were similar as they entered the study. Repeated measures for heart rate means of the whole experience (pre, peak, post) indicated a significant difference (f-12.712, p-.00) across time but only a trend (f-2.721, p- .073) toward difference between groups. In other words, everyone experienced an elevation in heart rate during the study period, but only a trend of a difference was detected between isolated and classroom settings.
The “maximum” heart rate mean for 5 minute periods was taken as an elevation in heart rate indicates reaction to aversive stimuli. The difference between the isolated and classroom groups “maximum” heart rate mean during the “peak stress” period was significant (t-8.959, p-.000). A minimum heart rate mean for each 5 minute period was also measured. The minimum heart rate mean was p-.05 (t-1.991). The difference indicates learning stress differences were greatest during the study period for the two groups. The post period means were compared for the two settings and no significant differences were found for the overall, maximum, or minimum means. A comparison between groups for maximum heart rate means found (f-10.647, p-.000) over time and (f-9.011, p-.001) for groups indicating that although everyone experienced a jump in heart rate at times, isolated students had higher peak heart rates than their peers.
Respiratory rates differed over time. One measure of stress is the sigh. Sigh volumes, or the amount of inspiration exceeding normal means by at least 20% were measured. The sigh volume means significantly differed between groups ( t-2.82, p-0.01). The whole sample differed in the sigh volume maximums from pre study and peak stress periods (t-2.46, p-0.02) and then again between peak stress and post study (t-2.38, p-0.02) indicating study periods had more sighs than pre and post periods.
The tidal volume, or amount of inspiration of regular breathing, demonstrated similar findings to sigh volumes over time. Maximum rates (t-9.67, p-.00) and minimum rates (t- 5.68, p-.00) were significant. The only difference between groups was found during the beginning relaxation period (t- 2.99, p-0.01). The number of breaths/minute indicates people breathe differently during learning (t-4.68, p-.00). There was also a difference in breaths/minute between the isolation and classroom groups. The variation may further indicate students in isolation were not as relaxed as those in the group situation (t-2.06, p-0.05).
Respiratory rates provided similar changes over time for different measurement periods (t- 9.05, p-.00). Differences between the two groups before learning were p-0.00 (t- 2.99), indicating again that isolation students might not have been as relaxed as the classroom group. Other respiratory measures provided similar findings with differences between the pre and post levels of the two groups and differences over time.
Students entered 1-5 feeling words whenever entering a new section of the module. Data indicates student emotions changed as they progressed through the tutorial. Negative emotions were expressed in terms like “confused” and “frustrated”. As students were asked to demonstrate the principles taught some students commented on feeling “lost” or “angry”. All students demonstrated the ability to perform the skills taught so their emotional reactions were not the result of uncapability.
The answer to the feasibility question is that the technologies worked in vivo and provided answers to differences in online learning settings. The feasibility of measuring biophysical variables like cortisol, heart rate, and respiratory function facilitates a more holistic approach for learning research. The continuous measurement of sensitive cardiopulmonary variables was able to dilineate differences between groups.
Participants judged the LifeShirt ® as comfortable and not interfering with the learning experience.
future trends
Future researchers may establish “normal levels” of biophysical fluctuation that can “diagnose” individual and product problems. Educators may find the nursing process framework adaptable to learning situations in which teachers “nurse” students through their learning process. Using a holistic approach to educational stress research that includes biophysical measures with self report can impact research on retention, remediation, and design disciplines.
Stress impacts the learning process according to researchers. Since the feasibility of measuring biophysical variables during lived experience is now possible, environments that impact learning such as distance education, simulations, and virtual learning can be compared. The immediate and continuous measurement of biophysical reactions can aid in understanding student process and filtering of psychological reactions.
Future discussion of the costs and benefits of delivery model differences could include biophysical measurements since research indicates stress impacts health. Once the holistic discussion begins, researchers can then explore coping strategies for learning stress. More understanding of individual responses to learning stress are needed from different age groups, cultures, situations, and disciplines. Nurse researchers can now explore the impact of stress during life-long learning, patient education, and health promotion situations.
conclusion
Differences found between isolation and classroom groups suggest that the learning environment influences student experience. Further study may indicate how and what types of supports are appropriate for the different settings. Combining subjective-self report with objective information reflects a more holistic picture of student process and permits the study of many variables at the same time as is suggested by the allostatic learning model.
The physiological response of distance learning may be different from face-to-face learning, although all students experienced elevations in heart and respiratory rates indicating stress reactions. Such differences need further study. Does group work increase or decrease distance education stress? How do student in virtual reality and simulation settings react to learning stress and later to professional performance? This knowledge would be useful in many professional schools.
Continuous measurement of cardiopulmonary variables reveals significant differences between pre, post, and peak learning periods. Amounts of “normal” fluctuations during study have not yet been determined. Further research may determine levels of eustress and distress.
Patterns in salivary cortisol indicate a need for more study. Analysis determined students exhibited four patterns of reaction with the most common being high-low-high cortisol levels (n-17). Since salivary cortisol reacts to stimuli occurring up to 20 minutes earlier, controls for life stress need to be instituted in future studies. The preparation time for the study took 30 minutes including relaxation period, instruction, and computer sign-on. In order to control for anticipation of the unknown, relaxation strategies could be introduced.
Students in isolation experienced higher respiratory rates before or after the learning than their classroom setting peers indicating students in isolation may not be as relaxed as those in classroom situations. The results from a small sample can not be generalized and need replication. In future studies reasons for “anticipatory learning stress” may need further examination. Interventions to reduce the anticipatory stress may be needed.
key terms
Ambulatory measurement device: A data gathering instrument that can be worn during everyday experiences. The device gathers biophysical data for later transmission or reading.
Cortisol: A glucocorticoid regulated by the adre-nocorticotrophic hormone that plays a major role in stress, learning, and memory processes underlying behavioral adaptation.
Eustress: A change in biophysical or psychological variables that is considered good.
Learning Stress: Physiological and psychological changes occurring during learning events.
LifeShirt®: A wearable ambulatory monitoring device produced by Vivometrics, Inc. that measures 30 cardiopulmonary variables. FDA approved for sleep studies.
Myocardium: Heart muscle
Personal Digital Assistant: A microcomputer that fits into the palm of the hand.
Repeated measures: A multiple ANOVA of variables over time performed in SPSS
Sigh: An inspiration that measures 20% over the mean inspiration.
Stress: The unspecified physiological reaction to aversive stimuli.
Tidal Volume: The amount of inspiration of regular breathing.
