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Advan. Physiol. Edu. 31: 347-351, 2007; doi:10.1152/advan.00015.2007
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ADV PHYSIOL EDUC 31:347-351, 2007
© 2007 American Physiological Society

TEACHING IN THE LABORATORY

Practical application of fundamental concepts in exercise physiology

R. Ramsbottom, R. F. T. Kinch, M. G. Morris and A. M. Dennis

School of Life Sciences, Oxford Brookes University, Oxford, United Kingdom

Address for reprint requests and other correspondence: R. Ramsbottom, School of Life Sciences, Oxford Brookes Univ., Gipsy Lane, Headington, Oxford OX3 0BP, UK (E-mail: rramsbottom{at}brookes.ac.uk)


   Abstract
TOP
 Abstract
Introduction
 REFERENCES
 
The collection of primary data in laboratory classes enhances undergraduate practical and critical thinking skills. The present article describes the use of a lecture program, running in parallel with a series of linked practical classes, that emphasizes classical or standard concepts in exercise physiology. The academic and practical program ran under the title of a particular year II module named Sports Performance: Physiology and Assessment, and results are presented over a 3-yr period (2004–2006), based on an undergraduate population of 31 men and 34 women. The module compared laboratory-based indexes of endurance (e.g., ventilatory threshold and exercise economy) and high-intensity exercise (e.g., anaerobic power), respectively, with measures of human performance (based on 20-m shuttle run tests). The specific experimental protocols reinforced the lecture content to improve student understanding of the physiological and metabolic responses (and later adaptations) to exercise. In the present study, the strongest relationship with endurance performance was the treadmill velocity at maximal aerobic power (r = +0.88, P < 0.01, n = 51); in contrast, the strongest relationship with high-intensity exercise performance was the mean power output (in W/kg) measured during a 30-s all-out cycle ergometer sprint (r = +0.80, P < 0.01, n = 48). In class student data analysis improved undergraduate indepth or critical thinking during seminars and enhanced computer and data presentation skills. The endurance-based laboratories are particularly useful for examining the underlying scientific principles that determine aerobic performance but could equally well be adapted to investigate other topics, e.g., differences in the exercise response between men and women.

Key words: endurance performance; experimental protocols; critical thinking; maximal aerobic power; exercise economy; blood lactate concentration; high intensity exercise


   Introduction
TOP
 Abstract
 Introduction
REFERENCES
 
A CORE TENET for academics interested in teaching undergraduate exercise physiology is the importance of practical work within the learning process. Thus learning-focused activities take center place in the three-component model of learning and teaching (4) for academic staff at Oxford Brookes University to enhance module-specific learning outcomes. Academic understanding and practical expertise would be enhanced if students could collect and analyze their own experimental data and place their results in the context of the worldwide literature. The overall aims of the teaching program were to 1) engage students with classic concepts in exercise physiology and 2) present students with a related series of laboratory practical work, challenging at both an academic and physical level. The students' aim was to reproduce classic protocols reported in sport science literature during practical classes and, using their collected experimental results, investigate the relationship between commonly used laboratory measures and human performance. The outcome was the production of an indepth word-processed laboratory report.

Students followed written experimental protocols and collected exercise data (e.g., heart rate and pulmonary ventilation), which actively engages students in enhancing their practical laboratory and mathematical skills (29, 32). The use of spreadsheets for statistical analyses and the later interpretation and presentation of results can be used both by students who are conversant with the underlying concepts and by students who need to practice their critical thinking skills (6).

Academic Program
The parallel lecture program of this year II module (entitled "Sports Performance: Physiology and Assessment") dealt with two separate "themes" in exercise physiology, namely, the responses and adaptations to 1) endurance and 1) high-intensity exercise, respectively. During lectures based on endurance exercise, the concept was repeatedly emphasized that submaximal physiological or metabolic measures (e.g., exercise economy, blood lactate concentration, and ventilation threshold) are often used to predict race performance (e.g., Refs. 8, 12, 23, and 31). During lectures based on high-intensity exercise, students were required to have an understanding of the concept of accumulated oxygen deficit (2, 17) and be conversant with standard ergometric tests of high-intensity exercise (e.g., Ref. 3). The supporting lectures explored endurance and high-intensity training with respect to both initial responses and later physiological, metabolic, and morphological adaptations consequent to training (10, 18, 19). Supporting the lecture and practical program was recommended reading from appropriate exercise physiology texts, e.g., chapter 5: aerobic metabolism during exercise and chapter 4: anaerobic metabolism during exercise (22) and chapter 8: physical performance (1). Students undertook de novo experimentation, with appropriate help and guidance from academic staff, rather than being simply supplied with data to fulfill honors-level descriptors (e.g., developing analytical techniques, problem-solving skills, and the evaluation of evidence) (24).

Subjects
The experimental data presented herein were collected over the preceding 3 yr (2004–2006), with the same staff and using the same methodology, equipment, and calibration procedures. In total, 65 students (31 men and 34 women) volunteered to take part in this series of linked experiments. The men were taller (1.82 ± 0.08 vs. 1.67 ± 0.06 m, P < 0.01) and heavier (80.2 ± 12.1 vs. 63.5 ± 10.7 kg, P < 0.01) compared with the women, although there was no difference in age (21.0 ± 3.6 yr for men vs. 20.4 ± 1.4 yr for women). All subjects signed a statement of informed consent, and all procedures had the approval of both the School of Life Sciences and Oxford Brookes University ethical committees. Once individual experimental data were entered onto the class spreadsheet it was completely anonymous.

Measures of Human Performance
To ensure constant underfoot and environmental conditions with a "practical" laboratory performance test that has been shown to be significantly correlated with 5-km run times (26), shuttle run tests were conducted in a sports hall with the results (final speed; in m/s) used as the measure of performance.

During high-intensity exercise, performance was defined as the geometric mean (GM) of two shuttle run tests: the 20-m multistage shuttle run test (MST) and a 20-m high-intensity shuttle run test (HIST), where GM was defined as the square root of the 20-m MST (in m) x 20-m HIST (in m) (27). The relationship between the (maximal) accumulated oxygen deficit (a laboratory measure of anaerobic capacity) and GM has been reported as r = +0.81 (P < 0.01) in physically active men and women (27).

Protocols
The following paragraphs briefly describe the experimental protocols followed by the year II undergraduates during practical classes.

Measures of endurance exercise.
An intermittent treadmill protocol was used to measure 1) individual exercise economy and 2) maximal aerobic power (VO2max). During submaximal exercise, the treadmill gradient was set at 1.0% to mimic outdoor running (i.e., air resistance) (14), and the running speeds were modified from those originally suggested by Eston and Reilly (11). Thus, the women performed the exercise economy test at treadmill running speeds of 1.94, 2.36, 2.78, and 3.19 m/s; the corresponding speeds for men were 2.36, 2.78, 3.19, and 3.61 m/s. Subjects ran for 4 min at each speed. During steady-rate exercise (minutes 3–4 of each speed), oxygen consumption (VO2), heart rate, and the rating of perceived exertion (5) were measured, and a small (10.0 µl) finger stick sample was taken for the analysis of blood lactate concentration (Analox GM-7, Analox Instruments, London, UK). Members of the staff were responsible for blood collection using standard procedures (30). After completion of the economy test, each subject had at least a 5-min recovery period, which allowed stretching and mental preparation, before the start of the second phase of the protocol, namely, to determine the VO2max.

During the VO2max phase of the test, the treadmill gradient remained at 1.0% and the starting speed was the penultimate speed attained on the economy test (e.g., if a man completed 3 speeds on the economy test, his VO2max test started at 2.78 m/s). After 2 min at this initial speed, treadmill speed was increased 0.28 m/s each minute until the subject signaled that they could continue for a further 1 min only when a final 60-s sample of expired air was collected. The final running speed that subjects sustained for a complete 60 s on the treadmill was defined as the velocity at VO2max (20).

VO2max was also measured during a continuous graded-cycle ergometer test. The present protocol used 60 rather than 50 pedal revolutions/minute as originally suggested by Yoshida and co-workers (34). Fifty-second expired air collections were made each minute during this test to volutary exhaustion. However, when a subject signaled s/he could continue to exercise for a final minute only, then a 60-s expired air sample was collected.

During treadmill and cycle ergometer exercise, expired air samples were collected in 150-liter plastic bags for the immediate analysis of VO2 and carbon dioxide production (VCO2) using standard laboratory techniques (e.g., repeated O2 and CO2 analyzer calibration and stopwatch timed collection of expired air samples). During each test, the subject's heart rate was continuously monitored using a telemetry system (Polar Electro, Kempele, Finland).

Measures of high-intensity exercise.
An individualized warm up and stretching routine preceded all measures of high-intensity exercise to minimize any risk of injury. Instantaneous power was estimated using the NewTest system (NewTest, Oulu, Finland). The protocol used a countermovement jump on an electronic jump mat, and the best of three jump heights was used to provide an index of anaerobic power (in W and W/kg). The Wingate 30-s cycle ergometer sprint (3) was used as an index of anaerobic power (peak power output; in W and W/kg) and capacity (mean power output; in W and W/kg) (33). The frictional resistance on the cycle ergometer was adjusted relative to body mass (0.075 g/kg body mass). Power output values from the Wingate test were corrected for the inertia of the flywheel as originally described by Lakomy (15). An intermittent high-intensity motorized treadmill test (maximal anaerobic running power test), originally described by Rusko et al. (28), was used to estimate human anaerobic power (determined as ml O2 equivalents·kg–1·min–1). The maximal anaerobic running power test consisted of 20-s runs on a motorized treadmill interspersed with 100-s recovery periods. The treadmill gradient was 5° (9%) with a starting speed of 3.97 m/s (14.3 km/h). On completion of each 20-s run, the speed of the treadmill increased by 0.35 m/s (1.26 km/h), although the treadmill gradient remained unchanged. Subjects in the original study were well-trained 400-m sprinters and hurdlers, and, therefore, the starting speed was individually adjusted to accommodate differing levels of ability.

Students performed simple correlation and linear regression analyses using Microsoft Excel to examine the relationship between laboratory-measured indexes of endurance and high-intensity exercise versus the appropriate shuttle run performance. Due to either illness or injury, not all undergraduates performed each test. Total numbers of subjects for correlational analysis are shown in GoTables 2 (laboratory measures vs. endurance performance) and 4 (laboratory measures vs. high-intensity performance). Collective data in Tables 1–4 are presented as means ± SD. Differences between men and women were determined using independent t-tests.


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  		Table 1. Selected physiological variables for men and women during endurance-based exercise tests

 

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  		Table 2. Pearson product moment correlation values between selected laboratory measures and endurance exercise performance, number of subjects, and probability

 

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  		Table 4. Pearson product moment correlation values between selected laboratory measures and high-intensity exercise performance, number of subjects, and probability

 
Treatment of Experimental Data
Once the raw data [e.g., %fraction of expired O2, %fraction of expired CO2, and minute ventilation (VE)ATPS, at ambient temperature and pressure saturated (ATPS)] had been collected and recorded in laboratory notebooks, students calculated, from first principles, VO2 and VCO2, including use of the Haldane transformation to calculate inspired minute ventilation (VI) (11). Students indicated potentially anomalous results, which were discussed with academic staff prior to spreadsheet entry. Thereafter, students graphed gas exchange measures [e.g., VE (in l/min), VCO2 (in l/min), ventilatory equivalent for oxygen (VE/VO2), percent fraction of expired O2, respiratory exchange ratio, and VO2 (in l/min)] versus cycle ergometer power output (in W) to identify any ventilation threshold(s). If a threshold was identified (that is, a deviation from linearity in gas exchange measures vs. power output relationship) and was confirmed independently by a member of the staff, the power output and heart rate at that point [i.e., at a specific power output (in W)] was entered onto the class data spreadsheet (Microsoft Excel).

Seminar
Integration of lecture program material and practical data during endurance exercise.
Once practical exercise testing had been completed, students attended a seminar where the completed spreadsheet was available on a number of laboratory personal computers. Using the data, students worked in groups of four to produce descriptive statistics for endurance (Table 1) and high-intensity exercise (Table 3), respectively, and used the Pearson product moment correlation coefficient and the graphical capacity of Microsoft Excel to examine relationships between laboratory measures and human performance (Table 2 and Fig. 1). The seminar also provided the ideal forum for staff-student discussion of the relevant exercise science literature (7), to which students would later refer in their written report.


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  		Table 3. Selected physiological variables for men and women during high-intensity-based exercise tests

 

Figure 1
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  		Fig. 1. Treadmill velocity at maximal anaerobic power (vVO2max; in m/s) plotted against performance on the 20-m multistage shuttle run test (MST; in m/s). n = 51.

 
The seminar provided a discussion forum for students to relate their own results to those already described in the literature. For example, treadmill-determined values for VO2max were 53.7 ± 8.9 and 45.6 ± 6.6 ml·kg–1·min–1 for men and women, respectively (P < 0.01), which could be compared with values from a similar undergraduate United Kingdom population (25) or with elite endurance athletes (e.g., Refs. 9 and 21). Academic staff members could also suggest examining the relationship between 20-m MST performance and VO2max (in this case, r = +0.79, P < 0.01; Table 2) compared with earlier work.

The VO2max was determined, for the same individual, during both cycle and treadmill ergometry, and thus two Pearson product moment correlations were derived: r = +0.73 (cycle) and r = +0.79 (treadmill) (Table 2). The difference in the strength of the correlation coefficient with endurance performance led directly to a discussion with respect to the specificity of laboratory-based ergometric tests.

Conceptually, it was useful to incorporate a common measure of exercise economy for men and women, specifically, the oxygen cost at 2.78 m/s during treadmill exercise versus performance (r = +0.00, not significant; Table 2). This emphasized to students that exercising at the same absolute treadmill speed (or power output) has little relationship with performance because both men and women at the same absolute power output use similar amounts of oxygen, 35.2 ± 3.1 (men) and 35.3 ± 4.7 ml·kg–1·min–1 (women; not significant; Table 1). However, students were encouraged to express the "absolute" VO2 (measured in ml·kg–1·min–1 in this case) as a relative measure (i.e., relative to the measured VO2max for that individual). With that modification, the strength of the correlation (now the "relative exercise economy") (9) with performance increased to r = –0.63 (P < 0.01) (Table 2) and also provided a further discussion point.

The incorporation of measures at reference blood lactate concentrations of 2.0 and 4.0 mmol/l also emphasized the theoretical (lecture) delivery of module content. The results of the present study reinforced those of many earlier studies (12, 13), namely, those individuals that could run at high speeds with little lactate accumulation tended to record better endurance performance (Table 2). The power output at ventilation threshold was modestly correlated with performance; in contrast to earlier studies (e.g., Ref. 23), this could have been mainly due to methodological issues with respect to identifying a "threshold" power output (e.g., Ref. 16). a point raised by students during the seminar/discussion periods.

Integration of lecture program material and practical data during high-intensity exercise.
A simple starting point for seminar discussion was to ask students to compare power output values between men and women. Students could statistically compare means to identify any difference between men and women for both absolute (in W) and relative power output values (in W/kg; Table 3). Students were encouraged to plot their data as a scatter graph (Microsoft Excel), produce the corresponding Pearson product moment correlation coefficient, and provide a reasoned argument for their analysis. Students quickly identified measures that took into account body mass (Table 4 and Fig. 2); these relative measures showed the strongest relationship with high-intensity exercise performance, which led to a discussion of the underlying physiology behind the relationship. The very fact that students generated their own data led to interesting discussions as to why their particular results were similar to or different from those reported in the literature. After practicing data analysis in the seminar, students were sent the summary class data sheet electronically, which acted as their results (raw data) for subsequent analysis and the eventual production of a word-processed laboratory report.


Figure 2
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  		Fig. 2. Mean power output (in W/kg) determined during a 30-s cycle ergometer sprint and high-intensity shuttle run performance (HIST) determined as the geometric mean (GM). n = 48.

 
Conclusions
In summary, module evaluation over the preceding 3 yr consistently revealed that students found the series of linked laboratory work challenging and rewarding in helping their understanding of the concepts dealt with in the module. The practical work fulfilled the aims of the module, namely, students performed "classic" experimental protocols in sports/exercise science and used their own data to investigate the relationships between laboratory-determined parameters and human performance. The same series of practical work could be used to examine, in greater depth, e.g., male versus female differences in the exercise response, the concept of "relative exercise intensity," or the reliability/validity data of ventilatory threshold determinations.

Received for publication March 8, 2007. Accepted for publication August 3, 2007.


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