Enhancing energy balance education through ...

Original Research

Enhancing energy balance education through physical education and selfmonitoring technology

European Physical Education Review 1–13 ª The Author(s) 2015 Reprints and permission: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/1356336X15588901 epe.sagepub.com

Senlin Chen Department of Kinesiology, Iowa State University, Ames, IA, USA

Xihe Zhu Department of Human Movement Sciences, Old Dominion University, VA, USA

Youngwon Kim MRC Epidemiology Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK

Gregory Welk Department of Kinesiology, Iowa State University, Ames, IA, USA

Lorraine Lanningham-Foster Department of Food Science and Human Nutrition, Iowa State University, Ames, IA, USA

Abstract Schools are positioned to play a key role in nurturing students with knowledge and behaviours associated with healthful living. Our study examined the effects of an intervention on energy balance (EB) knowledge. Twelve 6th and 7th grade classrooms (n ¼ 140) were assigned to receive either two standardised lessons on EB or a combined intervention that featured the same EB lessons, integrated with self-monitoring technology. EB knowledge was pre- and post-measured using a standardised written test, while the situational interest was measured at the end of experiment. Repeated measure analysis of variance and multivariate analysis of variance were conducted, to capture the differences in EB knowledge by time and group, and situational interest by group, respectively. Both groups significantly enhanced EB knowledge over time (F1,112 ¼ 11.85; p ¼ .001; 2 ¼ .10), but the combined group demonstrated a greater increase (F1,112 ¼ 5.36; p ¼ .02; 2 ¼ .05). An item-by-item mean comparison of EB knowledge and correct percent scores confirmed the above result (i.e. combined group versus education group: 7% versus 2% EB knowledge increase).The two groups were equally motivated to participate in the experiment,

Corresponding author: Senlin Chen, Department of Kinesiology, Iowa State University, 255 Forker Building, Ames, IA 50011, USA. Email: [email protected]

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European Physical Education Review

showing similar levels of total interest (education group: M/SD ¼ 4.00/.68; combined group: M/SD ¼ 4.17/.74; p ¼ .18). The research findings and their implications are discussed. Keywords Adolescents, education, energy balance, learning, physical education, situational interest, technology

Introduction Schools are positioned to play a key role in nurturing students with knowledge and behaviours associated with healthful living (Institute of Medicine of The National Academies, 2013). Energy balance (EB), the balance between the amount of energy we consume and spend, largely impacts the fluctuation of body weight (Katz, 2011). EB knowledge refers to the concepts, principles and strategies that relate to the balance between an individual’s energy intake and energy expenditure: The scientific mechanism underlying weight fluctuation (Chen and Chen, 2012; Katz, 2011). Previous studies report that understanding of EB-related knowledge is positively associated with healthful living behaviours, such as regular exercising and healthy eating (Blanchette and Brug, 2005; Nelson et al., 2009); however, it was also shown that adolescents have a deficiency in EB knowledge, especially the higher-order, relational knowledge (Chen and Chen, 2012; Manore et al., 2014; Nelson et al., 2009). Given the importance of the effect of EB knowledge on long-term weight status, deliberate research and practice focusing on this knowledge gap is warranted in schools (Manore et al., 2014; Shook et al., 2014). Numerous school-based intervention programmes have demonstrated efficacy in promoting positive weight management (Kriemler et al., 2011); however, many of these intervention programmes have limited effects on adherence or are contingent upon a high cost, for broader dissemination (Wallhead and Buckworth, 2004). School physical education (PE) is tasked with teaching students knowledge, skills and dispositions with which they can make rational decisions for well-being and performance (Ennis, 2007a). PE curricula that are coherent in nature and make good connections between what is learned in class and students’ lived experiences have good potential to foster healthy-living behaviours (Ennis, 2007a). Furthermore, contemporary children and adolescents live in an era enriched by interactive technology. Using relevant modern technology in and out of classroom can facilitate students’ learning processes and outcomes; and is often advocated by teachers (Gibbone et al., 2010). Intervention programmes that characterise both systematic education and modern technological tools are warranted, to advance EB education in adolescents. The curriculum encompasses the planned sequence of what students are to learn, how students acquire that learning, and how students’ learning is verified (Kelly and Melograno, 2004). Welldesigned PE curricula can provide systematic learning experiences that equip students with the necessary knowledge and motivation for healthful living (Sun et al., 2012). A promising PE curriculum for enhancing students’ health-related fitness knowledge is the ‘Science, PE and Me’ (SPEM) curriculum; which promotes learning through active, meaningful movement tasks (Sun et al., 2012). In spite of its focus on cognitive learning, SPEM lessons have been shown to promote as much physical activity as traditional PE lessons (Chen et al., 2007). While the SPEM curriculum was developed for elementary school PE, the lessons can be easily adapted for higher grades. This study adapted the SPEM lessons that focused on EB education, in order to suit the needs of middle school students. The Methods section describes more details about the adapted lessons.


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Modern educational technologies have proven facilitative in academic classrooms (Judson, 2006), as well as in gymnasia (Martin, 2003). Gibbone et al. (2010) surveyed 616 secondary PE teachers and found that most of the teachers reported positive attitudes towards technologies, but indicated a variety of barriers (e.g. limited budget, large class size and training needs) when putting them into practice. From the students’ perspective, technology is an amenity that motivates them for higher engagement. Studies show positive health and learning outcomes from technologies such as active video games (Sun, 2012, 2013) and smartphone applications (Lubans et al., 2014). Objective self-monitoring devices provide potential for increasing awareness about EB. The SenseWear armband (SWA) monitor (BodyMedia1, Pittsburg, PA, USA) provides a particularly promising platform, because it provides accurate estimates of energy expenditure and computed estimates of EB, when food logs are recorded. In a randomised controlled trial, the SWA was found to be efficacious in helping obese adults lose weight (Shuger et al., 2011). The mechanism underlying its effectiveness was attributed specifically to the electronic feedback that the users received from the SWA; which in turn, enabled them to choose and engage in behaviours leading to negative EB (Shuger et al., 2011). The utility of the SWA was investigated with adolescents in PE (Chen et al., 2014). As a novel technology (coupled with a portable diet journal), the technology was perceived as interesting; but did not render significant improvement in EB knowledge, due to the limited intervention period (i.e. 1 week). The study points out the need to combine the novel technology with meaningful educational lessons (Chen et al., 2014), so this is the focus of the present study; however, before fully implementing this type of approach on a large scale, it is important to understand the students’ level of motivation (Chen, 2013; Sun, 2013; Wallhead et al., 2014). In one study, motivation was specifically examined from the perspective of situational interest (Chen et al., 1999). Situational interest is a motivator activated in a situation, namely, the appealing effect of a learning task on the learner (Chen et al., 1999). Previous research identified five sources from which situational interest is derived in PE settings: novelty, challenge, attention demand, exploration and instant enjoyment, which are defined as follows (Chen et al., 1999; Sun et al., 2008): Novelty refers to the deficiency between information known and unknown by the learner; Challenge is defined as the level of difficulty relative to the learner’s personal ability. An optimal level of challenge, being neither too hard nor too easy, is believed to entice high situational interest; Attention demand is the concentrated cognition and mental energy required in learning an activity. A learning experience that demands and draws high student attention indicates high situational interest; Exploration is conceptualised as the learning aspects that drive the learner to explore and analyse their learning content. Similar to attention demand, a learning task worthy of exploration tends to energize students for enhanced learning; and Instant enjoyment refers to the characteristics that lead the learner to an instant positive feeling of being satisfied. Taking into account these sources of situational interest defined above, students’ total interest can be determined. In general, the total interest represents students’ overall interest in the given learning task or experience. The integration of the PE curriculum and modern technology offers potential to promote students’ healthful-living knowledge. This study directly evaluates the additive benefit of incorporating technology to advance education about EB. The primary purpose of the study was to evaluate the effect of


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the intervention on students’ EB knowledge. We hypothesized that the PE lessons would increase EB knowledge, but that gains would be larger with the supplemental inclusion of additional technology. Given the novelty of the two EB lessons and the technological package, it was further hypothesized that students receiving these experiences would show similar levels of situational interest.

Methods Participants and settings This study was conducted in two rural middle schools, located in a mid-western state in the USA, between 2013 and 2014. The two schools were the only middle schools in their respective districts: Both offered 5th to 9th grade education, with three classes per grade level. Class sizes for the 6th and 7th grade classes ranged from 20 to 26 individuals. PE lessons were primarily taught in a multipurpose gymnasium (regulation basketball court) in both schools, during the data collection period. A small number of lessons were taught in the schools’ fitness/wrestling room or their outside playground. We conducted the study in direct partnership with the schools, with the lessons provided by their PE teachers; however, separate consent was obtained from students, because the assessments were not part of the standard PE curriculum. For recruitment, the researchers introduced the study (e.g. purpose, procedures, benefits, harms, etc.) to all 6th and 7th grade students in PE, and reminders were sent via PE teachers in the following 2 weeks. A total of 140 students (Age: Mean (SD) ¼ 12.25 (.73); Male: n ¼ 48; Body mass index (BMI): Mean (SD) ¼ 22.01 (5.07)) provided written parental consent. The sample was predominantly Caucasian (n ¼ 120 or 86%), matching the student ethnic composition of the two school districts. The sample had higher enrolment among the 6th graders (n ¼ 89) than the 7th graders (n ¼ 51). The 12 classes ranged in size from 4–16 students per class (Median ¼ 6 students). Following the quasi-experimental design, the classes were randomly assigned into two groups: The education group (n ¼ 62) or the combined group (n ¼ 78). The study was approved by the Institutional Review Board (IRB) at these researchers’ university.

EB education’s lessons development The EB education lessons were developed based on the existing SPEM curriculum (Ennis and Lindsay, 2008). The original SPEM lessons were standardised to be 30 minutes long, each. In the present study, the EB education-related lessons from the SPEM curriculum were expanded to 50 minutes, for use in middle school. The movement tasks were also modified to be more physically active and game-like. The two adapted EB lessons provided tasks that enabled students to learn the essential EB concepts and knowledge. For example, in the ‘Activity Medley’ task, students were asked to choose and participate in a series of physical activities at different intensities, for a certain period of time, to balance the calories derived from a selected serving of food (e.g. an apple). From this task, the students were afforded the opportunity to make connections between foods and beverages, and conventional physical activities in the format of energy (in Kcal); and how to achieve a balance between energy intake and expenditure. Both lessons further employed a pedometer and a problem-solving handout, to facilitate engagement and learning. The lessons were validated by an expert panel, including two experienced PE teachers and two researchers. The PE teachers of the two participating schools were invited to review and comment on the two lessons, for a feasibility check 2 weeks before the intervention. Minor revisions were made before implementation, based upon the two teachers’ comments.


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Instrumentation Energy balance knowledge. EB knowledge was measured pre- and post-intervention by a standardised written test (Nelson et al., 2009). The EB knowledge test has 15 multiple-choice questions. For example, Q12 asks: ‘How many calories does the average teenage boy need to consume every day?’ The answer choices include: ‘(a) 100–999; (b) 1000–1999; (c) 2000–3999 (correct answer); (d) 4000–6000; (e) > 6000.’

Each item was scored to be either 1 (for a correct answer) or 0 (for an incorrect answer). The sum of the correct responses was obtained, to reflect the students’ performance on the test. The test had already demonstrated sound content validity and internally-consistent reliability (Nelson et al., 2009). Situational interest. We measured situational interest using the ‘Situational Interest Scale’ (SIS) (Chen et al., 1999). The SIS consists of 24 items, of a 5-point Likert type (5 ¼ strongly agree to 1 ¼ strongly disagree). The responses reflect the students’ perceptions of novelty, challenge, attention demand, exploration intention and instant enjoyment. For example, an item that measures perceived novelty is stated as follows: ‘This is a new-fashioned (sic) activity for me to do’. The students were instructed to reference the experience received as the ‘activity’, while completing the SIS. The SIS had previously displayed acceptable construct validity and internal consistency reliability (Chen et al., 1999).

Procedures for pilot intervention The pilot intervention evaluated the utility of two experiential EB education lessons, when used in combination with self-monitoring technology. Two specific lessons were provided to students in all classes. The two lessons were taught by the PE teachers in their respective schools. One trained observer was sent to the schools to observe the implementation of each lesson and check its fidelity. Training took place in a laboratory on the university campus, where the observer was instructed to read carefully the two lesson plans, and then present to the lead researcher how the lessons would unfold sequentially. The trainee was further instructed on how to unobtrusively observe the teaching and learning process and take notes of the congruence, as well as deviations, between the lesson plans and the ongoing teaching/learning process. One-half of the classes received the supplemental technology intervention. Before the intervention began, the students were given the opportunity to familiarize themselves with the technological tools (i.e. the SWA and the diet journal) for 1 day. This process was important, to minimize students’ reactivity to the newly-introduced items. In Week 1, upon familiarisation, the students used the SWA and the diet journal for 7 consecutive days. Each student was distributed, and instructed to use, a set of 12 measuring cups and spoons; to help determine the serving sizes of the foods and beverages that were documented on the dietary journal (breakfast, lunch, snack and dinner) for Week 1 and Week 4.


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In Week 2, a trained researcher met the students in the school media centre, where an individualized written report of daily energy expenditure (obtained from the SWA) was shared and explained to each student; and these students were instructed on how to enter the diet data from their journal into the online ‘Food Tracker’ (www.supertracker.usda.gov/foodtracker.aspx). This website allowed users to convert nutrition entries into numerical data in calories (Kcal), which was helpful for the students to become aware of the energy contained in the diet. In Week 3, the students were taught the EB lessons. Finally, in Week 4, they used the technology package for another 7 consecutive days.

Procedures for data collection Data collection procedures are described in detail chronologically, below. First, the students were informed of the group membership of their classes and were pre-tested on their EB knowledge along with collection of their demographic variables (age, gender and ethnicity). The combined group was distributed with SWAs and diet journals, and received instructions on how to use the two tools. Second, in the middle of Week 1, the students were provided with personalised informational feedback on the ongoing usage of the SWA and diet journal. The feedback process followed a standardised procedure, pre-established by the researchers. Specifically, a trained data collector gathered the students, one after another, to a gymnasium corner; and there retrieved the activity data for each student through a synchronized display device (Model DD100; BodyMedia, Pittsburgh, PA, USA). The summary data from the SWA, including total energy expenditure, number of steps and minutes of physical activity gained on the previous day were personally shared and explained. Then, the data collector checked each student’s diet journal for accuracy, and reminded each one to persistently keep the diet journal (to improve recall accuracy). The SWA and diet journal were collected at the end of Week 1. In Week 2 and/or Week 3, both groups received the two EB lessons. In Week 4, the combined group was re-distributed with the technology package for the second round of EB monitoring. Students of the education only and the combined (with technology) groups were measured on their EB knowledge and situational interest, at end of Week 4.

Data analysis To determine the effects of the two lessons and the technology package on EB knowledge, a 2-way repeated measure analysis of variance (RM ANOVA) was conducted, by specifying the post- and pre-test EB knowledge scores as the dependent variables, while time (baseline pre- versus postintervention) and group (education only versus combined (with technology)), as independent variables. Furthermore, an item-by-item mean comparison of the correct percent score for EB knowledge was conducted, to test the actual time and group differences on the questions at item level. In addition, to compare the level of situational interest (i.e. a motivation indicator) between the two groups (education versus combined), a multivariate analyses of variance (MANOVA) was conducted. If the MANOVA detected significant results, then univariate analyses (i.e. ANOVA or Welch’s analysis, if there were heterogeneous variances) were subsequently operated, to capture specific differences in situational interest constructs (i.e. novelty, challenge, attention demand, exploration intention and instant enjoyment), by group. We employed SPSS 22.0 (The International Business Machines (IBM) Corporation, Armonk, New York, USA) was employed for the data analyses, with a 95% CI (a ¼ .05).


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Figure 1. EB knowledge scores by group (education group) and time (pre-test versus post-test). RM ANOVA detected significant time (F1,112 ¼ 11.85; p < .01; 2 ¼ .10) and time*group (F1,112 ¼ 5.36; p ¼ .02; 2 ¼ .05) effects (the combined group showed greater increase) for EB knowledge score. EB: energy balance; RM ANOVA: Repeated Measure Analysis of Variance.

Results The field observations made by the trained observer showed good fidelity for the PE teachers to implement the two EB lessons. The teachers taught the lessons with minor deviations from the lesson plans. For example, a 6th-grade teacher taught one lesson in the school’s wrestling room, because the regular multi-purpose gymnasium was used by another teacher. The other deviation made by teachers was the use of movement tasks for the ‘Activity Medley’ game. Two teachers replaced less familiar tasks with tasks students had previously been exposed to. This modification was acceptable, because the replacements were similarly active as the original, in which students were still able to learn and make sense of the concept of exercise intensity, by experiencing distinct physical exertions. Figure 1 illustrates the comparative results of the EB knowledge score by group and time. On average, the students performed moderately on the knowledge test at baseline (Mean (SD) ¼ 5.98 (1.91); a 40% correct response) and the final (Mean (SD) ¼ 6.58 (1.93); a 44% correct response) measurements. At baseline, the education (only) group had a slightly higher EB knowledge performance (Mean (SD) ¼ 6.38 (1.99); a 43% correct response) than the combined group (Mean (SD) ¼ 5.65 (1.78); a 38% correct response). Both groups gained knowledge from the specific lessons; but the combined group (Mean (SD) ¼ 6.59 (1.97); a 44% correct response; Cohen’s d ¼ .50) had a greater increase than the education group (Mean (SD) ¼ 6.57 (1.89); a 44% correct response; Cohen’s d ¼ .10). The ‘Box’s M’ test of equality of covariance matrices did not reject the null hypothesis (Box’s M ¼ 2.41; p ¼ .50). The RM ANOVA showed significantly the main effect for time (Wilks’ ¼ .90, F1,112 ¼ 11.85; p ¼ .01; 2 ¼ .10) and group by time interaction effect (Wilks’ ¼ .95, F1,112 ¼ 5.36; p ¼ .02; 2 ¼ .05). An item-by-item mean comparison of the correct percentage scores for EB knowledge by time and group is shown in Table 1. The education group had an average 2.0% increase in EB knowledge, with all but five items (i.e. Q1, Q2, Q3, Q5 and Q15) showing a positive increase.


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61 61 60 61 60 61 61 61 61 61 60 59 60 61 60 59– 61

n

83.6% 77.0% 30.0% 45.9% 20.0% 36.1% 88.5% 34.4% 31.1% 27.9% 43.3% 40.7% 70.0% 49.2% 66.7% 49.6%

M

37.3% 42.4% 46.2% 50.2% 40.3% 48.4% 32.1% 47.9% 46.7% 45.2% 50.0% 49.5% 44.8% 50.4% 47.5% 45.3%

SD 60 60 60 59 58 60 58 60 60 60 59 60 60 60 59 58– 60

n 81.7% 76.7% 23.3% 47.5% 10.3% 38.3% 93.1% 41.7% 41.7% 31.7% 52.5% 48.3% 72.0% 56.7% 59.3% 51.7%

M

Post-test

39.0% 42.7% 42.7% 50.4% 30.7% 49.0% 25.6% 49.7% 49.7% 46.9% 50.4% 50.4% 43.5% 50.0% 49.5% 44.7%

SD –1.9% –0.4% –6.7% 1.6% –9.7% 2.3% 4.6% 7.2% 10.5% 3.8% 9.2% 7.7% 2.0% 7.5% 7.3% 2.0%

Mdiff

a Q1-Q15 denote question items 1–15 of the knowledge test (Nelson et al., 2009). M: Mean; n: number of individuals in the sample size; SD: standard deviation.

Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12 Q13 Q14 Q15 All

Itemsa

Pre-test

Education Group

Table 1. Item by item knowledge correct percentage score by group.

76 76 76 75 73 76 75 75 76 75 75 74 75 75 74 74–76

n 72.4% 57.9% 31.6% 45.3% 11.0% 39.5% 73.3% 40.0% 40.8% 18.7% 29.3% 37.8% 64.1% 52.0% 60.8% 45.0%

M

Pre-test

45.0% 49.7% 46.8% 50.1% 31.5% 49.2% 44.5% 49.3% 49.5% 39.2% 45.8% 48.8% 47.4% 50.3% 49.2% 46.4%

SD 71 71 71 71 71 71 71 70 71 71 71 71 71 71 70 70–71

n 87.3% 67.6% 31.0% 50.7% 18.3% 33.8% 90.1% 47.1% 40.8% 33.8% 33.8% 59.2% 71.0% 42.3% 72.9% 52.0%

M

Post-test

Combined Group

33.5% 47.1% 46.6% 50.4% 39.0% 47.6% 30.0% 50.3% 49.5% 47.6% 47.6% 49.5% 45.2% 49.7% 44.8% 45.2%

SD

15.0% 9.7% 0.6% 5.4% 7.4% 5.7% 16.8% 7.1% 0.1% 15.1% 4.5% 21.3% 6.9% 9.7% 12.0% 7.0%

Mdiff

16.9% 10.1% 6.1% 3.8% 17.0% 7.9% 12.2% 0.1% 10.5% 11.3% -4.7% 13.7% 4.9% 17.2% 19.4% 5.0%

Group Mdiff

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Table 2. Situational interest constructs by group. Education Group

Combined Group

Situational interest constructs

n

Mean

SD

n

Mean

SD

Exploration Enjoyment Novelty Attention Challenge Total interest

60 59 59 60 60 60

3.98 3.83 4.24a 4.26 3.87b 4.00

.63 .65 .63 .69 .91 .68

67 69 69 69 68 69

3.79 3.94 3.97a 4.01 3.22b 4.17

.90 .82 .83 .92 1.20 .74

a

p < .05. p < .01. Results from testing the second hypothesis. n: number of individuals in the sample size; SD: standard deviation b

In comparison, the combined group demonstrated an average 7.0% increase in EB knowledge, with all but three items (Q3, Q6 and Q14) showing a positive increase. The combined group had 5.0% more of an increase in knowledge score than the education group. Before testing the differences in situational interest between groups, the Box’s M test for equality of variance-covariance matrices was performed, which rejected the null hypothesis (Box’s M ¼ 57.47; p < .01). Therefore, the Pillai’s Trace test, as a more stringent criterion, was adopted for the MANOVA. The MANOVA showed a significant group difference (Pillai’s Trace ¼ .19; F ¼ 4.42; p < .01; 2 ¼ .19) and generated results for the univariate tests of between-subject effects. The comparative results for situational interest constructs by group are presented in Table 2. Both groups demonstrated relatively high total interest (4.09 on the 5-point scale) and high scores for other situational interest constructs (Mean ranged from 3.53 for the level of challenge to 4.13 for attention demand). In comparison, the education group had higher levels of perceived novelty, challenge, attention demand and exploration; but lower levels of instant enjoyment and total interest. The Levene’s tests showed homogeneous variances for novelty, attention demand and interest; but heterogeneous variances for exploration (p ¼ .01), enjoyment (p ¼ .01) and challenge (p ¼ .01). The follow-up univariate analyses (i.e. ANOVAs or Welch’s tests for groups with homogeneous or heterogeneous variances, respectively) revealed significant results for challenge (Welch Statistic1,123 ¼ 12.04; p < .01) and novelty (F1,126 ¼ 3.94; p < .05).

Discussion This pilot intervention study evaluated the effects of two EB lessons, the second used in combination with a self-monitoring technology package, on adolescent students’ EB knowledge. The students in both groups gained EB knowledge due to their exposure to the experiences. Students who received the combined experience of education and technology demonstrated a greater increase in EB knowledge than the students whom received the base education programme (Cohen’s d ¼ .40). The two groups had similar situational interest, but the education group perceived a higher challenge but lower novelty than the combined group. These findings and their implications are discussed in the following sections.


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Enabling students to learn EB knowledge The importance of educating youth to live an energy-balanced lifestyle is documented in the literature (Chen and Chen, 2012; Nelson et al., 2009). Surprisingly, formal education that is centred on teaching the principles of EB knowledge is uncommon in schools. Ennis (2007a) asserted that PE programmes should provide enriched learning experiences, for students to make connections among learning content, context, and the students’ past and current lived experience. Learning EB knowledge through authentic, active experiences in PE classes would make students’ acquisition of that knowledge more meaningful and beneficial, and could contribute to better long-term weight control practices. In this study, the researchers tested the utility of two adapted SPEM lessons, as well as the additive benefits from a personalized technological package designed to help students construct the meaning and importance of EB for healthful living. Through the lessons, the students, especially those whom also received the technological package, increased their EB knowledge (about a 7.0% increase; Cohen’s d ¼ .50). The above findings indicated that receiving a purposefully-designed intervention (technology and education) was effective in enhancing EB knowledge. These findings support previous research conclusions that the PE curriculum (e.g. SPEM) is capable of inducing a more superior knowledge gain than conventional PE (Sun et al., 2012), while also actively engaging students in physical activities (Chen et al., 2007). Our finding also further extends previous evidence (Shuger et al., 2011), in that the use of the SWA coupled with relevant ancillary materials (e.g. diet journal, SuperTracker website, informational feedback, etc.) is able to provide adolescent users with important electronic feedback. Taken together, the combination of carefully-tailored schooling (e.g. thematic EB lessons) and unofficial daily actions (e.g. tracking EB using technological tools) enabled the students to acquire meaningful learning experiences and to achieve them both in and out of the classroom (Ennis, 2007a). The structured, personalised experiences provided the students with opportunities to track their daily energy flux, make the connection between exercising and dietary behaviours and energy (in Kcal), and to comprehend the implication of such knowledge for weight management. Changing a sedentary lifestyle to an active lifestyle is challenging; and it requires concerted efforts, using more comprehensive, ecological approaches (Seabra et al., 2013). Ennis identified that many children and adolescents hold a misconception or naı¨ve conception of exercise and their body, and that these misconceptions are likely to guide inappropriate decision-making related to physical activity participation (Ennis, 2007b). To induce behavioural change for healthful-living habits, a radical restructuring of the learner’s mental model may be required, which often entails higher-order knowledge learning through coherent curricula (Ennis, 2007b). It is hoped that EB knowledge constructed through the intervention experiences utilised in the present study will enable students to make more rational decisions for healthful living (e.g. weight management). Nevertheless, more research studying the association between deep learning and behavioural change is warranted, to advance knowledge in this research area.

Situational interest in the EB-related experiences Interventions in PE and the school context should take into account the students’ motivation (Chen et al., 2012). In this study, the situational interest was gauged to evaluate students’ reaction to the interventions. Previous research identified that an interesting educational context can foster students’ motivation for physical activity participation and learning strategies (Shen and Chen, 2007; Subramaniam, 2010). As observed in the present study, both the EB lessons and the technology package were perceived as interesting (i.e. novel, exploratory, attention-demanding and overall


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interesting). This phenomenon is consistent with those observed in other studies that employ new modern technologies (Gao et al., 2013; Sun, 2013) or innovative curricula (Sun et al., 2012) in PE. In other words, students are inclined to demonstrate a high situational interest when being introduced to new experiences. The two groups showed different levels of perceived challenge and novelty (two sources for situational interest); that is, the education group reported a higher challenge, but lower novelty, than the combined group. While the two EB lessons were also perceived as novel, the technology package provided additional novelty for the students. In addition, while both groups demonstrated moderate levels of perceived challenge about the experiments, the perception of challenge about their experience in the combined group was lower (Mean (SD) ¼ 3.22 (1.20)), which appeared to be more desirable, from the motivational perspective. Compared to experiences with either too high or too low of a challenge, a learning task or experience with a moderate level of challenge is optimal to facilitate students’ motivation and continuous learning (Mitchell, 2009). While positive intervention effects were observed, it is important to acknowledge some limitations with this study. The first limitation is that the education experience only included two lessons. The two lessons were carefully adapted from the evidence-based SPEM curriculum (Ennis and Lindsay, 2008) and validated by an expert panel, but the development of additional lessons would provide a more coherent educational experience. The knowledge increase as a result of receiving the two lessons was smaller, compared to the knowledge increase observed in the group whom received both the two lessons and a technological package; however, it is important to recognize that this knowledge increase was achieved via two brief lessons. Furthermore, although the knowledge gain was greater in the combined group, the combined group received considerably more and longer duration of experiences than did the education-only group. Second, our study was conducted with a relatively small sample of students in two suburban schools. Studying a larger sample with more diverse characteristics would increase the generalisability of these findings. Third, a pedometer (per student) was utilised as a required ancillary tool of the SPEM lessons, by the education group. Despite its simplistic feature (with one single ‘reset’ button), the pedometer might have added a minor technological effect to the experiment. Modern PE instruction is often equipped with some educational technology (Gibbone et al., 2010). Students are often accustomed to having access to useful technological tools, such as a pedometer being incorporated into their PE classes.

Conclusions The epidemic of childhood obesity (Ogden et al., 2010) has increased attention on the importance of implementing effective school-based strategies to educate youth with the knowledge and skills for conscious weight management (Institute of Medicine of The National Academies, 2013). The present study revealed the positive effect of two EB lessons and a technology package that involved a physical activity monitor (i.e. SWA), a portable diet journal and several ancillary materials to enable adolescents to learn the EB knowledge. Although the EB lessons were standardised for research purposes, the lesson plans can be locally modified to allow for a teachers’ improvisation. The effect of these two lessons on EB knowledge supports the importance of purposefully teaching this knowledge to students. It is recommended that school curricula (PE and/or health education) incorporate and convey EB knowledge to students in a coherent manner (i.e. offer a whole unit of EB instruction). The other major finding of the study supported that students’ interaction with modern technology, formally (along with class activities) or informally, can lead to knowledge enhancement. Although


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the SWA utilized in this study was expensive (as a research device), affordable consumer-based tools with similar accuracy can be adopted for schools and families to utilize (Lee et al., 2014). These tools, in conjunction with a diet journal and other ancillary materials (e.g. SuperTracker website) can help students to learn how to live an energy-balanced lifestyle, in and out of the classroom. References Blanchette L and Brug J (2005) Determinants of fruit and vegetable consumption among 6–12 year-old children and effective interventions to increase consumption. Journal of Human Nutrition and Dietetics 18(6): 431–443. Chen A (2013) Top 10 research questions related to children’s physical activity motivation. Research Quarterly for Exercise and Sport 84(4): 441–447. Chen A, Darst PW and Pangrazi RP (1999) What constitutes situational interest? Validating a construct in physical education. Measurement in Physical Education and Exercise Science 3(3): 157–180. Chen A, Martin R, Sun H, et al. (2007) Is in-class physical activity at risk in constructivist physical education? Research Quarterly for Exercise and Sport 78(5): 500–509. Chen S and Chen A (2012) Youth physical activity behavior and energy-balance knowledge: An expectancyvalue perspective. Journal of Teaching in Physical Education 31(4): 329–343. Chen S, Chen A and Zhu X (2012) Are K-12 learners motivated in physical education? A meta-analysis. Research Quarterly for Exercise and Sport 83(1): 36–48. Chen S, Zhu X, Welk G, et al. (2014) Using Sensewear armband and diet journal to promote adolescents’ energy balance knowledge and motivation. Journal of Sport and Health Science 3(4): 326–332. Ennis CD (2007a) Curricular coherence: A key to effective physical activity programs. In: HeikinaroJohansson P and McEvoy E (eds) The Role of Physical Education and Sport in Promoting Physical Activity and Health. Jyvaskyla, Finland: AIESEP, pp.10–25. Ennis CD (2007b) Defining learning as conceptual change in physical education and physical activity settings. Research Quarterly for Exercise and Sport 78(3): 138–150. Ennis CD and Lindsay E (2008) Science, PE, and Me! Curriculum. Self-published. Department of Kinesiology, University of Maryland, College Park, MD. Gao Z, Hannan P, Xiang P, et al. (2013) Video game-based exercise, Latino children’s physical health, and academic achievement. American Journal of Preventive Medicine 44(3): S240–246. Gibbone A, Rukavina P and Silverman S (2010) Technology integration in secondary physical education: Teachers’ attitudes and practice. Journal of Educational Technology Development and Exchange 3(1): 27–42. Institute of Medicine of The National Academies (2013) Educating the Student Body: Taking Physical Activity and Physical Education to School. Washington, DC: National Academies Press. Judson E (2006) How teachers integrate technology and their beliefs about learning: Is there a connection? Journal of Technology and Teacher Education 14(3): 581–597. Katz DL (2011) Unfattening our children: Forks over feet. International Journal of Obesity 35: 33–37. Kelly LE and Melograno VJ (2004) Developing the physical education curriculum: An achievement-based approach. Champaign, IL: Human Kinetics. Kriemler S, Meyer U, Martin E, et al. (2011) Effect of school-based interventions on physical activity and fitness in children and adolescents: A review of reviews and systematic update. British Journal of Sports Medicine 45(11): 923–930. Lee JM, Kim Y and Welk GJ (2014) Validity of consumer-based physical activity monitors. Medicine and Science in Sports and Exercise 46(9): 1840–1848. Lubans DR, Smith JJ, Skinner G, et al. (2014) Development and implementation of a smartphone application to promote physical activity and reduce screen-time in adolescent boys. Frontiers in Public Health 2: 42. Epub ahead of print 20 May 2014. DOI: 10.3389/fpubh.2014.00042. Manore MM, Brown K, Houtkooper L, et al. (2014) Energy balance at a crossroads: Translating the science into action. Journal of the Academy of Nutrition and Dietetics 114(7): 1113–1119.


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Author biographies Senlin Chen is an Assistant Professor of Kinesiology at Iowa State University. Chen specializes in pedagogical kinesiology. His active research is mostly focused on physical education curriculum, learner motivation, and learning. Xihe Zhu is an Associate Professor in the Department of Human Movement Sciences at Old Dominion University. Youngwon Kim is a post doctoral research associate in the MRC Epidemiology Unit, School of Clinical Medicine at the University of Cambridge. Gregory Welk is a Professor in the Department of Kinesiology at Iowa State University. Lorraine Lanningham-Foster is an Associate Professor in the Department of Food Science and Human Nutrition at Iowa State University.
