Joo-Han Cho; Sook-Bae Kim; Soon-Kyung Kim; Mi-Hyun Kim; Gap-Soo Kim; Se-Na Kim; So-Young Kim; Jeong-Weon Kim

doi:10.5720/kjcn.2013.18.4.299

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Development of 'Children's Food Avatar' Application for Dietary Education: Joo-Han Cho, Sook-Bae Kim, Soon-Kyung Kim, Mi-Hyun Kim, Gap-Soo Kim, Se-Na Kim, So-Young Kim, Jeong-Weon Kim; Korean Journal of Community Nutrition 2013;18(4):299-311.
DOI: https://doi.org/10.5720/kjcn.2013.18.4.299
Published online: August 31, 2013

Major of Elementary Science & Technology Education for Life, Graduate School of Seoul National University of Education, Seoul, Korea.

¹Department of Food Science & Human Nutrition, Chonbuk National University, Jeonju, Korea.

²Department of Food Sciences & Nutrition, Soonchunhyang University, Asan, Korea.

³Department of Food and Nutrition, Kangwon National University, Samcheok, Korea.

⁴Department of Computer Education, Seoul National University of Education, Seoul, Korea.

⁵Department of Agrofood Resources, National Academy of Agricultural Sciences, RDA, Suwon, Korea.

⁶Department of Science & Technology Education for Life, Seoul National University of Education, Seoul, Korea.

Corresponding author: Jeong-Weon Kim, Department of Science & Technology Education for Life, Seoul National University of Education, Seochojoongang-ro 96, Seocho-gu, Seoul 137-742, Korea. Tel: (02) 3475-2516, Fax: (02) 3475-2263, kimjwe@snue.ac.kr

• Received: November 16, 2012 • Revised: February 9, 2013 • Accepted: July 31, 2013

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Abstract
NOTES
REFERENCES

Abstract

An educational application (App) called 'Children's Food Avatar' was developed in this study by using a food DB of nutrition and functionality from Rural Development Administration (RDA) as a smart-learning mobile device for elementary school students. This App was designed for the development of children's desirable dietary habits through an on-line activity of food choices for a meal from food DB of RDA provided as Green Water Mill guide. A customized avatar system was introduced as an element of fun and interactive animation for children which provides nutritional evaluation of selected foods by changing its appearance, facial look, and speech balloon, and consequently providing chances of correcting their food choices for balanced diet. In addition, nutrition information menu was included in the App to help children understand various nutrients, their function and healthy dietary life. When the App was applied to 54 elementary school students for a week in November, 2012, significant increases in the levels of knowledge, attitude and behavior in their diet were observed compared with those of the control group (p < 0.05, 0.01). Both elementary students and teachers showed high levels of satisfaction ranging from 4.30 to 4.89 for the App, therefore, it could be widely used for the dietary education for elementary school students as a smart-learning device.
Keywords: application; dietary education; children's food avatar; children

NOTES

This research was supported by a grant (PJ008237) from Rural Development Administration in 2012 for the development of national information system on nutrition and functionality of food.

REFERENCES

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Fig. 1

UX flow of Children's Food Avatar App.

Fig. 2

Screens of log-in and feedback messages of the App.

Fig. 3

Food choice menu of the App by Green Water Mill guide.

Fig. 4

Examples of children's frequently consumed food database.

Table 1

Developing stages of the App by ADDIE model

The ADDIE model : The five phases-Analysis, Design, Development, Implementation, and Evaluation-represent a dynamic, flexible guideline for building effective training and performance support tools

Table 2

Core elements for the development of the App contents

Table 3

Contents of the classroom education by using developed App

Table 4

Comparison of the levels of knowledge, attitude and behavior of treatment and control groups before using the App¹⁾

1) 5-point Likert scale questions: 1 for strongly disagree, 2 for disagree, 3 for neutral, 4 for agree, and 5 for strongly agree

2) T: Treatment group (n = 27)

3) C: Control group (n = 27)

4) Mean ± SD

Table 5

Comparison of the treatment and control groups with regard to the scores of correct answers on nutritional knowledge before and after using the App¹⁾

1) Multiple choice questions

2) T: Treatment group (n = 27)

3) C: Control group (n = 27)

4) N (%)

5) Mean

^*: p < 0.05, ^**: p < 0.01, ^***: p < 0.001

Table 6

Changes of nutritional knowledge, attitude and behavior in the treatment group of the App¹⁾

1) 5-point Likert scale questions: 1 for strongly disagree, 2 for disagree, 3 for neutral, 4 for agree, and 5 for strongly agree

2) n = 27

3) p-value of the t-test

^*: p < 0.05, ^**: p < 0.01, ^***: p < 0.001

Table 7

Comparison of the levels of knowledge, attitude and behavior of treatment and control groups after using the App¹⁾

1) 5-point Likert scale questions: 1 for strongly disagree, 2 for disagree, 3 for neutral, 4 for agree, and 5 for strongly agree

2) T: Treatment group (n = 27)

3) C: Control group (n = 27)

4) Mean ± SD

^*: p < 0.05, ^**: p < 0.01 by independent samples t-test

Table 8

Satisfaction levels of children and elementary teachers for the App

1) N (%)

Figure & Data

REFERENCES

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Development of 'Children's Food Avatar' Application for Dietary Education

Korean J Community Nutr. 2013;18(4):299-311. Published online August 31, 2013

DOI: https://doi.org/10.5720/kjcn.2013.18.4.299

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We recommend

Development of 'Children's Food Avatar' Application for Dietary Education

Fig. 1 UX flow of Children's Food Avatar App.

Fig. 2 Screens of log-in and feedback messages of the App.

Fig. 3 Food choice menu of the App by Green Water Mill guide.

Fig. 4 Examples of children's frequently consumed food database.

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Development of 'Children's Food Avatar' Application for Dietary Education

Table 1

Developing stages of the App by ADDIE model

The ADDIE model : The five phases-Analysis, Design, Development, Implementation, and Evaluation-represent a dynamic, flexible guideline for building effective training and performance support tools

Table 2

Core elements for the development of the App contents

Table 3

Contents of the classroom education by using developed App

Table 4

Comparison of the levels of knowledge, attitude and behavior of treatment and control groups before using the App¹⁾

1) 5-point Likert scale questions: 1 for strongly disagree, 2 for disagree, 3 for neutral, 4 for agree, and 5 for strongly agree

2) T: Treatment group (n = 27)

3) C: Control group (n = 27)

4) Mean ± SD

Table 5

Comparison of the treatment and control groups with regard to the scores of correct answers on nutritional knowledge before and after using the App¹⁾

1) Multiple choice questions

2) T: Treatment group (n = 27)

3) C: Control group (n = 27)

4) N (%)

5) Mean

^*: p < 0.05, ^**: p < 0.01, ^***: p < 0.001

Table 6

Changes of nutritional knowledge, attitude and behavior in the treatment group of the App¹⁾

1) 5-point Likert scale questions: 1 for strongly disagree, 2 for disagree, 3 for neutral, 4 for agree, and 5 for strongly agree

2) n = 27

3) p-value of the t-test

^*: p < 0.05, ^**: p < 0.01, ^***: p < 0.001

Table 7

Comparison of the levels of knowledge, attitude and behavior of treatment and control groups after using the App¹⁾

1) 5-point Likert scale questions: 1 for strongly disagree, 2 for disagree, 3 for neutral, 4 for agree, and 5 for strongly agree

2) T: Treatment group (n = 27)

3) C: Control group (n = 27)

4) Mean ± SD

^*: p < 0.05, ^**: p < 0.01 by independent samples t-test

Table 8

Satisfaction levels of children and elementary teachers for the App

1) N (%)

Table 1 Developing stages of the App by ADDIE model

The ADDIE model : The five phases-Analysis, Design, Development, Implementation, and Evaluation-represent a dynamic, flexible guideline for building effective training and performance support tools

Table 2 Core elements for the development of the App contents

Table 3 Contents of the classroom education by using developed App

Table 4 Comparison of the levels of knowledge, attitude and behavior of treatment and control groups before using the App1)

1) 5-point Likert scale questions: 1 for strongly disagree, 2 for disagree, 3 for neutral, 4 for agree, and 5 for strongly agree

2) T: Treatment group (n = 27)

3) C: Control group (n = 27)

4) Mean ± SD

Table 5 Comparison of the treatment and control groups with regard to the scores of correct answers on nutritional knowledge before and after using the App1)

1) Multiple choice questions

2) T: Treatment group (n = 27)

3) C: Control group (n = 27)

4) N (%)

5) Mean

^*: p < 0.05, ^**: p < 0.01, ^***: p < 0.001

Table 6 Changes of nutritional knowledge, attitude and behavior in the treatment group of the App1)

1) 5-point Likert scale questions: 1 for strongly disagree, 2 for disagree, 3 for neutral, 4 for agree, and 5 for strongly agree

2) n = 27

3) p-value of the t-test

^*: p < 0.05, ^**: p < 0.01, ^***: p < 0.001

Table 7 Comparison of the levels of knowledge, attitude and behavior of treatment and control groups after using the App1)

1) 5-point Likert scale questions: 1 for strongly disagree, 2 for disagree, 3 for neutral, 4 for agree, and 5 for strongly agree

2) T: Treatment group (n = 27)

3) C: Control group (n = 27)

4) Mean ± SD

^*: p < 0.05, ^**: p < 0.01 by independent samples t-test

Table 8 Satisfaction levels of children and elementary teachers for the App

1) N (%)