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A Dynamic 3D Pedagogical Model for Teaching and Learning in Clothing Functions with E-learning Practice

A Dynamic 3D Pedagogical Model for Teaching and Learning in Clothing Functions with E-learning Practice. Speaker: Ming-Liang Cao Author: Ming-Liang Cao, Yi Li, Josephine Csete E-mail: tccml@polyu.edu.hk The Hong Kong Polytechnic University, Hung Hom , Hong Kong 7, June 2010. Background.

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A Dynamic 3D Pedagogical Model for Teaching and Learning in Clothing Functions with E-learning Practice

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  1. A Dynamic 3D Pedagogical Model for Teaching and Learning in Clothing Functions with E-learning Practice Speaker: Ming-Liang CaoAuthor: Ming-Liang Cao, Yi Li, Josephine CseteE-mail: tccml@polyu.edu.hkThe Hong Kong Polytechnic University, Hung Hom, Hong Kong7, June 2010

  2. Background • Clothing functions is increasingly important in a wide range of, for example, clothing design and fashion marketing. The key issue of learning clothing functions lies on the demanding of the individual needs or some specific fashion market. One of the most difficulties in learning clothing functions is to clearly understand the detail requirements behind a lot of information. Generally, the students is used to study in class or do experiments in laboratory, which make them get more knowledge, theory and experiment data than analyzing the data to get a convictive conclusion. So how to get the learning in both class and laboratory effectively will be a problem. Our research concentrates on solving this problem by combining the learning with computer simulation technologies.

  3. Introduction • This paper presents a dynamic pedagogical model for 3D teaching and learning clothing functions with computer simulation technologies to enhance university students’ learning outcomes. The 3D teaching and learning relates to inside classroom (classroom, lecture room .etc), outside classroom (laboratory, marketplace.etc), and computer together with internet (computer lab .etc). By 3D learning, studentsenter a new level of engagementwiththe material and greatercriticalunderstanding. Theyreach a deeperlevel of learning and a higherlevel of reflection. The dynamic pedagogical model involving instruction, learning and assessment components were found to improve university students’ understanding, critical analysis and application of knowledge. How the instruction, learning and assessment modules are applied depends on both the students and the subject such as major of students, time available for teaching and learning, number of students, computer ability of students and also feedback from students in the first class etc. This paper describes the experience of designing the model and implementing it along with a computer simulation for university students’ learning clothing functions. Useful information was obtained for the further improvement of the pedagogical model design and also the further development of a virtual lab in Second Life to enhance students’ learning outcomes in clothing functions.

  4. Graphics were included to provide specific visualizations of simulation results Scientific simulation methods were used to facilitate creative learningof concrete images and to enhance memory and understanding 1 4 All opportunities and activities presented via scientific simulation technologieswere related to real life learning Computer-based interactionsbetween teachers and students were emphasized 2 5 The importance of scientific simulation environments would be recognized to promote meaningful learning 3 Benefits of the simulation study to students

  5. 3D Teaching and Learning

  6. 3D Teaching and Learning

  7. Pedagogical model for 3D T&L in clothing functions

  8. Pedagogical model for 3D T&L and implement guidelines

  9. Dynamic pedagogical model for 3D T&L with computer simulation study • In this paper, we have identified three elements (instruction, learning, and assessment) as the key dimensions which have the greatest influence on student achievement. We present a dynamic pedagogical model in which these three elements are combined. In this model students can cycle though this process many times in or just about any subject they are studying. How the three features are applied depends on the students and the subject. Major of the students, time available for teaching, number of students, computer ability of students and feedback from students in the first class are examples of relevant contextual factors that must be considered.

  10. Instruction design

  11. Learning design

  12. Assessment design

  13. E-learning Practice • A paper “Computer Thermal Functional Simulation to Enhance Students’ Learning on Fashion Product Development” [1] has presented a trial of using the computer thermal functional simulation for enhancing university students’ learning outcomes in “Fashion Product Development” in semester one of 2008/2009. Three kinds of garments (casual wear, active casual wear and active sportswear) were designed for the students to analyze the market potential in three cities (Hong Kong, Vancouver and Basra) with different climatic conditions. With the assistance of a CAD simulation system, the students could more easily find out the effects by comparing the visualization results especially the core temperature effects of 12 designed simulation cases. The study describes some helpful approaches to the incorporation of computer-based scientific simulation teaching utilizing clothing thermal functional technologies to facilitate student’s understanding of the clothing market potential analysis. Student feedback questionnaires were given to students after the trail e-learning study. Students’ feedback on this e-learning study is in order to help improve it.

  14. Study Design of the simulation study 6. Analysis method 1. Participants 5. Results collection 2. Method design 4. Instruction design 3. Question design

  15. Participants Subject: Fashion Product Development Major: Technology Marketing Design Student number: 67

  16. Garments: Casual wear Active casual wear Active sportswear Markets: Hong Kong (China) Vancouver (Canada) Basra (Iraq) Temperatures: 10 ℃ 20 ℃ 30 ℃ 40 ℃ Metabolic rate: 100 W/m2 300 W/m2 500 W/m2 Question design

  17. Annual temperature of three typical climatic cities Data source: http://www.bbc.co.uk

  18. Physical effects according to the change of core temperature Data source: http://en.wikipedia.org

  19. Question design • A total of 9 questions, which can be similarly sorted to three groups according to the markets, were designed for students to analyze the market potential. • The months for seasons of three places were uniformly set as: • Spring (March, April and May), • Summer (June, July and August), • Autumn (September, October and November) • Winter (December, January and February)

  20. Sample questions • The questions for the Hong Kong market illustrate the conceptual understanding that was expected. When presented with a garment description of specific properties such as “100% cotton of 1mm thickness”, students were expected to answer questions such as the following: • Question 1: This garment is not appropriate for the following Hong Kong apparel markets: • a. Casual wear for summer • b. Casual wear for winter • c. Casual wear for spring and autumn • d. Casual wear for spring, summer and autumn • Question 2: This garment is appropriate for the following Hong Kong apparel markets: • a. Active casual wear for summer • b. Active casual wear for winter • c. Active casual wear for spring and autumn • d. Active casual wear for the whole year • Question 3: This garment is not appropriate for the following Hong Kong apparel markets: • a. Active sportswear for winter • b. Active sportswear for summer • c. Active sportswear for spring and autumn • d. Active sportswear for spring, summer and autumn

  21. Instruction for the simulation study Relationship between simulation and question 12 cases for simulation

  22. Instruction for the simulation study

  23. Basic steps for simulation

  24. Simulation results of 10, 20, 30 and 40 ℃ for casual wear (100 W/m2)

  25. Simulation results of 10, 20, 30 and 40 ℃ for active casual wear (300 W/m2)

  26. Simulation results of 10, 20, 30 and 40 ℃ for active sportswear (500 W/m2)

  27. Flow chart for analyzing question

  28. Flow chart for analyzing question • According to many physiological studies, keeping core temperature within 37±0.5 ℃ is essential for human survival. Beyond this range, humans will feel substantial discomfort. The maximum deviations of the core temperature are approximately 2 ℃ from the normal level. Beyond this range, serious physical threats, such as hyperthermia and convulsions in case of high core temperature; and hypothermia and cardiac fibrillation in case of low core temperature, may occur. More extreme variations in core temperature may result in death. • Some suggestions for students to analyze the questions: • (1) Core temperature shown in the table of physical effects is the key factor while only “Normal” and “Hot” effects can be acceptable for comfort; • (2) Skin temperature and relative humidity of skin data can be used as a complementary reference combined with personal knowledge and daily life experience.

  29. Improvement by Students’ Feedback Another paper “Effects of an E-learning Case Computer Simulation on Student’s Learning of Clothing Functional Design and Student Feedback” [2] presents a pedagogical study to use student feedback to help improve the effects of e-learning case computer simulation for enhancing the students’ learning outcomes.

  30. Student Feedback Questionnaire

  31. Instructional Design Improvement • By analyzing the feedback of students, some useful information can be concluded to improve the pedagogical design of computer simulation-based study as following: • (1) Background information, learning process and clear assessment criterion should be passed to students at the beginning of e-learning study. • (2) Enough learning resources and instructions should be given to explain the relationship between e-learning study and subject study. • (3) Solid technology environments, user-friendly interface and clear simulation instruction are very important to improve students’ learning outcomes by implementing computer simulation-based approach.

  32. E-Learning Practice

  33. Instructional Design Improvement • Meanwhile, from the paper report organization , the students achieved more learning outcomes such as: • (1) Concept of clothing functional design; • (2) Understanding the design process by using computer-based simulation; • (3) The reason of using the computer-based simulation system; • (4) Self-case design by using simulations.

  34. Excerpts of Students’Paper Reports • Case 1: The reason of using the computer-based simulation system • “The computer-based simulation system and arranged to different cases by varying some design factors were designed to help finding out the best combination of the type of fabric, the garment style, for the specific market and to give the best thermal functional performance to the garment, and raises its design values. Additionally, it may help to find out other potential markets by analyzing the result of the skin temperature and relative humidity of skin or verifying the climate conditions (e.g. temperature, humidity and wind velocity) and compare those simulation results, for examples, sold at Hong Kong in winter and also at the Vancouver in summer. And the other advantages of using the computer-based simulation system are, (1) it simplified and smoothen the simulation process in a sense of not necessary to make samples with different combination of design factors to sent to laboratory testing, which could reduce the design cycle and gain the greatest efficiency with the best design values. (2) When some of the information or factors are changed in the system, a different result could be conducted, which is also convenience to use and compare at next time as the case could be saved as a record. (3) Lastly, it may also a source of inspiration to designer by varying the factors and creates another wonderful design.”

  35. Excerpts of Students’Paper Reports • Case 2: Understanding the design process by using computer- based simulation • “Pre-experiment preparation is the first step to design what is the purpose of the garment and what garment we should form to match up to the market, including the garment style, fabric properties and the expectation of garment. For the experiment, it should conduct for a wide range of factors that would affect the design and wearer, including outdoor air temperature, humidity, and thickness of fabric, etc. Then, the simulation model should be set up with scientific simulation software, following the steps to enter all data. After the visualization results are collected, it should analyze and plan the direction on the design of product. Furthermore, it needs to project a measure for improving the result of garment while the fabric is not suitable for the market after the experiment. In short, scientific simulation software is very useful in presenting a clothing thermal functional case simulation, which improves the analysis of performance and function of clothing. It is user friendly software that provides an opportunity for students learning simulation experiments via scientific simulation technologies. The operation of this software is simple and it is easy to understand since the results are shown by concrete images. It can enhance students’ learning motivation.”

  36. Excerpts of Students’Paper Reports • Case 3: Self-case design • “Garment for case design is unequal to that for purpose design. For the case design, the design is not just for a particular purpose but a given condition is also in calculation. When other environmental factors are in count, the performance of the product should both suit for the activity and the condition in which take place. For various countries and regions, different result of the garment’s performance would be taken. In the following, a case will be suggested to explain how to design for function and performance. A situation would be set and those data would be input to the scientific simulation software. With the helping of the software, simulation can be done easily as there are default values of physiological properties of human body and other control information. After the simulation, results reflecting garment’s performance would be presented. And we can attend to a prefect result by having this information. • Situation: A sports shirt for outdoor gymnastics activities is designed. It is a loose fit sports shirt with short sleeves which is made by a 100% cotton fabric of 0.1cm thick. For the activity to takes place in Hong Kong, the temperature range is 10°C - 20°C in winter; and 20°C - 30°C in summer, with relative humidity of 60% and wind velocity of 0.5m/s. The heat emit from human body during a gymnastics activity is about 319W/m2. • Objective: To determine the suitability of a 100% cotton sports shirt in fabric of 0.1cm thick in a given condition by understanding the relationship between the styles of a design and the thermal comfort of clothing when design for function and performance.”

  37. Conclusion • As a result of this research, the following conclusions can be drawn: • (1) By closely following the pedagogical model as described students achieved the desired learning outcomes. • (2) If adopted properly, this approach can improve the efficiency in using computer simulation to teach clothing functions concept. • (3) Although technology supports may cause some stress to the instructor, the outcomes surpass both common computer simulation teaching and the traditional classroom teaching modes. • In summary, by following the afore-mentioned pedagogical paradigm, effective learning outcomes and quality of education can be generated.

  38. Reference • [1] Cao ML, Li Y, Csete J. Computer Thermal Functional Simulation to Enhance Students’ Learning on Fashion Product Development. In: Proceedings of the Textile Bioengineering and Informatics Symposium, Hong Kong, 2009. p. 663-671. • [2] Cao ML, Li Y, Csete J., “Effects of an E-learning Case Computer Simulation on Student’s Learning of Clothing Functional Design and Student Feedbacks”, accepted by conference TBIS 2010, Shanghai, China (May 28-30, 2010)

  39. The End Thanks!

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