ANALYSIS OF A SOCIAL WEBQUEST FOR STATISTICS IN ENGINEERING Irene Epifanio Department of Mathematics, Universitat Jaume I (SPAIN) epifanio@uji.es Abstract A webquest for students of an introductory course in Statistics in Industrial Design Engineering is presented and analyzed. In order to make students work on the most basic concepts (sampling and description of data) and thinking skills, I have designed a webquest [1] where they are critical citizens. The webquest starts with a video from the outstanding series “Against All Odds: Inside Statistics” [2], Program 3, Describing Distributions, which shows how a local government used statistical methods to correct inequality between men’s and women’s salaries in the USA in the 1980's. Students should investigate the current wage gap, carrying out and analyzing a small survey, and using the official data of the INE (Spanish National Statistics Institute), where one of the variables they should collect and examine is the number of hours devoted to work at home. This webquest is designed to educate students for equality. Students also research a brilliant woman who used statistics to save many lives: Florence Nightingale. The other activities in the webquest also tackle current issues, such as climate change, through ecological footprints, and statistics in daily life, for example in clinical analysis, incorrect use of statistics in the media, or writing a letter to the city council to correct a high water bill based on incorrect water consumption estimates (this activity is based on a true story in which the citizen received a refund). The webquest also has research activities to show the importance of statistics in industrial design, and specifically, in ergonomics. These activities involve the description of relationships: regression line and principal component analysis for the accommodation of pilots in aircraft design [3]. I analyze the data collected from my students about their experience and opinion of the webquest. Keywords: WebQuest, Education for Equality, Statistics in Engineering, Ethical Values. 1 INTRODUCTION Firstly, I would like to give some of the reasons why I decided to create a webquest. This webquest is designed for students of Statistics in a degree in Industrial Design. There are a large number of students, with 120 new students starting each year, and in total there are 180 students, who study either in the mornings or afternoons. This subject covers the standard content of an introduction to statistics in engineering: descriptive statistics, sampling, probability and inference. The course is 137 hours, with 60 hours in the classroom or laboratory, and the remainder as independent study. The statistics subject is compulsory. The subject is run in the second semester of first year. Students may enter this engineering course from any option in high school, including arts, humanities and social sciences, and sciences (technology, and natural and health sciences). The percentage of students who did not study technology in the final years of high school is around 30% to 40%, according to the information provided by students in different years. In this case, the students may not be very suited to the study of mathematics. Furthermore, a large number of students have the preconceived idea that statistics are not going to be useful in their career, and so they are not very motivated to start with. It is always challenging to teach a subject that many students do not find interesting from the outset, and in particular it is a challenge to teach statistics to non-specialists [4]. Throughout the subject, I try to overcome students' prejudice with problems applied to the field of industrial design and the use of own data [5]. This is reflected in the webquest, where in addition to considering activities applied to industrial design, students will also see how statistics are present in everyday life and interesting social issues. In fact, the webquest is titled “Statistics in Everyday Life”. In it I use similar tactics to those described by Phua in [6]. The American Statistical Association (ASA) and the Mathematical Association of America (MAA), which created a committee to study the teaching of introductory Statistics [7], make three fundamental