Q2 33 Points An e-learning provider aims to offer an all-round educational support and resources for the secondary school pupils aged 11-16. They have a pool of resources such as articles, videos and quizzes on a range of subjects, and also contacts for clubs that meet face-to-face. The e-learning provider wants to implement a personalised educational resource recommender. Using stereotypes has been suggested as a way to provide personalised recommendations. Imagine that the e-learning provider maintains a profile of each learner that includes: gender, age, list-of-interests, where list-of-interests is a subset of school subjects such as English and Mathematics, and extra-curricular activities such as Football and Painting. Below are three stereotypes extracted about the learners. Sport-fanatics (P=0.8) Trigger: user is male, and aged 15-16, and interested in Football Facet Value Subjects Design and Technology Biology Scouts /Guides Computer Games Interest Rating (out of 100) 80 50 70 70 Hobbies Budding-scientists (P=0.5) Trigger: user is female and aged 12-16, and interested in Mathematics Facet Value Subjects Interest Rating (out of 100) 70 30 80 60 50 Biology Design and Technology Bird-watching Reading Computer Games Hobbies Creative-artists (P=0.62 Creative-artists (P=0.6) Trigger: user is female, and aged 12-14, and interested in (English or Mathematics or Painting) Facet Value Interest Rating (out of 100) Subjects Physics 10 Biology 90 Hobbies Choir 80 Computer Games 20 Scouts /Guides 40 A new club Simulation and evolution", which relates to Biology and Computer Games, is added. The above stereotypes are used to decide should the new club be recommended to a member, Mary, who is a 12-year-old girl and interested in Mathematics? Q2.1 2 Points What is the probability that Mary will like a club that relates to Biology (rounded to two digits after the decimal point)? O 0.54 O 0.70 O 0.80 O 0.90 Save Answer Q2.2 4 Points Show your working for obtaining the probability in Q2.1. Enter your answer here Save