Task 2 a) Deploy Al's machine learning to predict a student's final grade in a course. This will allow courses to be streamed so that all students predicted to fail will not be permitted to enrol, those predicted to get a bare pass in a class together, those predicted to get a credit in another class, etc. That way labs and lectures can be framed to suit the student's ability. This creating better learning environments and enhanced learning. Can be deployed as this can provide the lecturers/tutors insight on student's past performance which can be used by Uni staff to assist students improve their performance or encourage them to take up another course if they fail in the current course. b) Deploy Al's natural language to develop a multi-lingual intelligent chatbot to translate and interpret lectures and labs in English to the student's first language. This will enable the university to be the first to drop English language (IELTS) requirements and provide a competitive advantage over other universities. Yes, this can be deployed as it would be a unique method which will attract students all over the world come study at Fed Uni. c) Deploy Al's natural language and decision support to automatically generate individual feedback for each student as they submit responses to lab questions. The feedback goes further than telling the student whether an answer was correct but generates an interactive dialogue to explain why the answer was incorrect. Yes can be deployed, as it can help students improve in their course and gives teachers more help in assessing students. d) Deploy loT sensors to sense movement when student's attend online classes. This will ensure that students don't join Teams rooms to register attendance but turn video and audio off and leave the room. Should not be deployed as this will discourage key their audio and video off always and reduces factor of human interaction between lecturers and students. e) Deploy FitBit loT sensors to detect student's heart rate to inform the lecturer when students are getting excited (or bored) with the class Should not be deployed as it can be intrusive. Students would be hesitant to allow university to monitor health related data. f) Deploy loT sensors that detect a student's location in real time so that lab attendance can be known without having tutors spend time to record attendance. This will allow timetables to be generated daily and customised so that classes can be set around higher priority commitments like work.
Task 3 This can and cannot be deployed. It can be beneficial as university can track students and help them get to classes and lectures more often. However, it can be a invasion of students privacy once they are off campus and their every location/moment is monitored by Fed Uni. g) Deploy 5G optimisation so that thousands of students sitting an exam in a large exam hall can do their exam using virtual reality headsets, knowing that the 5G can deploy additional 'virtual' servers and