Additional Course Outline Information
The Computer Science department's grading policy states that in order to pass a course you must meet two requirements:
1. You must achieve an average grade of at least 50% over all assessment items.
2. You must achieve an average mark of at least 45% on invigilated assessment items.
If you satisfy both these criteria, your grade will be determined by the following University- wide scale for converting marks to grades: an average mark of 50% is sufficient for a C- grade, an average mark of 55% earns a C grade, 60% earns a B- grade and so forth. However if you do not satisfy both the passing criteria you will be given either a D or E grade depending on marks. Marks are sometimes scaled to achieve consistency between courses from year to year.
Students may apply for special consideration if their performance in an assessment is affected by extenuating circumstances beyond their control.
Applications for special consideration should be submitted via the Examinations Office website within five days of the assessment.
Where an extension may be granted for an assessment, this will be decided by direct application to the Department and an application to the Examinations Office may not be required.
Special consideration is not available for items worth less than 10% of the course.
Students prevented by extenuating circumstances from completing the course after the final date for withdrawing, may apply for special consideration for late discontinuation of the course. Applications must be submitted to the Examinations Office within five days of the end of the main examination period for the semester.
Week / Lecture topic
1 Psychology of learning, IT and education
2 Student Modeling
3 Model/Knowledge tracing
4 Constraint-based Modeling, SQL-Tutor
5 Think-aloud protocol, EER-Tutor, Comparing model-tracing tutors to constraint-based tutors
6 Easter - No Lecture
7 Evaluation of ITSs
8 Authoring tools / ASPIRE
9 Pedagogical module, Third generation tutors (metacognition and affect)
10 CSCL, OLM, Eye Tracking
11 Affective student modelling, AR + ITS
12 Course review