EDUC 1011 - Reasoning with Numbers: Statistical Literacy
North Terrace Campus - Semester 2 - 2020
General Course Information
Course Code EDUC 1011 Course Reasoning with Numbers: Statistical Literacy Coordinating Unit School of Education Term Semester 2 Level Undergraduate Location/s North Terrace Campus Units 3 Contact Up to 3 hours per week Available for Study Abroad and Exchange N Restrictions Available to University Preparatory Program or Wirltu Yarlu Preparatory Program students only Course Description This course covers broad quantitative skills in the context of academic reasoning and argumentation: it aims to make students literate in the use of numbers and the basic analysis of primary data for academic purposes. It will be useful for students entering courses where applied numeracy skills are necessary, such as Psychology, Health Sciences, or Business and Commerce disciplines. Students will be introduced to some basic statistical concepts such as averages (mean, median and mode), variance, distribution, and probability. All learning takes place in a practical context, and all concepts are given a strong grounding in real-life examples and hands-on activities. This course is compulsory for University Preparatory Program students wishing to undertaken studies in Nursing or Health Sciences.
This course is offered to all students who wish to gain a basic grasp of statistical skills and will relate these skills to their personal and academic experiences, i.e., students will be able to interpret material presented in publications delivered in several formats (e.g., via TV, Internet, newspapers, academic papers, etc). Assessment will consist of a self-directed research activity where students collect data and undertake some simple analysis of that data, and then present their analysis with some preliminary findings.
Course Coordinator: Ms Amy Robinson
Lecturer and Tutor: Sarah James
Office: Level 6, Nexus10
Phone: 08 8313 0168
The full timetable of all activities for this course can be accessed from Course Planner.
Course Learning OutcomesUpon the successful completion of this course, students should be able to:
- Discuss and apply basic concepts which are essential in statistics, including variance, probability, significance, and others;
- Apply statistical knowledge to academic and everyday life;
- Work cooperatively with others;
- Analyse a specific dataset in response to a question in order to form well-supported conclusions;
- Utilise technology to assist in the analysis and application of statistical knowledge.
University Graduate Attributes
This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:
University Graduate Attribute Course Learning Outcome(s) Deep discipline knowledge
- informed and infused by cutting edge research, scaffolded throughout their program of studies
- acquired from personal interaction with research active educators, from year 1
- accredited or validated against national or international standards (for relevant programs)
1, 2, 4, 5 Critical thinking and problem solving
- steeped in research methods and rigor
- based on empirical evidence and the scientific approach to knowledge development
- demonstrated through appropriate and relevant assessment
1, 2, 3, 4, 5 Teamwork and communication skills
- developed from, with, and via the SGDE
- honed through assessment and practice throughout the program of studies
- encouraged and valued in all aspects of learning
1, 3, 4 Career and leadership readiness
- technology savvy
- professional and, where relevant, fully accredited
- forward thinking and well informed
- tested and validated by work based experiences
2, 3, 4, 5 Intercultural and ethical competency
- adept at operating in other cultures
- comfortable with different nationalities and social contexts
- able to determine and contribute to desirable social outcomes
- demonstrated by study abroad or with an understanding of indigenous knowledges
3, 4 Self-awareness and emotional intelligence
- a capacity for self-reflection and a willingness to engage in self-appraisal
- open to objective and constructive feedback from supervisors and peers
- able to negotiate difficult social situations, defuse conflict and engage positively in purposeful debate
- Learning Resources
Learning & Teaching Activities
Learning & Teaching Modes
No information currently available.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
1 hour lecture per week - 12 hours
Preparation for lectures - 12 hours
2 hour tutorial per week - 24 hours
Preparation for tutorials - 12 hours
Assignments - 65 hours
Learning Activities Summary
Week 1: Introduction to the course and statistics
Week 2: Data, variables and analysis
Week 3: Data, variables and analysis
Week 4: Data, variables and analysis
Week 5: Normality
Week 6: TBC
Week 7: Hypothesis Testing
Week 8: Hypothesis Testing
MID SEMESTER BREAK - Two weeks
Week 9: Presentations
Week 10: Linear Regression
Week 11: Probability
Week 12: Probability
Weekly topics subject to change depending on cohort knowledge and skill set.
The University's policy on Assessment for Coursework Programs is based on the following four principles:
- Assessment must encourage and reinforce learning.
- Assessment must enable robust and fair judgements about student performance.
- Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
- Assessment must maintain academic standards.
Summary Formative Friday Week 5 25% 1,2,4 Presentation Summative Friday Week 9 25% 1,2,3,4,5 Report Summative Friday Week 13 40% 1,2,3,4,5 Active Participation Formative Ongoing - every two weeks 10% 1,2,4,5
For clarification on which dates correspond to which weeks, please visit: http://www.adelaide.edu.au/student/dates/
No information currently available.
No information currently available.
Grades for your performance in this course will be awarded in accordance with the following scheme:
M10 (Coursework Mark Scheme) Grade Mark Description FNS Fail No Submission F 1-49 Fail P 50-64 Pass C 65-74 Credit D 75-84 Distinction HD 85-100 High Distinction CN Continuing NFE No Formal Examination RP Result Pending
Further details of the grades/results can be obtained from Examinations.
Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.
Final results for this course will be made available through Access Adelaide.
The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.
SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.
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