EDUC 1011 - Reasoning with Numbers: Statistical Literacy
North Terrace Campus - Semester 1 - 2015
General Course Information
Course Code EDUC 1011 Course Reasoning with Numbers: Statistical Literacy Coordinating Unit School of Education Term Semester 1 Level Undergraduate Location/s North Terrace Campus Units 3 Contact Up to 3 hours per week Available for Study Abroad and Exchange N Restrictions This class is only open for students in the University Preparatory Program or Wilto Yerlo Preparatory Program. 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: Dr Chad HabelLecturer-in-charge/tutor: Lucy Andrew
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) Knowledge and understanding of the content and techniques of a chosen discipline at advanced levels that are internationally recognised. 1, 2, 4 The ability to locate, analyse, evaluate and synthesise information from a wide variety of sources in a planned and timely manner. 1, 2, 4 An ability to apply effective, creative and innovative solutions, both independently and cooperatively, to current and future problems. 2, 4 Skills of a high order in interpersonal understanding, teamwork and communication. 3 A proficiency in the appropriate use of contemporary technologies. 5 A commitment to continuous learning and the capacity to maintain intellectual curiosity throughout life. 2, 3 A commitment to the highest standards of professional endeavour and the ability to take a leadership role in the community. 4 An awareness of ethical, social and cultural issues within a global context and their importance in the exercise of professional skills and responsibilities. 1, 2, 4
Required ResourcesStudents will need to sign up to Khan Academy to receive homework questions. You can sign up using a Google or
Facebook account, or by using an email address. Students will be given the opportunity to sign up to Khan Academy during the first
Recommended ResourcesThe lecturer will establish the recommended resources during weeks 1 and 2.
Online LearningMyUni and Khan Academy (see above) will be essential portals for your learning in this course. It is very important that you are familiar with both these environments and use them effectively to support your learning.
Important information may be emailed to your student email account, so it is essential that you check your student email regularly.
Learning & Teaching Activities
Learning & Teaching ModesThis course will entail 1 hour of lectures per week and 2 hours of workshops per week. Students are expected to discuss key issues and concepts presented in the course. Most importantly, students are expected to relate the concepts discussed in the lecture/workshop to everyday life situations and applications. The student will be responsible for the non-contact activities which will include, but are not limited to, reading and studying.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
1 hour lecture per week (x12) 12 hours 2 hour tutorial per week (x12) 24 hours 4 hours online research per week (x12) 48 hours 6 hours reading and independent study per week (x12) 72 hours Total 156 hours
Learning Activities Summary
For clarification on which dates correspond to which weeks, please visit: http://www.adelaide.edu.au/student/dates/
Schedule Topic Notes Week 1 Introduction: Why use statistics? Descriptive vs. Inferential 5-6pm tutorial in Computer Lab Week 2 Central tendency, range, frequency, distribution Week 3 Variation; box and whisker plots Test: descriptive v inferential stats, central tendency, range, max, min, frequency Week 4 Graphical representations of data Week 5 Distribution of data Present data to the class. 5 minutes per group. Week 6 No lecture, no tutorial Data collection Mid-semester break Data collection Week 7 Gathering Data I Week 8 Gathering Data II Test: variation, interpreting graphs, distribution of data, box and whisker plots Week 9 Data and Chance I Week 10 Data and Chance II Week 11 Exploring Data I Test: Data and Chance (probability) Week 12 Exploring Data II Week 13 Exploring Data III Assignment questions will be answered in the tutorial
Specific Course RequirementsTo pass this course, students must attend at least 75% of tutorials; in cases of absence for medical or compassionate reasons, documentation must be provided and students must still attend at least 50% of
classes. If students fail to attend the minimum required number of tutorials, they will be considered to have not completed an assignment (see below).
Small Group Discovery ExperienceThe University of Adelaide has committed to a pedagogical approach termed the “Small Group Discovery Experience”, indicating that the SHDE will be a core component in a credit-bearing course of every undergraduate program, and that it will be part of every first-year level from 2014. Since the UPP is not an award-based program, it is not strictly required to include an SGDE in the UPP.
However, since the UPP is designed to prepare students for first-year study, and the SGDE will be a core component of all first-year study, it is important for the UPP to provide some preparation in Small Group Discovery. These should be of a scaffolded, preparatory nature as befits each course within the program, and the philosophy and program objectives of the UPP. The Program has been designed to include preparation for small group work and research activity in many of its courses.
More specifically, this course aims to prepare students for their small-group discovery experience by providing subject expertise in statistics and giving students the opportunity to develop an inquiry-based project to gather and analyse some data in order to draw conclusions.
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.
Assessment Task Task Type Due Weighting Learning Outcome Attendance and Participation Formative
5% 1, 2, 3, 5 In-class mini-quizzes x3 Formative In class (tutorial), Week 3, Week 8, Week 11 30% (3 x 10% each) 1, 4 Group presentations Formative In class (tutorial), Week 5 5% 1, 2, 3 Graphing Assignment Summative Friday, first week of mid-semester break 25% 2, 4, 5 Data Assignment Summative 5pm Friday, Week 13 35% 1, 2, 4, 5
For clarification on which dates correspond to which weeks, please visit: http://www.adelaide.edu.au/student/dates/
Assessment Related RequirementsStudents must attempt all assessment tasks to pass this course. If students miss a mini-quiz they will receive a mark of zero, unless they receive an extension on medical or compassionate grounds as per the University's Modified Arrangment of Coursework Assessment (MACA) policy.
Since the University Preparatory Program is designed to prepare students for success at University, completing and submitting all assignments is central to the intended learning outcomes of the program and each course within it. Often, at least attempting and submitting assignments in the face of difficulty or adversity is enough for success at University and the UPP encourages this resilience by employing this policy in select courses. Please note that the absolute last date for the submission of assignments in Semester 1 is the end of Swot Vac week, which is one week after the final assignment is due.
If a student fails to submit all assessment tasks and would otherwise have received a grade greater than 45, they will be given a nominal grade of 45 (Fail) for that course in that semester. This will permit them to undertake additional assessment (formerly called academic supplementary assessment) at the Course Coordinator’s discretion, as per policy at http://www.adelaide.edu.au/student/exams/supps.html
It is not necessary to apply for additional assessment; this assessment will usually consist of the missed pieces of assessment, but the course coordinator may require more. As per policy 184.108.40.206, if the student
passes the additional assessment to the Course Coordinator’s satisfaction, the maximum grade they can get for the course is 50 (Pass). If a student’s raw grade is below 45, regardless of whether all tasks have been attempted, this score will stand unless exceptional, documented circumstances apply as per the University’s Modified Arrangements for Coursework Assessment: https://www.adelaide.edu.au/student/exams/mod_arrange.html
Substantial non-engagement in this course (evidenced by repeated non-attendance at tutorials and failure to submit assessments) may result in students being withdrawn from the University Preparatory Program and being required to apply for reinstatement if they wish to continue.
Assessment DetailAttendance and Participation
Your lecturer/tutor will mark you on your participation in group and class discussions during tutorials. This mark is not based on 'correct' answers but a willingness to participate. Remember that being vocal in class is not the only way to demonstrate participation: asking questions after class or via email/MyUni, doing pre-readings, active listening and note-taking, and actively discussing with other students are all ways of showing that you are participating in the class.
Three Mini Quizzes (MQs) will be conducted at the beginning of the tutorial in weeks 3, 8 and 11.
The MQ will consist of 3-5 short questions; either a specific piece of information (SPI question type), a selection from multiple choices (MC question type), an extended piece of information, or open-ended question (OE question type). MQ questions will be similar to those questions/exercises worked out during the lecture/workshop sessions and will be based on topics discussed in previous lectures/workshops.
SPI example: Find the mean of the following values: 5, 0, 7, 3, 6, and 3
MC example: Which of the following answers is the mean of the following values: 5, 0, 7, 3, 6, and 3?
OE example: What does the mean of a data set tell us about the data?
Choose a data set (or your tutor will give you a data set). Use statistics to describe your data with specific reference ot the concepts and terms introduced in class. Graph your data (you may need to create more than one graph) and explain the meaning of the data to the class. What kinds of interpretations might your draw from the data? How might the data be used as evidence to support some kind of academic argument?
Graphing Assignment (500 words)
Compare and contrast 3 different graphical techniques for representing data. Use one data set and graph the data 3 different ways. What are the advantages/disadvantages of each type of graph? Which is the best graph to represent this data? Why?
The assignment must contain the following sections;
Introduction: Describe the data in terms of central tendency and variation. What is the population or sample? How was the data collected?
Body: Produce 3 types of graphs and discuss the advantages and disadvantages of each graph.
Conclusion: What can you conclude from the data? Which graph represents the data in the best way?
Data Assignment (700 words)
Choose a data set (or your tutor will give you a data set). What is the question you are trying to answer with your data? i.e. Are house prices in SA increasing at the same rate as house prices in NSW and Tasmania? How have Australians’ attitudes to gay marriage changed over the past 20 years? How does smoking effect the risk of heart attack in people over 50? Try to present your data in a way that support a sepcific conclusion/answer to your question. In this assignment, you should:
• Briefly describe how the data was collected
• Use statistics to describe your data (central tendency and variation)
• Graph the data in a way that best represents the data
• Interpret the data – what it the data telling you? You may want to calculate percentages, probability, frequency etc. You may need to include extra data to help interpret your original data set.
• Make conclusions – What can you conclude from your data? What can you NOT conclude i.e. identify a possible misinterpretation of the data by someone who doesn’t know as much as you about statistics. Clearly state what extra data you need to make relevant conclusions.
SubmissionAll assignments will be electronically submitted via MyUni, except for tests and group presentations.
Students may be granted extensions to assignments on medical or compassionate grounds; documentation to support these ground will be required. Requests for extension must be made before the due date; requests for extension submitted after the due date will not be considered. All extension requests must be submitted to the Course Coordinator (Chad Habel: firstname.lastname@example.org);
any extensions granted by the lecturer or tutor will not be considered valid.
All extension requests will be administered according to the Modified Arrangements for Coursework Assessment Policy: http://www.adelaide.edu.au/policies/3303/
For a concise information sheet on this policy, please visit http://www.adelaide.edu.au/student/exams/pdfs/maca_medical_compassionate_info.pdf
Penalties for Late Submission
Unless the Course Profile states otherwise when an assessment is submitted after the due date, and without an extension, 5% of the total mark possible will be deducted for every 24 hours or part thereof that it is late, including each day on a weekend. For example, an essay that is submitted after the due date and time but within the first 24 hour period, and that has been graded at 63%, will have 5% deducted, for a final grade of 58%. An essay that is more than 24 hours late will lose 10%, etc.
This course aims to return assessed work within 2 weeks of its submission, although this cannot be guaranteed. The resubmission of assignments is not possible for this course, except in exceptional circumstances as approved by the Course Coordinator.
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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