EDUC 7009 - Exam of Info & Analysis of Freq & Count Data

North Terrace Campus - Semester 1 - 2014

This course is designed to develop skills in the use of computer-based procedures for the storage and systematic examination of information obtained from published sources, extended interviews on the use of detailed observation schedules, particularly of learning and teaching in classroom situations. In some studies this leads to the discipline interpretation of the information, while in other studies this leads to the development of explanatory models that can be tested with frequency and count data. The first stage of the topic involves an introduction to storage and extraction procedures, and the sorting and shifting of the extracted information, while the second stage involves the analyses of contingency tables, configural frequency analyses, correspondence analyses, log-linear modelling, mobility tables and Markov chains. The emphasis in this course is on the unity of educational research across different disciplines and different methods of inquiry.

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Course Details

Course Code	EDUC 7009
Course	Exam of Info & Analysis of Freq & Count Data
Coordinating Unit	School of Education
Term	Semester 1
Level	Postgraduate Coursework
Location/s	North Terrace Campus
Units	3
Contact	Up to 2 hours per week
Prerequisites	EDUC 7001 Educational Inquiry, EDUC 7011 Introduction to Quantitative Educational Research, EDUC 7020 Qualitative Approach to Educational Research
Assessment	Weekly Practicals Portfolio 20%, 2 x Data Analysis Reports 40% each

Course Staff

Course Coordinator: Dr Igusti Darmawan

Name                 : Dr. I Gusti Ngurah Darmawan
Location             : Room 834, Level 8, 10 Pulteney Street
Telephone          : 8303 5788 (work)
Email                : igusti.darmawan@adelaide.edu.au
Course Website   : www.myuni.adelaide.edu.au

Course Timetable

The full timetable of all activities for this course can be accessed from Course Planner.

Course Learning Outcomes

This course is designed to:

Foster students’ understanding of the researcher’s work (model)
Introduce students to procedures for the storage and systematic examination of informationin educational research
Introduce students to procedures for analysis of frequency and count data
Promote students’ competence and confidence in using computer based procedures for the examination of information, using NVivo in particular, and various statistical test using SPSS for the analysis of frequency and count data
Develop students’ ability to understand and master the handling of data and employ proper analyses
Develop students’ understanding of output derived from statistical procedures and to converting such output to understandable statements in English.

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, 3, 4
The ability to locate, analyse, evaluate and synthesise information from a wide variety of sources in a planned and timely manner.	5, 6
An ability to apply effective, creative and innovative solutions, both independently and cooperatively, to current and future problems.	1, 2, 3 ,4 ,5 , 6
Skills of a high order in interpersonal understanding, teamwork and communication.	6
A proficiency in the appropriate use of contemporary technologies.	4
A commitment to continuous learning and the capacity to maintain intellectual curiosity throughout life.	1, 5, 6
A commitment to the highest standards of professional endeavour and the ability to take a leadership role in the community.	1, 2, 3, 4, 5, 6
An awareness of ethical, social and cultural issues within a global context and their importance in the exercise of professional skills and responsibilities.	1, 6

Learning Resources

Required Resources

No Specific text book is required.

Recommended Resources

Keeves, J.P. (ed.) (1997) Educational Research, Methodology, and Measurement: An International Handbook. (2nd Edn) Oxford: Pergamon.

Miles, M.B. and Huberman, A.M. (1994 ) Qualitative Data Analysis, Thousand Oaks, CA: Sage.

Online Learning

Occasionally, the instructor may assign readings of selected chapters from statistic textbooks, which will be made available online via MyUni.

Learning & Teaching Modes

A balance between ‘student centred’ and ‘teacher centred’ approaches to learning with emphasis on fostering an engaging learning pedagogy will be used in this course. Lectures will be supported by discussions and problem-solving practicals using statistical programs which will require active participation from students.

Workload

The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

Contact time : 24 hours (12 hours lectures, 12 hours practicals)

Non-contact time : 120 hours (readings, home works, and assignments)

Learning Activities Summary

Schedule
Week 1	Introduction to the conduct of inquiry Collecting information through interview and questionnaire Getting started in NVivo
Week 2	Information storage procedures
Week 3	Early step in data analysis: Explaining, coding and indexing information
Week 4	Identifying themes
Week 5	Attributes
Week 6	Searching for patterns
Week 7	Video, Audio, and Images
Week 8	Summarizing frequency and count data Contingency tables and identification of interaction Fisher Exact Test
Week 9	Contingency Table
Week 10	Cluster Analysis
Week 11	Correspondence Analysis
Week 12	The unity of educational research and the need for explanation Group Presentation

Specific Course Requirements

N/A

Small Group Discovery Experience

In a small group, students are required to explore and show competence in working with information storage procedures using NVivo and data analysis in addressing a particular educational problem.

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 Summary

Assignment 1 : Group Presentation
Type : Summative (Individual)
Due Date : Week 12
Weighting : 20%
Learning objectives : 1, 2, 3, 4, 5, 6

Assignment 2 : Report1
Type : Summative (Individual)
Due Date : Week 14
Weighting : 40%
Learning objectives : 1, 2, 3, 4, 5, 6

Assignment 3 : Report2
Type : Summative (Individual)
Due Date : Week 14
Weighting : 40%
Learning objectives : 1, 2, 3, 4, 5, 6

Assessment Related Requirements

Students are required to attend all practicals
Criteria that will be used to assess students’ work will be distributed and discussed in class
To gain a pass, a mark of at least 50% must be obtained on ALL assessed components as well as a total of at least 50% overall.

Assessment Detail

Assessment 1: Group Presentation
In a small group, students are required to explore and show competence in working with information storage procedures using NVivo and data analysis in addressing a particular educational problem.

Assignment 2 and 3: Report1 and Report2
You are required to show competence to analyse information and data using NVivo and various data analysis procedures. You can use your own dataset or one of those made available in the course, or with special permission, a dataset of your choosing.

Three optional assignments for assessment are proposed for this course. Each option involves the preparation of a report of around 6,000 words.

The three options include:
1. One major assignment on Descriptive analysis and NVivo includes
a. Descriptive analysis and NVivo Stage 1: 3,000 words, and
b. Descriptive analysis and NVivo Stage 2: 3,000 words

2. One major assignment on Statistical analysis and count models includes
a. Any two of statistical procedures listed below with 3,000 words each (6,000 words in total)

3. Two minor assignments on both Descriptive analysis and Statistical analysis include
a. Descriptive analysis and NVivo Stage 1 (3,000 words), and
b. Any one of statistical procedures listed below (3,000 words).

Options:

A. Descriptive analysis and NVivo

Stage 1

Introduction

Statement of problem

Design of investigation

Choice of questions

Interview protocol

Using NVivo for descriptive analysis

Data under examination

Data analysis

Coding

Creating Node

Refining Node (add nodes, change nodes, delete nodes)

Coding documents

Profile coding

Stage 2

Data analysis

Searching for patterns

Groups’ similarity and differences (e.g. gender differences, educational background differences, Australian vs others, etc which are basically links between nodes and attributes)

Proximity search (too see how close a construct to others, links between nodes and other nodes)

Model building

Summary

B. Statistical analysis and count models

Statistical procedures:

Fisher Exact Test

Contingency Table

Cluster Analysis

Correspondence analysis

Submission

Students must retain a copy of all assignments submitted.
All individual assignments must be attached to an Assignment Cover Sheet which must be signed and dated by the student before submission.
All group assignments must be attached to a Group Assignment Cover Sheet which must be signed and dated by all group members before submission. All team members are expected to contribute approximately equally to a group assignment.
Markers can refuse to accept assignments which do not have a signed acknowledgement of the University’s policy on plagiarism (refer to policy on plagiarism above).
Requests for extensions will be considered only if they are made three days before the due date for which the extension is being sought. Students must apply to the lecturer concerned on the ‘Application for Extension’ form at the back of the Academic Program Handbook.

Course Grading

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.

Student Feedback

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.
Student Support
Policies & Guidelines
This section contains links to relevant assessment-related policies and guidelines - all university policies.
Fraud Awareness

Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student’s disciplinary procedures.

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Authorised by:	Deputy Vice-Chancellor and Vice-President (Academic)
Maintained by:	Course Outlines Administrator