• Class Number 3098
  • Term Code 3230
  • Class Info
  • Unit Value 6 units
  • Topic On-campus
  • Mode of Delivery In Person
  • COURSE CONVENER
    • Prof Israr Qureshi
  • LECTURER
    • Prof Israr Qureshi
  • Class Dates
  • Class Start Date 21/02/2022
  • Class End Date 27/05/2022
  • Census Date 31/03/2022
  • Last Date to Enrol 28/02/2022
SELT Survey Results

The overarching goal of this course is to expose honours, MPhil and PhD students to a variety of empirical methods and data analytic tools to enable them to undertake high quality management research. This includes developing and validating survey measures, understanding and applying basic experimental methodologies, analyzing, interpreting, and writing-up quantitative data. It will also provide students a solid grounding in the use statistical software packages such as SPSS and AMOS as well as key issues and principles involving the linkage between theory and measurement. In sum, the course covers the designs and analyses that are commonly used in marketing, organizational behavior, human resource management and industrial/organizational psychology disciplines. It will emphasise appropriate data collection procedures, data analysis tools and communicating findings effectively, with the course taking the perspective of a management or behavioural researcher.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1. Identify the circumstances that call for advanced quantitative research methods
  2. Discuss the formulation of the research question to be investigated
  3. Formalise hypotheses that are in line with the research question
  4. Use the appropriate method of research to collect data relevant to the hypotheses
  5. Critically evaluate the analytical strengths and limitations of the different empirical research methods
  6. Develop appropriate analytical strategies to test the specific hypothesis
  7. Use relevant software tools to implement hypothesis testing
  8. Critically interpret and discuss results of analyses through appropriate engagement with extant knowledge and theories
  9. Synthesise findings, their meanings and subsequent recommendations competently in a structured written report

Research-Led Teaching

This course focuses on helping HDR students learn how to conduct research. In this effort, students will be exposed to academic standards in empirical research methods, will be involved in discussing the methods used in actual academic studies and in the application of these methods in their research. Lectures would be streamed live through ZOOM and made available on Echo360 and Wattle.

Field Trips

No field trips

Additional Course Costs

No additional class costs

Examination Material or equipment

There are no formal examination for this course

Required Resources

SPSS software

Mplus or SPSS Amos software

UCINET software


Free, trial, or fully licensed versions will be provided - students will not need to pay if use is related to their course studies.

Please refer to Wattle site for further details.

Staff Feedback

Students will be given feedback in the following forms in this course:
  • Written comments
  • Verbal comments
  • Feedback to the whole class, to groups, to individuals, focus groups

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). The feedback given in these surveys is anonymous and provides the Colleges, University Education Committee and Academic Board with opportunities to recognise excellent teaching, and opportunities for improvement. The Surveys and Evaluation website provides more information on student surveys at ANU and reports on the feedback provided on ANU courses.

Class Schedule

Week/Session Summary of Activities Assessment
1 Class 1: 31 April 2022 (Saturday) - Descriptive statistics, the measures of central tendencies, the basic understanding of various distributional properties Assigned Readings Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics. Allyn & Bacon/Pearson Education. Field, A. (2018). Discovering statistics using IBM SPSS statistics. Sage. In-class written assignment#1 towards the end of the session.
2 Class 2: 01 May 2022 (Sunday) - Various estimators, various t-tests, ANOVA, ANCOVA, MANOVA Assigned Readings Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics. Allyn & Bacon/Pearson Education. Field, A. (2018). Discovering statistics using IBM SPSS statistics. Sage. Quiz#1 (based on session 1) towards the beginning of the session. In-class written assignment#2 towards the end of the session.
3 Class 3: 07 May 2022 (Saturday) - Simple regression/ multiple regression/ interaction effects Assigned Readings Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences Quiz#2 (based on session 2) towards the beginning of the session. In-class written assignment#3 towards the end of the session.
4 Class 4: 14 May 2022 (Saturday) - SEM (Covariance- and component-based models) Fundamental concepts in of SEM (basics) Bollen, K., & Long, J. 1993. Testing structural equation models: Sage Publications Inc. Bollen, K. A. 1989. Structural Equations with Latent Variables. New York: John Wiley and Sons. Quiz#3 (based on session 3) towards the beginning of the session. In-class written assignment#4 towards the end of the session.
5 Class 5: 21 May 2022 (Saturday) - Longitudinal Data Analysis Bollen, K. A., & Curran, P. J. (2006). Latent curve models: A structural equation perspective (Vol. 467). John Wiley & Sons. Quiz#4 (based on session 4) towards the beginning of the session. In-class written assignment#5 towards the end of the session.
6 Class 6: 28 May 2022 (Saturday) - Social Network Analysis Scott, J. (2017). Social Network Analysis. Sage. Quiz#5 (based on session 5) towards the beginning of the session. In-class written assignment#6 towards the end of the session.

Tutorial Registration

Not relevant

Assessment Summary

Assessment task Value Return of assessment Learning Outcomes
In-class quizzes 40 % * 1,2,3,4,5,6,7,8,9
In-class written interpretation of the data/ findings/ results 60 % 01/07/2022 1,2,3,4,5,6,7,8,9

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details

Policies

ANU has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Misconduct Rule before the commencement of their course. Other key policies and guidelines include:

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the ANU Online website Students may choose not to submit assessment items through Turnitin. In this instance you will be required to submit, alongside the assessment item itself, hard copies of all references included in the assessment item.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.

Participation

Participation is expected in all classes and assessments

Examination(s)

There are no examination for this course

Assessment Task 1

Value: 40 %
Learning Outcomes: 1,2,3,4,5,6,7,8,9

In-class quizzes

Weighting: 40%

Instructions: There will be five quizzes during the entire course administered through Wattle. There will be one quiz each session (except for the first session). Each quiz will carry 8% of the total course grade. Each quiz will comprise of multiple-choice question and will require 10 minutes. The quizzes will be open book and will be invigilated via Zoom. Quizzes will be distributed to students via email, with responses submitted by email reply (quick confirmation) and Turnitin (record keeping).

Purpose: Assessing students understanding of methods covered and their basic assumptions.

Assessment Type: Individual

Marking Criteria: The marking criteria will be provided in Wattle at least two weeks prior to due date.

Submission: via email directly to Course Convener and Turnitin for record keeping

Feedback by: within 10 working days of completion

Assessment Task 2

Value: 60 %
Return of Assessment: 01/07/2022
Learning Outcomes: 1,2,3,4,5,6,7,8,9

In-class written interpretation of the data/ findings/ results

Weighting: 60%

Instructions: There will be six in-class written assignments (one in each session) administered through Wattle. Each written assignment will carry 10% of the total grade for the course. Students will be required to interpret the Tables, Figures, and other ways of representation of findings/ results. Each assessment task will take about 20 minutes and students will be allowed to consult their notes and assigned readings, and will be invigilated via Zoom. Assignments will be distributed to students via email, with responses submitted by email reply (quick confirmation) and Turnitin (record keeping).

Purpose: Assessing and developing students’ skills to understand basic tenets of the methods covered, interpret results/ findings, and write a concise report in the format acceptable as part of a conference submission.

Assessment Type: Individual

Marking Criteria: The marking criteria will be provided in Wattle at least two weeks prior to due date.

Submission: via email directly to Course Convener and Turnitin for record keeping

Feedback by: within 10 working days of completion

Academic Integrity

Academic integrity is a core part of our culture as a community of scholars. At its heart, academic integrity is about behaving ethically. This means that all members of the community commit to honest and responsible scholarly practice and to upholding these values with respect and fairness. The Australian National University commits to embedding the values of academic integrity in our teaching and learning. We ensure that all members of our community understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. The ANU expects staff and students to uphold high standards of academic integrity and act ethically and honestly, to ensure the quality and value of the qualification that you will graduate with. The University has policies and procedures in place to promote academic integrity and manage academic misconduct. Visit the following Academic honesty & plagiarism website for more information about academic integrity and what the ANU considers academic misconduct. The ANU offers a number of services to assist students with their assignments, examinations, and other learning activities. The Academic Skills and Learning Centre offers a number of workshops and seminars that you may find useful for your studies.

Online Submission

The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.

Hardcopy Submission

For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

Late Submission

No submission of assessment tasks without an extension after the due date will be permitted. If an assessment task is not submitted by the due date, a mark of 0 will be awarded.


All requests for extensions to assessment in RSM courses must be submitted to the RSM School Office with a completed application form and supporting documentation. The RSM Extension Application Form and further information on this process can be found at https://www.rsm.anu.edu.au/education/education-programs/rsm-assessment-extension/ .

Referencing Requirements

Accepted academic practice for referencing sources that you use in presentations can be found via the links on the Wattle site, under the file named “ANU and College Policies, Program Information, Student Support Services and Assessment”. Alternatively, you can seek help through the Students Learning Development website.

Returning Assignments

Please refer to assessment task details.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure The Course Convener may grant extensions for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Resubmission of Assignments

Assessment is completed during the class and resubmission is not applicable

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information. In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service — including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy. If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes. Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).
Prof Israr Qureshi
+61 02 612 52909
israr.qureshi@anu.edu.au

Research Interests


Social Entrepreneurship; Social Intermediation; Indigenous Entrepreneurship; ICT for Development; Grass-roots Initiatives to Combat Climate Change

Prof Israr Qureshi

Friday 16:00 17:00
Friday 16:00 17:00
Prof Israr Qureshi
+61 02 612 52909
israr.qureshi@anu.edu.au

Research Interests


Prof Israr Qureshi

Friday 16:00 17:00
Friday 16:00 17:00

Responsible Officer: Registrar, Student Administration / Page Contact: Website Administrator / Frequently Asked Questions