Credits: 6

Schedule: 29.10.2018 - 14.12.2018

Contact information for the course (applies in this implementation): Steffen Farny (Postdoctoral Researcher at
Aalto University School of Business)

steffen.farny@aalto.fi</

Teaching Period (valid 01.08.2018-31.07.2020): 

II autumn 2018 (Töölö campus) and IV 2018-19 (Otaniemi campus)
II and IV 2019-2020 (Otaniemi campus).

The course is a one-period online course and comprises one optional kick-off session.

Learning Outcomes (valid 01.08.2018-31.07.2020): 

Students will develop an understanding of entrepreneurship and innovation as multifaceted and multidisciplinary fields of research. They will also become familiar with a range of fundamental theoretical approaches that are derived from different disciplines, and how these are applied in innovation and entrepreneurship research. Students will also strengthen their academic reading, writing and research skills to a level required of a Master’s thesis.

Content (valid 01.08.2018-31.07.2020): 

This online course introduces students to the research methods applied in the fields of entrepreneurship and innovation management. It follows self-paced learning principles, and offers students the option to decide the order of learning topics. In particular, the course focuses on “how to collect reliable data” by providing exercises for different data collection techniques, such as interviews, observations, surveys, and secondary data (e.g. news articles, tweets, Facebook/Youtube comments). Further, the course focuses on “how to do good qualitative research” by offering training in techniques for qualitative analysis, such as Gioia method, discourse analysis, critical incident analysis, visual methods, and qualitative comparative analysis (QCA). The course also addresses “how to do good quantitative research” by learning some basic techniques for conducting statistical analysis, such as descriptive statistics, bivariate and partial correlations, factor analysis, reliability tests, linear regression and logistic regression.Students engage with the basics of qualitative as well as quantitative research, and engage more deeply in one research methodology of their interest.

Details on the course content (applies in this implementation): 

Fundamentals of Social Science Research

  • The Usefulness of Theory in Research
  • Research Paradigms in a Nutshell

Basics of Qualitative Research in Entrepreneurship and
Innovation Management

  • Different qualitative approaches to
    inquiry
  • Observation and Note-Taking
  • Interviewing and non-mainstream
    approaches to collect data
  • Qualitative Data Analysis

Basics of Quantitative Research in Entrepreneurship
and Innovation Management

  • Quantitative Data
  • From Theory to Empirics
  • Quantitative Analysis
  • Interpreting and Publishing Research
    Findings

Assessment Methods and Criteria (valid 01.08.2018-31.07.2020): 

Individual assignment (100%)

Elaboration of the evaluation criteria and methods, and acquainting students with the evaluation (applies in this implementation): 

In order to pass the course, you need to
collect a minimum of 50 points in the exercises and assignments. Note, it is
mandatory to submit both assignments, but you may choose the number of
exercises. If you decide to skip some exercises you will no longer have the
possibility to score maximum points, as in each exercise you can score a
maximum of 3 points of the final grade. For more information on the points to
grade conversion, see Table below:


Course Evaluation Overview

Course Requirements

Weighting (Points)

  1. Fundamentals
    of Research Exercises (2x2) (due Wed 21 Nov)

12

  1. Qualitative
    Research Exercises (4x2) (due Wed 21 Nov)

24

  1. Assignment
    1 (due Wed 21 Nov)

20

  1. Quantitative
    Research Exercises (4x2)
    (due Wed 12 Dec)

24

  1. Assignment
    2 (due Wed 12 Dec)

20

Total 

100

Points conversion scale

Final grade

(official scale)

90 - 100

5

80 - 89

4

70 - 79

3

60 - 69

2

50 - 59

1

0 - 49

0 (Fail)


Assignment and Exercise SUBMISSION Guidelines

Submit all exercises and assignments on
MyCourses. Note that the two assignments will be submitted via Turnitin (to check for plagiarism).

Format

The work must be presented in the following
format:

  • Font: Times New Roman
  • Size: 12
  • Spacing: 1.5
  • Alignment: justified
  • Pages: numbered
  • Margins: ‘normal’ in MS Word
  • Filename format: SURNAME First Name-Year-ID-ASSIGNMENT INITIALS.docx (example:
    FARNY Steffen-2018-1234567-A1.docx)

Late/Non-Submissions

  • Late assignments will lose 10 points per 24-hour
    period: this will be enforced as soon as the deadline is missed, as
    indicated by the timestamp in Turnitin.
    If an assignment is three or more days late, the grade will be converted
    to a zero for that assignment.

Workload (valid 01.08.2018-31.07.2020): 

Teachers: Ewald Kibler; Steffen Farny

1. Contact hours 6 h
2. Online-based exercises 74 h
3. Individual assignment 80 h

Details on calculating the workload (applies in this implementation): 

This course is a 6 ECTS unit course,
following the ECTS (European Credit Transfer System) guidelines of Aalto
University School of Business. The number of hours the average student is
expected to work in the course is 160.

ECTS Student Workload

 

Number of Hours

Work with course materials: required reading, videos
(in 10 Topics)

60

10 Exercises

20

 2 Final Assignments

74

2 Online Feedback Sessions

6

Total of all student
workload hours

160


Study Material (valid 01.08.2018-31.07.2020): 

A variety of selected articles and videos on research methods. More detailed instructions will be provided in the course syllabus.

Details on the course materials (applies in this implementation): 

Each topic has a combination of videos and
reading materials assigned. All materials are accessible on a university
computer or can be found in the library.

As a background reading on qualitative
research, we suggest:

  • Creswell, J.W., 2009. Qualitative,
    quantitative and mixed methods approaches. (3rd Ed) Sage
    Publications: Thousand Oaks, CA.

As a background reading on quantitative
research, we suggest:

  • Field, A., 2013. Discovering statistics
    using IBM SPSS statistics. Sage Publications: Thousand Oaks, CA.
  • Field,
    A., Miles, J., and Field, Z. 2012. Discovering statistics using R. Sage
    Publications: Thousand Oaks, CA.

Substitutes for Courses (valid 01.08.2018-31.07.2020): 

This course substitutes 25E32000 Entrepreneurship as a field of science.

Course Homepage (valid 01.08.2018-31.07.2020): 

https://mycourses.aalto.fi/course/search.php?search=25E53000

Grading Scale (valid 01.08.2018-31.07.2020): 

0 (fail) to 5 (excellent))

Registration for Courses (valid 01.08.2018-31.07.2020): 

Registration via WebOodi ends 7 days before the period starts.

Further Information (valid 01.08.2018-31.07.2020): 

This course is open to all Aalto students.

Additional information for the course (applies in this implementation): 

Citation Style: Harvard Referencing
(uploaded on the course website)

Academic excellence and high achievement
levels are only possible in an environment where the highest standards of
academic honesty and integrity are maintained. Students are expected to abide
by the Aalto University Code of Academic
Integrity
, other relevant codes
and regulations, as well as the canons of ethical conduct within the
disciplines of business and management education.

Link:
https://into.aalto.fi/display/ensaannot/Aalto+University+Code+of+Academic+Integrity+and+Handling+Violations+Thereof

Details on the schedule (applies in this implementation): 

This is a self-paced online course, and as
such the students can decide how to allocate the topics according to their own
needs and interests. In general, we suggest the following structure to ensure
that assignment deadlines are met:


Period II 

29 Oct – 
14 Dec 2018

 

Week 1

29.10.-2.11.

Topic 1: Usefulness of Theory in Research
Topic 2: Research Paradigms in a Nutshell

Week 2

5.11.-9.11.

Topic 3: Different qualitative approaches to inquiry and Sampling 
Topic 4: Observation and Note-taking

Week 3

12.11.-16.11.

Topic 5: Interviewing and non-mainstream approaches to collect data
Topic 6: Qualitative Data Analysis

Week 4

19.11.-23.11.

Assignment 1 and Exercises (Topics 1-6) due on Wednesday 21.11. 
Feedback Session on Friday 23.11. (Optional)

Week 5

26.11.-30.11.

Topic 7: Quantitative Data 
Topic 8: From Theory to Empirics

Week 6

3.12.-7.12.

Topic 9: Quantitative Analysis
Topic 10: Interpreting and Publishing Research Findings

Week 7

10.12-14.12

Assignment 2 and Exercises (Topics 7-10) due on Wednesday 12.12. 
Feedback Session on Friday 14.12. (Optional)

 




Description

Registration and further information