Learning outcomes:

The aim of this course is to strengthen the general researcher skills of the participant by training her to grasp her own particular field of research in a wider and more general context through some central issues in philosophy of science.

Teaching schedule: 19.10. and 26.10.2017 at 9-16 o'clock.

Place: 19.10. Lecture hall D11 (Main building), 26.10. Room C6 (Main building)

General description:

The course consists of alternating sessions of lectures and discussions. The lectures will cover some central themes in philosophy of science, and these will then be further discussed in smaller groups whose members (to the extent that this is possible) come from related scientific fields.

Course contents:

1. Objects of Study and the Classification of Sciences
2. Concepts, Propositions, and Arguments
3. Hypotheses, Explanations, and Justification
4. Scientific Realism and Antirealism

Completion: Passing the course requires a tight following of the lectures and an active participation in the group discussions. There will be no final exam as such, but the participants are required to produce a three-page written presentation where one of the central themes of the course is connected with the participant’s own scientific field and research topic.

Teacher: Docent, PhD Heikki J. Koskinen

Enrolment in NettiOpsu. The maximum number of students is 50 (4 places reserved for TUT students). Selection method is draw.

This course consists of face-to-face teaching and online learning in Moodle (Research Ethics online course).

The course invites students in various stages of their doctoral thesis to think through, write and process the ethical questions and themes in their own ongoing research projects. It provides a compact knowledge package on ethical issues concerning the research design, data collection/field work and writing-up phases. The course consists of lectures, discussion & student presentations in class and assignments.

Learning outcomes: After the course, students will

- be better equipped to think about and deal with ethical issues at different phases of their research projects
- have skills to discuss and identify issues concerning the ethics both in relation to research participant and the academic community (treatment of participants, informed consent, data lifespan, publication and ethical reporting)
- have knowledge on the key guidelines concerning ethical conduct and know where to go for further information
- have practical tools and means for the writing-up of ethical question in the doctoral thesis.
- have access to an information package on ethics
- know the basic functions of Turnitin plagiarism checker programme

Course Schedule:

1. Face-to-face lectures on 12.9.2017 at 16-20 in Room A08 (Main building)

2. Individual learning using Moodle (Research Ethics online course)

3. Face-to-face workshop on

- 26.9. (Room C7, Main building) at 10-16 and
- 3.10.2017 (Room A2A, Main building) at 10-16

Teacher: PhD Marika Enwald

Enrolment: At the maximum 20 students (2 places reserved for TUT students). Priority in selection is given to non-Finnish-speaking students. Otherwise, selection method is draw. Enrolment in NettiOpsu.  Please check the selection result from NettiOpsu after the enrolment period.

Completion mode: Those accepted to the course are required to send in a pre-assignment (max one page A 4) through Moodle. Active participation is required. Every student will give a 15-20 minutes presentation in the workshop. Every student will write an 6-7 pages essay after the course.

THE PRE-ASSIGNMENT: Please include the following in short:
1)    Your name & discipline
2)    Your Research topic
3)    Potential ethical issues you have encountered or anticipated to encounter as part of your doctoral research and solutions you may already have in mind
4)    Any issues relating to research ethics you wish to be discussed during the course
5)    It is presumed that you could present briefly during the course the ethical questions that you are facing during your research.

Doing Thematic Analysis: A two-day mini-intensive introduction (2 ECTS)

Learning outcomes:
At the end of the teaching sessions, the students have a deep understanding of the potential (and limitations) of thematic analysis, and what doing thematic analysis looks like in practice. Due to the nature of qualitative analysis, not every aspect is covered in depth, but the students gain foundational skills related to coding and starting theme development, that set them on the path for doing rigorous and theoretically/methodologically coherent analysis.

Course description:
Thematic analysis (TA) is a now-widely-used qualitative data analysis method. It is one of a cluster of methods that focus on identifying, and interpreting, patterned-meaning across a dataset. The method is highly popular across the social, behavioural, health, and clinical sciences, as well as in other areas such as education, and even marketing and computing.

Various versions of thematic analysis exist, some bound to particular epistemological, ontological and methodological assumptions and practices; others freer to be applied in diverse ways. The version of TA developed by Victoria Clarke and myself exemplifies the latter: it offers a method, not a methodology. It offers a framework for the analysis of data, but does not pre-specify the interpretative or theoretical bases of the analysis.  Researchers need to interpret the meanings they identify through thematic analysis within frameworks they themselves specify. This means thematic analysis can address a very wide range of research questions, from quite essentialist or realist ones, through to more critical or constructionist ones.  

What this course offers:
This course is designed to give a theoretically-informed, hands-on introduction to the doing of thematic analysis, according to the approach developed by AP Victoria Clarke and Prof Virginia Braun. The teaching combines a range of pedagogical styles and activities, from mini-lectures through classroom discussion, small-group and individual class-time activity, and homework. Students are expected to actively engage in the classroom discussion and activities, and do the preparatory work.

Teacher: Professor Virginia Braun, School of Psychology, University of Auckland, New Zealand

Course structure & assessment

12.10.2017 at 9-16

Getting started on TA – focuses on:
•    introducing and locating thematic analysis
•    exploring and understanding key concepts
•    dataset familiarisation
•    understanding and starting coding
Day 1 also includes ‘take home’ work as preparation for Day 2

13.10.2017 at 9-16

Developing your analysis – focuses on:
•    developing coding
•    coding rigour and quality
•    theme development and exploration
•    theme/data interpretation.

Assessment
The course is assessed pass/fail, with participation in expected tasks and discussion, as well as demonstration of developing understanding, and application of concepts, key to passing.  

Place:

12.10. at 9-16, Room 3110 (at 9-13), Room 3111 (at 13-16) (Pinni B building)

13.10. at 9-16, Room 3110 (Pinni B building)

Enrolment in Nettiopsu. 25 students at the maximum. Selection method is draw. Students should check the enrolment result from Nettiopsu after the enrolment period.

Course background reading:
Braun, Virginia & Clarke, Victoria (2006) Using thematic analysis in psychology. Qualitative Research in Psychology 3:2, 77–101.

Learning outcomes:

This course will give you practical tips and strategies for writing scientific articles in English. Designed as a two-day workshop, the main objective of this course is to learn to identify and produce the most important elements in English academic writing. The first day offers a series of exercises and points to ponder, whereas the second day offers the students an opportunity to apply these tips and strategies in an "Editing Clinic". During the second day, the students will be taught a ten-step editing process that they will apply to texts in class.

Contents:

Day 1

Group 1, 21.9.2017 at 9-16 o'clock (Room 3103, Pinni A building)

Group 2, 28.9.2017 at 9-16 o'clock (Room 3103, Pinni A building)

9:15-9:45  Online sources: Scientific, clear, transparent
9:45-11:00 Drafting, Differences between Finnish and Anglo-American traditions
11:00-11:30  Components of a Scientific Article, The Sequence of Writing
11:30 Lunch
12:15 Problems, Transitions, Tenses
14:00 Coffee break
14:15 Old Information and New Information, Nouns and Verbs for Academic Writing
15:30 Self-editing
16:00 End of the day

Scientific Writing: The "Editing Clinic": Revising English Texts

Day 2, 5.10.2017 at 9-16 o'clock (both groups) (Room 114, Virta building)

The students select a scientific text from their field and also bring in two to three pages of their own writing (5 copies of these pages). These texts will be evaluated in class.

9:15-10:30 Introduction to editing. Practice of editing on the "ideal" article in your field
10:30-10:40 Short break
10:40-11:30 Editing
11:30-12:10 Lunch  (40 min.)
12:10-14:00 Editing groups
14:00-14:20 Coffee break (20 min.)
14:20-15:25  Editing Groups
15:25-16:00  Course Discussions (Questions and Answers)
16:00   End of the course

Teacher: Lecturer Kathleen Moore

Enrolment in NettiOpsu. The maximum number of students is 18 in both groups. Selection method is draw. The student has to check the selection from NettiOpsu (Courses > Enrolments) after the enrolment period.

Learning outcomes:

Goal of this online course is to get the participant acquainted with the processes of systematic information management within the participants’ own research work. After completing the course, the participant

• will be able to seek and manage information efficiently
• recognizes how metrics can be utilized in evaluating scientific visibility and impact
• understands the open science principles in research publication and can assess scientific publication channels
• knows the key principles of research data management

Student group: Doctoral researchers and researchers

Contents:
Module 1: Scientific literature retrieval
Module 2: Visibility and impact
Module 3: Research data management
Module 4: Open Access publishing

Organised by: Tampere University Library

People in charge: Tomi Toikko, Sari Leppänen, Saija Tapio

Teaching period:  2.10.2017 – 12.11.2017. All modules will last for one week (during 2.10. – 29.10.). All exercises are expected to be returned on 12.11. at the latest.

Modes of study: Online course. The participant is expected to complete the weekly exercises on time by utilizing the course materials present on the platform. The exercises include short essays, quizzes and discussions with other participants.

Group size: No limit

Enrolment: Via Nettiopsu

Enrolment time: Until 18.9.2017

Evaluation: Pass/fail

Evaluation criteria: Active participation in web-based working and exercises done on time.

More information: tomi.toikko@staff.uta.fi

General description

Planning makes perfect they say, and this holds true also when it comes to academic work. Do you wish to stop and think ahead how to make best use of your time, and to develop both your academic and transferable skills as a doctoral researcher? This concise two-day course provides practical tools and support for the management of the 4-year doctoral thesis project. The course is directed at doctoral students at the beginning phase of their studies.

The course
- Guides participants to identify and use the various tools already at their disposal
- Discusses forms of supervision and the supervisor- supervisee relationship
- Provides concrete tools for planning & managing the writing process
- Encourages doctoral researchers to better their media skills and digital research profiles
- Discusses how to use academic conferences as a means of chapter and article writing
- Encourages doctoral researchers to share their experiences and expertise

Place: 18.9. Room E222 (Main building), 25.9. Room E222 (Main building)

Programme:

Day 1: 18.9.2017
09.15-12.00   Identifying academic skills and tools
12.00-13.00    lunch break
13.00-16.00   ‘Using’ vs. ‘going to’ academic conferences: A before - during and after model


Day 2:  25.9.2017
09.15-12.00   Having a practical map for it all: drafting your thesis outline
  Developing and updating our own digital research profile
12.00-13.00   lunch break
13.00-16.00   Giving and receiving feedback: supervisory relationships from start to finish.

PLEASE NOTE: Attendance to BOTH days is required for the completion of the course.

Teacher: Dr. Pirjo Nikander

Pre-assignment: Please write a short (one A4) text stating:
1)    Your name & field of research
2)    The format of your thesis to be (article doctorate/monograph)
3)    3 key journals + 3 key conferences in your own field
4)    3 issues that you find are the most challenging when it comes to managing the day-to-day reality of thesis writing.
5)    Your digital profile today. Do you use: ResearchGate, Twitter, Academia.edu, or LinkedIn?

DEADLINE for the pre-assignments is Mon 11.9.2017 (noon).
In addition participants will write a mini-assignment before the second meeting. Both assignments will be sent through Moodle,

Enrolment via NettiOpsu. Maximum number of students is 20. Selection method is draw. Students should check the selection result via NettiOpsu after the enrolment period.

After the course, the participants
•    have a deeper understanding of the need, importance and practicalities of research mobility
•    are aware of and able to identify opportunities available to undertake international research mobility
•    know the different sources of funding available and how best to access them
•    are able to design a mobility plan
•    receive the necessary support to execute their mobility plan

Description
International research mobility is a crucial part of academic life for universities and particularly for the early stage researcher. Shorter and longer-term stays abroad not only support one’s research work, develop one’s research qualification and network but also contribute to personal development and networking skills on a broad range. This course offers practical tools, guide, information and support necessary to successfully engage in international mobility during one’s doctoral research career.

Course Schedule

Day 1: 9.10.2017 in Room C5 (Main building)
Time: 9-16

9:15-9:30 Opening words, Participants’ introduction
9:30-10:30 Research Mobility: What, why, how, when and where?
10:30-11:00 UTA policy and support for mobility – Lecture by International education office
11:00-11:30 Funding opportunities for mobility 1 (Internal and external funding)
11:30-12:30 Lunch
12:30-13:30 Funding opportunities for mobility 2 (Workshop tailored to student’s need): databases and search strategies
13:30-14:30 Practical issues to consider before, during and after mobility (International HR office)
14:30-14:45 Coffee break
14:45-15:30 Cultural issues commonly faced during mobility
15:30-16:00 Instructions on assignment and groups

Day 2: 23.10.2017 in Room C5 (Main building)
Time: 9-16

9:15-9:30 Working in a new environment
9:30-10:00 Building useful networks
10:00-11:00 Class discussion- Participants to share insights from the interviews conducted (see below)
11:00-11:15 Coffee Break
11:15-12:15 Class discussion- Participants to share insights from the interviews conducted (see below)
12:15-13:15 Lunch
13:15-14:15 Group session for peer-to-peer feedback on mobility plan
14:15-15:15 Optimising your mobility for future career opportunities
15:15-15:45 Closing words

Teacher: Ms.Sci. Motolani Agbebi

Pre-assignment: To participate in this course, please provide a short pre-assignment through Moodle outlining the following:
•    Your name and discipline
•    Stage in doctoral studies
•    Two main issues you would most like to know about undertaking research mobility or obstacles to undertaking research mobility
•    Details of your mobility experience or plans if any, and mobility types and potential funding sources/forms you wish to target.

Between the course days’ assignment:
•    participants will be asked to discuss their plan or desire to embark on a study or research visit abroad with their supervisor(s), should they not have already done so
•    Participants are required to design a mobility plan.
•    Participants are to carry out an interview with one doctoral researcher or post-doc researcher in their faculty on the overall experience during mobility. This should include details on planning, being and returning from a period abroad.
•    Participants are required to submit an updated mobility plan a week after the course is completed. Students will be strongly encouraged and offered support by the doctoral school, the international office and their supervisors to implement their mobility plans.

Number of students: Max. 20 (priority will be given to 2nd year doctoral students, otherwise selection method is draw)

Organised by: UTA Doctoral School and UTA International Education Office

Modes of completion: Pre-Assignment, mobility plan, active participation, peer to peer feedback.

Evaluation: Pass/Fail

Target group: New and newish non-Finnish doctoral researchers of the University of Tampere

Content: Organization of doctoral studies at the University of Tampere, Joint doctoral studies, Funding opportunities, Library services, Supervision and planning of studies

Time: 8.9.2017 at 13-16 o'clock

Place: Room C5 (Main building)

Programme:

13.15-13.30 Welcome to the University of Tampere
13.30-14.00 Organization of doctoral studies at the University of Tampere, Joint doctoral studies (coordinator Olli Nuutinen)
14.00-14.30 Funding opportunities (Markku Ihonen, Research development director)
14.30-14.50 International HR Team at Your Service! (Jonna Rinne, HR Services)
14.50-15.10 Coffee break
15.10-15.30 Library services  (Tomi Toikko, Information specialist)
15.30-16.00 Supervision and tips on Planning and Managing your Doctoral Process (Research Director Pirjo Nikander)
16.00 -16.20 About University of Tampere Association of Researchers and Teachers (shop steward Mikko Poutanen, TATTE)

Responsible teacher: Dr. Pirjo Nikander

Pre-registration with e-form:
https://elomake3.uta.fi/lomakkeet/827/lomake.html?rinnakkaislomake=registration

NB! No credits are awarded.

IASR Lectures are studia generalia lectures in the study of society given weekly by the fellows of the Institute for Advanced Social Research (IASR) and the New Social Research Programme (NSR). Although the lecture topics vary, they always touch the study of society in one way or another.

Programme: http://www.uta.fi/iasr/lectures/

Doctoral researchers can get 2 ECTS for attending a minimum of six IASR Lectures, altogether 6 ECTS at the maximum. These 2 ECTS for attending 6 lectures can be earned during two successive semesters.

Responsible teacher: Dr. Risto Heiskala

No pre-registration.

Learning outcomes:

The aim of this course is to strengthen the general researcher skills of the participant by training her to grasp her own particular field of research in a wider and more general context through some central issues in philosophy of science.

Teaching schedule: 19.10. and 26.10.2017 at 9-16 o'clock.

Place: 19.10. Lecture hall D11 (Main building), 26.10. Room C6 (Main building)

General description:

The course consists of alternating sessions of lectures and discussions. The lectures will cover some central themes in philosophy of science, and these will then be further discussed in smaller groups whose members (to the extent that this is possible) come from related scientific fields.

Course contents:

1. Objects of Study and the Classification of Sciences
2. Concepts, Propositions, and Arguments
3. Hypotheses, Explanations, and Justification
4. Scientific Realism and Antirealism

Completion: Passing the course requires a tight following of the lectures and an active participation in the group discussions. There will be no final exam as such, but the participants are required to produce a three-page written presentation where one of the central themes of the course is connected with the participant’s own scientific field and research topic.

Teacher: Docent, PhD Heikki J. Koskinen

Enrolment in NettiOpsu. The maximum number of students is 50 (4 places reserved for TUT students). Selection method is draw.

Learning outcomes:

Goal of this online course is to get the participant acquainted with the processes of systematic information management within the participants’ own research work. After completing the course, the participant

• will be able to seek and manage information efficiently
• recognizes how metrics can be utilized in evaluating scientific visibility and impact
• understands the open science principles in research publication and can assess scientific publication channels
• knows the key principles of research data management

Student group: Doctoral researchers and researchers

Contents:
Module 1: Scientific literature retrieval
Module 2: Visibility and impact
Module 3: Research data management
Module 4: Open Access publishing

Organised by: Tampere University Library

People in charge: Tomi Toikko, Sari Leppänen, Saija Tapio

Teaching period:  2.10.2017 – 12.11.2017. All modules will last for one week (during 2.10. – 29.10.). All exercises are expected to be returned on 12.11. at the latest.

Modes of study: Online course. The participant is expected to complete the weekly exercises on time by utilizing the course materials present on the platform. The exercises include short essays, quizzes and discussions with other participants.

Group size: No limit

Enrolment: Via Nettiopsu

Enrolment time: Until 18.9.2017

Evaluation: Pass/fail

Evaluation criteria: Active participation in web-based working and exercises done on time.

More information: tomi.toikko@staff.uta.fi

After the course, the participants
•    have a deeper understanding of the need, importance and practicalities of research mobility
•    are aware of and able to identify opportunities available to undertake international research mobility
•    know the different sources of funding available and how best to access them
•    are able to design a mobility plan
•    receive the necessary support to execute their mobility plan

Description
International research mobility is a crucial part of academic life for universities and particularly for the early stage researcher. Shorter and longer-term stays abroad not only support one’s research work, develop one’s research qualification and network but also contribute to personal development and networking skills on a broad range. This course offers practical tools, guide, information and support necessary to successfully engage in international mobility during one’s doctoral research career.

Course Schedule

Day 1: 9.10.2017 in Room C5 (Main building)
Time: 9-16

9:15-9:30 Opening words, Participants’ introduction
9:30-10:30 Research Mobility: What, why, how, when and where?
10:30-11:00 UTA policy and support for mobility – Lecture by International education office
11:00-11:30 Funding opportunities for mobility 1 (Internal and external funding)
11:30-12:30 Lunch
12:30-13:30 Funding opportunities for mobility 2 (Workshop tailored to student’s need): databases and search strategies
13:30-14:30 Practical issues to consider before, during and after mobility (International HR office)
14:30-14:45 Coffee break
14:45-15:30 Cultural issues commonly faced during mobility
15:30-16:00 Instructions on assignment and groups

Day 2: 23.10.2017 in Room C5 (Main building)
Time: 9-16

9:15-9:30 Working in a new environment
9:30-10:00 Building useful networks
10:00-11:00 Class discussion- Participants to share insights from the interviews conducted (see below)
11:00-11:15 Coffee Break
11:15-12:15 Class discussion- Participants to share insights from the interviews conducted (see below)
12:15-13:15 Lunch
13:15-14:15 Group session for peer-to-peer feedback on mobility plan
14:15-15:15 Optimising your mobility for future career opportunities
15:15-15:45 Closing words

Teacher: Ms.Sci. Motolani Agbebi

Pre-assignment: To participate in this course, please provide a short pre-assignment through Moodle outlining the following:
•    Your name and discipline
•    Stage in doctoral studies
•    Two main issues you would most like to know about undertaking research mobility or obstacles to undertaking research mobility
•    Details of your mobility experience or plans if any, and mobility types and potential funding sources/forms you wish to target.

Between the course days’ assignment:
•    participants will be asked to discuss their plan or desire to embark on a study or research visit abroad with their supervisor(s), should they not have already done so
•    Participants are required to design a mobility plan.
•    Participants are to carry out an interview with one doctoral researcher or post-doc researcher in their faculty on the overall experience during mobility. This should include details on planning, being and returning from a period abroad.
•    Participants are required to submit an updated mobility plan a week after the course is completed. Students will be strongly encouraged and offered support by the doctoral school, the international office and their supervisors to implement their mobility plans.

Number of students: Max. 20 (priority will be given to 2nd year doctoral students, otherwise selection method is draw)

Organised by: UTA Doctoral School and UTA International Education Office

Modes of completion: Pre-Assignment, mobility plan, active participation, peer to peer feedback.

Evaluation: Pass/Fail

IASR Lectures are studia generalia lectures in the study of society given weekly by the fellows of the Institute for Advanced Social Research (IASR) and the New Social Research Programme (NSR). Although the lecture topics vary, they always touch the study of society in one way or another.

Programme: http://www.uta.fi/iasr/lectures/

Doctoral researchers can get 2 ECTS for attending a minimum of six IASR Lectures, altogether 6 ECTS at the maximum. These 2 ECTS for attending 6 lectures can be earned during two successive semesters.

Responsible teacher: Dr. Risto Heiskala

No pre-registration.

The course focuses on the basic and general features of scientific research, methodology, and argumentation, as applicable to any field of study. Some central themes in the philosophy of science will also be discussed, in an introductory manner.

The course is intended to all new international UTA Master’s degree students, but it will serve also international Doctoral students. Other degree and exchange students may join if there are free places.

Contact person: Coordinator of international education, Anna Wansén-Kaseva

Visualization of quantitative data when reporting and publishing findings

Course description:

It is commonly said that “a picture is worth a thousand words”. The same is true when reporting findings of an analysis of quantitative data. A proper visualization of the results might make the difference between the success and failure in telling a story or in publishing one’s findings. This course gives, first, a brief introduction to the R software and to D3 JavaScript library for manipulating documents based on data. Second, the course focuses on visualization of quantitative data which is of utmost importance when reporting and publishing findings. Examples and applications will be done for multivariate, temporal, spatial and text data. Examples used during the course will be based on the R software, and preliminary knowledge of this software is advisable but nor required. Participants can learn more about the R software prior to the course online at: http://www.uta.fi/cast/events/Ronline.html.

Goals: The course:

• Introduces participants to the R environment and to D3
• Introduces the participants to data exploration and data visualization
• Provides a recent variety of techniques and strategies to visualize quantitative data

Place: Computer classroom Ml 50 Linna

Programme

Day 1: 3.11.2017

09.15-12.00   Introduction to R

12.00-13.00   Lunch break

13.00-16.00   Introduction to data exploration and data visualization: types of data and of databases; online databases; Visualization of multivariate data

Day 2: 10.11.2017

09.15-12.00   Visualization of temporal data and of spatial data; text visualization

12.00-13.00   lunch break

13.00-16.00 Introduction to D3; Real time big data applications

PLEASE NOTE: Attendance to BOTH days is required for the completion of the course.

Teacher: Paulo Canas Rodrigues

Pre-assignment: Please write a short (one A4) text stating:

1)    Your name & disciplinary background

2)    State your own motivation for participating on this course and what do you expect to learn.

DEADLINE for the pre-assignments to be announced.

In addition, participants will write a mini-assignment after the second meeting with a two weeks’ deadline.

Enrolment via NettiOpsu. Maximum number of students is 24. Selection method is draw. Students should check the selection result via NettiOpsu after the enrolment period.

Learning outcomes

On completion of the course, the participants
•    are more aware of discipline-specific academic conventions, i.e. the academic conventions of their field
•    are able to read and assess the relevancy of articles in a faster and more efficient manner
•    are aware of their responsibilities and role as peer reviewers
•    are able to understand the expectations of their target audience,  in order to tailor their  own research articles for specific contexts
•    are aware of the different functions of language in academic writing in English: i.e.
o    how to interpret writer’s attitude, level of commitment
o     the  use of tense, voice, register
o    how to create cohesion

Contents

In order to attain the intended learning outcomes, the participants will take an active role. They will be given guidance and information in the form of mini-lectures. However, students will be asked to  deconstruct articles in their own field, analyze journals in order to gain a better understanding of their expectations and profile,  and act as peer reviewers.

Special attention will be given to address the multidisciplinary concerns of the groups and focus will also be given to gaining a better understanding of the language and structural functions of writing for research. Although academic disciplines are different, many of the same key strategies and components can be used.

Target group

The course is intended for post-graduate students who feel  that they need support in writing and reading research in English.

Proficiency level

B2=>C1 (European framework)

Teaching methods

Contact classes and independent assignments.

Schedule and place:

November 17, 2017 at 9.15-16 (Room 113, Virta building)
November 24, 2017 at 9.15-16 (Room C5, Main building)
December 1, 2017 at 9.15-16 (Room C5, Main building)

Teacher: Christine Horton

Student selection

At the maximum 20 students group. Selection method is draw. The student has to check the selection from NettiOpsu after the enrolment period.

Evaluation and evaluation criteria

Continuous self-assessment, peer assessment and assessment by the instructor. Pass/fail.

Goals:
1. To begin, proceed, digress, summarize and end a presentation, and to respond to questions in an effective manner
2. To convert written into spoken English: stylistic differences
3. To practice correct pronunciation and intonation
4. To deliver a talk in a relaxed manner using effective visual aids, but without reading
5. To analyze one's own presentation and (in groups) others' presentations in a supportive, affirmative manner, including attention to body language and visual aids.

Contents:

Day 1  (common to both groups) in Room 114, Virta building

2.11.2017

9:15-10:30 Structure of English presentations; Introduction and Conclusions-tips
10:30-10:45 Break
10:45-11:30 Language performance issues
11:30-12:10   Lunch
12:10-14:00   Preparing and Using Visuals: Tips and Concerns
14:00-14:20   Coffee
14:20-16:00   Training for the Question-and-Answer period at conferences

Day 2 

- group 1: 9.11.2017 in Room C5, Main building
- group 2: 16.11.2017 in Room K112, Linna building

9:15-10:30  Individual Presentations + Judges feedback and evaluation
10:30-10:45  Break
10:45-11:30  Individual Presentations + Judges feedback and evaluation
11:30-12:10  Lunch
12:10-14:00  Individual Presentations + Judges feedback and evaluation
14:00-14:20 Coffee
14:20-16:00  Individual Presentations + Judges feedback and evaluation

Teacher: Lecturer Kathleen Moore

Enrolment in NettiOpsu. The maximum number of students is 10 in all  groups. The selection method is draw. The student has to check the selection from NettiOpsu (Courses > Enrolments) after the enrolment period.

Knowledge about statistical methods and data analysis is of great importance in almost any field of research. In this course, general concepts of statistics will be provided so that the students can be able to independently carry out a small scale empirical research with the statistical software R.

Contents

1. Basic concepts (1 lecture)
   1. What is statistics?
   2. Statistical research and its phases of work
   3. Population and sample
   4. Types of variables and scales of measurement
2. Descriptive statistics (2 lectures)
   1. What is data?
   2. summary statistics (mean, median, quartiles, standard deviation and variance)
   3. Plotting the data (scatter plot, histogram, QQ-plot and boxplot)
   4. Contingency tables
3. Basics of statistical inference (4-5 lectures)
   1. Basic concepts of probability
   2. Probability distributions (Binomial and Normal)
   3. Basic concepts in sampling theory
   4. Confidence intervals (mean and difference of means in independent samples)
   5. Hypothesis testing (mean and equality of means in independent samples, type I and type II-errors and p-values)
   6. Introduction to some non-parametric tests
4. Linear models (3 lectures)
   1. Introduction to linear regression
   2. Basics of logistic regression
   3. Basics of Analysis of Variance (ANOVA)

A maximum number of 50 students will be allowed in this course (70% doctoral students and 30% masters students).

Please note that this course cannot be included inside the minimum 120 ECTS of Master's Degree Programme in CBDA (basic level course).

MTTTP1 Tilastotieteen johdantokurssi lectured in period I, II or III-IV is recommended for Finnish students.

Are most published research findings false (Ionnadis, 2005, Open Science Collaboration, 2015)? The course deals with the interpretations of and possible solutions to the lack of replicating results in empirical research (e.g. social psychology and cancer research). As a result of the lack of successful registered replications, a growing number journals such as Psychological Science are favouring practices such as direct replications and registered reports. The course gives a hands-on introduction to two methods which are thought to improve the reliability and replicability of empirical research: p-curve analysis and pre-registration.

The course:

• Introduces participants to the ongoing conversation about the replicability of empirical research
• Introduces participants to different interpretative frameworks of p-values and statistical significance (Null Hypothesis Significance Testing, Fisher, Neyman-Pearson, Bayes)
• Provides participants with skills for pre-registration and p-curve analysis

Masters Degree students of CBDA-programme: course can be included in the advanced studies of CBDA (Statistical Data Analytics). For details, contact your Personal Study Plan teacher.

Learning outcomes
The focus of the course is on the acquisition of the skill of discerning and evaluating arguments found in scientific (or more broadly, academic) texts. The aim of the course is to provide students with analytic tools that enable and facilitate the construction and assessment of justifications for hypotheses and theories. On completing the course, the students will have a strong working grasp of different types of arguments, their interplay and the fallacies related to them.  On a more general level, the students will gain an appreciation of the nature and role of rational, intersubjective justification of claims as part of scientific inquiry.

Course contents
1. Justification: Assertions and grounds
2. Argumentation as a form of justification: types of arguments, types of fallacies
3. Deductive reasoning and its uses in justification
4. Observation, data, statistical inference: inductive reasoning and its uses in justification
5. Causal and hypothetical inference
6. Theoretical virtues and justification

Place: to be announced

Course schedule

17.1.2018 at 10-16 o'clock, Room A2A (Main building)

24.1.2018 at 10-16 o'clock, Room A2A (Main building)

31.1.2018 at 10-16 o'clock, Room D13 (Main building)

7.2.2018 at 10-16 o'clock, Room Pinni B 4113

Teacher: PhD Antti Keskinen

Evaluation criteria
The course work consists of lectures, discussions and exercises. As the aim of the course is the acquisition of a practical skill of assessing arguments, special emphasis will be put on discussion and exercises. Passing the course requires active participation, and the production of a short essay (appr. 5 pages) in which the student applies the skills acquired during the course to her/his own research topic.

Evaluation
Pass/fail

Enrolment in NettiOpsu. Maximum group size 40. Selection method is draw.

General description: This course will give you practical tips and strategies for writing scientific articles in English. Designed as a two-day workshop, the main objective of this course is to learn to identify and produce the most important elements in English academic writing.

The first day offers a series of exercises and points to ponder, whereas the second day offers the students an opportunity to apply these tips and strategies in an "Editing Clinic". During the second day, the students will be taught a ten-step editing process that they will apply to texts in class.

Contents:

Day 1

group 1: 18.1.2018 at 9-16 o'clock in Room E350 (Main building)

CANCELLED! group 2: 25.1.2018 at 9-16 o'clock. Group 2 will be held on 8.2. at 9-16 o'clock in Room C7 (Main building).

9:15-9:45 Online sources: Scientific, clear, transparent
9:45-11:00 Drafting, Differences between Finnish and Anglo-American traditions
11:00-11:30  Components of a Scientific Article, The Sequence of Writing
11:30 Lunch
12:15 Problems, Transitions, Tenses
14:00 Coffee break
14:15 Old Information and New Information, Nouns and Verbs for Academic Writing
15:30 Self-editing
16:00 End of the day

Scientific Writing: The "Editing Clinic": Revising English Texts

Day 2: 1.2.2018 at 9-16 o'clock in Room A2A (Main building)

both groups

The students select a scientific text from their field and also bring in two to three pages of their own writing (5 copies of these pages). These texts will be evaluated in class.

9:15-10:30 Introduction to editing. Practice of editing on the "ideal" article in your field
10:30-10:40 Short break
10:40-11:30 Editing
11:30-12:10 Lunch  (40 min.)
12:10-14:00 Editing groups
14:00-14:20 Coffee break (20 min.)
14:20-15:25  Editing Groups
15:25-16:00  Course Discussions (Questions and Answers)
16:00   End of the course

Teacher: Lecturer Kathleen Moore

The maximum number of students is 18 in both groups. Selection method is draw. The student has to check the selection from NettiOpsu after the enrolment period.

Evaluation: Pass/fail.

Study materials: Booklet handed out by the instructor.

Learning outcomes

On completion of the course, the participants
•    are more aware of discipline-specific academic conventions, i.e. the academic conventions of their field
•    are able to read and assess the relevancy of articles in a faster and more efficient manner
•    are aware of their responsibilities and role as peer reviewers
•    are able to understand the expectations of their target audience,  in order to tailor their  own research articles for specific contexts
•    are aware of the different functions of language in academic writing in English: i.e.
o    how to interpret writer’s attitude, level of commitment
o     the  use of tense, voice, register
o    how to create cohesion

Contents

In order to attain the intended learning outcomes, the participants will take an active role. They will be given guidance and information in the form of mini-lectures. However, students will be asked to  deconstruct articles in their own field, analyze journals in order to gain a better understanding of their expectations and profile,  and act as peer reviewers.

Special attention will be given to address the multidisciplinary concerns of the groups and focus will also be given to gaining a better understanding of the language and structural functions of writing for research. Although academic disciplines are different, many of the same key strategies and components can be used.

Target group

The course is intended for post-graduate students who feel  that they need support in writing and reading research in English.

Proficiency level

B2=>C1 (European framework)

Teaching methods

Contact classes and independent assignments.

Timetable

19 January, 2018 at 9.15-16 o'clock in Room A32 (Main building)

26 January, 2018 at 9.15-16 o'clock in Room A32 (Main building)

2 February, 2018 at 9.15-16 o'clock in Room A32 (Main building)

Teacher: Christine Horton

Student selection

At the maximum 20 students group. The selection method is draw. The student has to check the selection from NettiOpsu after the enrolment period.

Evaluation and evaluation criteria

Continuous self-assessment, peer assessment and assessment by the instructor. Pass/fail.

IASR Lectures are studia generalia lectures in the study of society given weekly by the fellows of the Institute for Advanced Social Research (IASR) and the New Social Research Programme (NSR). Although the lecture topics vary, they always touch the study of society in one way or another.

Programme: http://www.uta.fi/iasr/lectures/

Doctoral researchers can get 2 ECTS for attending a minimum of six IASR Lectures, altogether 6 ECTS at the maximum. These 2 ECTS for attending 6 lectures can be earned during two successive semesters.

Responsible teacher: Dr. Risto Heiskala

No pre-registration.

The course focuses on the basic and general features of scientific research, methodology, and argumentation, as applicable to any field of study. Some central themes in the philosophy of science will also be discussed, in an introductory manner.

The course is intended to all new international UTA Master’s degree students, but it will serve also international Doctoral students. Other degree and exchange students may join if there are free places.

Contact person: Coordinator of international education, Anna Wansén-Kaseva

IASR Lectures are studia generalia lectures in the study of society given weekly by the fellows of the Institute for Advanced Social Research (IASR) and the New Social Research Programme (NSR). Although the lecture topics vary, they always touch the study of society in one way or another.

Programme: http://www.uta.fi/iasr/lectures/

Doctoral researchers can get 2 ECTS for attending a minimum of six IASR Lectures, altogether 6 ECTS at the maximum. These 2 ECTS for attending 6 lectures can be earned during two successive semesters.

Responsible teacher: Dr. Risto Heiskala

No pre-registration.

The course focuses on the basic and general features of scientific research, methodology, and argumentation, as applicable to any field of study. Some central themes in the philosophy of science will also be discussed, in an introductory manner.

The course is intended to all new international UTA Master’s degree students, but it will serve also international Doctoral students. Other degree and exchange students may join if there are free places.

Contact person: Coordinator of international education, Anna Wansén-Kaseva

This course invites students in various stages of their doctoral thesis to think through, write and process the ethical questions and themes in their own ongoing research projects. It provides a compact knowledge package on ethical issues concerning the research design, data collection/field work and writing-up phases. The course consists of lectures, discussion & student presentations in class and assignments.

Learning outcomes: After the course, students will

- be better equipped to think about and deal with ethical issues at different phases of their research projects
- have skills to discuss and identify issues concerning the ethics both in relation to research participant and the academic community (treatment of participants, informed consent, data lifespan, publication and ethical reporting)
- have knowledge on the key guidelines concerning ethical conduct and know where to go for further information
- have practical tools and means for the writing-up of ethical question in the doctoral thesis.
- have access to an information package on ethics
- know the basic functions of Turnitin plagiarism checker programme

Course Schedule:

Lectures

Fri 13.4.2018 at 12-16 o'clock, Room E221 (Main building)

Fri 20.4.2018 at 12-16 o'clock, Room E221 (Main building)

Fri 27.4.2018 at 12 -16 o'clock, Room E221 (Main building)

Workshop

Fri 4.5.2018 at 10-16 o'clock, Room D14 (Main building)

Fri 11.5.2018 at 10-16 o'clock, Room D14 (Main building)

Enrolment in NettiOpsu. At the maximum 20 students (2 places reserved for TUT students). TUT students apply the right to study through the Service of Cross-Institutional Studies. 

Priority in selection is given to non-Finnish-speaking students. Otherwise, selection method is draw. Please check the selection result from NettiOpsu after the enrolment period.

Completion mode: Those accepted to the course are required to send in a pre-assignment (max one page A 4) through Moodle. Active participation is required. Every student will give a 15-20 minutes presentation in the workshop. Every student will write an 6-7 pages essay after the course.

THE PRE-ASSIGNMENT: Please include the following in short:
1)    Your name & discipline
2)    Your Research topic
3)    Potential ethical issues you have encountered or anticipated to encounter as part of your doctoral research and solutions you may already have in mind
4)    Any issues relating to research ethics you wish to be discussed during the course
5)    It is presumed that you could present briefly during the course the ethical questions that you are facing during your research.

Learning outcomes

After the course, participants:

- recognize different approaches to reading, analyzing and interpreting interview data

- are aware of crucial issues concerning scientific and analytic rigour

- find relevant literature on theoretical and analytical aspects on interviews

- are able to discuss the validity and ethics of their own interview research

Course Description

The qualitative interview has become one of the most frequently used methods to generate data to make sense of our lives, and an invaluable tool for the qualitative researcher. Whether chosen as the default and sole means of data generation on its own, or combined with other forms of data gathering and analyses, interview practice continues to evolve, diversify and flourish. This three-day course focuses on the analysis of interview data. It deals with the variety of styles and traditions of analysis, the practical aspects and steps along the way, as well as key questions analyst should be asking and the practical coding tools available.  The course consists of lectures on specific analytic stances and approaches by specialist in the field, discussion on doctoral researchers’ own ongoing analysis and the key questions tackled therein, and information on relevant software (Atlas.ti) one can use to code the data and support the analysis phase.

Time: 10.4. 17.4. & 24.4. 10.15 - 16.00

Teacher in charge: Pirjo Nikander, Univ. of Tampere + key experts in the field

Number of students: 25

Place: Linna K110

Tue 10.4.2018

10.15-12.00      Introduction to the course themes and to the ongoing research projects of the participants

12.00-13.00      Lunch

13.00-14.00      The variety of data generation and epistemological stances to interview data

14.00-16.00      Discussion on participants’ data sets, the questions raised in pre-assignments and on-going projects

Tue 17.4. 2018

10.15-11.00      Crossing that hurdle: From data generation to analysis proper  

11.00-12.00      Dr. Zsuzsa Millei (Research Collegium) Poststructural discourse analysis: Reading data of children in institutional settings

12.00-13.00      Lunch

13.00-14.00     Jaakko Hyytiä (University of Tampere): Using Atlas.ti to manage and code your interview data

14.-16.00           Presentations by participants + discussion

Tue 24.4.2018

10.15-12.00      Ilkka Pietilä (Assistant prof. University of Helsinki) Analysing group interviews: a focus on interaction

12.00-13.00      Lunch

13.00-16.00     Presentations by participants + discussion

The course consists of active participation to ALL THREE days and of a pre-assignment. Your pre-assignment is sent to Moodle (deadline 31.3.2018) and should include the following:

Pre-assignment:

1. You name and disciplinary background

2. Your topic of research, the stage you are currently in (collecting data, analyzing interviews + potentially data gathered by other means), your analytic tools and means of analysis (how do I approach my interview data).

3. What you find most challenging when working with your data?

4. What you expect to learn and discuss during the course.

5. Indication of your wish to present or discuss your work and analysis during the course.

Evaluation: pass/fail, students presenting data or presenting on their ongoing analytic process will receive 3 ECTS, others 2 ECTS.

Learning outcomes
After the course, the student:
•    has developed an understanding of the nature of bibliometric research
•    is familiar with the most commonly utilised sources of bibliometric data and ways of applying this data in (daily) research conduct
•    is able to collect bibliometric data and to apply this data in various research settings
•    is able to utilise bibliometric tools for the benefit of his/her thesis writing and future career building
•    understands the limitations of bibliometric data and methods

General description
First, bibliometrics is a methodological approach in which the scientific literature itself becomes the subject of analysis. Bibliometrics offers a powerful set of tools that help scholars to, for example:

• delineate samples for literature reviews

• understand scientific citations

• investigate the research impact of authors, journals and institutes

• identify the most influential works of a given topic

• map the cognitive and organisational characteristics of research fields

• describe scientific networks within the knowledge base of distinct disciplines

• produce indicators for use in policy and management contexts

• understand the basics of (statistical) meta-analysis

As such, bibliometrics can be considered as the science of science.
Second, making an impact in the scientific community is a must for young researchers aiming for building a career at the university. Bibliometrics provides researchers a means of promoting and monitoring their own research impact.
This course focuses on the general features of bibliometrics 1) as a pivotal tool for conducting research and 2) as an integral part of building a research career.

Teaching schedule: 5.3. and 6.3.2018 at 10–16 o'clock

Teacher: Dr. Teemu Makkonen

Place: Computer Classroom Ml 50 (Linna building)

Completion: Those accepted to the course are required to send in a pre-assignment through Moodle. During the lectures and exercises, active participation is required. After the course, every student will write a short essay on how to apply bibliometrics in connection to their own scientific field and research topic.

Evaluation: Pass/Fail.

Enrolment: In NettiOpsu. Number of participants 20 at the maximum. Selection method is draw. Students should check the selection result from NettiOpsu after the enrolment period.

Course pre-assignment:
Before the course, course participants are expected to write a short summary-description (max 2–3 pages) of their own doctoral research by introducing:
1)    the topic of their research,
2)    the discipline and specific research field they are engaged in
3)    the “keywords” of their thesis, significant works (books, book chapters, articles) they are referring to in their research
4)    (if applicable) a list of their own published work.
Detailed instructions will be made available to enrolled students through Moodle.

Learning outcomes
After completing the course, the participants
- know the phases of the process of knowledge discovery (data prepocessing, data mining and postprocessing)
- know basic data mining tasks and methods
- are aware of possibilities of utilising data mining in different research fields

Description

In data mining, large quantities of data are explored and analysed by automatic and semi-automatic means to discover novel, interesting information. Data mining is an interdisciplinary field combining e.g. methods from computer sciences and statistics. It has wide, diverse application areas from education, social, business and administrative sciences to medical and life sciences.

Course contents
-    Lectures 10 h
-    Hands-on exercises with data mining tools 10 h
-    Reading research articles related to applications of data mining methods in participant’s own field and writing a short report
-    Giving a presentation on applications of data mining in participant’s own field (presentation session 3 h)

Teachers: Kati Iltanen, Martti Juhola, Henry Joutsijoki

Target group
The course is intended for post-graduate students who are interested in data mining. No computer sciences or statistics background is required.

Enrolment: At the maximum 15 students. Selection method is draw.

Teaching:

Lectures:
Wed 2.5.2018 at 10-12 Pinni B1083
Fri 4.5.2018 at 10-12 Pinni B1083
Wed 9.5.2018 at 10-12 Pinni B1083
Fri 11.5.2018 at 10-12 Pinni B1083
Wed 16.5.2018 at 10-12 Pinni B1083

Practices:

Wed 2.5.2018 at 12-14 computer classroom Pinni B1084
Fri 4.5.2018 at 12-14 computer classroom Pinni B1084
Wed 9.5.2018 at 12-14 computer classroom Pinni B1084
Fri 11.5.2018 at 12-14 computer classroom Pinni B1084
Wed 16.5.2018 at 12-14 computer classroom Pinni B1084

Presentation session
Fri 25.5.2018 at 10-13 Pinni B1083


Evaluation: Pass/fail

Learning outcomes: Students get familiar with various aspects of scientific communication.

Form of education: Lectures 14 hours, different lecturers

Lecture hall: Arvo-building F114, 1st floor

All our lectures begin at 15.15

7.3.2018
15.15-15.20 Opening the course, Kalle Kurppa
15.20-16.15 Writing a scientific article from biomedical research, Kalle Kurppa
 
14.3.2018
15.15- 16.30 Science communications, Laura Tohka

28.3.2018
15.15-16.15 Statistical reporting, Heini Huhtala
16.30-17.45 Tables and statistical graphics, Raili Salmelin

18.4.2018
15.15- 16.45 The role of the editor in Scientific publishing, Timo Partonen
17.00- 18.15 Scientific lectures, congress abstracts and posters, Kalle Kurppa

25.4.2018
15.15- 16.00 Research article publishing: open access, Sari Leppänen
16.15- 18.00 Producing better English text, Robert Hollingsworth

9.5.2018
15.15- 16.00 Publishing a doctoral dissertation, Minna Mecklin
16.15- 17.00 Doctoral dissertation- practical aspects, Markku Kulomaa

Responsible teacher: Kalle Kurppa

Participants: Open to all. Especially recommended for doctoral researchers and students enrolled on the Tampere Research Training Program for Medical Students.

Evaluation: Pass/fail. Students write a learning diary on the basis of lectures.

Enrolment: Students are required to enrol the course with e-form: https://elomake3.uta.fi/lomakkeet/7859/lomake.html (open 22.1- 11.2.2018)

Course information

Learning outcomes: This course provides doctoral students with understanding over writing scientific journal articles. The lecture will motivate students to start writing sooner. After the lecture the student will understand what is required from a scientific article and what the related publishing processes entail. The student will know how to approach and write a scientific journal article effectively.

The lecture aims at providing tips to researchers in all fields. Especially starting researchers have experienced the lecture and workshop as very beneficial.

Contents: The course consists of

• lecture  at 12-16 (4 hours)
• pre-assignment
• seminar work (group 1) or (group 2)) at 9-16 o'clock

All students should take part in the lecture and the workshop.

Lecture on 22.5.2018 at 12-16 o'clock
Lecture hall Paavo Koli (Pinni A building)

Contents:
 - Practical tips for writing scientific articles
 - Improving chances for acceptance
 - Article logic, beginning and end
 - Editor's viewpoints
 - Group dynamics for writing articles
 - Discussion

Seminar

group 1 on 23.5.2018 at 9-16 o'clock (Room A05 Main building)

OR

group 2 on 24.5.2018 at 9-16 o'clock (Room A05 Main building)

Seminar will deepen issues discussed on the lecture.

Reference material: Tips for writing scientific journal articles

Pre-meeting assignment:

•             Read the guidebook "Tips for writing scientific journal articles" (http://herkules.oulu.fi/isbn9789514293801/isbn9789514293801.pdf). Choose a potential target journal where you wish to publish in the future. Analyse the structure, not substance, of 2-3 articles recently published in this journal by comparing them against the structure presented in the guidebook. If the structure in the target journal is different, please describe it. Write a report in text format (e.g. MSWord) of your observations, pay attention to any deviations in structure. 

•             Prepare a short presentation of your observations, for instance, using 3-4 PowerPoint slides. This presentation will be publicly shown in the workshop.
•             In the report, include your reflections about the issues you consider as bottlenecks in your scientific writing. These will be discussed in the workshop anonymously.
•             In the report, include the topics you wish to be discussed during the workshop
•             Please, remember to include your name, academic field, and your research topic

Pre-meeting assignment to be sent to course Moodle-area on 14.5.2017 at the latest (Moodle area address to be informed to students).

Lecturer: Dr Pekka Belt

More information about the lecturer: www.tinyurl.com/efficient-doctoral-studies

Enrolment: Enrolment in NettiOpsu either to group 1 or 2. The selection method is draw. The student has to check the selection from NettiOpsu after the enrolment period. Maximum 18 students per seminar group can be accepted.

Evaluation: Pass/fail.

Goals:

1. To begin, proceed, digress, summarize and end a presentation, and to respond to questions in an effective manner
2. To convert written into spoken English: stylistic differences
3. To practice correct pronunciation and intonation
4. To deliver a talk in a relaxed manner using effective visual aids, but without reading
5. To analyze one's own presentation and (in groups) others' presentations in a supportive, affirmative manner, including attention to body language and visual aids.

Contents:

Day 1 (common to both groups): 12.4.2018, Room A05 (Main building)

9:15-10:30 Structure of English presentations; Introduction and Conclusions-tips
10:30-10:45 Break
10:45-11:30 Language performance issues
11:30-12:10 Lunch
12:10-14:00 Preparing and Using Visuals: Tips and Concerns
14:00-14:20 Coffee
14:20-16:00 Training for the Question-and-Answer period at conferences

Day 2

group 1: 19.4.2018, Room C2 (Main building)

group 2: 26.4.2018, Room D12 (Main building)

9:15-10:30 Individual Presentations + Judges feedback and evaluation
10:30-10:45 Break
10:45-11:30 Individual Presentations + Judges feedback and evaluation
11:30-12:10 Lunch
12:10-14:00 Individual Presentations + Judges feedback and evaluation
14:00-14:20 Coffee
14:20-16:00 Individual Presentations + Judges feedback and evaluation

Teacher: Lecturer Kathleen Moore

The maximum number of students is 10 in each group. The selection method is draw. The student has to check the selection from NettiOpsu after the enrolment period.

Evaluation: Pass/fail.

Learning outcomes:

Goal of this online course is to get the participant acquainted with the processes of systematic information management within the participants’ own research work. After completing the course, the participant

• will be able to seek and manage information efficiently
• recognizes how metrics can be utilized in evaluating scientific visibility and impact
• understands the open science principles in research publication and can assess scientific publication channels
• knows the key principles of research data management

Student group: Doctoral researchers and researchers

Contents:
Module 1: Scientific literature retrieval
Module 2: Visibility and impact
Module 3: Research data management
Module 4: Open Access publishing

Organised by: Tampere University Library

People in charge: Miikka Sipilä, Sari Leppänen, Saija Tapio

Teaching period:  5.3.2018 – 8.4.2018. All modules will last for one week. All exercises are expected to be returned on 16.4.2018 at the latest.

Modes of study: Online course. The participant is expected to complete the weekly exercises on time by utilizing the course materials present on the platform. The exercises include short essays, quizzes and discussions with other participants.

Group size: No limit

Enrolment: Via Nettiopsu

Evaluation: Pass/fail

Evaluation criteria: Active participation in web-based working and exercises done on time.

More information: miikka.sipila@uta.fi

R is one of the most widely used software for statistics and data science. In this course, the students will have the chance to become familiar with basic R objects, operations, visualizations tools and programming. The course will have in-class and online components. The online material (more information here: http://www.uta.fi/cast/events/Ronline.html) should be done before the first day of the course or between the two in-class days of the course. The second in-class day of the course will offer the chance to get a deeper knowledge about R and to analyze own data.

Modes of study: pre-assignment, participation in course work

BOTH online and in-class parts are required for the completion of the course.

 Pre-assignment: Please write a short (half A4) text stating:

1)    Your name & disciplinary background

2)    State your own motivation for participating on this course and what do you expect to learn.

Maximum number of students is 20. Priority will be granted for the first enrolments, based on the proportions: 60% PhD students 30% MSc students and 10% BSc students. Students should check the selection result via NettiOpsu after the enrolment period.

Multilevel models are designed to explore and analyse data that come from populations which have a complex structure. Behavioural and social data commonly have a nested structure. Multilevel models are becoming an increasingly popular method of analysis for situations where responses are grouped, such as in schools or other institutions, neighbourhoods, firms, parliamentary constituencies, or any other social or spatial clusters. A particular version of multilevel modelling is where there are multiple measures on each respondent, so that the grouping is of measures within person; where these multiple measures are taken on successive occasions, multilevel modelling provides a means of modelling individual change over time. This course will emphasise the practical application of multilevel models and lectures will be combined with practical sessions in order to reinforce concepts.

Course contents

• Duration (2 days)
• Lectures (6 h)
• Hands-on exercises with MLM tools (6 h)

Flash presentation on application of MLM in participant’s own research or field (5-10 minutes each)

Target group
The course is intended for post-graduate candidates and researchers who are interested in the use of multi-level modelling in their research. Understanding of basic statistics is required.

Enrolment: At the maximum 24 students. Priority will be given to those who need MLM in their research (PhD researchers most especially).

For pre-selection evaluation, please write a short text stating:

• Your name and disciplinary background
• Your motivation for participating in the course and what you expect to learn