Thesis Design

Introduction

This course is dedicated to supporting your development as a master of science with a focus on high-level scientific skills relating to synthesis, analysis, logical reasoning, and the ability to communicate clearly in different mediums, with a focus on academic writing. We also extend attention to scientific rigor and replicability in literature review and experimental design (including participant recruitment, stimuli design/selection, experimental design, and analyses of outcomes).  In this course you will develop your research proposal for your thesis along with a proof-of-concept for your demonstrator, which will be a critical step for you in autonomous writing your thesis project.

Note that the course structure is subject to change -- perhaps more so than in other courses. This is a feature, not a bug. I want this class to provide you with the necessary intellectual framework for writing a thesis and performing research, on the one hand, while, on the other, I want to make time in class for you to write. In other words, part writing-workshop, part lecture. By design, many of the assignments will be done in class. This is also on purpose, by dedicating time to writing and reading, I believe students are more likely to develop good academic habits. Critical, then, is that you USE the time appropriately.

There are two read threads in this course which focus on the values of peer review and open science. In aligning with the dual themes of peer review and open science, this course is structured to not only enhance your academic and research skills but also to foster a culture of transparency, collaboration, and ethical scholarly practices. The emphasis on in-class writing and reading assignments is designed to provide you with dedicated time to refine your ideas, receive immediate feedback, and engage deeply with both the subject matter and your peers. This approach aims to cultivate a supportive learning environment where you can develop the skills necessary for independent research and critical analysis. The course will guide you through the process of transforming your ideas into a well-structured, scientifically sound, and rigorously peer-reviewed thesis proposal. By the end of this course, you should be well-equipped to undertake your thesis with confidence and a clear understanding of the principles of effective research and scholarly communication in the field of speech technology

Learning outcomes

Upon the successful completion of the course “Thesis Design”, you will be able to:

1. Perform a critical, targeted literature review in the field of voice technology.
2. Elaborate testable hypotheses based on the state-of-the-art in voice technology.
3. Perform novel scientific research autonomously related to the proposed thesis topic.
4. Elaborate standard experimental procedures related to the proposed thesis topic.
5. Work collaboratively in international, cross-cultural teams on shared experiments related to the proposed thesis topic.
6. Provide and receive critical peer review in a constructive way.
7. Share research outcomes through popular abstracts, posters and high level academic writing.
8. Design and perform a voice technology pilot study.

Course structure

The course runs for 8 weeks. Each week has 2 classes of 1 hour 45 minutes (with a 15 minute break in the middle).

Classes are on Monday (15:15 -- 17:00) and Wednesday (13:15 -- 15:00).

AI Policy

As an instructor, I acknowledge the evolving role of AI, specifically generative models like GPT, in academic research. Such tools offer significant potential in enhancing research methodologies, idea generation, and data analysis. However, their use must be aligned with our commitment to academic integrity, scientific rigor, and ethical standards. This policy outlines the responsible use of AI tools in the context of this course.

Principles of AI Usage

1. Transparency and honesty: Any use of AI-generated content in assignments, proposals, or research must be clearly indicated. Students are required to disclose when and how AI tools were utilized in their work.
2. Supplementary, not substitutive: AI tools should be used as an aid to supplement your own ideas and research, not to replace your original thought process or academic effort.
3. Ethical use: AI tools must be used in a manner that respects intellectual property rights, privacy, and data ethics. Misuse of AI for generating dishonest or misleading content is strictly prohibited.
4. Critical engagement: Students are expected to critically engage with and evaluate AI-generated content. Users should not accept AI outputs uncritically but should assess their relevance, accuracy, and applicability to the research context.
5. Learning and innovation: Students are encouraged to explore AI capabilities to augment their learning and research, understanding both the potential and the limitations of these technologies.

Application in Coursework

• AI-generated content may be used for initial drafts, idea generation, or data analysis but must be critically reviewed and revised by the student.
• Direct submissions of AI-generated content without significant student modification or contribution are not acceptable.
• In group projects, consensus on the use of AI tools should be reached and transparently reported.

Monitoring and Accountability

• The use of AI tools will be monitored through regular check-ins and reviews of student work.
• Students are encouraged to discuss their use of AI tools during office hours or class discussions, fostering an open dialogue on the ethical implications and best practices.

Consequences of Policy Violation

Non-compliance with these guidelines will be considered a breach of academic integrity and will be addressed according to the academic misconduct procedures with the Board of Examiners.

Contact information

Your instructor for the course is Dr Matt Coler (m.coler@rug.nl). For general questions you can contact the Educational Secretary or Student Service Desk (cf-sec@rug.nl, +31(0) 58 205 5009).

You can book an office hours meeting with Dr Coler here.

Practical Information

Literature

We will mostly be reading literature that is available online. Obligatory readings are either accessible through open access or online through SmartCat of the library.

Brightspace

We use the virtual learning environment “Brightspace” as the main platform for communication. If there is any necessary change on the syllabus, I will announce it in class and in Brightspace.

Assessment

Your final grade is calculated as per below. There is no final exam. Dates below are indicative. There may be changes depending on the speed with which we proceed.

Note the predominance of peer review in this course. Assessment rubrics can be found here.

Assignment	%	Date assigned	Date due
Participation	10	N/A	N/A
Peer review 1: RQ + Hypothesis	10	Week 2	Week 3
Peer review 2: RQ + Hypothesis + method	15	Week 4	Week 6
Peer review 3: Research proposal	35	Week 6	Week 8
Article presentation	15	Week 1	var
Interactive poster pitch	15	Week 5	Week 8
TOTAL	100

Assignment descriptions

• Participation: Active participation is crucial in this course. This includes engaging in class discussions, contributing to group activities, and consistent attendance. Students are expected to demonstrate engagement with course materials and contribute thoughtfully to peer interactions. Participation will be assessed on the quality of contributions rather than quantity. Note that during class you may be requested to upload some evidence of class participation to a dedicated folder. This will be assessed P/F.
• Peer review 1: Research question and hypothesis . This assignment requires peer review, where each student will provide constructive feedback on a classmate's submitted RQ and hypothesis, focusing on clarity, relevance, and feasibility. Your score on this assignment is based on the text you submit and the review you produce. See this FBF resource for all peer review assignments.
• Peer review 2: Building upon the first peer review assignment, students will refine their RQ and hypothesis and add a provisional methodology. This assignment involves a second round of peer review, where students critique each other's proposed methods for research, assessing the appropriateness, clarity, and potential effectiveness. As before, your score on this assignment is based on the text you submit and the review you produce.
• Peer review 3: In this comprehensive assignment, students will complete a detailed research proposal, including the refined RQ, hypothesis, methodology, and a brief literature review. The proposal will undergo a rigorous peer review process, where students are expected to provide in-depth, constructive feedback. The focus will be on the overall coherence, scientific rigor, and originality of the proposals. As before, your score on this assignment is based on the text you submit and the review you produce. This deliverable also includes a link to a hypothesis Pre-registering a project with OSF.
• Article resources: Collaborative article resource assignment

• Interactive poster pitch: I'll organize an event with external colleagues in which you will present your proposal, either individually or in small groups. Details to be determined based on class progress.
  • Make a slide in accordance with #BetterPoster
  • Add your slides to this deck under the appropriate heading and also submit it to BrightSpace.
  • Due date: Wednesday midnight
  • On Thursday I'll send to the visitors and invite them to prepare questions/comments.

Information on scoring the participation activities can be found in the overview of rubrics.

Cheating and plagiarism

Cheating and plagiarism are academic offenses, with severe consequences. They are acts or omissions by students to partly or wholly hinder accurate assessment. As per the Teaching and Examination Regulations, cases of cheating and plagiarism are reported by the instructor to the Board of Examiners, which will decide on the consequences.

Student services

Ask for help as soon as you need it. The student services desk can answer many of your questions. They are open M-F 10:30-13:00 / 13:30-15:30 and can be reached at cf-sec@rug.nl.

The student advisor, Hieke Hoekstra (h.hoekstra@rug.nl), works on Monday, Wednesday, Thursday and Friday. She can offer you confidential advise, support, and tips. Go to her as soon as you have some concerns. She's here to help!

Planning

Week 1: Research questions and the literature

Class I: Research questions (Feb 5)

Preparation:

• Familiarize yourself with the master’s thesis assessment criteria.
• Select and acquaint yourself with a citation management system.
• Examine theses related to topics of interest.
• Read: The Wiley peer review guide (optionally, watch the video).
• Read: How to write a rebuttal from Nature Methagora blog.
• Fill out this form

Class II: Lit review (Feb 7)

Preparation

• Read: Verkhodanova, V. (2021). More than words: Recognizing speech of people with Parkinson's disease (Doctoral dissertation, University of Groningen). Chapter 3 -- no need to read cover-to-cover, just note structure of replicable lit review. See Fig 3.1 and Table 3.1
• Familiarize yourself with the Open Science Foundation:
  • Check out this video about the OSF tool
  • Make an account at OSF.io and fork this repository
  • Review the research proposal LaTeX template

Week 2: Hypotheses and methodologies to answer your RQs

Class I: Hypotheses (Feb 12)

Preparation:

• Keep working on your RQ and hypothesis. Read widely. Take notes.
• Familiarize yourself with Feedback Fruits. See this FBF resource for all peer review assignments.
• Watch the first 30 minutes of this video about pre-registration in OSF (start at the beginning)

Class II: Methodologies (Feb 14)

Preparation:

• Reflect on the methods you have seen in your readings. To what extent are they transparent and replicable?

Week 3: Analyses

Class I: Experiment design (Feb 19) -- DUTCH SPEECH TECH DAY

Preparation:

• Reflect on the articles you've read. What makes for a good experiment design? How can we recruit participants?

Class II: Experiment analyses (Feb 21)

Preparation:

• Reflect on the different ways results are analyzed in the articles you read. Qualitative, quantitative, and more...

Week 4: Risk mitigation + ethics

Class I: Ethical considerations (Feb 26)

Preparation:

• Reflect on how ethics fits into your research. All research proposals (and theses) require a section on ethics.

Class II: Risk mitigation (Feb 28)

Preparation:

• Reflect on the risks that are inherent in your research. Enumerate them as best you can.

Week 5: Conducting a pilot experiment

Class I: Pilot experiment / feasibility study (Mar 4)

Preparation:

• Reflect on how a pilot experiment or feasibility study could be conducted to e.g. validate questionnaire suitability, demonstrate basic assumptions, or similar.

Class II: Experiment (Mar 6)

Preparation:

• Keep working on your thesis proposal.
• On this day we will perform a fun in-class experiment.

Week 6: Analyzing outcomes -- From research project to thesis [or: Writing week?]

Class I: Outcome analysis (Mar 11)

• tbd

Class II: Prototypes (Mar 13)

• tbd

Week 7: Communicating outcomes + dissemination

Class I: Communication of outputs (Mar 18)

Preparation:

• Reflect on how you would describe your research proposal to someone from another field.
• Start search for academic posters: find good and bad examples.

Class II: Posters, elevator pitches, and more (Mar 20)

Preparation:

• Practice a brief description of your research.

Week 8:

Class I: (Mar 25)

• Interactive session with Daan van Esch (Google) et al.

Class II: (Mar 27)

• Combo class with ASR2