SOW-MKI66
Advanced Academic & Professional Skills
Course infoSchedule
Course moduleSOW-MKI66
Credits (ECTS)6
Category-
Language of instructionEnglish
Offered byRadboud University; Faculty of Social Sciences; Artificial Intelligence;
Lecturer(s)
PreviousNext 1
Lecturer
dr. U. Güçlü
Other course modules lecturer
Lecturer
dr. P.A. Kamsteeg
Other course modules lecturer
Lecturer
prof. dr. J.M. McQueen
Other course modules lecturer
Examiner
dr. M. Sadakata
Other course modules lecturer
Coordinator
dr. M. Sadakata
Other course modules lecturer
Academic year2018
Period
SEM1  (03/09/2018 to 03/02/2019)
Starting block
SEM1
Course mode
full-time
Remarks-
Registration using OSIRISYes
Course open to students from other facultiesNo
Pre-registrationNo
Waiting listNo
Placement procedure-
Aims
This course consists of two modules, namely, Research Methods, Academic Writing. Each module offers distinct learning goals:
Research Methods module: At the end of this module, student will
  1. have learned different research methodologies in AI
  2. have learned how to formulate research questions in AI
  3. be able to critically read and evaluate academic articles
  4. be able to translate a theory into a practical framework, algorithm or a computational model.

Academic writing module: At the end of this module, student will have learned
  1. how to write better academic English and
  2. how to evaluate their own writing and that of others.

Part of each module will contain lectures about practical skills and knowledge that support their future study and career.
Content
Students can take part in this course in the three ways:
  1. Full course, attend all and complete all assignments (6EC)
  2. Advanced Research Methods: attend all and complete all assignments in the first block (3EC) 
  3. Academic Writing and Review: attend subset of lectures and complete subset of assignments in the 2nd block (3EC)
The first option is the standard way to follow the course. In case a student wishes to enrol in the 2nd or the 3rd options, please contact the coordinator in advance.


Block 1
Lectures in the 1st block will provide students with a variety of topics and methodologies in AI. During the practical sessions, students will subscribe to one of the AI research themes and will jointly design and coordinate a panel discussion on the topic. At the end of the 1st block, each student will write a research proposal that includes the design and evaluation of a computational and/or cognitive model. Close attention should be paid to the embedding of the research into existing literature, the rationale of the research and consistency of argumentation, the formulation of research questions and hypotheses, and the design of a proper methodology.


Block 2
One of the core contents in the 2nd block is Academic Writing. There students will be introduced to the art of academic writing. They will be introduced to the differences between and the challenges of writing different kinds of documents, including: shorter and longer research articles, grant proposals, CVs, reviews, and letters to the editor.
 
This course consists of a plenary and a student-specific part. The plenary part consists of lectures with short writing assignments. It will cover guidelines on how to prepare, structure and write scientific articles. In addition, advice will be given on how to write reviews, letters of motivation, and grant/project proposals. The student-specific part of the course will consist of individual feedback on a writing sample, which may be an initial version a research proposal written at the end of Block 1 (but note that this part of the course is concerned with writing skills only). Writing samples will be reviewed by the other students following the course and the teachers. Students will revise their sample on the basis of these reviews. They will then send in the rewritten sample with a “letter to the editor” explaining how they have dealt with the issues raised by their reviewers.


Another core content, given in both Block 1 and 2 is Professional Skills. It includes practical knowledge and tips when attending conference, reviewing and commenting the work done by the others, applying for academic and non-academic jobs, managing projects.
Levels
AI-MA

Test information
The final evaluation is the weighted average of assignments and report.

Tests:
1) Full course, attend all and complete all assignments (6EC)
• Panel discussion session: group (25%)
• Research proposal (25%)
• Presentation of research proposal (10%)
• Peer review of other students’ proposals (20%)
• Response to the review reports and revised writing sample (20%)

(2) Advanced Research Methods: attend all and complete all assignments in the first block (3EC)
• Panel discussion session: group (50%)
• Research proposal (50%)

(3) Academic Writing and Review: attend subset of lectures and complete subset of assignments in the 2nd block (3EC)
• Peer review of other students’ proposals (50%)
• Response to the review reports and revised writing sample (50%)

Prerequisites
For students who are following the Academic Writing and Reviewing part only: At least a full year of prior master study in the field of cognitive science, artificial intelligence, or computer science. When only taking part in the Academic Writing part, students are strongly recommended to have their thesis project started, or have a project proposal at hand.

Contact information
Dr.M.Sadakata, T:3615417, E.:M.sadakata@donders.ru.nl

Instructional modes
Lecture

General
Lectures

Tests
Assignment
Test weight25
Test typeAssignment
OpportunitiesBlock SEM1

Proposal
Test weight25
OpportunitiesBlock SEM1, Block SEM1

Presentation
Test weight10
Test typePresentation
OpportunitiesBlock SEM1

Peer review report
Test weight20
OpportunitiesBlock SEM1, Block SEM1

Revised report
Test weight20
OpportunitiesBlock SEM1, Block SEM1